The Meal by Meal Dynamic Energy Balance in Blood: Habits & Risks

The Meal by Meal Dynamic Energy Balance in Blood: Habits & Risks Editor

Mario Ciampolini Preventive Gastroenterology Unit, Department of Paediatrics, UniversitĂ di Firenze 50132 Florence, Italy

Research Signpost, T.C. 37/661 (2), Fort P.O., Trivandrum-695 023 Kerala, India

Published by Research Signpost 2011; Rights Reserved Research Signpost T.C. 37/661(2), Fort P.O., Trivandrum-695 023, Kerala, India Editor Mario Ciampolini Managing Editor S.G. Pandalai Publication Manager A. Gayathri Research Signpost and the Editor assume no responsibility for the opinions and statements advanced by contributors ISBN: 978-81-308-0457-6

Contents

Chapter 1 Background Mario Ciampolini

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Part I. Long Pathogenic Chain Chapter 2 Bacterial growth on intestinal mucosa Microflora persistence on duodenojejunal flat or normal mucosa in time after a meal in children

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Mario Ciampolini, Stefania Bini and Alessandra Orsi Chapter 3 Absorption slowdown Mario Ciampolini

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Chapter 4 Subclinical inflammation Giovanni Feminò

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Part II. Awareness and Effects Chapter 5 Initial Hunger (IH) Training to estimate blood glucose and to form associations with initial hunger

Mario Ciampolini and Riccardo Bianchi

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Chapter 6 “Recognizing hunger” (initial hunger meal pattern) and insulin sensitivity Sustained self-regulation of energy intake: Initial hunger improves insulin sensitivity

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Mario Ciampolini, David Lovell-Smith, Riccardo Bianchi, Boudewijn de Pont Massimiliano Sifone, Martine van Weeren, Willem de Hahn Lorenzo Borselli and Angelo Pietrobelli Chapter 7 Differences in maintenance of mean blood glucose (BG) and their association with response to “recognizing hunger” Mario Ciampolini and Massimiliano Sifone

95

Chapter 8 “Recognizing hunger” (initial hunger meal pattern) and body weight Sustained self-regulation of energy intake. Loss of weight in overweight subjects.

Maintenance of weight in normal-weight subjects

119

Mario Ciampolini, David Lovell-Smith and Massimiliano Sifone Chapter 9 Systemic immune stimulation Attention to metabolic hunger and its effects on Helicobacter pylori infection

145

Mario Ciampolini, Lorenzo Borselli and Valerio Giannellini Chapter 10 Conclusions Mario Ciampolini

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Index

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Research Signpost 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

The Meal by Meal Dynamic Energy Balance in Blood: Habits & Risks, 2011: 1-9 ISBN: 978-81-308-0457-6 Editor: Mario Ciampolini

1. Background Mario Ciampolini

Preventive Gastroenterology Unit, Department of Paediatrics Università di Firenze, 50132 Florence, Italy

Aim Eating begins and ends on the evaluation of sensations that are subjective, i.e. not shared with other people, e.g., a headache in comparison with sounds and figures. We have trained an order in this subjectivity to improve energy balance in young, clinically healthy subjects with normal BG. A target sensation of hunger before meals produced this order (Chapter V). After training, meals adapted content (e.g., 50 grams in order to eat after 2 hours and 100 grams in order to eat beyond 4 hours with the same physical activity) to the arousal of the target sensation before the planned, subsequent intake. The association with glucose concentration (BG) proved the identity of the recognized sensation as target for meal consumption. In healthy people with normal levels of insulin, BG is representative of other nutrients in blood because of the close correlation with other nutrients, exhaustibility, operative experience and published and unpublished results.

BG increases in the first hour after a meal and slowly declines in the subsequent hours, reaching the pre-prandial level in healthy conditions after two – five hours. Later, BG lowers and is, usually, subjectively insufficient.

At this point, subjects focused and memorized characteristics of hunger sensations, and validated from one to three sensations by BG labeling. We Correspondence/Reprint request: Dr. Mario Ciampolini, Preventive Gastroenterology Unit, Department of Paediatrics, Università di Firenze, 50132 Florence, Italy. E-mail: mlciampolini@fastwebnet.it

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Mario Ciampolini

termed the validated sensations together with the name: Initial Hunger (IH, Chapter V). 111 We investigated 1) if meal consumption may be adapted to IH arousal three times a day (Initial Hunger Meal Pattern, IHMP, or better “recognizing hunger”, Chapters VI - VIII); 2) if this meal pattern sustains usual daily activity (Chapter VII); 3) if it maintains body weight in lean subjects who are insulin sensitive (Chapter VIII); 4) if it increases insulin sensitivity (Chapter VI); 5) if it decreases body weight in insulin resistant or overweight subjects (Chapters VI and VIII); 6) if it lowers immune stimulation, the basic mechanism in the development of subclinical inflammation (Chapter IX). 7) and lastly, BG and body weight homeostasis (stability) are the final objectives. In Chapter VII stability may be maintained at high levels that are associated with high risks (High mean BG, HBG). Homeostasis is an ideal objective which includes stability of nutrients at a level that prevents risks and deterioration (suppression of subclinical inflammation, Chapter IV and actual results reported by Chapters VI - IX) and improves body functions (Low mean BG, LBG). Chapter VII shows the point of division of LBG from HBG. In this research, “recognizing hunger”, prevents insulin resistance and non-insulin dependent diabetes (NIDD; Chapters V –VIII). The aim is suppressing subclinical inflammation and the associated functional disorders and evolving diseases (Chapter IV). The adaptation of “recognizing hunger”, in the treatment of the elderly with fully developed NIDD requires further investigation.

The results modify views on metabolism and on insulin resistance. We present our views, although the content of this Chapter has not been the center of our studies.

The meal by meal dynamic balance of energy The yearly or monthly steady balance is insufficient to guarantee nutritional health because it ignores weight wavering and periods of excessive energy availability. Available macronutrients in blood for energy expenditure in body cells, or energy provision, affects directly life maintenance and health risks (Chapters V –IX). The provision includes glucose, fatty acids and aminoacids and is the scope and consequence of meal intake. Available nutrients are in mutual correlation and blood glucose (BG) can substitute others. BG is used before other nutrients, reserves are exhaustible, the utilization decreases with abundance of nutrients in all tissues, and we used BG as representative of other nutrients in blood [1 - 3]. Thus, nutrients provision, i.e. BG rise, is the

Background

3

aim for any meal. The time length in the rise allows an evaluation of either deficient or excessive meal energy provision.

Provision to body cells consists in the instant concentration of macronutrients and in their energy content. Provision depends on instant balance between entry and efflux of nutrients in blood. This balance is dynamic like a flux in a small tank with a tap that provides the input at intervals and with a permanently open exit. Blood contains about 6 - 7 grams of glucose, thus the meal is mostly stored in a transient container produced by insulin release during meal and after meal. Instant balance and instant provision consist of BG value. Meal by meal dynamic balance of energy is much more important and consists of BG value before further energy addition, before meal consumption. At this time, the level of nutrients and glucose in blood results from balance in blood between entry (previous meal intake and fatty acids release in blood from adipose tissues) and exit (expenditure plus fatty acids deposition) in previous inter-meal interval, according to findings in Chapters VI – VIII. Somebody might suggest that inter-meal balance is positive when the second pre-prandial value in a day (before lunch) is higher than the first (before breakfast). Yet, balance is positive all the times it is associated with energy accumulation. Meal by meal balance is thus positive when BG is high, even if it is constant from breakfast to lunch. Meal by meal balance is negative when meal energy plus influx from adipose tissues is lower than expenditure and pre-prandial BG is very low. Meal by meal balance is often null and BG is just low (Chapter VII). Meal by meal energy (BG) balance in blood coincides only approximately with body energy balance in the interval between meals. Instead, we found a close correlation between the habit in meal by meal energy balance in blood and body energy balance in lean, insulin sensitive subjects in a period of five months (Chapter VIII). Mean pre-prandial BG measured habitual meal by meal BG balance in blood and body weight measured body energy balance (Chapter VII and VIII). For health purposes, achievement of null energy balance in blood through days and weeks is more effective than a precisely null meal by meal body energy balance (e.g., the fever condition in Chapter III). Take, please, into consideration also the topics on null meal by meal balance and homeostasis in the Aim section in this Chapter, and in Chapter VIII. Yet, meal by meal null balance in blood is an effective tool in the achievement of long term healthiest body functions and weight. A healthy hormonal function might even develop the most attractive body.

Achievement of null balance is difficult, but rather more common than expectation. Small physiological adaptations in intake time or amount, or in expenditure, deliberate or unconscious, allow frequent achievement of null balance. This research might help in focusing attention on this achievement

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and related factors. Chapters III and V shall report requirements for standard BG measurements.

Insulin resistance and fattening Positivity of dynamic balance is sustained by a vicious circle (positive feed-back). In the absence of any voluntary limitation, insulin release increases in response to increased intake, and this fact is associated with increases in number of beta cells in the pancreas to an inborn limit that has a high variance. This number and the amount of insulin release dictate meal sizes (Chapter VII and [4 - 6]). Insulin level dictates energy utilization by tissues, a different variable from energy availability (provision). More than half population is able to increase insulin release and to increase progressively fat tissues [7]. In the absence of any personal limitation, these people enlarge meal sizes, maintain positive meal by meal dynamic balance for days, weeks, months, years, and insulin resistance increases slowly. The habit to positive dynamic balance is causal on insulin resistance and fattening (Chapters VI VIII). The two increases, adipocyte proliferation and insulin release are correlated, although both depend also on independent inborn factors. When skin-fold thickness is thin, poor adipocyte proliferation is associated with rapid development of insulin resistance, We saw a 12 year child in condition of insulin resistance, but his arm and leg skin-fold thickness was only three mm and now, after 20 years is still four mm. Infants have recurrent diarrhea in association with insulin resistance (Chapter III). They have six – seven mm of arm skin-fold thickness that is on 15th percentile of normal reference distribution (NCHS, USA and Tuscan reference). These infants show rapid recovery from diarrhea and prevention of relapses from 25% to 30% decrease of energy intake [8, 9]. Rapid development and recovery from insulin resistance has been reported in rodents by increase and subsequent decrease in food intake [10]. Also these experimental animals have thin subcutaneous tissues. A decision on intake is sufficient for regression from insulin resistance in a few days when subcutaneous tissues are thin [8, 9].

Insulin as (determinant of) meal container enlarges but becomes progressively less expansible. Inter-individual differences in expansion capability is high, we found differences in peak insulin at GGT between 20 mU L-1 and 800 mU L-1. We speak of hyperinsulinism when insulin release is high, and insulin resistance (IR) when insulin is high and the release is ineffective in lowering BG. Insulin sensitivity shows the elasticity or expansibility of the meal container, and consists of grams of glucose that exit from blood in the unit of time by effect of one unit of insulin. A person

Background

5

showing insulin resistance needs more insulin to decrease high BG. If this further compensatory increase does not occur, blood glucose concentrations increase up to the occurrence of type 2 diabetes. If more insulin and cortisol are secreted, adipocytes increase their volume, pre-adipocytes increase proliferation and enhance differentiation compared to normal cells [18]. The poor utilization (exit from blood or storage plus oxidation) of BG depends on fatty cells that are increased in diameter and release high amounts of fatty acids [10, 11]. Enlarged fatty cells deliver three – five times fatty acids to blood compared to subjects with normal size cells during the post-absorptive phase of inter-meal period, three – five hours after the last meal [11]. Thus, insulin resistance is associated with abundance of energy nutrients throughout the body, and contributes in association with meal amounts to maintain a positive meal by meal balance (Chapters VII, VIII). Liver accumulates glycogen and fat and develops steato-hepatitis [12, 13]. This liver obviously releases increased amounts of glucose and triglycerides as VLDL. Tissues accumulate energetic nutrients [10, 11, 14, 15]. Muscles accumulate fatty droplets and glycogen. Cell membranes poorly regulate fatty acid entry (facilitated passage), but tightly regulate the entry of glucose. This entry is inhibited by fatty acid abundance inside and outside the cells [10, 11, 16].

Thus, the measurement of glucose efflux (utilization) from blood becomes a good, inverse measure of this condition of excessive energy provision.

We have many indices of nutrient excess. The gold standard for quantifying insulin sensitivity (and resistance) is the "hyperinsulinemic euglycemic clamp," so-called because it measures the amount of glucose necessary to maintain BG at constant level after increase of blood insulin at constant level by i.v. infusion. If high levels of glucose (7.5 mg/min or higher) are required, the patient is insulin-sensitive. Very low levels (4.0 mg/min or lower) indicate that the body is resistant to insulin action. The glucose tolerance test (GTT) measures BG and insulin plasma levels for three hours after 300 kcal of oral glucose. A mathematical formula takes into account the elevations of BG and insulin to calculate an index of insulin efficiency [17] and the index of beta cell function [18]. BG represents instant balance between influx and efflux of nutrients from blood. Pre-prandial BG and preprandial insulin show energy balance meal by meal (Chapters V - VIII). The two measurements are used together in the denominator of HOMA estimate (22.5/BG in mmol/L multiplied by plasma in sulin in microU/mL). HOMA is considered an estimate of insulin sensitivity [19]. We consider HOMA as the best (inverse) estimation of meal by meal energy balance in blood: high HOMA suggests negative balance and low HOMA suggests a positive balance from previous meal. Meals are habitual (Chapter VII) and low HOMA

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Mario Ciampolini

suggests insulin resistance development. We used mean BG in a week (Chapter VII); HbA1c, fasting insulin, insulin resistance as measures of excess energy availability. Each measurement may change in time and changes are correlated. Rapidity of change is different for each measurement.

“Insulin resistance” is associated with a “pro-inflammatory state” or “subclinical inflammation”, and the association is supported by a huge amount of research (Chapter IV). The finding of this association represents a high achievement in understanding human nutrition and health. General scientific acceptance of this association took unfortunately 80 years [20 - 22].

Overweight depends on a division in the sequence of humans ordered by weight and measured as BMI (weight in kg divided by the square of height in meters). The division at 25 separates two populations with significantly different prevalence of vascular disease. Beyond 30 BMI, we speak of obesity.

BMI and insulin resistance are two heterogeneous measures. Given the definition, insulin resistance is a metabolic condition of excess, and is necessarily associated with early increase in weight, before manifest overweight development (OW, BMI higher than 25.0; Chapter VIII). In a survey on 120 adults, we found 30 subjects who were OW (Chapters VI – VIII) and 55 who were insulin resistant. The survey by 7-d diary revealed no difference in mean weekly pre-prandial BG between overweight and normalweight (NW) subjects (Chapter VII). A positive correlation exists between mean BG and insulin resistance (Chapters VI, VII). In lean subjects insulin resistance is a modest, not manifest and not measurable condition of overweight. These insulin resistant subjects remain lean for either a low fatfree mass or an inborn low number of adipocytes throughout the body.

The OW condition reveals past positive balance, from a week to many years before measurement. OW and obese people may have low mean BG despite of huge energy accumulated in tissues, they have even more frequent Slightly Depressed BG (SDBG) events than NW people (Table 1). The high prevalence of SDBGs in OW people means that delivery of fatty acids to blood is high in OW people, although delivery remains insufficient for RMR maintenance. Delivery may arrive to one third – two thirds RMR in OW people during months underfeeding like in the Minnesota experiment (See please, also Chapter V – VII). Like for every habit, implementing a novel decision suffices in changing the sign of an habitual meal by meal balance from positive to null once and for all!

In our overview, meal by meal positive energy balance in blood and insulin resistance are directly involved in risk increase. Overweight degree tells us the endurance in meal by meal positive balance that was needed to develop high risks (and deterioration), as well as the time needed for regressing from high risks (Chapter VIII).

7

Background

Table 1. Number of events of Slightly Depressed Blood Glucose (SDBG, BG between 3.3 mmol/l and 2.2 mmol/l) of the total number of pre-prandial measurements. Last row: number of SDBG during Oral Glucose Tolerance Test (GTT).

Chi2 y

The text mentions

At recruitment

Trained

NW infants 1

25/792 (3.2%) vp

61/1511 (4.0%) vj 1.12

NW children 2

4/638

(0.6%)

34/2574 (1.3%)

2.10

OW children

2/245

(0.8%)

8/743

0.12

NW adults 3

3/450

(0.6%)

10/1394 (0.7%)

Group

(1.0%)

0.01 p

OW adults

13/937 (1.4%)

45/2808 (1.6 %)

Total

47/3062 (1.5%)

158/9030 (1.8%)

0.63

During GTT z

6/50

8/50

0.33

(12%)

(14%)

0.21

p= v= j= y= z=

P <0.05 vs. NW adults, at the Chi square analysis, P <0.001 vs. subsequent age-group, P< 0.001 vs. NW adults.

Chi square between recruitment and after 5 months training composition of the group: 50 subjects; 13 children (6 NW/7OW); 37 adults (14NW and 23OW). NW = BMI < 25.0.

1 = age up to 3 years, body weight lower than 110% of reference of same height.

2 = age 3 â&#x20AC;&#x201C; 12 years 3 = age over 18 years

References 1.

2.

3.

4.

5.

6.

Gavin, J.R. Pathophysiologic mechanisms of postprandial hyperglycemia. 2001, Am. J. Cardiol., 88, S4-S8. de Graaf, C., Blom, W.A.M., Smeets, P.A.M., Stafleu, A. and Hendriks, H.F.J. Biomarkers of satiation and satiety. 2004, Am. J. Clin. Nutr. 79. 946-961.

Elliott, S.S., Keim, N.L., Stern, J.S., Teff, K., and Havel, P.J. Fructose, weight gain, and the insulin resistance syndrome. 2002, Am. J. Clin. Nutr. 76, 911-922.

Lang, L. Insulin-producing beta-cells arise via self-duplication. 2004, Gastroenterology, 127, 1288.

Polonsky, K.S., Sturis, J. and Bell, G.I. Non-Insulin-Dependent Diabetes Mellitus â&#x20AC;&#x201D; A Genetically Programmed Failure of the Beta Cell to Compensate for Insulin Resistance. 1996, N. Engl. J. Med., 334, 777-783.

Dulloo, A.G. Thrifty energy metabolism in catch-up growth trajectories to insulin and leptin resistance. 2008, Best Practice & Research Clinical Endocrinology & Metabolism, 22, 155-171.

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7.

Verdich, C., Toubro, S., Buemann, B., Madsen, J.L., Holst, J.J. and Astrup, A. The role of postprandial releases of insulin and incretin hormones in meal induced satiety.

Effect of obesity and weight reduction. 2001, Intern. J. Obesity., 25, 1206-1214.

Ciampolini, M., Conti, A., Bernardini, S., Vicarelli, D., Becherucci, P., Seminara, S. and Pacciani, G. Internal stimuli controlled lower calorie intake: effects after eight months in toddlerâ&#x20AC;&#x2122;s diarrhoea. 1987, Ital. J. Gastroenterology, 19, 201-204.

Ciampolini, M., Vicarelli, D. and Seminara S. Normal energy intake range in children with chronic non-specific diarrhea. Association of relapses with the higher level. 1990, J. Pediatr. Gastroenter. Nutr., 11, 342-50.

Kraegen, E., Cooney, G., Ye, J.M. and Furler S. Peroxisome proliferator activated receptors, fatty acids and muscle insulin resistance. 2002, J.R. Soc. Med., 95(Suppl 42),14-22.

Corcoran, M.P., Lamon-Fava S. and Fielding R.A. Skeletal muscle lipid deposition and insulin resistance: effect of dietary fatty acids and exercise. 2007, Am. J. Clin. Nutr., 85, 662-677.

Sanyal, A.J., Campbell-Sargent, C., Mirshahi, F., Rizzo, W.B., Contos, M.J., Sterling, R.K., Luketic, V.A., Mitchell, L., Shifman, M.L. and Clore, J.N. Nonalcoholic Steatohepatitis: Association of Insulin Resistance and Mitochondrial Abnormalities. 2001, Gastroenterology, 120, 1183-1192 Donati G., Stagni, B., Piscaglia, F., Venturoli, N., Morselli-Labate, A.M., Rasciti, L. and Bolondi L. Increased prevalence of fatty liver in arterial hypertensive patients with normal liver enzymes: role of insulin resistance. 2004, Gut, 53,1020-1023.

Westerterp, K.R. Diet induced thermogenesis. 2004, Nutrition & Metabolism 1, 5.

Jequier, E. Thermogenic responses induced by nutrients in man: their importance in Energy balance regulation. 1983, J., Mauron Ed. Nestle Nutrition Research Symposium, Vevey, 26-44.

De Baer, J.O., van Es, A.J.H., Roovers, L.A., van Raaij J.M.A. and Hautvast J.G.A.J. Adaptation of energy metabolism of overweight women to low-energy intake, studied with whole body calorimeters. 1986, Am. J. Clin. Nutr., 44, 585-595.

Matsuda, M. and DeFronzo R. A. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. 1999, Diabetes Care, 22, 1462-1470.

Wiesli, P., Schaeffler, E., Seifert B., Schmid, C., and Donath, M. Y. Islet secretory capacity determines glucose homoeostasis in the face of insulin resistance. 2004, Swiss Medical Weekly, 134, 559-564.

Mattheus, D.R., Hosker, J.P., Rudenski, A.S., Naylor, B.A., Treacher, D.F:, and Turner, R.C. Homeostasis model assessment: insulin resistance aand beta cell function from fasting plasma glucose and insulin concentrations in man. 1985, Diabetologia, 28, 412-419.

Kylin, E. Studien ueber Hypertonie-Hyperglykamie-Hyperurikamie syndrome.

1923, Zentralblatt fur innere Medizin, 44.

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21. Randle, P.J., Garland, P.B., Hales, C.N. and Newsholme, E.,A. The glucose-fatty acid cycle: its role in insulin sensityvity and the metabolic disturbances of diabetes mellitus. 1963, Lancet 93, 785-789.

22. Reaven, G.,M. The metabolic syndrome: is this diagnosis necessary? 2006, Am. J. Clin. Nutr., 83,1237-1247. Â

Part I

Long Pathogenic Chain

Research Signpost 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

The Meal by Meal Dynamic Energy Balance in Blood: Habits & Risks, 2011: 11-29 ISBN: 978-81-308-0457-6 Editor: Mario Ciampolini

2. Bacterial growth on intestinal mucosa Microflora persistence on duodenojejunal flat or normal mucosa in time after a meal in children 1

Mario Ciampolini1, Stefania Bini1 and Alessandra Orsi2

Department of Pediatrics, University of Florence, Via L. Giordano 13, 50132 Florence Italy; 2Microbiological Laboratory, SMN Hospital, Florence, Italy

Abstract. CIAMPOLINI, M., S. BINI AND A. ORSI. Microflora persistence on duodenojejunal flat or normal mucosa in time after a meal in children. PHYSIOL BEHAV 60(6) 1551-1556, 1996. -A pathogenic role for high numbers of bacteria in the small intestine had been suggested previously by bacterial counts on luminal aspirates, but these investigations were flawed by the sampling device "contamination" in the mouth and the changing nature of fluent intestinal content. A procedure was developed to sterilize the Watson biopsy capsule with HCl in the upper portion of the duodenum. Bacteria were counted in the mucosal homogenate of the first (diagnostic) duodenojejunal biopsy in 80 untreated celiac children, and in 46 children with irritable bowel syndrome (IBS) in a four-cell, controlled, randomized investigation. Persistence of bacteria on the mucosa for 20 h after the last meal was investigated in 62 subjects, and for 26 h after the last meal in 64 subjects.

Bacteria, mainly streptococci and staphylococci, persisted at a Correspondence/Reprint request: Dr. Mario Ciampolini, Department of Pediatrics, University of Florence, Via L. Giordano 13, 50132 Florence, Italy. E-mail: mlciampolini@fastwebnet.it

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concentration of 106 per gram of mucosa 20 h after the last meal. The number of bacteria per gram of mucosa was 24 times higher in all 62 children of the 20-h fast groups than in all 64 children of the 26-h fast groups (p < 0.001). The bacteria count in celiac children was 39 times higher in the 20-h fast group than in the 26-h one. This difference was significantly higher than the 11 times difference that was found on the normal mucosa between the 20- and 26-h fast IBS groups (p < 0.001), which was still significant. The number of bacteria on duodenojejunal mucosa depends on nutrient absorption and persists longer than the intermeal interval in these subjects. Copyright Š 1996 Elsevier Science Inc. Digestion Intestinal absorption Intestinal bacteria Celiac disease Chronic diarrhea Weaning Health education Microflora Ingestive behavior Insulin resistance

INTESTINAL flow and absorption of nutrients is rapid, and very few bacteria, if any, are cultivated in duodenojejunal aspirates of healthy children and adults examined in the fasting condition. Thus, 33 luminal aspirates were sterile and 83 of 92 contained less than 105 CFUs (colony-forming units) per ml in 9 studies in "healthy" children (4,6-8,13,23,24,43,47). Conversely, only 32 were sterile and 76 of 187 showed less than 105 CFUs per ml in 9 studies in children with chronic or persistent diarrhea (6,8,11,13,18,24,29,32,49).

Both differences are highly significant and the high bacterial concentration, above 105 CFUs per ml (including gram-positive cocci), may either affect the pathogenesis or represent an index in the pathogenesis, or be a consequence of the disease. Studies on luminal fluid are flawed by possible contamination of sampling devices in the mouth and throat (30) and by the flushing out of luminal content (38). The same strains and similar bacterial density occur in simultaneous cultures of mucosa and luminal aspirate (22,51,55). This mucosal flora might more directly affect disease than the luminal kind.

Microbiology counts on duodenojejunal mucosa have been reported worldwide in only about 20 children in two investigations (6,22), although persistence over time and changes with meals have not been investigated.

Methods Subjects Between 1981 and 1987, 140 children from 8 months to 16 years of age were consecutively selected for intestinal biopsy and randomized by use of a random-number table (5) into the experimental and control groups at the Pediatric Gastroenterology Unit of Florence University. A definitive diagnosis of irritable bowel syndrome (IBS) or celiac disease was made in

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Bacterial growth on intestinal mucosa

Table 1. Number, Gender, and Age Distribution in the Four Investigated Groups.

Group Fast (hours) Number Male/femal Age (months)*

Celiac 20 42 17/25 67.6 ± 56.4

26 38 15/23 79.2 ± 50.0

Normal 20 20 15/5 59.7 ± 56.8

26 26 19/7 65.3 ± 51.9

* Mean ± SD.

126 of the 140 biopsied children after a 2-year follow-up and the 126 children were included in a four-cell, prospective, controlled, randomized investigation. At the end of the investigation, 62 children were assigned to a 20-h fast group and 64 to a 26-h fast group (Table 1). No child had intestinal symptoms in the 5 days before biopsy, or had febrile disease, or had used any drug or medication in the previous 3 weeks, or had been on a gluten-free diet in the last few years. The study was reviewed and approved by the Departmental Human Experimentation Committee. Informed consent was obtained from the children's parents.

Diagnostic criteria Celiac disease was diagnosed according to the criteria of the "European Society of Pediatric Gastroenterology and Nutrition" (59). Subtotal villous atrophy (i.e., mucosa flattening) was originally found in the small intestine at presentation and on gluten challenge in all subjects after a period of about 6 months of gluten-free diet. A decrease in antigliadin antibodies and rapid nutritional recovery on a gluten-free diet were also a requirement.

The diagnosis of IBS was made in infants with chronic or intermittent diarrhea less than 3 years of age (12,58), and in older subjects with chronic or intermittent abdominal pain associated with 3 of the following symptoms or signs: relief of abdominal pain with defecation; loose stools with or without the onset of pain; more frequent stools with the onset of pain; abdominal bloating; feelings of incomplete evacuation; passage of mucus via the rectum; urgency (42,50,60). Normal hemogram, sedimentation rate, urinalysis, urine culture, stool tests for occult blood, and ultrasound abdomen examination (including kidney) were required, as well as absence of ova and parasites and pathogenic bacteria, milk or egg allergy; IV rehydration therapy was not needed. Organic disorders, including lactose intolerance, cystic fibrosis, pancreatitis, inflammatory bowel disease, liver and peptic ulcer diseases, and lower respiratory or urinary tract infections were excluded. Children with IBS eventually recovered in 1 to 3 months and maintained good health in the following year.

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Procedure We were able to investigate the bacterial count per gram of mucosa in untreated children with celiac disease and in those with IBS. These children were studied during the course of intestinal biopsy for diagnostic purposes.

Both subject groups were studied a few days after abatement of intestinal symptoms, diarrhea, or abdominal pain. Children with celiac disease were eating gluten-containing foods and had subtotal atrophy of the mucosa.

Children with IBS showed normal mucosa and were considered as healthy controls. A sterile method of sampling was developed. Persistence of bacteria on mucosa was investigated either 20 or 26 h after the last meal. The postmeal-time interval was assigned at random.

Experimental comparison Intestinal biopsy was performed in the afternoon after feeding cessation of either 20 h (i.e., since the previous day's dinner at 1900 h) or 26 h (i.e., since the previous day's lunch at 1300 h. The 20-h fast children were also allowed a small snack between lunch and dinner, whereas the 26-h fast children were not. A day's abstinence from food was useful for accelerating progression of the capsule and avoiding failures in its advancement.

Intestinal biopsy and microbiological procedures Intestinal biopsy was performed in every case by means of the Watson capsule at the Treitz level, or just after this level with fluoroscopic examination. The biopsy capsule was aseptically mounted, and introduced into the stomach. The pH was measured to exclude hypochlorhydric subjects with gastric juice over 6.0 (20). The capsule was advanced into the duodenum, and sterilized with 1 ml of HC1 0.1 N in the second third of the duodenum and flushed with 10 ml saline after 1 min. Oxygen-free CO2 gas was introduced. The jejunal mucosa was sampled after a further 30 cm progression (i.e., at the Treitz level) after 15-45 min. Care was taken to avoid contamination of the biopsy after withdrawal, by cleansing the closed capsule with dry, sterile gauze. The capsule was opened and the mucous layer was smeared on a slide, stained with Methylene Blue, and observed under a microscope. A 2-8 mg portion of the biopsy without the mucous layer was immediately weighed, washed, homogenized in 0.1 ml Columbia CO2 broth, and diluted 4 times with 1:10 dilution. Five microliters were plated in duplicate on nonselective blood agar. This procedure was repeated under anaerobic conditions to ensure cultivation of anaerobic organisms (3). The

Bacterial growth on intestinal mucosa

15

CFUs were counted and at least 10 random colonies were kept after 2-day incubation for the assessment of the cultural, microscopic, and biochemical characteristics of the bacteria (27). Diplococci were counted with streptococci, and Sarcinae and micrococci with staphylococci (27). The lower limit was about 103 per g for the total CFU counts and 1% of the total CFU count for the isolation of less numerous strains. The variation coefficient (SD and mean) was 4.5% in 10 measurements on the same sample.

Validations HCl sterilization and equilibration procedures were performed in duplicate samples of mouth saliva in 10 fasting children with IBS. The tightness of the Watson capsule was verified in the mouth saliva of 35 subjects (22 IBS and 13 celiac) after an over-night fast. Five microliters were plated in blood agar. CFU counts lower than 200 bacteria per ml could not be visualized and the sample appeared sterile. The saliva contained over 105 CFUs per ml in 10 subjects.

HCl sterilization procedure. Saliva was sucked into the Watson biopsy capsule in the mouth. The tube and capsule were injected with 1 ml of HC1 0.1 N, and flushed with 10 ml of saline after 1 min. The pH was over 6.0 at this time and no growth of bacteria was observed in the juice obtained from inside the capsule in 10 subjects.

Equilibration procedure. The capsule was flushed with 10 ml of air, and saliva sucked from the tube after the HCl sterilization. The first 2 ml of saliva were discarded and 5 ÂľL were plated. The pH of this sample was approximately 7.0, and the CFU count was over 105 per ml in all subjects.

Tightness verification. The capsule was HCl-sterilized, equilibrated with saline, fired, filled with sterile saline, immersed in the mouth saliva for 2 s, and cleansed with sterile gauze. From the fluid inside the capsule, 3.5 Âą 2.9 X 104 CFUs per gram were counted.

The HC1 sterilization was twice performed in 13 children with celiac disease and 5 with IBS during biopsy procedure, in the antrum and the duodenum. Fluid was collected through a biopsy tube before and after sterilization plus equilibration with antral juice. Up to 105 CFUs were found per ml of juice before sterilization, whereas only 1-2 colonies were grown from 3 of 18 samples after sterilization and equilibration. The same bacteria were grown in the same numbers in anaerobic cultures.

These results were interpreted as showing that contamination of the open capsule was unavoidable in the mouth and throat and persisted down to the stomach. The antral juice was practically devoid of bacteria at the time of biopsy (i.e., 20-26 It after the last meal). The HCl sterilization was highly

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Mario Ciampolini et al.

effective, as was the equilibration procedure, but the closed capsule allowed slight leakage of salivary fluid during withdrawal.

Assessments The presence of symptoms was assessed in an interview by a validated method (12). Diaries were kept by the nursing staff for a week before the biopsy. Intake records and computerized food composition tables were used to estimate energy intake. The anthropometric, biochemical and hematological measurements have been previously described (12).

Statistical analyses The CFU count was expressed in log(10) as mean ± SD, but SEM was used in the figure. Differences between groups were evaluated with Student's unpaired 2-tailed t-test or by Chi square analysis on logarithms.

Group sizes were estimated to detect 1 half logarithm difference in the total CFU count between groups at a significance level of 0.05 and a power of 0.90 (5).

Results Subtotal villous atrophy of the intestinal mucosa, which is diagnostic of celiac disease, was found in 80 of 126 children. Of these, 42 subjects were in the 20-h fast group and 38 in the 26-h fast group. A further 46 children showed normal mucosa and fit the diagnosis of IBS; 20 of these were in the 20-h fast group and 26 in the 26-h fast group. No difference was found in gender, age, clinical symptoms, or biochemical tests between the 20- and the 26-h fast groups (Table 1). Malabsorption and malnutrition were present in children with celiac disease, and those with IBS were in the range of normality in the investigated anthropometric and biochemical parameters.

The tricipital and quadricipital skin-folds were significantly thinner in all 4 investigated groups than the local reference for the same age.

The antral juice pH was between 1.4 and 4.3 with a mean of 2.3. Bacteria were located on intestinal epithelial cells (not in-side) and in the nearby mucus in microscopic observations of surface mucus immediately after biopsy (Figs. 1 and 2). No difference emerged in the CFU counts of children with celiac disease and IBS who were in the same fasting-time group. Total CFU count was 6.4 ± 1.4 log(10) per gram of intestinal mucosa in celiac disease and 6.2 ± 1.0 log (10) in IBS among those who were in the 20-h fast group. Total CFU counts were 4.8 ± 2.2 and 5.1 ± 2.1 log(10) per gram of

Bacterial growth on intestinal mucosa

17

Figure 1. Epithelial shedded cell covered with bacteria from a normal intestinal mucosa. Biopsy mucous layer smeared and stained with Methylene Blue.

Figure 2. Epithelial shedded cell with bacteria and a lump of aggregated bacteria in the nearby mucus from a subtotal atrophy intestinal mucosa. See Fig. 1.

mucosa respectively, in the 2 groups in the 26-h fast group (Figs. 3 and 4).

Neither count showed any significant difference from CFUs counted inside the closed Watson capsule after immersion in saliva: 4.5 Âą 0.6 log (10) (see Validations). The bacteria count per gram of mucosa was 24 times higher in

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Mario Ciampolini et al.

all 62 children of the 20-h fast groups than in all 64 children of the 26-h fast groups (p < 0.001). The bacteria count in celiac children was 39 times higher in the 20-h fast group than in the 26-h one (Fig. 3). This difference was significantly higher than the 11 times difference that was found on the normal mucosa between the 20- and 26-h fast IBS groups (Chi square, p < 0.001), which was still significant (Fig. 4).

Only 1 child from the 20-h fast group had no bacteria in the biopsy, compared to 8 of those from the 26-h fast group (Chi square, p < 0.05).

Jejunal flora was mainly composed of streptococci, which were isolated more than twice as often as staphylococci (Figs. 3 and 4). Biopsies showing growth of these two genera were compared in the 20- and 26-h fast groups. Both genera had higher CFU counts in the biopsies of the 20-h fast groups than in those of the 26-h fast groups, although the differences were significant only in celiac disease. The difference in staphylococci maintained significance

Figure 3. Number of streptococci, staphylococci, and total CFU counts in atrophic jejunal biopsies of untreated children with celiac disease 20 h after last meal (white columns), or 26 h after last meal (dashed columns). Geometric mean of CFU counts shown in log(10) by height of columns. SEM shown by vertical bars. Significance vs. group with dinner consumption shown by asterisk: p < 0.005, < 0.005, < 0.001, respectively, from the left. Mean streptococcal and staphylococcal growth calculated only in biopsies showing growth of these genera (see notes). The difference in staphylococci was significant also after inclusion of biopsies showing no growth of this generum. a, geometric mean CFUs in 31 of 42 biopsies; b, geometric mean CFUs in 33 of 38 biopsies; c, geometric mean CFUs in 18 of 42 biopsies; d, geometric mean CFUs in 10 of 38 biopsies; e and f, geometric mean CFUs in all biopsies performed (42 and 38, respectively).

Bacterial growth on intestinal mucosa

19

Figure 4. Number of streptococci, staphylococci, and total CFU counts in normal jejunal biopsies of untreated children with IBS 20 h after last meal (white columns), or 26 h after last meal (dashed columns). Symbols as in Fig. 1, p < 0.05. a, geometric mean CFUs in 17 of 20 biopsies; b, geometric mean CFUs in 22 of 26 biopsies; c, geometric mean CFUs in 9 of 20 biopsies; d, geometric mean CFUs in 7 of 26 biopsies; e and f, geometric mean CFUs in all biopsies performed (20 and 26, respectively).

after inclusion of biopsies showing no growth of this generum (p < 0.05).

Differences in alpha, beta, or gamma streptococci, coagulasepositive or negative staphylococci isolations, and CFU counts in the 4 investigated groups resembled those found in total streptococcal and staphylococcal spp, without reaching significance. A further 31 strains were isolated in 23 total biopsies, with no difference between the 20- and 26-h fast groups, although these additional strains were more frequently found in biopsies with low CFU counts: 9 were isolated from 19 biopsies with lower counts than 105 per gram and 14 from 98 biopsies with higher counts (Chi square, p < 0.05). Neisseria spp were found 20 times; Escherichia coli 4 times; Propionibacteria and yeasts twice; Proteus, Clostridium perfringens and Chromobacterium once.

Lower counts were found in anaerobic than aerobic cultures in children fasting 20 h, without any significant differences. Anaerobic CFU counts were significantly lower in children fasting for 26 h than in those fasting for 20 h in the celiac and overall groups. (p < 0.001 and p < 0.01). The difference observed in celiac disease (18 times) was significantly wider than that in healthy children (4 times, p < 0.01). The same spps with similar CFUs were isolated in aerobic and anaerobic cultures.

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Mario Ciampolini et al.

Mean daily intake was 6.7 Âą 1.2 MJ in the week investigated before the biopsy. The intakes at lunch and dinner were 32.4% and 32.2% of the total daily intake, and 35.4% was consumed at breakfast and in 1-2 optional snacks. No intake difference was significant among groups. The snack between lunch and dinner was consumed by 90.5% of all children fasting 20 h.

Discussion In the present study, bacteria were still found on mucosa at a density of 10 per gram of mucosal homogenate after 20 h without meals in IBS and untreated children with celiac disease who had been diarrhea-free for a few days. Evans et al. found 7.6 log (10) CFUs per gram of normal mucosa in 2 of 4 children investigated for suspected celiac disease (22). The other 2 had sterile biopsies. Avigad et al. found about 105 bacteria in 7 biopsies in children who had recovered from diarrhea, with a range between 103 and 107 per gram of mucosa (6). Three studies in healthy volunteer adults or in adults at surgery found 5 sterile samples, 7 with counts lower than 104, and 4 with counts up to 106 CFUs per gram of mucosa (46,48,51). CFU counts on celiac mucosa have been reported in 3 children (22). Two subjects had over 108 CFUs per gram and the third showed no growth (22). In the lumen of children and adults with untreated celiac disease 106-108 CFUs have been observed, but the samples were sterile or of low growth in other subjects (4,15,21,22,31,52).

Bacteria persisted on both atrophic and normal mucosa up to 20 h after the previous meal, and rapidly decreased in number in the following 6-h fast.

These are the most important findings of this report. Mucosa-associated bacteria may stimulate intestinal immune cells (1,2,9,16,33,39,44,54,57), and high bacterial counts in the lumen are associated with diarrhea relapses in infants (4,6-8,11,13,18,23,24,29,32,43,47,49). The decrease was significantly higher on flat mucosa (39-fold) than on the normal mucosa in children with IBS (11-fold, significant). CFUs on biopsies obtained 26 h after the last meal were not significantly different from CFUs contaminating saline inside the closed capsule after immersion in mouth saliva in validation experiments.

These biopsies may have been almost sterile before withdrawal through the mouth.

Sampling contamination from mouth bacteria was ruled out before biopsy by highly effective sterilization with HC1 0.1 N. Contamination of the closed capsule by saliva (see Validations) had a negligible influence (about 2%) on counts performed after 20 h of fasting. Permanent spillover of bacteria with fasting gastric juice from the upper respiratory tract into the duodenojejunum might be suggested by four papers (10,11,32,43). The 6

Bacterial growth on intestinal mucosa

21

subjects in all these reports were different from those of the present study in regard to country, age, background illness, presence of symptoms, fasting period, and gastric pH. The investigated gastric juices had a low pH, compatible with the common finding of sterility or few bacteria (less than 1000 bacteria per ml) (20,26,28,34,45). The samples of prepyloric juice were practically sterile in 18 of the present subjects investigated for validation purposes after HCl capsule sterilization and equilibration with juice in the antrum during biopsy. Moreover, bacteria spillover from the stomach could not explain the significant decrease in flora that was found 26 h after the last meal.

Upper respiratory tract bacteria are often brought down with ingesta into the duodenum at a concentration of over 105 per ml during meals (20). This wave of bacteria is cleared from duo-denojejunum luminal aspirates in normal adults after complete stomach emptying, within 1-2 h (19,20). These bacteria might accumulate on mucosa at the last meal, reach the concentration of over 106 within 20 h, and decrease to significantly lower concentrations between 20 and 26 h from the last meal in the investigated children.

Bacteria are able to multiply in the nutrients inside the small bowel, and rapid proliferation has been widely shown both in experimental animals and in humans after mechanical impairment to progression or adhesion to the intestinal surface (35). The deep location of many bacteria on the cell surface, in long chains or aggregates with the same morphologies as were observed in the present investigation, the significantly lower number of isolations when the CFU count was high, as well as the significant difference observed between children with celiac malabsorption and those (IBS) with normal mucosa, all support local proliferation on the mucosa during absorption time.

A positive correlation has been shown between carbohydrate malabsorption, severity of diarrhea, and the CFU count in the small intestinal juices of children with protracted diarrhea (1,29).

With a few exceptions, bacteria in the intestinal lumen tend to mirror in number and strain those found on the mucosa in simultaneous cultures of luminal aspirate and mucosal biopsy at the same level (22,51,55). Five studies were repeatedly conducted on the small intestinal juice at different levels or at the same level after a few days (14,23,37,41). Three were performed in healthy volunteer adults (37,41,51), and two in diarrheic children or adults (14,23). CFU numbers and bacterial types were similar in the luminal samples repeated in the same subject, despite normal renewal of small intestinal content within 90 min (36), or even less in diarrheic subjects (40,53,56). This consistency of the microflora in the renewal of luminal content confirms our finding of a rather stable colonization of duodenojejunal mucosa, and suggests both meal-to-meal accumulation and shedding of

22

Mario Ciampolini et al.

bacteria into the lumen, as also shown for uroepithelial cells and urine infection (17).

High numbers of bacteria were associated with flat and also normal duodenojejunal mucosa in children with recent intestinal symptoms, under usual feeding habits. The high number persisted for a period (20 h) that is longer than the usual inter-meal time for children having 4 meals a day. The number of bacteria on the mucosa depended on meals, because the number was significantly lower in children fasting for 26 h (i.e., those who did not consume a further meal, the last dinner).

What's the meaning of the rapid growth of bacteria on intestinal mucosa with meals? Is it generalized to the whole population? No. It was observed in people with frequent symptoms, such as diarrhea, abdominal pain, anorexia, or vomiting, and promotes development of these symptoms, as well as more complex pathological conditions. Mucosa-associated bacteria stimulate intestinal immune cells in correlation with the extent of bacterial growth (1,2,9,16,33,39,44,54,57). This stimulation accounts for two thirds, on average, of the global stimulation of the immune system (1,9). The intestinal microflora proliferation largely depends on absorption rate, and increases with persistence of nutrients in the lumen, as in celiac malabsorption. The absorption rate depends on insulin sensitivity, and decreases with insulin resistance (25). There is indirect evidence that subjects with IBS develop this diffuse condition of insulin resistance during symptomatic periods (12). High insulin sensitivity has to be maintained on these grounds to preserve an efficient and healthy immune system (12). Conversely, the suggested chain of events explains the many pathologic associations of insulin resistance.

Comment Normal, ‘healthy’ humans host 600 bacterial species in the colon and only a few in small intestine. The identification of a “pathogen” is sufficient to explain an illness (Salmonella typhi or cholera). Most species are innocuous, and seem to have no relation with the host, except for elaborating useful nutrients. Beyond pathogens and innocuous species, a third bacterial category affects mucosa. Immunogenic bacteria are controlled in their growth by mucosal ‘normal’ inflammation, IgA production and phagocytosis. At least half immune system is located in small intestine in humans, 1010 cells [61]. Production of IgA in small intestine is as high as 10 grams or 1017 molecules per day [62]. 24-74% of fecal bacteria are covered by ten thousands molecules of immunoglobulin IgA [62]. The mucosa in small intestine is a border of dynamic defense in permanent war against the content.

Bacteria on epithelial border show an aggressiveness that differs from a

Bacterial growth on intestinal mucosa

23

bacterial species to another, from a low to a high concentration, from a person to another and from a day to another. The inflammatory response within the mucosa shows differences that are consistent with differences in aggressiveness. Mucosa plasma cells produce IgA, IgM and IgG in the ratio 14 to 4 to 1 in the condition of healthy inflammation against a low aggressiveness [63], but the proportion of IgM and IgG increases with the increase of bacterial number and aggressiveness. A healthy intestinal inflammation is tolerogenic in humans [64], it devitalizes bacteria and removes bacterial, immunogenic mass from mucosa into blood and lymphatic vessels in small amounts [64 - 73]. Increase in bacterial growth on mucosa evokes reaction by IgG and IgM and cytotoxic lymphocytes that produce local damage by complement and reactive oxygen species (ROS) [64]. A mean of 15% (with high SD) of fecal bacteria are covered by IgG, and this immunoglobulin can fix the complement and directly produce destructions in bacteria and mucosa as well [62]. The destructive reaction is common though highly variable, and is additional to the healthy inflammation. The destructive development depends on meal by meal positive energy balance in blood and on insulin resistance and on associated long permanence of food in small intestine (Chapter 3, 4). Permanence of nutrient solutes in the small intestine is usually three hours, and the number of bacteria before a meal is below 105, though often as high as 106/g. Prolonged permanence of nutrients on epithelial border for 10 hours may bring about rapid, logarythmic bacterial growth, and the immune defense changes accordingly within mucosa. We saw a ten thousand bacterial increase in a day during continuous enteral feeding in a three months infant who had a surgical duodeno-stomy. The first count reported 105 bacteria from duodenal juice aspirated directly by fistula.

The infant appeared in good condition. After 24 hours the count in duodenal juice was about 109. The infant collapsed. A billion immunogenic bacteria per gram mucosa may extend over about 400 square meters of intestinal mucosa. This bacterial overgrowth produces few microscopic alterations in mucosa, but transfers this antigen amount into circulation, and produces a subclinical inflammation (pro-inflammatory state [65]): vascular damages, vessel thrombosis, poor immune efficiency, allergy, autoimmunity and a worsening of inflammation in respiratory mucosa and in other organs [73 - 79].

In minimally damaged tissues by mechanical stress like in joints, a subclinical inflammation may maintain long standing local inflammation or worsen current disease [80].

Subclinical inflammation follows a long pathogenic sequence. What does give rise to the sequence? We performed an investigation on intestinal bacteria to see if a meal might allow bacterial growth in wellbeing humans.

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Mario Ciampolini et al.

The investigation in children was possible because the Pediatric Gastroenterology of University of Florence received children with malabsorption, chronic diarrhea, i.e. functional disorders (irritable bowel syndrome, IBS), and/or malnutrition from Tuscany. In the seventies, antigliadin or anti-endomisium antibodies had not been yet developed to suggest celiac disease. Nutritional condition gave a hint to perform duodenal biopsy.

Children had last meal either 20 (from dinner) or 26 hours (from previous day lunch) before biopsy at 2 pm. The microbiological findings of this paper imply that clinically healthy children, indistinguishable from those who attend school and maintain usual activities, still have 106 bacteria per gram of mucosa 20 hours after last dinner, at 2 pm. These subjects would have consumed usual breakfast and lunch in presence of 106 bacteria or more, and this amount increased by one – two logarithms soon after each of the two meals. Thus a bacterial species may easily reach the level of 109 per gram of mucosa, that promotes subclinical inflammation, without symptoms.

We found a microbial rapid growth on mucosa, but it was no consequence of an ill state. We waited for recovery from symptoms before taking the biopsy. At this moment IBS children were clinically healthy, wellbeing. We considered these children at biopsy as «convalescent», like at school in the first one-two months after recovery from a bad bronchitis. This convalescent state coincides with the pro-inflammatory condition [65] that we have previously mentioned with the name subclinical inflammation (Chapter 1 and 4). The subclinical inflammation involves half human beings in our studies, but half humans are not ill. Half human beings have cardiovascular risks without being ill. The convalescent state has no influence on physiological functions like working and gym, but is associated with risks of relapse of bronchial disease like in our example.

Acknowledgements The authors wish to thank Sara Agostini and Lorenzo Ciampolini for work with statistics and computer processes.

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49. Penny, M. E., Da Silva, D. G. H., Mc Neish, A. S. Bacterial contamination of the small intestine with enteropathogenic Escherichia coli and other enteric infections, a factor in the etiology of persistent diarrhoea. Br. Med. J. 292: 1223-1226, 1986.

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50. Pineiro-Carrero, V. M., Andres, J. M., Davis, R. H., Mathias, J. R. Abnormal gastroduodenal motility in children and adolescents with recurrent functional abdominal pain. J. Pediatr. 113:820-825, 1988.

51. Plant, G. A., Gorbach, S. L., Nahas, L., Weinstein, L., Spanknebel, G., Levitan, R. III. The microbial flora of human small intestinal mucosa and fluids.

Gastroenterology 53:868-873, 1967.

52. Prizont, R., Hersh, T., Floch, M. H. Jejunal bacterial flora in chronic small bowel disease. Am. J. Clin. Nutr. 23:1602-1607, 1970.

53. Read, N. W. Diarrhee motrice. Chin. Gastroenter. 15:657-686, 1986.

54. Sunshine, P., Herbst, J. J., Koldovsky, 0., Kretchmer, N. Adaptation of the gastrointestinal tract to extrauterine life. Ann. N. Y. Acad. Sci. 176:16-29, 971.

55. Tomkins, A. M., Drasar, B. S., James, W. P. T. Bacterial colonization of jejunal mucosa in acute tropical sprue. Lancet 1:59-62, 1975.

56. Vassalllo, M., Camilleri, M., Phillips, S. F., Brown, M. L., Chapman, N. J., Thomforde, G. M. Transit through the proximal colon influences stool weight in the irritable bowel syndrome. Gastroenterology 102:102-108, 1982.

57. Walker-Smith, J. A. Toddler's diarrhoea. Arch. Dis. Child. 55:329-330, 1980.

58. Walker-Smith, J. A., Guandalini, S.; Schmitz, J.; Schmerling, D. H.; Visakorpi, J. K. Revised criteria for diagnosis of coeliac disease. Report of working group of European Society of Pediatric Gastroenterology and Nutrition. Arch. Dis. Childh.

65:909-911, 1990.

59. Walker-Smith, J. Variation of small intestinal morphology with age. Arch. Dis. Childh. 47:80, 1972.

60. Whitehead, W. E., Crowell, M. D., Bosmajian, L., Zonderman, A., Costa, P. T. Jr., Benjamin, C., Robinson, J. C., Heller, B. R., Schuster, M. M. Existence of irritable bowel syndrome supported by factor analysis of symptoms in two community samples. Gastroenterology 98:336-340, 1990.

61. Rothkoetter, H.J., Kirchhoff, T., Pabst, R. Lymphoid and non-lymphoid cells in the epithelium and lamina propria of intestinal mucosa of pigs. 1994, Gut, 35, 1582-1589.

62. van der Waaij,L. A., Limburg, P.C., Mesander, G. and van der Waaij, D. In vivo IgA coating of anaerobic bacteria in human faeces. 1996 Gut 38, 348-354 63. Brandtzaeg, P., and Baklien K. Immunoglobulin-producing cells in the intestine in health and disease. 1976, Clinics in Gastroenterology, 5, 251-269.

64. Brandtzaeg, P., Halstensen, T.S., Kett, K., Krajci, P., Kvale, D., Rognum, T.O., Scott, H. and Sollid, L.M. Immunobiology and immunopathology of human gut mucosa: humoral immunity and intreaepithelial lymphocytes. 1989, Gastroenterology 97, 1562-1584.

65. Reaven, G.M. The metabolic syndrome: is this diagnosis necessary? 2006, Am. J. Clin. Nutr., 83, 1237-1247.

66. Kinugasa, T., Sakaguchi, T., Gu, X. and Reinecker H.C. Claudins regulate the intestinal barrier in response to immune mediators. 2000, Gastroenterology, 118, 1001-1011.

67. Perez, P.F., DorĂŠ, J., Leclerc, M., Levenez, F., Benyacoub, J., Serrant, P., SeguraRoggero, I., Schiffrin, E.J. and Donnet-Hughes, A. Bacterial Imprinting of the

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Feminò, G. Nuove frontiere per l’asma: le endotossine batteriche. 2000, Ass. Med. Prev. Riabilitativa ‘Marco Taschler’ Agnano, Pisa.

Lovell-Smith, D. Perfect blood pressure. 2001, Penguin Books, Auckland, NZ, Smith, C.W. Diet and leukocytes. 2007, Am. J. Clin. Nutr., 86, 1257-1258.

Reaven, G.M. Role of insulin resistance in human disease. Banting Lecture 1988.

1988, Diabetes, 37, 1595-1607.

Bigorgne, A.E., Bouchet–Delbos, L., Naveau, S., Dagher, I., Prévot, S., Durand– Gasselin, I., Couderc, J., Valet, V., Emilie, D. and Perlemuter, G. ObesityInduced Lymphocyte Hyperresponsiveness to Chemokines: A New Mechanism of Fatty Liver Inflammation in Obese Mice. 2008, Gastroenterology, 134, 1459-1469.

Amar, J., Burcelin, R., Ruidavets, J.B., Cani, P.D., Fauvel, J., Alessi, M.C., Chamontin, B. and Ferriéres, J. Energy intake is associated with endotoxemia in apparently healthy men. 2008, Am. J. Clin. Nutr., 87, 1219-1223.

Schultsz, C., van den Berg, F.M., Ten Kate, F.W., Tytgat,G.N.J. and Dankert, J. The intestinal mucus Layer from patients with inflammatory bowel disese harbors high numbers of bacteria compared with controls. 1999, Gastroenterology, 117, 1089-1097.

Martin, H.M., Campbell, B.J., Hart, C.A., Mpofu, C., Nayar, M., Singh, R., Englyst, H., Williams, H.F. and Rhodes, J.M. Enhanced Escherichia coli adherence and invasion in Crohn’s disease and colon cancer. 2004, Gastroenterology, 127, 80-93.

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1998, Diabetes Res. Clin. Pract., 40, Suppl:S35-S42 Scrivani, S.J., Keith, D.A. and Kaban, L.B. Temporomandibular Disorders. 2008, N. Engl. J. Med., 359, 2693-2705.

Research Signpost 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

The Meal by Meal Dynamic Energy Balance in Blood: Habits & Risks, 2011: 31-48 ISBN: 978-81-308-0457-6 Editor: Mario Ciampolini

3. Absorption slowdown Mario Ciampolini

Preventive Gastroenterology Unit, Department of Paediatrics Università di Firenze, 50132 Florence, Italy

A fixed amount of energy intake is a wrong approximation for living.

Being aware of the many expenditure factors is useful to convince oneself of the need for meal by meal adaptation of intake to expenditure (Chapter 6). Moreover, being aware suggests self-promotion of increase in daily expenditure. This goal has diffuse consensus. People easily perceives personal improvements by physical activity, but are unaware about the major role of thermo-dispersion on expenditure, about changes of thermo-dispersion from one hour to another, and about need for promoting thermo-dispersion by multiple ways in our indoor living that is thermally moderate.

Thermodynamics, metabolic rate and insulin resistance affect absorption, two subsequent meal by meal balances cumulate all factors influencing all intestinal events after the first meal, and both might result to be highly positive. Energy imbalance by means of an abrupt decrease in metabolic expenditure might slow nutrient absorption and provoke long permanence of nutrients in the small intestine. We thus compared absorption in a warm environment (30 °C) with absorption in cold environment (18 °C for humans and 6 °C for animals).

Correspondence/Reprint request: Dr. Mario Ciampolini, Preventive Gastroenterology Unit, Department of Paediatrics, Università di Firenze, 50132 Florence, Italy. E-mail: mlciampolini@fastwebnet.it

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Influence of environmental temperature on intestinal absorption of xylose in rats in vivo Oral tests with D-xylose in normal children in our hospital (unpublished results) gave rather low blood levels as compared with normal averages in northern countries (l , 2).

Since in our hospital the tests were performed at an environmental temperature of 28 °C we decided to investigate whether in animals the absorption would be greater in a cool environment than in a warm one.

We have chosen 28 pairs of female rats (Wistar, weight 70 to 200 g) in which both components consumed the same quantity of food during three days, repeating the selection for the second time immediately before the test.

The partners were then divided into two groups, the first kept in an environment at 31 °C and the other at 6 °C; these were again subdivided into five groups each: the first was kept for 96 h in the established temperature, the second for 24 h, the third for l0 h, the fourth for 4 h, and the fifth for l h before the administration of xylose; all of them remained in the established temperature for 90 min after the reception of xylose.

Figure 1. Percentage excess of absorption in cool environment (6 °C) over absorption in warm envvonmerzt (31 °C) of xylose administred intragastrically to rats, (5 paired groups) Vertical bars: standard error of the mean (SEM). In parenthesis: number of animal pairs. P values calculated by paired t test.

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After a 7 h fast the animals received 1.1 g of soya oil by gastric tube. Ten h later they received 100 mg of xylose in a 5% solution, also by gastric tube.

For 90 min the animals were left to absorb the xylose, then they were beheaded, the contents of the stomach and the colon were washed out with 20 ml of saline and the contents of the small intestine with 40 ml of saline.

After having measured the volume of the washing liquid, we analysed the xylose concentration (3).

In the next experiment 4 pairs of rats (after a 7 h fast) received atropine (1 mg orally) mixed with 1.1 g of soya oil. The partners were then put for 10 h into environments kept respectively at 31 °C and 6 °C; after this period they were given by gastric tube 1 mg atropine and 100 mg of xylose.

The quantity of xylose found in the colon was very small (0.7-0.9%); therefore we considered the quantity of xylose administered to the animals, minus its quantity found in the digestive apparatus as the intestinal absorption.

With the exception of the animals treated with atropine, the quantity of xylose which left the stomach in the cool environment (89.1%) was almost the same as in warm environment (86.2%).

As shown in the figure, the absorption rate has risen significantly after the sojourn in a cool environment. The greatest rise (23.9%, P < 0.01) resulted after a 10 h period, and only an insignificant one after a 1 h period.

In the second experiment the absorption in the cool environment was almost the same as in the warm environment, and precisely 7.0 ± 5.1% (SEM) (P > 0.1) inferior; the small difference was due to correspondingly diminished emptying of the stomach. This result proves that atropine nullifies cholinergic (vagal ?) stimuli, which cause the rise in the absorption in the cool environment.

Influence of environmental temperature on xylose absorption in man Oral tests with D(+)xylose in normal children in our hospital, at an environmental temperature of 28 °C gave rather low blood levels compared with normal values obtained in ventilated rooms at 24 °C (4). Furthermore, xylose absorption decreased in rats at an environmental temperature of 31 °C, compared with observations made at 6 °C (Previous article). We have therefore studied urinary xylose excretion at an environmental temperature of 18 and 28 °C in 18 normal adults, aged 25-45 years.

After an overnight fast, every subject received 40 grams of a wheat flour cake and was placed for six hours in a room whose environmental temperature was 18 °C, After exactly four hours he received 0.4 grams

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Figure 2. Urinary xylose excretion. Shaded columns represents the result of two hours xylose urinary output in the warm environment (28 °C) as percentage of the output in the cool environment (18 °C) in the same subject following oral xylose administration, Each adjacent hatched column represents results on the same subject of two hours xylose urinary output in an equally warm environment as percentage of the output in an equallv cool environment following intravenous administration. On the right are the means ± SEM.

D(+)xylose per kg body weight in 10 % solution by mouth. Urine was taken just before and exactly two hours after ingestion of xylose; the volume was measured; a sample was stored at -20 °C and its xylose concentration was measured by the method of Roe and Rice (3).

After 48 hours the experiment was repeated at 28 °C and the same subject with the same clothing ingested the same breakfast, stayed at 28 °C for four hours, and repeated the same two hours xylose absorption test. At intervals of 48 hours the experiments were again repeated at 18 °C and at 28 °C in ten adults, by administering, over 100 minutes intravenously 0.1 gram xylose per kg body weight in 200 ml distilled water. At 28 °C care was taken to make the subjects ingest, after the xylose, about the same volume of water as that of xylose solution. At 18 °C after the oral ingestion 10 out of 18 had diarrhoea and two had abdominal cramps. At 28 C after oral ingestion 8 out of 18 had headaches, 4 anorexia, 2 abdominal cramps. In the i.v. experiments there were no complaints.

Only very small traces of xylose (0-0.1 mg/ml) were found in the urine samples before xylose ingestion. Average urine volumes at 18 °C were 162.0 ml and at 28 °C 162.6 ml in the oral experiments, whereas they were respectively 248.5 and 417.1 by vein. There was no correlation between urinary volumes and urinary xylose excretions (ordinal coefficient of Spearman P > 0.1).

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As shown in the figure, after administration by mouth the average xylose urinary excretion at 28 °C was 85.1 ± 4.9 (SEM) per cent of the value at 18 °C; 15 out 18 subjects recorded decreased excretion; the difference was significant (paired t test, P < 0.001). After i.v. administration, the average xylose urinary excretion at 28 °C was 119.4 ± 10.2 (SEM) per cent of the value at 18 °C; 7 out 10 subjects recorded increased excretion; but the difference was not significant (P > 0.1).

These data show that intestinal absorption and not renal clearance is decreased in the warm environment; this finding confirms the results of our experiments on rats (2) and demonstrates in man that increases in the environmental temperature as short as six hours and likely to be found in temperate climates, may decrease xylose absorption.

More work must be done to relate these findings to possible geographic or day to day variations of nutrient absorption and even more to relate them to intestinal complaints.

Comment We published the following figure and related data in Italian [4].

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The article [4] included subjects and data that we reported in the paper on man in I.R.C.S. 1975 and data from 5 additional adults. The 5 subjects performed the experiment at 33 °C at the high environmental temperature and at 18 °C at the low one. All protocol followed the report on I.R.C.S. 1975.

The figure adds an important finding. Decrease in intestinal absorption is progressive by increasing environmental temperature and absorption decline accelerates beyond 28 °C [4].

The mucosal surface in the small intestine cannot be sterilized, and is poor of oxygen, rich of nutrients, and has suitable osmotic pressure, pH and temperature for bacteria growth. Rapid absorption has a major role in protecting mucosa. Microflora grows until nutrients remain inside the small intestine and bacteria double every 10 – 20 minutes. After meals, we have found a significantly higher growth on flat, absorbing mucosa of celiac children compared to mucosa of normal children. We suggest that flat mucosa slows absorption allowing rapid bacterial growth. Increase in bacteria from one million per gram of mucosa to one billion per gram requires ten duplications. Nutrients remaining only three hours beyond usual permanence in small intestine are sufficient to allow this overgrowth. An unforeseen slowdown of absorption can produce an unpredictable bacterial concentration on mucosa.

We once infused a barium meal containing few calories, into the duodenum of a 14 years old boy, who did not consume food in the previous day and who resulted clinically healthy. The marker arrived to the middle of the large intestine within only five min. An Australian study assessed 50% emptying time of the small intestine by using a wholly scintigraphic technique in clinically healthy adults who complained functional disorders [5]. Subjects consumed a light breakfast of about 420 kcal. Most subjects showed a median half emptying time of 78 min, but a minority showed a median half emptying time of 256 min. The transit time in small intestine depends on energy content of meal. In dogs, transit time is associated with the square root of energy content [6]. Absorption rate by surface unit is constant [7], and thus global absorption rate increases when transit time is rapid. In humans, whole (100%) meal transit time is 168±14 min (SEM) after 220 kcal and 368±36 min after 880 kcal [7].

We treated recurrent diarrhea in two year old infants to stop both microflora overgrowth and overstimulation of intestinal mucosa [8 - 10]. We believe these events are a consequence of absorption slowdown for persistent positivity in meal by meal balance. A long pathogenic chain, unfortunately.

In our controlled investigations, diarrhea relapses definitively subsided after significant decrease of energy intake of about 25% - 30% 10]. Infants improved their nutritional state [10]. On the basis of this controlled

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investigation and a few other investigations in adults (Chapter 7) we consider this intestinal functional disorder as a consequence of persistent positivity in meal by meal balance that is the way to insulin resistance. Persistent positivity acts by means of events of absorption slowdown and consequent additions of microflora growth.

A number of researchers experimentally confirmed the slowdown in this long factorial chain. The researchers infused glucose IV in opposition to saline infusion in healthy adults. During infusion, they administered a meal at usual mealtime. Subjects receiving glucose consumed the offered meal despite high BG [11]. Under glucose infusion, digestion and absorption slowed down in comparison with saline [12 - 16]. The emission of pancreatic enzymes and bile salts, the small intestine motility and absorption were lower when BG was high. Also a moderate meal slowed down intestinal progression. One meal taken when BG was 150 mg/dL was sufficient to produce relapse in children with recurrent diarrhea or malabsorption [10, 17].

Our curative intervention (Chapters 5, 6) eliminated forestalling food request and premature food administration. This elimination abolished any positivity in meal by meal balance of energy, although infants grew up regularly [10]. The meal by meal balance became null rather than negative, except for few initial days [10]. The null meal by meal balance included the increased amount of fat that insulin resistance delivered to blood from adipocytes (Chapter 8) and those produced by all particular conditions that we are now listing.

Thermodynamics Mammals have an intake and an expenditure up to ten times those of reptiles to maintain constant body temperature against a variable climate and lower environmental temperature than skin temperature [18]. When animals run, the rate between mammals and reptiles decreases to about 7 times.

Before feeding, Burma python shows this difference from a mammal. After ingestion of a lamb, the reptile increases its energy emission almost to the level of mammals, and returns to the pre-meal value after about a month without food [19]. In humans, energy expenditure depends on energy availability as well, without such huge difference, only ±15% of resting metabolic rate, although the value has been insufficiently assessed in conditions of meal by meal null balance. The difference between reptiles and mammals show us that energy expenditure in mammals is mainly devolved to maintain body temperature at 37° C against a variable gradient. Yet, energy expenditure for constancy of body temperature has huge variations. The human body loses four times energy at 8 C° compared to 27 C° [20].

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Emission of body energy ceases at 30 °C at humidity saturation [21]. In opposite circumstances, immersion in cold water increases thermo-dispersion 25 times compared to the same gradient in air, so survival becomes poor [22].

Thermo-dispersion in a cold climate increases energy expenditure, energy absorption, intake, and hunger [22]. Thus, a cold environment tends to be protective against intestinal microflora growth by increasing absorption and flow rate of nutrients. High environmental temperature sufficiently prolongs high BG in time after last meal either requiring suppression of a meal or promoting insulin resistance [23] and intestinal microflora growth.

Compensation by fat deposition and ‘well being’ maintenance is possible by most humans, except for lipodistrophy. Any event of meal by meal positive balance promotes insulin resistance increase that is usually negligible but not desirable. In conclusion, we should be aware of effects of thermal environment as much as possible, but we do not suggest to substitute physiological signals of achieving the meal by meal null balance (of exhaustion of previous meal) with calculations on thermal environment at meals (Chapter 5). What we suggest is to plan intake after arousal of Initial Hunger (Chapter 5) on predictable expenditure by coarse approximation: two apples for dinner before a night in overheated hospital as opposed to one thousand calories swimming in cold water.

Heat loss depends on temperature gradient between body and environment, but this is only one of 6 factors. Conduction, convection, perspiration (i.e. evaporation), irradiation and dressing influence our energy expenditure [24 - 25]. Conduction allows a loss of heat from skin to the air near the skin that acquires the same temperature of the skin. For the human body, relative humidity is important. With this term, we indicate the amount in air in percentage of the amount of water at saturation. Humidity potentiates the effect of warm and cold environment. Relative humidity at a temperature below 18 °C increases the thermal losses as a general effect on electromagnetic waves. Over 18 °C, relative humidity changes the sign of the correlation. High relative humidity impairs thermo-dispersion to complete inhibition at saturation at 30 °C. The division at 18 is rough, it changes depending on the cofactors. Evaporation is permanent like life, we are immersed in a thin water film (perspiratio insensibilis). The film is greater on mucosa. Thirty six liters of water pass from blood to mucosal surface in the alimentary canal in a day, and this amount is soon reabsorbed. By breathing, we emit vapor even in a cold environment and below 0 C° and in fog. At a certain combination, the warm and humid environment provokes decrease in energy metabolism, as we already said for dry hot climate. We report suggestions for home environment by the metereologic center in Florence:

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Relative humidity of 40%, movement of air between 0.1 e 0.2 m s-1 (= 0.36 â&#x20AC;&#x201C; 0.72 km/h), temperature between 19 and 22 °C. Higher relative humidity depresses metabolism in warm environment and increases cold sensations in a cold environment suggesting ambient heating. Over 60%, humidity promotes molds and bacteria growth, as well as risk increase (subclinical inflammation) [23 - 25]. In Florence, monthly means in the year 2009 were between 65% e 78%.

Dressing increases the thickness of insulating air and convection decreases the thickness. Convection is a loss of heat by movement of air.

Large rooms and high ceilings have more air movement than small rooms.

Outdoors staying and windy weather are effective by thinning the immobile thickness of air over skin, thus potentiating conduction and evaporation. A ventilated, dry environment may allow better life. Briefly, people (we should better say hours) differ in expenditure for different lifestyles, for amount of walking and outdoor hours, for dressing, habituation to indoor air movement (either open or closed window), home exposition to either sun or wind, living in either a coastal oceanic or continental climate, and either in mountain or at the sea level. Differences in lifestyle may allow over ten times interindividual differences in daily intake, and are much more effective on expenditure than inborn factors.

Acute inflammation and insulin resistance Monocytes/macrophages contact bacteria and viruses during an infection to capture them in a vacuole. This action is associated with release of cytokines that are active on hypothalamic centers [26]. The subsequent events are symptoms of illness with inter-individual differences in their full development. The subject develops fatigue, hypotension, anorexia, sleepiness, increase in body temperature (fever) and the insulin resistance complex: high fatty acid release from adipose tissues and high BG. BG remains sufficient up to the end of illness despite poor or no intake. Fever is always associated with decrease of intestinal absorption, which may develop in absence of fever [26, 27]. Food may be consumed in spite of anorexia, and arrives in the small intestine that functions poorly. Microflora takes advantage from prolonged persistence of nutrients inside the lumen. Spots of bacteria expand on mucosa. Mucosal invasion is rapidly stopped by prompt killing of invaders. Bacterial antigens and endotoxins invade circulatory system and raise a subclinical inflammatory state (Chapter 4) that slows and aggravates the main infection in a vicious circle. The physician may break this vicious circle by specific therapy. The patient may not ask for food: complete abstinence from food may be fruitful for a few days until BG

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remains over 80 mg/dL and systolic pressure over 85 mm Hg. A useful experiment shows the negative effect of maintaining usual intake during illness. A number of mice received the 50% lethal dose of bacteria. Part of the mice consumed poor amounts and lost weight. These survived. The others maintained their weight and died [28]. During infections, negative body balance is associated with meal by meal BG positive balance and this paradoxical association is useful for recovery. During fever, blood automatically (i.e. by hormonal changes) has large provision of fatty acids, but requires Na, Cl, K and water: vegetal broth, i.e. filtered water of cooked carrots, celery and a spoon of rice. Abstinence from food for two days is easy and without untoward consequences. We suggest this procedure or a modest decrease in intake also in local inflammation, like torticollis, knee or lumbar ache, headache, abdominal pain, which we consider as a local expression of subclinical inflammatory state (Chapter 4). On the other hand, infection may persist for months and suspension or reduction of meals may become unsustainable.

Healthy humans have to promote increase in energy expenditure by physical exercise, cool and ventilated environment, light dressing, outdoor living. We overthrow this strategy during acute respiratory illness, and encourage rest in a warm indoor ambient from the early hours of infection, when the patient may only perceive a little reddening of eyes and modest nose inflammation. We suggest indoor rest and warm ambient before the development of local pain, cough, and general symptoms like weakness.

People hardly follow these suggestions. Occasionally, we observed recovery from cold by intense physical activity like two hours running.

Speculation on chronic inflammation, insulin resistance and malnutrition development Chronic infections are frequent in old people. Elderly people have little pain in the throat, modest cough and little complaints like fatigue, and do not stop usual activity to rapidly recover from a flu-like illness. Sometimes, conditions become worse after weeks. The supervened infection worsens a subclinical inflammatory state that already pre-existed at lower intensity before infection. If intake and activity have not been promptly reduced [28], the inflammatory state worsens further. People lose weight, especially fatfree mass, bone and muscle. Experimentally, feverish subjects received IV 2000 kcal/day. After a week, skin-fold thickness showed a significant increase without avoiding loss of muscle and bone mass in comparison to control subjects who received a saline solution [29]. A tuberculosis patient

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represents a typical person who is affected by malnutrition, even by eating as much as possible. Unfortunately, increase in fat tissues is associated with gradual development of insulin resistance that increases risks (subclinical inflammation or pro-inflammatory state). The infection does not subside.

This patient needs promotion of rapid intestinal absorption to stop intestinal immune stimulation. During Summer, sojourn in mountain and long walks have been useful. Outdoor moderate physical exercise is essential.

Accurate adaptation of intake to variable expenditure is the solution (with antibiotics).

By these infective and inflammatory mechanisms, about one billion people are currently affected by malnutrition in present world because of malaria, parasites, chronic hepatitis, tuberculosis, celiac disease, urinary diseases. Also AIDS is very well known. Thus, malnutrition usually requires treatment of these illnesses, which is much more difficult than food provision. How many people with subclinical inflammation do we see every day? Nobody can encourage them to eat less than usual amount at price of lowering body weight. This responsibility may be taken only by the subject, if he/she knows himself/herself and his/her own illness, development of insulin resistance and diffuse inflammatory states. Physicians may be of help in many ways but cannot take the initiative. Does health in a population depend more on diffuse knowledge on illnesses and eating than on money to buy drugs and medical devices?

Physical exercise Muscles contain an important nutrient reserve, about 6000 kcal [30]. The exercising muscle breaks down a larger amount than the one that is completely oxidized. During anaerobic physical activity, production of lactic acid is abundant, and lactate, the small molecule, escapes from muscles into blood to be recovered by liver, reconstituted to glucose and released into blood. BG availability increases in blood and the increase is in proportion to intensity and time length of activity. Home work and sedentary activity is poorly effective on expenditure, 1.3 - 1.5 times as much as resting metabolic rate [31]. After cessation, walking or cycling for half an hour elevates BG and delays hunger arousal for half an hour or more. Running for half an hour delays hunger for three quarters of an hour [32]. Young subjects occurred in our Gastroenterology Unit who practiced three hours of intense activity like cycling or running in cold environment without breakfast in morning. They had no perception of hunger during activity. After three hours, hunger sometimes occurred even in trained subjects. After no consumption of

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breakfast or other snack in the morning, deep and persistent weakness ensued without being alleviated by a meal. In general, physical exercise lightly increases subsequent meal consumption. During meal, absorbed nutrients are taken up by depleted muscles, and this increased uptake represents an increase in insulin sensitivity.

Menstrual cycle In women, energy expenditure has a minimum on the 7th day after the onset of last menses [33 - 36]. On the14th day, progesterone increases, and so does energy expenditure and energy intake. Toward the end of the cycle, women confusedly perceive hunger and BG lowering. They eat more than expenditure and insulin resistance increases by 15% of the value at cycle onset [33 - 36].

Old age Metabolism declines in old age: IV infusion of triolein and measurement of breath carbon dioxide for 8 hours showed oxidation decline by 23% between 17 and 65 years, and 25% between 65 and 87 years [37]. The decline may depend on decrease of oxidative metabolism in all tissues. Uncoupling proteins 1, 2 and 3 decrease in mitochondria, in association with decrease of energy destination to dissipation [38]. Production of ATP and energy for cell function have no change. Elderly people revert their own metabolism toward that of reptiles, and feel cold at higher temperatures than young people do, due to decrease in production of metabolic energy. At the same time elderly people need to lower energy intake, but may have no information or do not notice the metabolic change. No adaptation of intake to lower expenditure means developing diabetes. We can contrast metabolic regression by physical activity. Heavy physical activity for half an hour every day increases about 250 grams lean body mass per year. Muscles, bones, arterial diameter, capillary network increase at same time. These improvements may fail after the age of 80 [39]. These observations imply that country people in Tuscany who worked on land without motor utensils, gained over 10 kg lean body mass over the amount that may be gained by an informatics worker who worked indoor all lifelong. Long endurance of physical activity in outdoor, ventilated, cool environment promotes meal by meal achievement of null energy balance in blood. Regular achievement of null balance contrasts development of autoimmune markers, a basic mechanism of aging [40].

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Stressful states Acute stress is unexpected, external and almost instantaneous, and is elaborated with different, subjective intensity toward depression or anger.

The stress state elevates adrenalin, cortisol and BG for a few hours or longer, and during this time the stressed subject presents anorexia or increased eating, although gastric motility always decreases [41]. The stressful condition implies polarized attention to the anxiety factor and automatic responses to problems that do not depend on stressing factor, no perception of personal dynamic balance and of high BG at mealtimes. In this psychological sequence consists the primum movens of the vicious circle depicted in Chapter 4. Stressed people may eat as usually, and even more. Automatic eating means weight increase in subjects capable of fattening [42], and rapid development of insulin resistance and of associated diseases in people genetically incapable of weight increase [43]. Automatic eating implies slow absorption, pro-inflammatory state, change in weight, vascular disease and infarction, schizophrenic or depressive recurrences, relapses of intestinal disorder (Chapter 4). Stress is largely liable of human sufferings!

It is difficult for those near the patient to break the vicious circle. Only the affective relation of the patient to relatives or friends might allow success by external intervention. We can see here the role of Mediterranean and western objectives of confidence. Maintenance of self confidence and on nearby people contributes to resilience. This confidence coincides with the subject’s appreciation of his/her own and others’ enterprise and with enjoying life. Creating joy by performing different activities like singing, reading, exploring, physical exercise in children is the main objective for parents and teachers, and why not, for governments, and the American Constitution took this aim up.

Interferences with BG measurement In hospital, the laboratory measured BG just after patients’ BG estimation (Chapter 5). The estimation error was the difference between estimation and measurement. During training, we observed an increase in this estimation error during 30 – 90 minutes after physical exercise, after food tasting, after intake of one – two grams of food, after indoor entry, after stop in ventilation in a closed ambient, after increase in wearing or after a stressful event, or during a feverish or not feverish infection. The listed events elevate BG from about an hour, two hours or few days, but subjects in training fail the elevation at estimation. Subjects must omit BG measurement in all these circumstances and busy people must postpone training. A significant increase

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in error was unfortunately permanent despite of any training after 60 years of age in comparison with younger ages (unpublished findings).

Empty stomach Good functioning by small intestine means rapid absorption, low bacterial growth on mucosa, no or modest immune stimulation in mucosa and finally poor systemic immune stimulation. Rapidity largely depends on the choice of the consumption time. This is a metabolic time, measured by BG decrease, that is associated with many physiological changes, for example, emptying of small intestine, start of peristaltic waves in duodenum, decrease of insulin in bloodâ&#x20AC;Ś. In experimental animals, a test meal by gastric probes has been investigated for an hour in a comparison between rats not fed for three hours and fed rats. At the end of the experiment, i.e. after one hour from administration, not fed rats had almost completed absorption, whereas fed rats still presented half meal in small intestine [44]. In human experiments, emptying of small intestine coincides with perception of hunger [45, 46]. We thus investigated sensations of hunger in relation to BG and meal onset (Chapter 5). Before reporting this investigation, we have to complete the long pathogenic chain that began with hunger forestalling by premature intake.

Central Nervous System (CNS) and small intestine Chapter 4 deals with translocation and the effects of translocation of bacteria and bacterial products from luminal side of small intestine into mucosa and blood stream and the entire body. The diffuse presence of endotoxin and bacterial products in body tissues activates mast cells and monocytes and this diffuse activation configures the condition of subclinical inflammation. We have found the primum movens in the moment of decision on intake. The intake that covers inter-meal expenditure is always approximate and may be dangerous even without any ill manifestation. In our studies, habitual unhealthy choices involve about two thirds of population (Chapters 7 and 8). During stress, attention to eating weakens and this multiplies and magnifies failures in venturing null meal by meal balance.

During stress, additional energy provision to body pushes meal by meal balance in blood toward positivity. This positivity slows absorption (Chapter 3). As we have seen in Chapter 2, healthy people presents growth of this or other bacterial species on mucosal surface. About one-hundred species are immunogenic in human intestine. One or two of these may rapidly grow after an unbalanced meal especially in a condition of stress. A billion of immunogenic bacteria per gram of mucosa (the concentration of a broth-

Absorption slowdown

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culture), evokes an inflammation that may remain subclinical or become devastating. This inflammation is tolerogenic in mucosa and develops mainly in blood and body tissues. How is possible that a human being can survive stress?

I welcome Dr. Feminoâ&#x20AC;&#x2122; and his Chapter for reporting huge evidence on bacteria products translocation from mucosal surface to blood and body tissues and evidence on development of subclinical inflammation, and for reporting current psychological explanation of this phenomenon. Man has currently an excessively intense emotional life, hence a wide evidence on the association between altered activity of nervous endings plus the increase in corticotrophin releasing factor (CRF) and derangement of mucosal permeability. Here is the core of our research: association is not primum movens. Modern man is not a victim of his furious activity. Man is a victim of nutritional abundance, a blessed achievement per se. Insulin resistance is the measure of a personal harmful abundance in eating and in nutrient provision to body. Increase in immunogenic flora on mucosal surface of small intestine is the harmful consequence of insulin resistance. At stressful moments, CRF and nervous endings only multiply and magnify intake errors and risks in an environment of nutritional abundance [47].

Man needs to get aware of the dilemma. Findings here collected point that we need to adapt to the biochemical and biophysical changes of internal and external environment. During stressful moments, including fever, we need to stop eating! Huge evidence on prevalence of insulin resistance in several populations and its associations with vascular, malignant and immune diseases are sustaining this conclusion [48]. Maintaining high blood glucose (HBG, Chapter 7) is sufficient to produce subclinical inflammation that does not develop during stress by eating suspension.

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30. Corcoran, M.P., Lamon-Fava, S., Fielding, R.A. Skeletal muscle lipid deposition and insulin resistance: effect of dietary fatty acids and exercise. 2007, Am. J. Clin. Nutr., 85, 662-677.

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32. Wuorinen, E.C. Varied Exercise Intensity and The Effects on Appetite and Food Consumption in Lean Young Women. 2008, Appetite, 51, 410.

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42. Flaa, A., Sandvik, L., Kjeldsen, S.E., Eide, I.K.,and Rostrup, M. Does sympathoadrenal activity predict changes in body fat? An 18-y follow-up study.

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Research Signpost 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

The Meal by Meal Dynamic Energy Balance in Blood: Habits & Risks, 2011: 49-55 ISBN: 978-81-308-0457-6 Editor: Mario Ciampolini

4. Subclinical inflammation Giovanni Feminò

Director, Immunology Division, EMC – Firenze, Via Alamanni, 35 - 50123 - Firenze

Abstract. Persistent biological stimuli and/or psychophysical stresses modify activity of monocytes, macrophages and mast cells, and together alter the neuro-endocrine system. These disorders increase intestinal permeability. Bacterial biofilms may develop inside the alimentary canal and produce endotoxins that invade blood and all tissues. Immunogenic bacteria (Chapter II) induce a huge biological pressure on human immune system and a deep functional alteration. The invasion of body tissues by bacterial products and endotoxins sustains subclinical inflammation and causes the slow progression of many chronic diseases. Thus, body tissues develop a pro-inflammatory state (subclinical inflammation, a synonym) that is sterile, ineffective and dangerous for body tissues in the intestine and elsewhere.

Activation of immune cells and mast cells Bacterial products increase mucosal permeability and persistently and systematically activate monocytes, macrophages and mast cells, [1 - 13].

Dendritic cells, mast cells and resident monocyte-macrophages largely perform surveillance of bacteria and bacterial products [14]. These cells rule the inflammatory response against external molecules, including bacterial Correspondence/Reprint request: Dr. Giovanni Feminò, Director, Immunology Division, EMC – Firenze, Via Alamanni, 35 - 50123 – Firenze, Italy. E-mail: feminog@yahoo.it

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products [15]. Lymphocytes join monocytes and mast cells in subsequent adaptive immune responses. Mast cells regulate the immune response against allergens, bacterial products, infectious agents, and regulate immune and neuro-endocrine functions [16, 17]. Mast cells represent 2% â&#x20AC;&#x201C; 3% of all cells in lamina propria, and recognize bacteria by means of many membrane receptors like the Toll-like receptor 4 that is specific for the endotoxin. After recognizing immunogenic bacteria, mast cells promptly raise an innate immune response and attract neutrophils and lymphocytes [18]. Mast cells release pro-inflammatory and anti-inflammatory substances regulating the influx of immune cells into the inflamed area. In a subsequent period, cytokines from mast cells raise an adaptive response [18]. In inflammation, mast cells have a central regulatory role. These cells can amplify or suppress inflammation by either promoting or inhibiting the influx of neutrophils and of lymphocytes. Mast cells can influence peristalsis and the functions of epithelial cells, and maintain bidirectional communication with local nervous and endocrine systems [18]. In a subsequent challenge, bacteria or bacterial products stimulate the adaptive immune response that elaborates specific antibodies that increase activation of mast cells [18]. Mast cells thus keep up inflammation and damages to the barrier function of the intestinal mucosa [15].

Peripheral administration of lipopolysaccharides (LPS) in rats provokes activation, degranulation and an increase of proteases in intestinal mast cells, provokes increase in paracellular permeability in small intestine epithelium and a consequent increase in bacterial translocation. Drug stabilization of mast cells prevents these events [19]. No demonstration supports such capability in other inflammatory cells.

Damage of intestinal nervous system Neurons in the enteric nervous system are located close to mast cells, epithelial and immune cells to allow rapid communication. All intestinal inflammatory cells, i.e., mast cells, dendritic cells, lymphocytes and macrophages have receptors for neurotransmitters of nervous terminations, vice versa, enteric neurons respond with neurotransmitters to cytokines released from inflammatory cells. The suffering of one component affects the function of the others. Enteric nervous terminations can influence inflammation by releasing P substance. This substance activates receptors on mast cells and on other immune cells [20].

The bacterial presence in mucosa [21, 22] (translocation) and the presence of neutrophils and eosinophils [23 - 25] damage, among many other damages to mucosal structures, also the enteric nervous system. Mast cells

Subclinical inflammation

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direct location and activity of inflammatory cells that provoke nervous damage. Experimentally, mast cells can reduce survival of neurons of smooth muscle [26]. A stressful or emotional state may directly alter mast cell response by intense activation of enteric nervous endings [26].

Enteric endocrine involvement Enterochromaffin cells (E cells) are abundant in the intestinal epithelium of small intestine. These cells produce and store serotonin and contain over 80% of body serotonin. E cells respond to the presence of bacteria and bacterial products [27]. The inflammation of intestinal mucosa is associated with an increase of the number of E cells and of serotonin release. High levels of this mediator affect the enteric nervous system and epithelium [28, 29]. A large number of evidence show an association between the emotional state of CNS and high levels of serotonin and CRF. These factors activate mast cells, alterate motility, secretion and absorption in mucosa. As a consequence, bacterial products and endotoxin invade the mucosa producing mucosal inflammation. The inflammation may be either mild, like in functional disorders, or heavy, like in inflammatory bowel disease [30 - 32].

CNS can modulate immune function by efferent pathways [33]. Vagal afferences can modulate mood and behavior [34, 35]. This evidence proves the existence of a derangement of the brain â&#x20AC;&#x201C; gut axis in mild (and heavy) intestinal mucosa inflammation [36]. An activation of body immune system by bacterial products and cytokines, serotonin and CRF persists in the body for at least one month after intestinal recovery from mucosal inflammation [37 - 44]. The activation of the immune system i.e., a subclinical inflammation may persist longer through the mentioned vicious circles of the brainâ&#x20AC;&#x201C;gut axis or through relapses of microflora overgrowth or intestinal infections [37 - 44]. The liver eliminates bacterial products and endotoxins, although insufficiently. An activated immune system in the body eliminates slowly remaining bacterial products in a month or two [37 - 44]. These bodily immune events configure a subclinical inflammation throughout body tissues.

Activated mast cells and activated monocytes-macrophages guide the subclinical inflammation. These cells have the receptor TLR4 on membrane and this receptor is specific for the endotoxins that are pervading body tissues. Activated mast cells and activated monocyte-macrophages decrease the production and release of interleukin-10 [43]. A lack of this suppressive cytokine and a sustained activation of mast cells and monocytes amplifies and prolongs all inflammatory processes that arise everywhere. These facts, i.e., the amplification in the number of cells and the prolongation of the process in time, involve even neglected processes in the body like eliminating

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small traumatic necroses in joints and small infections in the respiratory tract.

The ensued processes are ineffective in the elimination of locally initial stimulating events, e.g. a respiratory infection [36 – 38, 41 – 44]. These facts are associated with an increase in CRF and the consequent depression of small intestinal functions including slowdown of absorption and promotion of bacterial overgrowth on mucosa (Chapter 3, [41 - 44]).

In conclusion, an acute distress puts great amounts of energy (fatty acids and glucose) into circulation. A positive meal by meal energy balance in blood forage bacteria that reach a concentration of billions per gram of intestinal mucosa. 80% of species are commensal and innocuous but others are immunogenic (Chapter 2). Bacterial products invade mucosa and provoke mast cell activation and increase the ‘normal’ mucosa inflammation. Further positive meal by meal energy balance and vicious circles in brain–gut axis may aggravate or prolong the intestinal mucosa disorder.

The alteration of intestinal, immune, neurologic and endocrine systems sustains the condition of “low grade systemic inflammation” or “subclinical inflammation” or “proinflammatory state”. This condition may regress in one – two months (convalescence time) as well as persist and worsen through time.

Thus subclinical inflammation may promote atherosclerosis, steatohepatitis [44], deterioration by ageing and some kinds of cancer [45 - 48].

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38. Li, X., Chen, H., Lu, H., Li, W., Chen, X., Peng, Y., Ge, Z. The study on the role of inflammatory cells and mediators in post-infectious functional dyspepsia.

2010, Scand. J. Gastroenterol.,May, 45(5), 573-581.

39. Wallon, C., Söderholm, J.D. Corticotropin-releasing hormone and mast cells in the regulation of mucosal barrier function in the human colon. 2009, Ann. N. Y. Acad. Sci., May;1165, 206-10.

40. Larauche, M., Kiank, C., Tache, Y. Corticotropin releasing factor signaling in colon and ileum: regulation by stress and pathophysiological implications. 2009, J. Physiol, Pharmacol., Dec,60 Suppl 7, 33-46.

41. Reaven, G.M. The metabolic syndrome: is this diagnosis necessary? 2006, Am. J. Clin. Nutr., 83,1237-1247.

42. Smith, C.W. Diet and leukocytes. 2007, Am. J. Clin. Nutr., 86, 1257-1258.

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43. Bigorgne, A., E., Bouchet–Delbos, L., Naveau, S., Dagher, I., Prévot, S., Durand–Gasselin, I., Couderc, J., Valet, V., Perlemuter, E.D. Obesity-Induced Lymphocyte Hyperresponsiveness to Chemokines: A New Mechanism of Fatty Liver Inflammation in Obese Mice. 2008, Gastroenterology, 134, 1459-1469.

44. Cani, P.D., Amar, J., Iglesias, M. A., Poggi M., Knauf, C., Bastelica, D., Neyrinck A.M., Fava, F., Tuohy, K.M., Chabo, C., Waget, A., Delmée, E., Cousin, B., Sulpice, T., Chamontin, B., Ferrières, J., Tanti, J.F., Gibson, G.R., Casteilla, L., Delzenne, N.M., Alessi, M.C., Burcelin, R. Metabolic endotoxemia initiates Obesity and Insulin Resistance. 2007, Diabetes 56, 1761- 1767.

45. Chichlowski, M., Westwood, G.S., Abraham, S.N., Hale, L.P. Role of mast cells in inflammatory bowel disease and inflammation-associated colorectal neoplasia in IL-10-deficient mice. 2010, PLoS One. Aug 17, 5(8). pii: e12220.

46. Kinlen, L.J. Non-Hodkin’s lymphoma after immunosuppressive therapy. 2000, Gut, 47, 462-463.

47. Chow, W.H., Gridley, G., Fraumeni, J.F., Jaervholm, B. Obesity, Hypertension, and the risk of kidney cancer in men. 2000, N Engl J Med; 343: 1305-1311.

48. Lichtenstein, P., Holm, N.V., Verkasalo, P.K., Iliadou, A., Kaprio, J., Koskenvuo, M., Pukkala, E., Skytthe, A., Hemminki, K. 2000, Environmental and heritable factors in the causation of cancer. Analyses of cohorts of twins from Sweden, Denmark, and Finland. N. Engl. J. Med., 343, 78-85.

Part II

Awareness and Effects

Research Signpost 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

The Meal by Meal Dynamic Energy Balance in Blood: Habits & Risks, 2011: 57-77 ISBN: 978-81-308-0457-6 Editor: Mario Ciampolini

5. Initial Hunger (IH) Training to estimate blood glucose and to form associations with initial hunger 1

Mario Ciampolini1 and Riccardo Bianchi2 Unit of Preventive Gastroenterology, Department of Pediatrics, University of Florence Florence, Italy and ONLUS "Nutrizione e Prevenzione", Florence, Italy 2 Department of Physiology and Pharmacology, State University of New York Downstate Medical Center, Brooklyn, New York, USA

In the following article, we describe subjects’ exploration of personal sensations after eating suspension. Subjects had to choose the “Initial Hunger” sensations and validate them by BG to use consistently their arousal as their own personal signal for meal onset.

Abstract Background: The will to eat is a decision associated with conditioned responses and with unconditioned body sensations that reflect changes in metabolic biomarkers. Here, we investigate whether this decision can be delayed until blood glucose is allowed to fall to low levels, when presumably feeding behavior is mostly unconditioned. Following such an eating pattern might avoid some of the metabolic risk factors that are associated with high glycemia.

Results: In this 7-week study, patients were trained to estimate their blood glucose at meal times by associating feelings of hunger Correspondence/Reprint request: Dr. Mario Ciampolini, Unit of Preventive Gastroenterology, Department of Pediatrics, University of Florence, Florence, Italy and ONLUS "Nutrizione e Prevenzione", Florence, Italy Email: mlciampolini@fastwebnet.it

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with glycemic levels determined by standard blood glucose monitors and to eat only when glycemia was < 85 mg/dL. At the end of the 7-week training period, estimated and measured glycemic values were found to be linearly correlated in the trained group (r = 0.82; p = 0.0001) but not in the control (untrained) group (r = 0.10; p = 0.40). Fewer subjects in the trained group were hungry than those in the control group (p = 0.001). The 18 hungry subjects of the trained group had significantly lower glucose levels (80.1 ± 6.3 mg/dL) than the 42 hungry control subjects (89.2 ± 10.2 mg/dL; p = 0.01). Moreover, the trained hungry subjects estimated their glycemia (78.1 ± 6.7 mg/dL; estimation error: 3.2 ± 2.4% of the measured glycemia) more accurately than the control hungry subjects (75.9 ± 9.8 mg/dL; estimation error: 16.7 ± 11.0%; p = 0.0001). Also the estimation error of the entire trained group (4.7 ± 3.6%) was significantly lower than that of the control group (17.1 ± 11.5%; p = 0.0001). A value of glycemia at initial feelings of hunger was provisionally identified as 87 mg/dL. Below this level, estimation showed lower error in both trained (p = 0.04) and control subjects (p = 0.001).

Conclusion: Subjects could be trained to accurately estimate their blood glucose and to recognize their sensations of initial hunger at low glucose concentrations.

These results suggest that it is possible to make a behavioral distinction between unconditioned and conditioned hunger, and to achieve a cognitive will to eat by training.

Abbreviations BMI R

: body mass index, weight (kg)/square height (m) : linear correlation coefficient

Background The will to eat is a decision associated with conditioned responses and with body feelings reflecting changes in metabolic biomarkers. The body feelings are often described as hunger, but have components that are strongly conditioned by time, social, and metabolic factors, for which there are salient unconditioned physiologic correlates. Blood glucose has long been considered a biomarker of hunger [1]. In extensive rat studies, Steffens [2] measured glucose at discrete intervals, and showed that blood glucose concentration declined before a meal, remained at a lower plateau until a meal started, and rose sharply shortly after the initiation of a meal. Transient blood glucose declines coincided with spontaneous feelings of hunger and meal initiation in humans and rats, suggesting that these feelings correlate with metabolic insufficiency [3-6]. This condition of hunger was associated with glucose concentrations of 80 mg/dL or lower in humans [1,3-6] and was exacerbated by injection or infusion of insulin [7].

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Blood glucose has a central role in the regulation of energy metabolism. It provides energy to the brain, has limited and exhaustible storage, is regulated by the availability of other fuels, and its blood levels correlate with the time interval between spontaneously requested meals [3,8-10]. Our previous investigations indicated that food request in infants [11,12] and diary reports of hunger in adequately trained children and adults [13] were associated with significantly lower glycemic concentrations than conditioned responses were before any training, and that these levels were lower than 85 mg/dL after training [11-13]. Hunger at comparable low glucose concentrations has been reported in time-blinded subjects [3-6]. In the present investigation, we test if appropriate training can lead to recognition of initial hunger at glycemia below 85 mg/dL. We hypothesize that feelings of hunger or discomfort might provide an indicator of the adequacy of glycemia and energy state. Eating in response to these lower blood glucose concentrations rather than to conditioned signals may improve energy balance and, in addition, reduce metabolic risk factors [8-10].

Previous investigations have reported the use of hunger feelings with [11,13] or without [12,14-16] metabolic biomarkers to allow intake and control of energy balance. The current study investigated the associations of subjective estimation, consummatory behavior, and glycemia in trained subjects versus control subjects at breakfast-time to evaluate the subjective feelings of hunger as meal-start signals and to distinguish whether they were either unconditioned or conditioned after training.

The investigation was carried out in patients with functional disorders of the bowel such as dyspepsia, abdominal pain, and diarrhea [17]. Data from this group of patient provide the basis for studies on the effects of behavioral control of feeding on intestinal diseases in adults, as it has been obtained in infants [11,14] and children [12].

Methods Setting In this 7-week pilot study, 158 adults suffering from diarrhea, abdominal pain, and dyspepsia were recruited and randomized to experimental (trained; n = 80) and control (untrained; n = 78) groups (Figure 1). Informed consent was obtained at the initial meeting from all the participants, and the local Hospital Committee approved the study according to the Helsinki Declaration. The subjects did not have impaired glucose tolerance or morphological, physical, or biochemical signs of diseases. Reactive C protein was normal. All subjects reduced work for 3-4 days at the beginning of the

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experiment and then conducted their normal routine. The experimental group was trained with tutorial assistance while the control group followed their normal routine (Figure 2). After 7 weeks, 64 trained and 72 control subjects completed the program (Figure 1; Table 1). In the final investigative session (week 7; Figure 2), they were asked to estimate their glucose concentrations in the laboratory and these values were compared to those determined through a glucose autoanalyzer. Glycemic measurements were reported on seven-day food diaries that were available before training and in the 7th experimental week.

Measurement of glycemia and validation Subjects in training measured capillary blood by glucometer (a portable potentiometer for whole blood glucose measurement: Glucocard Memory; Menarini Diagnostics; Florence, Italy) in the quarter-of-an-hour before intended meal consumption. Accuracy of measurements by the glucometer was validated at periodic laboratory visits with measurements by autoanalyzer on blood samples from the same subjects. In contrast, control subjects did not have their glycemia measured until the final laboratory session.

Estimation of glycemia and intake adjustment On the first training day, subjects were told to ignore previous meal times and to pay attention to their feelings of hunger or discomfort. At the earliest feelings of hunger or discomfort, the subjects measured glucose

Figure 1. Consort flow chart. Randomization of the subjects recruited for this study into trained and control (untrained) groups. The subjects were men and women, 18 to 60 years of age, with recurrent functional disorders of diarrhea, abdominal pain, or dyspepsia.

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Figure 2. Investigation design. A randomized and controlled 7-week pilot clinical investigation to study the acquisition of the capacity to estimate blood glucose by body feelings after adequate training.

concentrations with the portable instrument. This first event of hunger appeared after the training session with a time interval that varied widely from 0 up to 48 hours (average 2 h) and was often far from the usual meal times during the next 3 training days. This suggests that the recorded behavioral responses were largely spontaneous (unconditioned).

Measurements obtained less than 1 h after a small amount of food consumption, intense physical activity, or changes in environmental temperature were excluded from the analysis. When glycemia was higher than 85 mg/dL, patients were instructed to delay or skip the meal, to engage in some activity as a distraction from food, and to wait for the spontaneous development of novel hunger feelings for at least one hour before making further blood glucose measurements. When glycemia was under 85 mg/dL, patients were instructed to remember their feelings and to proceed to meal consumption. The glycemic level of 85 mg/dL was chosen based on the hypothesis, suggested by previous studies, that it represents the upper limit of homeostatic control of feeding [3-6,11-14]. [Authorâ&#x20AC;&#x2122;s note: The limitation and the delay were sometimes necessary during the training at older or younger ages than those here investigated. The limitation was

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actually dismissed for adults after this work. The glycemia attained at hunger arousal was around 76 mg/dL in most studies, see chapter VII, and even here was significantly lower than 85 mg/dL, P< 0.0001. High values in table 2 may depend on very high hospital temperature at final examination, see chapter III. Given the difficult environment, recognition of glycemia by hunger was surprisingly strong]. The subjects in training attempted to identify the initial hunger or discomfort that was in reliable (Âą 4 mg/dL) association with a particular blood glucose level below 85 mg/dL. During the first 3-4 days, energy intake was decreased and the amount of fruits and vegetables was increased (0.5-1 kg per day) to reduce conditioned feeding behavior and to promote early occurrence of spontaneous events of hunger outside of the usual meal time. Following meals with low glycemic index [18], hunger events could be detected and sustained for at least 1 h without substantial impairment of daily activity. Subjects were instructed to start a meal within 1 h of the appearance of these hunger events. They were prohibited from sustaining hunger for longer than 1 h, to avoid glycemic declines below 65 mg/dL that are known to induce counter-regulatory glucose responses [19].

The subjects repeated and refined this procedure three times a day for at least two weeks. Phone assistance was provided for the subject to describe the events of hunger and to report the times of occurrence, glycemic values, food energy-content, energy expenditure factors, and meal composition adjustments. After this training period, patients annotated their estimations of glycemia before the measurements.

Final session At the final investigative session, the subjects returned to the laboratory, stated whether they were hungry or not hungry, and estimated their glucose concentrations before blood sampling and before breakfast. Control subjects had ignored the relation between glycemia (referred to the subjects as "nutrient levels") and feelings of hunger up to the final session. They were asked to estimate their glucose levels referring to a range of values that could vary between the extremes of 60 mg/dL during intense hunger and 110 mg/dL after a satiating meal. Blood was sampled, centrifuged immediately, and analyzed in duplicate. The subjects were then free to eat food that they brought from home or from the hospital cafeteria under the observation of an investigator.

Statistics Values were expressed as means Âą SD. The analyses included the t-test on difference and analyses of simple, linear correlation (r = correlation

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coefficient in linear regression), agreement limits and estimation error between the estimated and measured values of glucose. The estimation of error was calculated as the mean ± SD of the absolute values of differences from the reference measurement. The significance of difference and correlation was analyzed by two-tailed t-test analysis and Yates test, and was set at p < 0.05 when one difference was analyzed between two groups and at p < 0.025 when two differences were analyzed between the same two subject groups, e.g. measured glycemia and estimation error (Table 2) [20]. Excel 5 (Microsoft Corporation, Redmond, WA, USA) was used for the analyses.

Results Sixty-four subjects were trained to regulate eating at home by measuring blood glucose during feelings of hunger. The association between feelings and glucose readings were reported by phone, and could be evaluated during the 7 weeks of training (see Methods). Subjects showed an estimation error lower than ± 4 mg/dL after less than a week of training (n = 8) or within the first two weeks of training (n = 47). The remaining 9 subjects either reached an estimation error lower than ± 4 mg/dL in > 2 weeks or still showed an estimation error higher than ± 4 mg/dL at the end of the 7-week-training.

Hungry subjects (gastric hunger) At the final session, the number of trained subjects stating that they were hungry (18 of 64) was significantly lower than that of hungry control subjects (42 out of 72; Table 2). All hungry subjects described the hunger feeling as Table 1. Trained and control (untrained) groups at baseline and after seven weeks at the final investigative session.

Weeks after baseline Number of subjects Age (years) Gender (F/M) Overweight/normal-weight2 Weight (kg) Body Mass Index (BMI) 1

Trained group Baseline Investigative 0 7 64 64 1 37.2 ± 11.0 37.4 ± 11.1 38/26 38/26 22/42 20/44 68.4 ± 15.7 66.2 ± 14.63 24.0 ± 4.7 23.6 ± 4.63

Control group Baseline Investigative 0 7 72 72 37.7 ± 10.6 37.9 ± 10.7 46/26 46/26 20/52 20/52 63.9 ± 10.6 63.2 ± 10.7 22.8 ± 2.7 22.6 ± 2.8

Mean ± SD. BMI = weight (kg)/height2 (m2); Overweight: BMI > 25; Normal-weight: BMI < 25.

3 Not significant vs baseline.

2

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Table 2. Estimated versus measured blood glucose at the final laboratory session (week 7).

N

All Trained Hungry Trained5 Not-hungry Trained6 All Controls Hungry Controls5 Not-hungry Controls6

64 18 46 72 4211 30

Estimated blood glucose 84.9 ± 7.81 78.1 ± 6.7 87.6 ± 6.5 78.5 ± 11.6 75.9 ± 9.8 82.2 ± 12.9

Measured blood glucose 87.2 ± 7.92 80.1 ± 6.3 90.0 ± 6.67 89.8 ± 10.58 89.2 ± 10.27 90.6 ± 10.9

Difference (Estimated – Measured) -2.3 ± 4.73 -2.0 ± 2.53 -2.4 ± 5.33 -11.3 ± 14.89,10 -13.3 ± 11.912,13 -8.4 ± 17.914,15

Estimation error (%)

4.1 ± 3.1 (4.7 ± 3.6)4 2.6 ± 1.9 (3.2 ± 2.4) 4.8 ± 3.2 (5.4 ± 3.6) 15.4 ± 10.4 (17.1 ± 11.5) 14.9 ± 9.8 (16.7 ± 11.0) 16.1 ± 11.3 (17.8 ± 12.4)

1

Mean ± SD, mg/dL. Subjects stated to be either hungry or not hungry and they estimated their blood glucose at the hospital laboratory before breakfast.

2 Measurements performed by hospital autoanalyzer.

3 Estimated less measured blood glucose, significant at p < 0.01.

4 Absolute value of difference between estimated and measured blood glucose and, inside parenthesis, % of measurement.

5 Subjects who declared feeling hungry at the laboratory investigative session. The agreement limits (mean difference ± 2SD) were -7.0 to +3.0 mg/ dL and -41.3 to +18.6 mg/dL in trained and control groups, respectively.

6 Subjects reporting to be not hungry at the laboratory investigative session. The agreement limits were 12.9 to +8.2 mg/dL and -45.0 to +28.0 mg/ dL in trained and control groups, respectively.

7 p < 0.01 vs trained hungry subjects in the respective column.

8 p = 0.08, not significant, vs all 64 trained subjects.

9 F = 10.6, p = 0.0001 on the difference between estimated and measured blood glucose.

10 t-test p = 0.0001 vs all trained subjects.

11 p = 0.001 vs number of hungry subjects in the trained group.

12 F = 24.6, p = 0.0001 on the difference between estimated and measured blood glucose.

13 t test p = 0.0001 vs trained hungry subjects.

14 F = 11.9, p = 0.0001 on the difference between estimated and measured blood glucose.

15 t test p = 0.07 vs trained not-hungry subjects.

gastric emptiness or gastric pangs. In the hungry trained group, the mean estimated glycemic concentration was 78.1 ± 6.7 and the mean measured value was 80.1 ± 6.3 mg/dL (Table 2; Figure 3). This measured glycemia was significantly lower than the measurements in hungry control subjects (89.2 ± 10.2 mg/dL) and in not-hungry subjects of both trained (90.0 ± 6.6 mg/dL) and control (90.6 ± 10.9 mg/dL) groups (Table 2).

The estimation error (the absolute value of the difference between estimated and measured glucose) in the hungry trained group (2.6 ± 1.9 mg/dL; 3.2 ± 2.4% of the measured value) was significantly lower than that in the hungry control group (14.9 ± 9.8 mg/dL; 16.7 ± 11.0%; Table 2; Figure 3). Linear regressions of the values in the hungry groups in Figure 3 also show that there was significant correlation between estimated and measured glycemia in the trained group (r = 0.92; p = 0.0001) but not in the control group (r = 0.29; p = 0.06).

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Figure 3. Estimated vs measured blood glucose of subjects reporting to be hungry at the final laboratory investigative session. Hollow red circles, trained hungry subjects (n = 18); hollow black circles, control (untrained) hungry subjects (n = 42). Linear correlation was significant for the trained data (dashed red line; r = 0.92; p = 0.0001) but not for the control data (dashed black line; r = 0.29, p = 0.06).

Not-hungry subjects (hunger equivalents) The trained and control subjects that were not hungry at the final investigative session significantly underestimated their glucose levels. The estimation errors were 4.8± 3.2 mg/dL and 16.1 ± 11.3 mg/dL in trained and control groups, respectively (Table 2). The linear correlation between estimated and measured glycemia was highly significant (r = 0.68; p = 0.0001) in the trained group and not significant in controls (r = -0.12; p = 0.32). The difference between trained and control groups did not depend on gender, age, number of years at school, weight, or body mass index (Table 1).

Fourteen out of 46 trained subjects who were not hungry had glucose concentrations below 87 mg/dL, the maximum limit of glycemia of those who were hungry (Figure 4). These 14 subjects showed an average estimation error of 4.5 ± 3.1% of the measured glycemia, which did not significantly differ from the estimation error of the 18 trained subjects who were hungry

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Figure 4. Estimated vs measured blood glucose of trained subjects with levels below 87 mg/dL at the final session. The highest glycemic value measured in trained hungry subjects was 87 mg/dL. Below this value of measured blood glucose, 18 subjects reported to be hungry (hollow red circles) and 14 subjects were not hungry (filled red squares). Linear regression is significant for the hungry subjects (dashed red line; r = 0.92; p = 0.0001) but not for those not hungry (solid red line; r = 0.18; p = 0.54).

(3.2 ± 2.4%; p = 0.20). Under 87 mg/dL, estimation error was low in both trained and control groups (n = 32; 3.8 ± 3.7% and n = 31; 13.5 ± 8.9% of the measurement, respectively), independently of the subject's statement on hunger. In subjects with values above 87 mg/dL of glycemia, the estimation error increased significantly to 5.7 ± 3.7% (trained; n = 32; p = 0.04; Figure 5) and to 19.5 ± 11.8% (controls; n = 41; p = 0.001).

Despite their not being hungry, 12 of 14 trained subjects under 87 mg/dL and 3 of 32 above 87 mg/dL (p = 0.001) described the subtle feelings they employed to estimate glycemic concentrations. Thus, compared to controls who did not report equivalents of hunger (n = 30) - a significantly higher proportion of the 46 not-hungry trained subject (p = 0.001) was able to report feelings other than gastric hunger, which were useful in estimating their glycemic levels, and this ability prevailed below 87 mg/dL. In their reports, these 15 subjects described physical (3 subjects) or mental (10) weakness or abdominal changes in tension or movement (2). Another 6 of the 46 nothungry trained subjects, but none of the control subjects, had felt gastric

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hunger before entering the hospital for the final session; however the feeling faded while waiting for the laboratory session.

In the not-hungry subjects' reports, the feelings of mental weakness consisted of difficulty in sustained mental concentration, impatience, irritability, drowsiness, gnawing feeling, loss of enthusiasm and effectiveness at mental work, or poor mood at their jobs. The mental feelings emerged alone or in addition to gastric or other feelings and ceased with the meal. Sensing impairment during physical activity was associated with heavy physical exercise outdoors and often accompanied a change from a sedentary life style.

This feeling was used regularly to indicate meal signal with an increased requirement of high-energy-dense food for the next meal(s). The prevalence of these 'hunger equivalents' ranged from an occasional occurrence to less than 15% of the meals in the phone reports. Two subjects reported that they never felt (gastric) hunger, but estimated glycemic concentrations within 6% estimation error always by assessing mental or muscular weakness during training or during the final investigative session. In their reports, these subjects consumed meals at glycemic estimation of 78 to 85 mg/dL. Cognitive adaptation to the glycemic concentrations at initial feelings of hunger At the final laboratory session, the 64 trained subjects showed a decrease of 43.1% in reporting hunger events before breakfast compared to the reported events of the previous week (Table 3). In contrast, the corresponding decrease in hunger reports of the 72 controls was only 11.7% (p < 0.0001; Table 3). Compared to the diary reports of the last training week, the 64 Table 3. Number of hunger events and breakfast consumptions during the 7th week of training (diary) and at the final laboratory session in trained (n = 64) and control (n = 72) subjects.

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trained subjects also decreased breakfast consumption by 13.7%, significantly more than control subjects (3.8% decrease; p < 0.01; Table 3).

The significant reduction in prevalence of attaining the feelings of initial hunger and consuming breakfast at the final session in trained subjects suggests maintenance of surveillance of body feelings and adaptation of intake to this indicator.

Discussion The main result of this study is that adult individuals can be trained to accurately estimate their glucose levels at meal times. This cognition was achieved by conditioning the subjects to associate feelings of hunger with low glucose concentrations (Figure 5, red symbols). In contrast, control (untrained) subjects were unable to recognize their glycemic levels at meal times (Figure 5, black symbols) and expressed the will to eat at a wide range

Figure 5. Estimation error vs measured blood glucose in the trained and control groups. Consistent with previous figures, symbols and regression lines are: hollow red circles and dashed red line, trained hungry subjects (n = 18; r = 0.20; p = 0.43); filled red squares and solid red line, trained not-hungry subjects (n = 46; r = 0.24; p = 0.18); hollow black circles and dashed black line, control hungry subjects (n = 42; r = 0.55; p = 0.0001); filled black squares and solid black line, control not-hungry subjects (n = 30; r = 0.58; p = 0.001).

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of glycemic values. The main result of this study is that adult individuals can be trained to accurately estimate their glucose levels at meal times. This cognition was achieved by conditioning the subjects to associate feelings of hunger with low glucose concentrations (Figure 5, red symbols). In contrast, control (untrained) subjects were unable to recognize their glycemic levels at meal times (Figure 5, black symbols) and expressed the will to eat at a wide range of glycemic values.

These findings suggest (1) that food consumption at high glycemic concentrations in control subjects may lead to higher energy intake than in trained subjects [8-14], and (2) that the lack of correlation between food consumption and glycemia may, at least in part, explain why part of the population cannot maintain its energy balance. Since our study was conducted on subjects with gastroenteric disorders, it remains to be determined whether such deficit of association between food intake and glycemia is limited to this patient population or is a more general mechanism involved in other metabolic disorders, as suggested by findings on IgE and antibody to H. pylori plasma levels [13,14], and by preliminary studies on overweight and insulin-resistant adults [21,22].

The collected evidence supports the interpretation that trained subjects learned to recognize the unconditioned feelings of hunger. The training in this study was intended to cut off excess food consumption, i.e. caloric intake occurring at high (> 85 mg/dL) glycemic concentrations, through conscious exposure of the subjects to the initial sensations of hunger arising when glycemia declined below 85 mg/dL. A 7-week period with association of estimated and measured glycemic values repeated 3 times per day was sufficient to train the subjects to accurately recognize their glycemia (estimation error < 3-5%; compared to 10-20% of controls; Table 2 and Figure 5), as tested at the final laboratory session. In addition to greater accuracy in glycemia estimation in the trained subjects compared to the control group, the data also indicate that estimated glycemic values were more accurate at glycemic concentrations below 87 mg/dL in both groups, independently of the feelings of hunger, compared to values estimated at high glycemic concentrations (Figure 5). Greater accuracy in the recognition of the sensations of initial hunger identified at low glycemic concentrations suggests that such feelings could be used as a reliable signal for meal consumption.

It is unlikely that the training per se simply established a new conditioning of the feeding behavior at lower glucose levels. First, most patients had pre-prandial high glycemic levels at baseline and they reported the sensations of initial hunger associated with low glycemia during the initial training as 'novel'. Second, during the first 3-4 days of training, the

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chosen sensations of initial hunger used to start a meal arose spontaneously (i.e. they were not triggered by external events related to food consumption, such as the sight of the dinner-table) and unexpectedly during working or entertaining activities, and persisted for at least 1 h. Third, at the final laboratory session, the number of trained subjects that recognized the appearance of sensations of initial hunger similar to those experienced during the training at low glycemic concentrations was significantly lower than in the control group (18 out of 64 vs 42 of 72, respectively; Table 3) and the number of trained subjects who refused breakfast was significantly higher (39.1%) than that of controls (18.1%; Table 3). These observations suggest that the expression of a spontaneous and novel sensation of initial hunger at low glycemia in trained subjects did not simply reflect habitual repetition of a new conditioning caused by the training but rather was a cognitive ability to distinguish between low and high glycemic levels. In previous studies, expressions of hunger have been reported at levels below about 60 mg/dL obtained following infusion of insulin or following prolonged food abstention [19,23]. These values are lower than those reported here.

However, other studies showed that hunger in time-blinded subjects was preceded by transient blood glucose declines beginning at about 80 mg/dL [36,24] or, in some cases, at values as high as 100 mg/dL [5,24]. These data suggest that many factors - such as composition of previous meal, health status, age, and time-conditioning - affect the initiation of hunger and/or that different sensations of hunger are caused by separate mechanisms.

The arousal of unconditioned sensations of initial hunger below 87 mg/dL of glycemia in the trained subjects of our study is similar to the data of Melanson et al. [3] on time-blinded subjects in the morning who expressed hunger around 80 mg/dL after different lag times. In time-blinded young adults, Chapelot et al. [24] also showed that hunger expressions were associated with transient blood glucose declines from a mean glycemia of 100 mg/dL, but the subjects were conditioned by the past habit of snacking in the afternoon. The present study suggests that, in addition to time-blinding [3,24] and transient declines in blood glucose [[3,24], and this study], recognition of the sensations experienced during early training in association with low glycemia, as observed at the final session, indicate identification of unconditioned mechanisms of hunger in coincidence with metabolic insufficiency, as shown in rats by Nicolaiidis and Even [25]. This ability appeared particularly well trained in six subjects who reported that their hunger feelings outdoors, in the cold winter climate, faded indoors, in the overheated hospital rooms, due to decreased metabolic rate at high environmental temperature [26].

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One possible explanation for the effects of training observed in this study is that, below a given level of glycemia, the trained subject responded to sensations of hunger similar to those that stimulate a two-year old child to demand food [11]. Young humans [24] and mice [6] accustomed to scheduled eating express hunger and transient blood glucose declines at a mean glycemia of 100 mg/dL. This implies that adults acquire conditioned hunger reflexes at high glycemia, leading to consumption of food in excess to what is necessary for energy balance. Consistent with this hypothesis is the observation that feeding 2-year-old children only following their unconditioned request of food succeeded in energy balance and body growth, and that their growth was associated with decreased energy intake [11-13] and with decreased metabolic rate [27].

Further data are necessary to establish if the training presented in this study will lead to reduced food intake and improvement of symptoms associated with gastro-intestinal disorders or other pathologic states [13,14,21,22].

Conclusion Humans can learn to distinguish the feelings of unconditioned hunger that arise at glycemic concentrations below 80-90 mg/dL from those that are conditioned and arise at glycemic concentrations higher than 80-90 mg/dL. This cognition may help in reducing conditioned eating in order to maintain energy balance.

Comment Hunger has been reviewed recently [28]. The sensation is not merely mental, but coincides with a complex physiological function. After completion of absorption, small intestine develops migrant motor complexes [29]. These are powerful constrictive and propulsive movements (waves) that descend in rhythmic sequence along the small intestine for 30 – 40 centimeters. A subsequent wave starts in about the middle of the previous wave after 3 – 30 minutes. The wave coincides with subject’s reporting hunger [29, 30]. In animal experiment, gastric and pancreatic secretions ensue together with waves. Hypothalamic centers govern the digestive activation. Here neurons respond to hormones, afferent nerves, blood glucose (BG) and insulin. Hypothalamic centers activate small intestine, liver, part of the large intestine through the vagal nerve. This activation takes place at arousal of “Transient BG Decline” (TBGD). These TBGDs arise together with hunger epigastric sensations, often around 80 mg/dL of BG, and may

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depend on insufficient glucose influx into blood [3, 4]. Is exhaustion of liver glycogen the primum movens of hunger function? In an overweight condition, the final hour(s) in the interval between meals are covered by a larger influx of fatty acids from adipocytes as compared to normal weight people (Chapter VIII).

BG, nutrients in blood and resting metabolic rate (RMR) follow nutrients provided by meals [5 – 7, 31 - 33]. BG and RMR increase (RMR: 3% – 15%) transiently after a meal [5 – 7, 31- 34], and this RMR increase is said dietary induced thermogenesis (DIT). DIT is variable in humans [35], and the main determinant of DIT is the energy content of food [35, 36]. The state of replenishment of body cells by nutrients (= insulin resistance) may have a even bigger influence. People in insulin resistance have high RMR, poor space for further RMR increase, and have small DIT [36]. Throughout the day, resting metabolic rate and BG do not return to the basal metabolic rate of early morning before breakfast [36]. A suspension of intake for two - four hours produces a rapid decrease from inter-meal baseline, up to 15%, in BG (present and following Chapter VI) and RMR [34, 37, 38] and these rapid decreases might activate the hunger function like in animals before taking food [39]. Consistently, animals show a drop in metabolic rate at this time, i.e., before food consumption [39].

In the published article within this chapter, we suggested a verification of the first identification of initial hunger by immediate BG measurement that should be lower than 85 mg/dL. On the first day, subjects always found however Initial Hunger under this limit and the prescribed BG limit revealed to be useless. On the other hand Initial Hunger might develop beyond 85 mg/dL of BG during or after (1 hour) heavy outdoor work or physical exercise (Chapter VII).

Prolonged starvation adds further decrease of BG and RMR in subsequent days [31, 40]. Briefly, BG and RMR might have a sinusoidal relation against time: BG and RMR have their highest levels half-an-hour after meals, followed by rapid decrease. After DIT end, BG and RMR are almost stable, and have a rapid decrease around next mealtime. However, 70% to 80% of population forestalls hunger or appropriate hunger by premature intake (Chapters V and VII). Diffuse forestalling in population confounds measurements of RMR in relation to meal. We have preliminary results [27] and may thoroughly discuss this point in a further complete work.

After post-absorptive period and eating suspension, TBGDs emerge, their frequency in time, and are associated with hunger sensations followed by food intake, but are not associated with increased plasma insulin before eating [24]. We largely investigated meal patterns by 7-d diary reporting preprandial BG. On these reports, we suggest that bursts of hunger pangs

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(usually associated with TBGD) become more and more prevalent with BG lowering as a signal of insufficiency in nutrient provision for RMR maintenance at constant levels. This metabolic moment (initial insufficiency, initial decrease in RMR) coincides with the meal by meal maintenance of null energy balance in blood. We achieved this goal by practicing a pattern of consuming meals only after spontaneous arousal of IH, and named the pattern “recognizing hunger” or Initial Hunger Meal Pattern (IHMP). Subsequent Chapters shall substantiate this hypothesis of eating rationalization. Chapters VI - VIII demonstrate achievement of null meal by meal energy balance in the long period by results in mean BG and in weight.

Starting all researches, our Gastroenterology Unit designed a working hypothesis about hunger: the activation of this complex function signaled the emptying of the stomach and of the small intestine and the preparation for a high absorption rate. Chapter III ended by reporting these associations in an experiment on animals that have not been fed for three hours. The ‘emptiness’ means cleansing of mucosal bacteria, rapid absorption, minimal bacteria growth, minimal immune stimulation of mucosa and of the whole body system. Now we may add prevention of insulin resistance, of the associated subclinical inflammation and of health risks (Chapters VI - VIII).

Our Unit employed a meal pattern based on initial request for food (infants’ manifestations of hunger) to prevent diarrhea relapses in the first two years of life [11, 25]. We fully relied on painstaking mothers’ reports on infants’ manifestations [27]. We instead had no trust on adults addressed to the Gastroenterology Unit for intestinal functional disorders similar to those of infants. Adults’ description of mental and physical weakness or gastric pangs poorly improved our reliance. Hunger may arise as a conditioned reflex after learning an association with the same day hour or the same sound or same sight [41, 42]. We were not able to distinguish conditioned hunger from the one provoked by food abstinence. We required confirmation of reported sensations by BG associated measurement. The confirmation had to consist in the same values across subsequent measurements at hunger arousals. We added thus pre-prandial BG measurements to 7-d food diary that patients routinely reported at recruitment, after 7 weeks training and after 5 months. A boy of 12, recovered from the worst malnutrition for lipodistrofy, after 5 months told us: ‘I know the number before BG measurement’, and most adults confirmed this statement. BG served to validate hunger.

In diary or phone call and in the hospital investigation, adults reported the arousal of gastric emptiness or either mental or physical weakness, and the three types of hunger sensations had similar accuracy at BG estimation.

We wondered if adults’ BG estimation relied upon perception of RMR

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decreases and associated events [43]. Only further investigation will clarify this point.

Last consideration Training and practicing “recognizing hunger” (IHMP) required willing, active collaboration by subjects who were already motivated at their addressing to the Gastroenterology Unit of the University of Firenze for a medical problem. The motivation often consisted of the expected definitive recovery from functional bowel disorders. Today, patients train “recognizing hunger” (IHMP) to escape from the many manifestations of subclinical inflammation. The Unit successfully treated abdominal pain, chronic diarrhea, gastritis associated or not to H pylori infection, hypertension, cardiac extra systoles, back pain, Sioegren disease, anorexia, atopic dermatitis, acnes, tendinitis, obesity and malnutrition. After the first few months, the Unit annually recalled trained patients, checked their meal pattern and clinical conditions, and suggested further improvements [12]. By this activity, the Unit took into practice the 2010 Affordable Care Act «P.L. 111-148, 23 March 2010» [44].

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Jenkins, DJA., Wolever, TMS., Jenkins, AL., Josse, RG., Wong, GS. The glycemic response to carbohydrate foods. Lancet 1984, 2:388-391.

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Ciampolini, M., de Pont, B., de Haan, W., Fognani, G., Cavuta, M. Can you only care of insulin sensitivity and physical fitness? (Abstract). Appetite 1999, 33: 237.

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24. Chapelot, D., Marmonier, C., Aubert, R., Gausseres, N., Louis- Sylvestre . A role for glucose and insulin preprandial profiles to differentiate meals and snacks.

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In Handbook of Physiology, Sect 4, Adaptation to the Environment Edited by: Dill DB. Washington DC: Amer Physiol Soc; 1964:413-434.

27. Ciampolini, M. Infants do request food at the hunger glycemic level, but adults don't any more (Abstract). Appetite 2006, 46:345.

28. Harshaw, C. Alimentary epigenetics: A developmental psychobiological systems view of the perception of hunger, thirst and satiety. Developmental Review 2008; doi:10.1016/j.dr.2008.08.001 29. Itoh, Z., Aizawa, I. and Sekiguchi, T. The interdigestive migrating complex and its significance in man. 1982, Clinics in Gastroenterology,11, 497-521.

30. Bulatao, E., Carlson, AJ. Contribution to physiology of stomach: influence of experimental changes in blood-sugar levels on gastric hunger contractions. Am J Physiol 1924; 59: 107-115.

31. Dulloo, A.G. Thrifty energy metabolism in catch-up growth trajectories to insulin and leptin resistance. 2008, Best Practice & Research Clinical Endocrinology & Metabolism, 22, 155-171.

32. Verdich, C., Toubro, S., Buemann, B., Madsen, J.L., Holst, J.J. and Astrup, A. The role of postprandial releases of insulin and incretin hormones in meal induced satiety. Effect of obesity and weight reduction. 2001, Intern. J. Obesity., 25, 1206-1214.

33. Welle, SL., Seaton, TB., Campbell, RG. Some metabolic effects of overfeeding in man. Am J Clin Nutr 1986; 44:718-724.

34. Weyer, C., Vozarova, B., Ravussin, E., Tataranni, PA. Changes in energy metabolism in response to 48h of overfeeding in Caucasians and Pima Indians.

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35. Tataranni, P.A., Larson, D.E., Snitker, S. and Ravussin, E. Thermic effect of food inn humans: method and resuls from use of a respiratory chamber. 1995, Am. J. Clin. Nutr. 61, 1013-1019.

36. Westerterp, K.R. Diet induced thermogenesis. 2004, Nutrition & Metabolism 1, 5.

37. Jequier, E. Thermogenic responses induced by nutrients in man: their importance in Energy balance regulation. 1983, J., Mauron Ed. Nestle Nutrition Research Symposium, Vevey, 26-44 38. Garrow, J.S. Effect of obesity in human energy expenditure. 1983, A., Angel, C.H., Hollenberg, D.A.K., Roncari Eds. Raven Press, NY, 251-258.

39. Nicolaidis, S., Even, P. Physiological determinant of hunger, satiation and satiety. Am J Clin Nutr 1985; 42: 1083-92.

40. De Baer, J.O., van Es, A.J.H., Roovers, L.A., van Raaij J.M.A. and Hautvast J.G.A.J. Adaptation of energy metabolism of overweight women to low-energy intake, studied with whole body calorimeters. 1986, Am. J. Clin. Nutr., 44, 585-595.

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41. Weingarten, H.P. Meal initiation controlled by learned cues: basic behavioral properties. 1984, Appetite 5, 147-158.

42. Morley, J.E., Levine, A.S. The central control of appetite. 1983, Lancet 1, 398-401.

43. Landsberg, L., Young, J.B. Fasting, feeding and regulation of the sympathetic nervous system. 1978, N. Engl. J. Med., 298, 1295-1301.

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Research Signpost 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

The Meal by Meal Dynamic Energy Balance in Blood: Habits & Risks, 2011: 79-94 ISBN: 978-81-308-0457-6 Editor: Mario Ciampolini

6. “Recognizing hunger” (initial hunger meal pattern) and insulin sensitivity Sustained self-regulation of energy intake: Initial hunger improves insulin sensitivity

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Mario Ciampolini1, David Lovell-Smith2, Riccardo Bianchi3 Boudewijn de Pont4, Massimiliano Sifone5, Martine van Weeren4 Willem de Hahn4, Lorenzo Borselli1 and Angelo Pietrobelli6

Unit of Preventive Gastroenterology, Department of Paediatrics, Università di Firenze, 50132 Florence, Italy; 2Department of General Practice and Primary Health Care, University of Auckland, Auckland, New Zealand; 3Department of Physiology and Pharmacology Robert F. Furchgott Center for Neural and Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn, NY, USA; 4AMC, 1100 DDAmsterdam The Netherlands; 5Department of Statistics, Università di Firenze, Florence, Italy 6 Paediatric Unit, Università di Verona, Verona, Italy

Abstract Background: Excessive energy intake has been implicated in diabetes, hypertension, coronary artery disease, and obesity.

Dietary restraint has been unsuccessful as a method for the selfregulation of eating. Recognition of initial hunger (IH) is easily learned, can be validated by associated blood glucose (BG) concentration, and may improve insulin sensitivity.

Objective: To investigate whether the initial hunger meal pattern (IHMP) is associated with improved insulin sensitivity over a 5-month period.

Correspondence/Reprint request: Dr. Mario Ciampolini, Unit of Preventive Gastroenterology, Department of Paediatrics, Università di Firenze, 50132 Florence, Italy. E-mail: mlciampolini@fastwebnet.it

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Methods: Subjects were trained to recognize and validate sensations of IH, then adjust food intake so that initial hunger was present pre-meal at each meal time (IHMP). The purpose was to provide meal-by-meal subjective feedback for selfregulation of food intake. In a randomised trial, we measured blood glucose and calculated insulin sensitivity in 89 trained adults and 31 not-trained controls, before training in the IHMP and 5 months after training.

Results: In trained subjects, significant decreases were found in insulin sensitivity index, insulin and BG peaks, glycated hemoglobin, mean pre-meal BG, standard deviation of diary BG (BG as recorded by subjects’ 7-day diary), energy intake, BMI, and body weight when compared to control subjects.

Conclusion: The “recognizing hunger” (IHMP) improved insulin sensitivity and other cardiovascular risk factors over a 5-month period.

List of abbreviations IHMP

: “recognizing hunger” or initial hunger meal pattern (see chapter 7) AUC : Area under curve BMI : Body mass index BG : Blood glucose concentration GTT : Oral glucose tolerance test LBG : Low blood glucose Diary-BG SD : Mean pre-meal blood glucose standard deviation reported by seven day diary CRP : C reactive protein.

1. Introduction In industrialised countries, most people regulate their energy expenditure poorly. Individual energy expenditure may differ up to 20-fold between resting conditions and high physical activity, but such differences have until now been weakly correlated to energy intake at subsequent meals [1].

Frequent episodes of positive energy balance can lead to insulin resistance, overweight, obesity, diabetes, and heart disease [1, 2]. Dietary regimes that attempt to restrain eating have been only marginally successful [3, 4] and the feasibility of self-regulation of energy intake regimes has been questioned [5]. A key reason for this lack of success may be that most dietary methods rely on weekly or monthly measurements of weight. These measurements provide no immediate feedback to dieters, who usually ingest food at least three times daily.

The body’s own physiological signaling system is hunger. Blood glucose concentration (BG) is a reliable index of energy availability to body cells

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[6–8]. It seems reasonable to assume that BG slowly declines in the absence of food intake during the day until hunger emerges to trigger eating behaviour [9, 10]. Previous studies suggested that waiting for hunger before eating is associated with a significant decrease in energy intake [11–15].

Subjects can be trained to predict when BG is low by attending to their subjective experience of hunger [16]. Thus low blood glucose (LBG) can be regarded as a biochemical marker for hunger. The first intimations of hunger we term Initial Hunger (IH), to differentiate it from the uncomfortable symptoms that occur when hunger is prolonged. IH is not a reflex conditioned by external events such as time or social circumstances [17]. For example, IH is not conditioned by meal times since it arises unexpectedly (outside meal times) if energy content of the previous meal was not planned to cover the intermeal interval [16]. The Initial Hunger Meal Pattern (IHMP) is a pattern of eating such that IH is present before most meals. We reasoned that the IHMP should predict closely regulated BG concentration with associated improvements in metabolic biomarkers.

In this study, we tested the hypothesis that the IHMP is associated with improvements in metabolic biomarkers, in particular insulin sensitivity.

2. Methods 2.1. Participants 2.1.1. Eligibility criteria The Paediatric Gastroenterology Unit of Florence University recruited 143 subjects to this study from 1996 to 2000. This unit diagnoses and treats celiac disease in children and adults. Aged 18 to 60 years, subjects suffered from symptoms of functional bowel disorders such as dyspepsia, abdominal pain, and diarrhoea (Figure 1) [18, 19]. They showed no morphological, physical, or biochemical signs of organic disease [11, 18, 19]. Subjects with impaired glucose tolerance (fasting plasma-glucose >115 mg/dL (6.4 mmol/L)), and noninsulin dependent diabetes mellitus (NIDDM), celiac, liver, heart, brain, thyroid, and kidney diseases were excluded from this study (Figure 1).

Written informed consent was obtained from all subjects. The local Hospital Ethics Committee approved the study in compliance with the Helsinki Declaration.

2.1.2. Setting The trained group continued their regular work or recreational activities under tutorial assistance for seven weeks and maintained the IHMP for a further three months independently (Figure 1).

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Figure 1. Consort flow chart and investigation design. Randomized controlled 5-month clinical investigation to study the metabolic effects of the IHMP.

2.2. The intervention Subjects were trained in the IHMP, first by identifying IH, which was guided by consistency in subjective sensations and the association of these sensations with BG measurement. During training, subjects measured capillary blood by portable glucometer (Glucocard Memory; Menarini Diagnostics; Florence, Italy) in the 15 min before a meal. Accuracy of measurements by the glucometer was validated against periodic measurements by hospital autoanalyzer. Seven-day home diaries reported BG measurements and presence or absence of IH before the three main meal times. Also recorded in the diary were energy and vegetable intake, hours in bed, and hours spent during physical and outdoor activities (weekly mean and SD). Subjects were advised that BG measurements after taking small quantities of food (even a few grams), after changes in ambient temperature, after physical activity such as walking or cycling, and when under psychological stress would be misleading since we had previously found that BG and IH do not correlate well under these conditions [16].

Subjects reported IH as gastric pangs, sensations of emptiness and hollowness, and mental or physical weakness [16]. IH was cultivated premeal by adjusting composition, portion size, or timing of food intake. After a few days of trial and error, and sometimes irregular meal times, subjects were able to arrange their food intake so that IH appeared before the usual three meal times per day with an average error of half-an-hour in 80% of instances

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[15, 16, 20–23]. Training ended after the first 7 weeks, to be resumed only at the end of the investigation. Thus, after the first 7 weeks, subjects relied upon the identified subjective sensation (IH) alone, as the signal to begin a meal.

Control subjects (N = 31) were given the same information on food energy content and were recommended vegetable intake and physical activity per day as were the trained subjects (weeks 0–7, Figure 1).

120 subjects who completed the study were assessed for blood parameters at baseline (before training), after the first 7 weeks of training, and at the end of the investigation after a further three months (total duration of the investigation: 5 months). During the glucose tolerance test, after a 12-hour overnight fast, all subjects were given a 75 g-oral glucose load.

Venous blood samples were taken immediately before glucose was administered, and 30, 60, 90, 120, and 180 min thereafter to determine plasma glucose and serum insulin. Serum insulin was measured with the IMx insulin assay (Abbott Lab. Diagn. Div. USA) [24]. From the glucose tolerance test (GTT), we calculated the area under the curve (AUC), the index of whole-body insulin sensitivity (10,000/square root of [fasting glucose × fasting insulin] × [mean glucose × mean insulin during GTT]) [25], and the insulinogenic index of beta cell function (ratio of the increment of plasma insulin to that of plasma glucose 30 min after glucose loading) [26].

2.3. Outcomes 2.3.1. Primary endpoint The primary endpoint was the change in insulin sensitivity [25] from baseline at 5 months in trained subjects compared to controls.

2.3.2. Secondary endpoints Analyses were also performed on beta cell function [26], BG AUC, GTT measurements of BG and insulin concentrations, and mean pre-meal BG and HbA1c values [27] as well as energy intake, BMI, body weight and arm and leg skinfold thickness.

2.4. Sample size Previous work in similar patients found that the insulin sensitivity index in the intervention group was greater by 3 than that in the control group, with a standard deviation (SD) of 3.0 [23]. Based on these figures, our sample size calculations suggested that we needed a minimum of 14 subjects in each

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comparison group to detect a similar difference in group means, with a power of 80% and a 1 sided alpha of 0.05.

2.5. Randomization A list was divided into blocks of 1 to 4 places, and the blocks were randomly assigned using Armitage even and odds random numbers on a 3 : 1 ratio to either training or control groups. A dietician kept the list and subsequently assigned each recruited subject to the first empty list place.

Control or training destination was revealed after the first visit (Figure 1).

2.6. Statistical methods Values are expressed as means Âą SD, except in Figure 2, where the Standard Error is shown. Logistic regression analysis was used to investigate the association of training with BG mean, Hb1c, insulin and BG AUCs, intakes and anthropometric measures (trained versus untrained control groups) for significance of multiple results [28]. The significance of difference and correlation was set at P < .05 in these analyses. Yates test and two-tailed Studentâ&#x20AC;&#x2122;s t-test on paired or unpaired samples according to data requirements were used to analyse the significance of difference and two-tailed Studentâ&#x20AC;&#x2122;s t-test for correlation. The significance was set at P < .05 for single measurements and at P < .025 for the GTT insulin and BG AUCs [29]. Custom-made software was used to tabulate data for statistical analyses. Microsoft Excel (Microsoft Corp., USA) and SAS 8 (SAS Institute Inc., Cary, NC, USA) were used for data presentation and for statistical analyses.

A training effect and correlations between the two body size parameters (weight and BMI), the two energy balance parameters (arm and skinfold thickness), the four metabolic indexes (mean BG and HbA1c values, and BG and insulin AUCs), and three intake factors (energy, fruit, and vegetable) were longitudinally investigated (i.e., on post minus pre-differences) by simple, linear correlation and regression analyses in all of the 120 subjects completing the study (Figure 1). Results were validated by chi square testcollinearity diagnostics-residual analysis.

3. Results Figure 1 shows the flow chart of participants through each phase of the study. Data were eventually collected from 120 subjects who completed the study (60 females and 60 males, 89 trained subjects and 31 control subjects).

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3.1. Losses and exclusions 3.1.1. Protocol deviations In this study the protocol was to follow the IHMP. We do not have data on the extent to which IH was present pre-meal for each meal, that is, we do not know how closely each subject adhered to the IHMP. Achieving the IHMP appeared to be difficult for 12 subjects who had high pretraining mean BG concentrations (e.g., around 100 mg/dL) or participated in heavy manual labour, especially in cold conditions. Although some subjects may not have been faithful to the IHMP for all meals, we have included all those who completed the study in the final analysis, since it was our intention to treat them [30, 31].

3.1.2. Dropouts Twenty-three subjects (18 trained and 5 control) did not complete the study (dropouts). All were contacted by telephone. Their given reasons were that they “required no further training” or had “busy schedules.” To ascertain whether these biases could have affected the generalisability of the study’s conclusions, we performed a sensitivity analysis using baseline and 7-week data from all 23 dropouts. The 18 trained dropouts significantly decreased mean BG (from 83.3 ± 5.9 mg/dL to 78.9 ± 5.4 mg/dL; P = .005), energy intake (from 1651 ± 451 to 1124 ± 401; P = .0001), BMI (from 23.7±3.4 to 22.9±3.2; P = .04), and arm skinfold thickness (from 20.5 ± 8.5 to 18.5 ± 8.8; P = .03). The 5 control dropout subjects showed no change in these assessments.

3.2. Baseline demographics Since no significant gender difference in baseline mean BG concentrations was observed in the control group (females: 82.3 ± 8.0 mg/dL; N = 14; and males: 87.5 ± 7.6 mg/dL; N = 17; Student’s t-test for unpaired data: P = .075) and in the training group (females: 84.3 ± 8.7 mg/dL; N = 46; and males: 87.5 ± 10.6 mg/dL; N = 43; P = .115), the measurements from both genders were pooled in each group (Figure 1). Baseline BG means of the control subjects (85.2±8.1 mg/dL; N = 31) did not differ from those of the training subjects (85.9±9.7 mg/dL; N = 89; P = .733).

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Baseline values of mean age, school education years, body weight, BMI, arm and leg skinfold thickness, and blood values did not significantly differ between control and trained groups (Tables 1 and 2).

Figure 2. Blood glucose and plasma insulin concentrations during GTT in control and trained subjects at the beginning and at the end of the study. Blood glucose (a) and insulin (b) mean levels in control (black circles) and trained (red squares) subjects at baseline (open symbols) and after 5 months (closed symbols). Vertical bars are standard errors. Asterisks indicate significant decrease of blood glucose (a) and insulin (b) in the trained subjects after training compared to their respective baseline values (P < .01). In contrast, no decrease between baseline values and those at the end of the study was observed in control subjects. The insulin decrease in trained subjects at 60 and 90 min also differed significantly from the control group (P < .01 and < .05, resp.).

Table 1. Group composition and effects of training on anthropometry.

Values are expressed as means ± SD. 1Values at the beginning of the study. Asterisks indicate significance (Student’s t-test: ‫כ‬P < .05; ‫ככ‬P < .01; ‫כככ‬P < .001) of longitudinal difference versus respective control group (a), or versus baseline values of the same group (b).

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Table 2. Effects of training on metabolic and intake parameters.

1

Diary SD refers to BG SD of 21 measurements reported by each of 7 d diary.

AUC: area under GTT curve.

3 Whole body insulin sensitivity index [25].

4 Meal was an event of higher energy intake than 20 kcal.

Values are expressed as mean ± SD. Peak values include different observations from those at 30’ during GTT. Asterisks indicate significance (Student’s t-test: ‫כ‬P < .05; ‫ככ‬P < .01; ‫כככ‬P < .001) of longitudinal difference versus respective control group (a) or versus baseline values of the same group (b).

2

3.3. Outcomes Significant decreases among trained subjects compared to controls were found in insulin sensitivity index, insulin and BG peaks, insulin at 60 minutes and 90 minutes during GTT, glycated haemoglobin, mean pre-meal BG, BG diary standard deviation (SD), energy intake, BMI, body weight, arm and leg skinfold thickness.

Index of beta cell function changed from1.0±0.8 to 1.1± 1.1 in trained subjects and from 1.0±1.0 to 0.7±0.6 in control subjects. These changes were not significant. Insulin and BG AUCs in the trained group significantly decreased in the pre/postcomparison but the decreases were not significantly different from those of the control subjects.

A significant decrease of preprandial BG mean values achieved during training was maintained three months after the training period ceased (baseline: 85.6±9.5 mg/dL; after 5 months: 79.4±6.5 mg/dL; N = 89; Student’s t-test for paired data: P < .0001) (Table 2). In contrast, mean preprandial BG in control subjects did not change from baseline (baseline: 85.2 ± 8.1 mg/dL; after 5 months: 85.3 ± 7.6 mg/dL; N = 31; P = .935) and the longitudinal difference from the trained group was significant (P < .001; Table 2).

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3.3.1. Ancillary analyses The absolute pre/post change (increase or decrease) in 31 control subjects was 6.0 ± 4.6 mg/dL (13.2%±10.1% of the baseline range in mean BG in the 120 investigated subjects: 64.5 mg/dL to 109.9 mg/dL). Factors that most characterized the differences between the trained group and the control group were investigated in all 120 subjects together by a logistic regression analysis. Energy intake (P = .004) and HbA1c (P = .0001) were significantly and negatively associated with the training. Further effects associated with training were investigated by stepwise regression analysis. The training was significantly and negatively associated with BMI (P = .001) and with arm and leg skinfold thickness (balance during the 5 months of investigation; P = .005 and P = .015, resp.). Decrease in BMI by training was significantly associated with decreases in energy intake (P = .001) and insulin AUC (P = .001). Analysis of weight confirmed the BMI findings.

3.4. Adverse events Trained subjects reported few negative effects when adjusting their food intake and in accommodating irregular intermeal intervals in the first few days of trial and error. The reported adverse effects included a slightly depressed BG (below 60 mg/dL (3.3 mmol/l)) and weakness or abdominal pain.

4. Discussion 4.1. Limitations of the study The high number of dropouts is an important limitation of this study.

However, from our sensitivity analysis, we conclude that the dropout subjects are unlikely to represent a significantly different population with respect to the endpoint measures of this study and that the absence of final data from these subjects is unlikely to have significantly affected the overall results.

4.2. Generalisability Our findings are from subjects who attended a gastroenterology clinic over a 5-month period. Further investigation will be necessary to evaluate the effect of the IHMP in other populations and what “reminder” training might be necessary to ensure compliance with the IHMP over years.

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4.3. Interpretation 4.3.1. Synopsis of key findings A seven-week training program to establish the IHMP led to significant decreases in insulin sensitivity index, insulin and BG peaks, glycated haemoglobin, mean pre-meal BG and BG diary SD. Energy intake, BMI, and body weight also significantly decreased.

4.3.2. Possible mechanisms and explanations IH may represent an important afferent arm of a physiological regulation mechanism that provides meal-by-meal feedback on energy need thus optimizing energy intake. The observed improved insulin sensitivity may reflect lowered energy intake resulting from the IHMP. 4.3.3. Comparison with previous findings Before training, mean pre-meal BG showed high intersubject variability, in agreement with other authors’ findings. This variability has engendered a perception that BG has no relevance to food intake regulation [8]. The mean pre-meal BG in trained subjects decreased significantly over 5 months, whereas control subjects showed no change. We suggest, therefore, that intersubject variability arises because in many subjects hunger (and thus LBG) is, by habit, forestalled by premature food intake leading to sustained mild hyperglycemia. That the absolute pre/post change (increase or decrease) in premeal BG was modest in 31 control subjects (13.2% ± 10.1% of baseline range in mean BG variation of 120 investigated subjects) supports the contention that in untrained subjects eating occurs according to long-standing habit.

4.3.4. Clinical and research implications We suggest the IHMP offers a viable alternative to low fat and low carbohydrate diets [32] that is safe, cost-effective, and likely to be met with greater acceptance since it does not involve energy deprivation.

The ramifications of improved insulin sensitivity extend well beyond glucose homoeostasis [33–36]. For example, the chronic subclinical inflammation indicated by C reactive protein (CRP) is now seen as part of the insulin resistance syndrome [33, 35]. Our results could thus have implications

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in a variety of inflammatory conditions. Trained subjects showed a cumulative energy balance that was negative after 5 months, and the longitudinal difference was significant in comparison with control subjects.

Elsewhere, we describe the effect of the IHMP on body weight in relation to baseline weight and mean BG, using a larger sample size [23].

5. Conclusions Our data suggest that (i) IH provides meal-by-meal feedback allowing the conscious formation of a new eating pattern (“recognizing hunger” or IHMP, see chapter 7) and sustained self-regulation of energy intake, and (ii) over a five-month period the IHMP is associated with improvement in insulin sensitivity, LBG, HbA1c, and other cardiovascular risk factors.

These findings, together with those of an associated study on weight [23], suggest that the current epidemic of insulin resistance and overweight may have its origin in noncognizance of hunger. This may owe to habitual forestalling of hunger in early life and subsequent reinforcement of this behaviour pattern. By restoring and validating hunger, the IHMP could help in the prevention and treatment of diabetes and obesity and associated disorders. This could lessen the high economic burden of health services in industrialized societies.

Comment Children and adults soon recovered from intestinal disorders relapses by application of IHMP. ‘We cannot live for a better gastrointestinal canal!’ was the main objection. In the meantime, measurement of excess nutrient provision became possible by measuring glucose disappearance from blood at constant serum insulin (Chapter 1). An impaired disappearance configured the condition of insulin resistance, and this condition became diffusely known after the Toronto presentation in 1988 [33, 37 - 39]. Insulin resistance resulted to be associated with more and more diseases in thousands of researches. Practicing IHMP decreased energy intake by a unexpected, huge 30% and prevented diarrhea relapses in the initial investigations by the Gastroenterology Unit of Firenze, [11, 12]. The meal pattern based on signals of Initial Hunger might solve also insulin resistance in adults!

In our large experience, the simple meal consumption after waiting for IH arousal insufficiently solved adult’s functional disorders like abdominal pain or headache. Development of hunger depends on previous activity and more precisely on previous null meal by meal energy balance in blood, but

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absorption rate and intestinal microflora overgrowth depend largely on subsequent meal by meal energy balance in blood. We now recall the opening of this book, and the identification between BG and nutrients amount in blood for practical purposes. A rhythm of three decreases to LBG (This article) or the validated recognition of three IH arousals per day was the most effective solution (Initial Hunger Meal Pattern, IHMP) to achieve health.

This objective implies that meal by meal balance of energy becomes null or negative or poorly positive in blood three times a day.

Seven-d food diary was effective in training null balance in the sequence of meals, and in showing errors. Subjects reported subsequent measurements of BG and meal components and physical activity, and became able to understand the relation of different types of food and of different physical activities with BG. The diary taught the habit of focusing attention on those energy rich components of meals that mostly delay IH arousal after intermeal interval. The diary compilation trained the subject to routinely notice IH arousal or not arousal toward the end of inter-meal interval. These acts became an easy habit to maintain. Obtaining this rhythm forced attention to evaluate meal size at each meal and voluntarily stop intake at the right amount.

Fruit and vegetable intake, slow consumption of meal, increase in dressing, a warm dining room and small amounts of alcohol (half drinks) are helpful to stop intake. Knowing the energy content of food was helpful, although poorly educated person were able to timely develop hunger by simply manipulating amounts of food rich in flour and fat. Ability in estimating current BG may fade with time and IHMP may be partly dismissed, although the training experience remains indefinitely as an awareness or subconscious habitual aim (Chapter 8).

The pathogenic chain from food intake to diseases is long and affected by supervening factors like respiratory infections, stress and trauma (Chapter 3).

Chronic, inflammatory diseases may promote vascular diseases, deterioration, allergy and autoimmunity, often in conjunction with insulin resistance. Yet, present investigation show beyond any doubt that intake may be the only causal factor in producing insulin resistance and associated subclinical inflammation (Chapter 4).

Good health requires attention to initial inflammatory changes in respiratory, urinary and genital tracts. Western social relations create rather distraction than promotion to these surveillances. ‘Carpe diem’ and depression are prevalent. Our investigation supports the minority that has strong hopes (e.g., rearing a child), and is able of collecting information and of reasoning about evidence to achieve a healthy, efficient life and fulfill hopes.

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Acknowledgments The authors thank Laura Chiesi and Stefania Bini MD for dietary analyses and Stephen Buetow, Tim Kenealy, Chris Harshaw, Simon Thornton, Kent Berridge, James Gibbs, Charlotte Erlanson-Albertsson, and Michael Hermanussen for helpful insights on earlier drafts of this paper. This research was supported by the Italian Ministry of University, Research, Science and Technology grants for the years 1998–2002 and ONLUS Nutrizione e Prevenzione, Firenze for years 2003–2008. The authors declare that they have no competing interests.

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Research Signpost 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

The Meal by Meal Dynamic Energy Balance in Blood: Habits & Risks, 2011: 95-117 ISBN: 978-81-308-0457-6 Editor: Mario Ciampolini

7. Differences in maintenance of mean blood glucose (BG) and their association with response to “recognizing hunger” 1

Mario Ciampolini1 and Massimiliano Sifone2

Preventive Gastroenterology Unit, Department of Paediatrics Università di Firenze, 50132 Florence, Italy; 2Department of Statistics Università di Firenze, Florence, Italy

Abstract Background: Meals begin and end subjectively. We trained healthy subjects to recognize initial hunger as a preprandial target for meal consumption, and to create a “recognizing hunger” or initial hunger meal pattern.

Objective: Training subjects to “recognize hunger” lowers blood glucose (BG) and improves energy balance, and lowers metabolic risks and bodyweight. A minority may have low BG and low metabolic risks at recruitment, but the others may recover this favorable condition by training.

Methods: In a 7-day food diary, subjects reported their preprandial BG measurements; BG and energy availability by blood were assessed at the lowest BG during the day, and diarymean BG thus characterized the individual meal pattern (daily energy intake). We analyzed the same diaries of a recent paper on a global, randomized comparison of subjects trained in “recognizing hunger” with control subjects. This time, we checked whether subjects who had maintained low BG (LBG subgroup) at Correspondence/Reprint request: Dr. Mario Ciampolini, Preventive Gastroenterology Unit, Department of Paediatrics, Università di Firenze, 50132 Florence, Italy. E-mail: mlciampolini@fastwebnet.it

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recruitment were able to decrease mean BG and metabolic risk factors during “hunger recognition” like those who presented high BG (HBG subgroup).

Results: At recruitment, the BG means of 120 investigated subjects were within mean confidence limits of ± 3.84 mg/dL, and we could stratify subjects in ten small strata of which each significantly differed by mean BG. Mean BG was stable in each control subject over five months; the mean absolute change being 6.0 ± 4.6 mg/dL. Only three out of 34 trained subjects who had lower mean BG than 81.8 mg/dL significantly decreased mean BG, whereas 41 out of 55 subjects whose mean BG was greater than 81.8 mg/dL significantly decreased mean BG after training (P < 0.0001).

At recruitment, the LBG subgroup showed significantly lower insulin, lower BG area under curve (AUC) in the oral glucose tolerance test (GTT), and lower HbA1c than the HBG group. After training, only HBG subjects, compared with HBG controls, significantly decreased preprandial BG from 91.6 ± 7.7 mg/dL to 81.0 ± 7.7 mg/dL, in association with a decrease of HbA1c from 4.81% ± 0.44% to 4.56% ± 0.47%, of GTT insulin AUC from 244 ± 138 mU/L to 164 ± 92 mU/L, and of energy intake from 1872 ± 655 kcal to 1251 ± 470 kcal (P < 0.001), with an increase of indices of insulin sensitivity from 5.9 ± 3.3 to 9.8 ± 5.6 and of beta cell function from 1.0 ± 0.7 to 1.4 ± 1.1 (P < 0.05). LBG subjects only decreased weekly-diary BG standard deviation in comparison with controls.

Conclusion: At recruitment, the 120 subjects maintained mean BG at one personal level of ten possibilities, and 34 subjects were below 81.8 mg/dL (LBG) and 55 were over (HBG). The 55 HBG subjects showed higher mean insulin resistance, HbA1c, other cardiovascular risk factors, and increased bodyweight compared with the 34 LBG subjects. A total of 41 out of the 55 HBG subjects regressed to LBG with training.

Introduction Meals begin and end subjectively. People cannot share subjective sensations with others, such as sights and sounds. Subjective sensations guide a person’s food intake. In past investigations, we suggested subjects find a subjective target (initial hunger [IH]) before food intake on the first day, and measure blood glucose (BG) concentration as a marker of this target on the first and subsequent days.1-6 We named this ability to adjust food intake to times of IH arousal before meals three times a day “initial hunger meal pattern” (IHMP). This is a meal pattern based on “recognizing hunger”. We use these two simple words here to be more evocative than IHMP. We chose the target assessment and BG measurement before meals for the following five reasons: 1. Before meals, people sometimes recognize definite hunger sensations and are able to validate them through BG measurement.4-6

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2. A BG measurement (as well as validated hunger sensations, IH) is an evaluation of either sufficiency or excess of energy intake at previous meal, and is useful in planning meal sizes.4 3. Seven-day food-diary reporting, 21 consecutive BG measurements, and meal compositions may prove to be highly effective educational tools to evaluate food intake meal by meal as suggested in point 2.

4. Before mixed meals, in our experience, BG is lower than after food consumption in healthy individuals. A sequence of preprandial BG measurements provides information on the lowest mean BG and lowest mean energy availability during the examined days.

5. Point 4 is a metabolic characterization of an individual energy meal pattern, which is standard during the examined days, and the mean BG allows comparisons and classifications better than daily energy intake.

We previously investigated a pool of diaries of 120 subjects by assessing mean weekly BG of the group.6 Meal adaptation to “recognizing hunger” decreased mean BG, metabolic risks, insulin resistance, and bodyweight in the trained group compared with control subjects.5,6 The overall response in mean BG and the overall improvement overlooks differences in single meal patterns, insulin sensitivity, health at recruitment, and health in response to training. If mean BG is maintained as a personal habit, the differences may explain huge risk differences that can be personally felt and corrected by “recognizing hunger”.

Methods Participants Eligibility criteria and randomization Subjects were reported in a previous paper.6 Briefly, the Pediatric Gastroenterology Unit of Florence University recruited 143 subjects from 1996 to 2000. Aged 18-60 years old, subjects suffered from symptoms of functional bowel disorders such as dyspepsia, abdominal pain, and diarrhea (Figure 1)7,8 but were otherwise clinically healthy. Informed consent had been signed by all subjects. The local Hospital Ethics Committee approved the investigation in compliance with the Helsinki Declaration.

Before recruitment, we prepared a list of blocks of 1-4 empty places. In a ratio of 1:3 blocks, we randomly assigned the blocks of empty places to either control or training groups by using Armitage odd and even random numbers. A dietician kept the list and subsequently assigned each recruited

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Figure 1. Consort flow chart and study design. Notes: randomized and controlled 5-month clinical investigation to study mean blood glucose at recruitment and its association with response to “recognizing hunger”. Abbreviations: GTT, glucose tolerance test; HBG, high blood glucose; IHMP, initial hunger meal pattern (recognizing hunger); LBG, low blood glucose.

subject to the first empty list place. Control or training destination was revealed after the first visit (Figure 1).

The training The trained group exercised regularly under guided instruction for 7 weeks, and maintained the new strategies of food consumption and energy expenditure for a further 3 months without any assistance (Figure 1).

Subjects suspended food intake until arousal of a sensation of hunger, generally epigastric hunger.4 Meal consumption delayed 2 hours on average; range 0-48 hours. Hungry subjects measured BG by a portable instrument (see measurements below) and consumed a meal. The energy content was initially lower than before training to obtain a further hunger arousal before the subsequent mealtime. After 3-14 days of this training, subjects became aware of their current BG state before meals by sensations.4 IH was maintained pre-meal, adjusting meal sizes, composition, or timing of food intake. After a few days of trial and error, and sometimes irregular mealtimes, subjects were able to adjust their food intake so that IH appeared before the usual three mealtimes per day, with an average error of 30 minutes in 80% of instances in adults, and 90% in children (“recognizing hunger” or IHMP).9-14

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Both control (N = 31) and trained (N = 89) subjects had the same information on food energy content, recommended vegetable intake, and physical activity amount per day (weeks 0-7) (Figure 1).

Design All 120 subjects who completed the protocol were fully assessed at recruitment (before training), clinically only after the first 7 weeks of training, and completely at the end of the investigation (total investigation 5 months).

In 31 control subjects, we investigated whether food intake is habitual, ie, maintaining the same meal pattern by mean BG. Moreover, habits in BG maintenance may be personal, ie, sharply defined from most others. In all 120 subjects, we calculated mean confidence interval at recruitment (0.95%) for this purpose, and we stratified all 120 subjects in groups that contained subjects without significant differences in mean BG. Some subjects who had low mean BG at recruitment might fail any response to “recognizing hunger”, because this meal pattern lowers mean BG to the point of imminent subjective insufficiency (see description of training in previous studies).4-6 We decided to find the most significant cutoff point on the basis of individual response in mean BG, either significant or not due to training. After finding the cutoff, we separately investigated (at recruitment and during “recognizing hunger” 5 months from recruitment, compared with controls) the association of subjects with low mean BG (LBG) and high mean BG (HBG) with insulin area under curve (AUC), and indices of insulin sensitivity and beta cell function (primary endpoints). Analyses were also performed on BG AUC, measurements of BG and insulin concentrations during oral glucose tolerance test (GTT), mean BG, and glycated hemoglobin (HbA1c) values (secondary endpoints).15 Data are presented post hoc division. Data without division have been previously published6 and are not reported here.

Oral GTT After a 12-hour overnight fast, all subjects were given a 75 g oral glucose load. Venous blood samples were taken immediately before the glucose was administered, and 30, 60, 90, 120, and 180 minutes later to determine plasma glucose and serum insulin. Serum insulin was measured with the IMx insulin assay (Abbott Laboratories, Abbott Park, IL).16 From the GTT, we calculated the AUC, the index of whole-body insulin sensitivity (10,000/square root of

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[fasting glucose Ă&#x2014; fasting insulin] Ă&#x2014; [mean glucose Ă&#x2014; mean insulin during GTT]),17 and the insulinogenic index of beta cell function (ratio of the increment of plasma insulin to that of plasma glucose 30 minutes after glucose loading).18

Measurements Subjects measured capillary blood themselves using a glucometer (a portable device for whole blood glucose measurement) (Glucocard Memory; Menarini Diagnostics, Florence, Italy) within 15 minutes before each meal. Accuracy of measurements by the glucometer was validated against periodic measurements by hospital autoanalyzer. Subjects avoided BG measurements taken less than 1 hour after consuming even a few grams of food, after changes in ambient temperature, after physical activity such as walking or cycling, or under psychological stress or being feverish, because BG in these circumstances is higher than 1 hour after cessation of the transient metabolic condition.4 The 7-day home diaries reported BG measurements before the three main mealtimes, energy and vegetable intake, hours in bed and hours spent during physical and outdoor activities (weekly mean and standard deviation [SD]), and presence or absence of preprandial sensation of epigastric hunger.10-14 Subjects compiled the diaries before training, after 7 weeks, and at the end of the study. Our previous studies include more details on the validation of BG estimation compared with BG measurements,4,10-14 comparison of energy intake and total energy expenditure as assessed by doubly labeled water in infants,12 HbA1c,15 methods for anthropometric measurements, structured interviews, and relevant clinical blood tests.11-13,19

Additional assessments Additional analyses were performed on energy balance, wellbeing, nutrition, and cardiovascular status, as follows.

1. Structured interviews ascertained the number of days in which each of the five functional symptoms (diarrhea, vomiting, headache, epigastric, or abdominal pain) occurred during the previous 3 months. The hours of daily physical activity and time spent in bed reported in the 7-day diary were also assessed because an increase of the former and a small decrease in the latter suggests improvement in wellbeing.11,19

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2. Nutrition was assessed by monitoring blood hemoglobin, mean cellular volume, transferrin saturation, plasma ferritin, zinc, folates, and vitamin B12.19 3. Cardiovascular status was assessed by systolic and diastolic blood pressures, plasma low density lipoprotein (LDL) cholesterol/high density lipoprotein (HDL) cholesterol ratio, triglycerides, and HDL cholesterol.

4. Energy balance during the 5-month investigation interval was assessed through measurement of arm and leg skin-fold thickness changes, by measurements of body weight and body mass index (BMI), and by assessment of reported energy and vegetable intake. BMI and body weight constituted the primary endpoint of a recent article.5

Statistical methods In a previous study, we found an insulin sensitivity index in the intervention group 3 mg/dL higher than in the control group, with an SD of 3.0.6 Based on these figures, our sample size calculations suggested that we need a minimum of 14 subjects in each comparison group to detect a similar difference between index means, with a power of 80% and a unilateral alpha of 0.05.

Values are expressed as mean ± SD. Twenty-one diarized BG measurements had a normal distribution around the mean. Confidence intervals were calculated to include 95% of measurements.20 Stratification of 120 subjects by mean BG and search for the cutoff point at recruitment between subjects who significantly responded to “recognizing hunger” by mean BG and nonresponders was discussed in the Statistics Department of the University of Firenze (see Acknowledgments). In the separate LBG and HBG subgroups, a logistic regression analysis investigated the association of the training and BG mean, Hb1c, insulin and BG AUCs, intakes, and anthropometric measures (trained vs untrained control groups) to overcome doubts on significance of multiple results.21 Collinearity diagnostics and residual analysis validated the statistical model. The significance of difference and correlation was set at P < 0.05 in these analyses. Yates test and two-tailed Student’s t-test on paired or unpaired samples according to data requirements were used to analyze the significance of difference and twotailed Student’s t-test for correlation. The significance was set at P < 0.05 for single measurements and at P < 0.025 for the GTT insulin and BG AUCs.20 The trials on wellbeing, nutrition, and cardiovascular risks comprised five to seven tests each.20,21 The significance was set at P < 0.01 for the outcome of a single measurement within these trials. The Bonferroni correction was applied when required in the evaluation of multiple comparison results.20,21 In

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multiple analyses, the “<” symbol indicates the least significant P-value.

Specially provided software was used to tabulate data for statistical analyses.

Microsoft Excel and SAS (v 8; SAS Institute, Inc, Cary, NC) were used for data presentation and for statistical analyses.

Results Flow of participants Figure 1 shows the flow of participants through each phase of the investigation. Although some subjects may not have been compliant to the “recognition of hunger” for all meals, we have included all 89 trained subjects who completed the investigation in the final analysis because it was our intention to treat them.

Twenty-three dropouts were contacted by telephone at the end of the investigation and their reasons noted. Their reasons were that they “required no further training” or had “busy schedules”. We have 7-week data from all 23 dropouts. We allocated the 18 trained dropout subjects to LBG or HBG subgroups (see Design section) and obtained nine subjects in each subgroup.

Over the 7-week training period, LBG subjects maintained constant mean BG (from 78.6 ± 2.6 to 76.3 ± 4.7 mg/dL). HBG subjects significantly decreased mean BG (from 88.1 ± 4.1 mg/dL to 81.5 ± 5.0 mg/dL; P = 0.004), energy intake (from 1657 ± 423 to 1005 ± 319; P = 0.0001), BMI (from 23.6 ± 2.5 to 22.6 ± 1.8; P = 0.04), and leg skin-fold thickness (from 31.8 ± 8.2 to 27.8 ± 9.9; P = 0.04). The five control dropout subjects showed no change in these assessments.

At recruitment, values of mean BG, mean age, school education years, body weight, BMI, height, skin-fold thickness, arm and leg circumferences, systolic and diastolic blood pressure, and blood values did not significantly differ between control and trained groups and between LBG and HBG subgroups in both the trained and the control groups (Tables 1-3).

The results reported refer to the 120 subjects (60 females and 60 males) who completed the study (89 trained versus 31 controls).

Stratification of 120 subjects by significant differences in mean preprandial BG At recruitment, mean BG was distributed from 64.5 to 109.9 mg/dL in all 120 subjects, but the mean confidence interval (95%) of diary measurements around mean BG was ± 3.84 mg/dL. In Figure 2, all 120 subjects were

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Figure 2. Increasing sequence of mean BG of all 120 trained and control subjects divided into ten strata (columns) at recruitment. Notes: Strata consist of subjects with no significant difference in mean BG inside the stratum. Moreover, each stratum excludes subsequent subjects whose mean BG is significantly higher than that of the first subject in the stratum. Column height shows the first component. Mean BG is reported in sequentially increasing order at recruitment, not in linear correlation with segment length on the x-axis scale. Abbreviation: BG, blood glucose.

stratified into ten groups by increasing mean BG at recruitment. Each of the ten stratifications included subjects who showed no difference in mean BG (P > 0.05), but excluded subjects who had significant differences.

Stability of mean BG in control subjects 31 control subjects maintained a stable mean BG after 5 months (from 85.2 ± 8.1 mg/dL to 85.3 ± 7.6 mg/dL). The absolute pre/post change (increase or decrease) was 6.0 ± 4.6 mg/dL, with a confidence interval (95%) of 3.1-8.9 mg/dL.

LBG and HBG subgroups by response to “recognizing hunger” Figure 3 shows the increasing mean BG sequence in 89 trained subjects and their response to “recognizing hunger” training. Significant decrease of mean BG by the end of the investigation occurred mainly in subjects with high mean BG at recruitment, whereas mean BG remained relatively constant in subjects with low BG at recruitment. A cutoff value (demarcation point) of mean BG that most significantly divided these two subgroups was identified at 81.8 mg/dL. Figure 3 shows mean BG changes (post- minus pre-values as

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Figure 3. Difference after training versus value in mean blood glucose for each trained subject at recruitment. Notes: Column height shows 5-month post- less premean blood glucose difference from 7-day diary in each trained subject. Significant increases in blue, significant decreases in red, and no significant changes in black.

Mean blood glucose reported in sequentially increasing order at recruitment, not in linear correlation with segment length on the x-axis scale. The dashed division indicates the most significant division between subjects who showed no mean blood glucose decrease after training (LBG group, n = 34 subjects) and those who showed significant decrease of mean blood glucose (HBG group, n = 55 subjects; Ď&#x2021;2 analysis: P = 0.00001). This threshold blood glucose at recruitment (demarcation point) is 81.8 mg/dL (4.5 mmol/L). Abbreviations: HBG, high blood glucose; LBG, low blood glucose.

a function of the BG means at recruitment). A total of 34 subjects below this demarcation point formed the LBG subgroup. A total of 55 subjects above this demarcation point formed the HBG subgroup. Similarly, the BG value of 81.8 mg/dL was used to divide control subjects into LBG and HBG control subgroups (Tables 1 and 2).

Differences between LBG and HBG subgroups at recruitment At recruitment (before training), the LBG subgroup (over the difference in mean BG) showed significantly higher insulin sensitivity index (P = 0.0003), lower insulin AUC (P = 0.02) and BG AUC and peak (both P = 0.0001), diary BG standard deviation (P = 0.01), energy intake per day (P = 0.03), and HbA1c (P = 0.0001) compared with the HBG subgroup. At recruitment, the two LBG and HBG subgroups sharply differed from each other in meal pattern and risk factors.

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Effects of “recognizing hunger” in LBG and HBG subgroups In LBG subjects (BG < 81.8 mg/dL; n = 34: 38.3%) (Tables 1 and 2), mean BG remained constant after training (pre, 76.6 ± 3.7 mg/dL; post, 77.2 ± 4.2 mg/dL; P = 0.499) (Table 2), whereas in HBG subjects (> 81.8 mg/dL; n = 55: 61.7%) (Tables 1 and 2), mean BG significantly decreased after training (pre, 91.6 ± 7.7 mg/dL; post, 81.0 ± 7.7 mg/dL; P < 0.0001) (Table 2). In the control subgroups, mean BG did not decrease throughout the study in either the LBG or HBG subgroups (Table 2). The mean BG, diaryBG SD, and HbA1c significantly decreased in the trained HBG subgroup compared with the control subjects (Table 2). Logistic regression longitudinal analyses in these trained and control HBG groups confirmed a significant training effect on mean BG (P = 0.007) and on HbA1c (P = 0.014). In the LBG group, most variables were significantly lower than those in the HBG group since recruitment (Table 2), and despite the low value, the diaryBG SD significantly decreased in the longitudinal comparison and in the comparison with the LBG control group.

In summary, the training decreased insulin AUC, index of whole body insulin resistance, and HbA1c, and increased the insulinogenic index only in HBG subjects, and prevented the rise of these metabolic risk factors in LBG subjects.

Table 1. Group composition and effects of training on anthropometry in low and high BG subjects.

Notes: Values are expressed as mean ± SD. aValues at the beginning of the study; bSignificant difference (Student’s t-test: P < 0.01) on pre/post difference versus value of the same group at recruitment; cSignificant difference (Student’s t-test: P < 0.01) on pre/post difference versus respective control group; dSignificant difference (Student’s t-test: P < 0.001) on pre/post difference versus value of the same group at recruitment; eSignificant difference (Student’s t-test: P < 0.05) on pre/post difference versus value of the same group at recruitment; fSignificant difference (Student’s t-test: P < 0.05) on pre/post difference versus respective control group. Abbreviations: BG, blood glucose; BMI, body mass index; F, female; M, male; SD, standard deviation.

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Table 2. Effects of training on metabolic and intake parameters in low and high BG subjects.

Notes: Values are expressed as mean ± SD. Peak values include different observations from those at 30’ during GTT. aSignificant difference (Student’s t-test: P < 0.001) versus the value of LBG trained group at recruitment; bSignificant difference (Student’s t-test: P < 0.001) on pre/post difference versus respective control group; cSignificant difference (Student’s t-test: P < 0.001) on pre/post difference versus the value of the same group at recruitment; dDiary SD refers to the mean of the mean BG standard deviations of 21 measurements reported by each of the 7-day diaries; eSignificant difference (Student’s t-test: P < 0.01) versus the value of the same group at recruitment; fSignificant difference (Student’s t-test: P < 0.05) on pre/post difference versus respective control group; gSignificant difference (Student’s t-test: P < 0.01) on pre/post difference versus the value of LBG trained group at recruitment; hSignificant difference (Student’s t-test: P < 0.01) on pre/post difference versus respective control group; i Significant difference (Student’s t-test: P < 0.05) on pre/post difference versus the value of LBG trained group at recruitment; jWhole body insulin sensitivity index;17 kInsulinogenic index of beta cell function;18 lSignificant difference (Student’s t-test: P < 0.05) on pre/post difference versus the value of the same group at recruitment; mMeal was an event of higher intake than 20 kcal. Abbreviations: AUC, area under glucose tolerance test curve; BG, blood glucose; Hb, hemoglobin; SD, standard deviation.

Other trials The wellbeing, nutrition, and cardiovascular trials (see Methods section) showed no significant differences between trained and control subjects in the LBG group. In the trained HBG group (Table 3), the decreases in days with abdominal pain or stomachache, in diastolic blood pressure and in LDL to HDL cholesterol ratio, and the increase in the HDL cholesterol were

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Table 3. Effects of training on wellbeing, cardiovascular, and nutrition parameters in HBG groups.

Notes: aSignificant difference (Student’s t-test: P < 0.01) on pre/post difference versus the value of the same group at recruitment; bSignificant difference (Student’s t-test: P < 0.001) on pre/post difference versus respective control group; cSignificant difference (Student’s t-test: P < 0.001) on pre/post difference versus the value of the same group at recruitment; d Significant difference (suppressed for Bonferroni correction) on pre/post difference versus respective control group; eSignificant difference (Student’s t-test: P < 0.01) on pre/post difference versus respective control group; fSignificant difference (suppressed for Bonferroni correction) on pre/post difference versus the value of the same group at recruitment.

Abbreviations: fl, femtoliters; HBG, high blood glucose; HDL, high density lipoprotein; LDL, low density lipoprotein; MCV, mean cellular volume.

significant and significantly larger than in the control HBG group (P < 0.005; the Bonferroni correction required at least P < 0.01; see Statistical analysis section above).

“Recognizing hunger” fading and overlapping HBG At clinical examination after 7 weeks of training, 77 out of 89 trained subjects reached mean preprandial LBG, and 62 maintained this level at the end of the study. Achieving LBG appeared to be difficult for six out of nine subjects with high pre-training BG means (around 100 mg/dL). Six further HBG subjects reported being involved in heavy outdoor work for 8-10 hours

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Table 4. Effects of heavy outdoor work in 6 of 27 trained subjects who remained with high BG at investigation end.

Notes: aSix HBG subjects reported doing heavy work all day in outdoor environment during cold weather while practicing “recognizing hunger”. No significant differences in the five parameters from recruitment. At recruitment, mean BG = 86.9 ± 5.3 mg/dL in 27 HBG subjects; bThe 21 HBG subjects included 15 that were LBG after 7 weeks training (clinical assessment) and six who had higher mean BG than 100 mg/dL at recruitment; cP < 0.01; dP < 0.05; eP < 0.001.

Abbreviations: AUC, area under curve at glucose tolerance test; BG, blood glucose; HBG, high blood glucose.

every day in a cold winter during the study. Their reports, insulin, BG AUCs, and insulin sensitivity index (Table 4) at final examination suggested they complied with the “recognizing hunger”, but they did not achieve mean preprandial LBG.

Discussion Clinical events In a third-level referring center, we investigated gastroenterology patients with a functional bowel disorder, a self-recovering disease. Subjects considered compliance as difficult before training and easy after training.

Yet, about one-third of the subjects already maintained a mean LBG by free personal choice at recruitment. The easy maintenance between the ages of 18 and 60 years and the rapid recovery allowed sustained compliance. The functional disorder was significantly associated with high mean BG (and insulin resistance) in HBG subjects, and possibly with high SD of BG in LBG. In infants, we suggested that positive balance of energy stimulates a diarrheic feedback.9 Recurrences are prevalent in the adult population throughout life and are sufficient to motivate balance correction (training in “recognizing hunger”) in a large part of population to improve insulin sensitivity and metabolic risk factors.

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Subjective and objective assessments The training was subjective. Subjects learned to recognize IH on the first day and adapted food intake to the arousal of this target sensation three times a day. The BG association checked the consistency of the “recognition of hunger”. BG is an index of current energy availability to body cells in healthy people on a mixed diet.1-3 In our experience of BG measurements, premeal values are actually lower than after food intake in healthy people on a mixed diet. A week sequence of BG measurements before meals shows nutrient delivery (in situations of mixed food intake) to body tissues at their lowest points. This is a standard metabolic assessment that allows comparisons and also the evaluation of sufficiency or excess of nutrient delivery to body tissues. This delivery of nutrients is the purpose of eating. Daily energy intake does not give information on energy availability. The standard week assessment is even more important because mean BG was maintained as a habit in control subjects, ie, for a longer period than 1 week, and was individual, differing from one person to another. Before initial abstinence from food (before training), HBG subjects habitually forestalled the arousal of the physiological regulation mechanism and maintained positive energy balance. On the basis of the high SD of BG (Table 2), the meal pattern of untrained LBG subjects was irregular from one meal to another in comparison with during the “recognition of hunger”, regardless of null balance, low mean BG, and weight stability in a longer period.5 We cannot conclude that LBG coincided with “recognizing hunger” (see below).

Unremitting adjustment to energy expenditure The food diary with preprandial BG measurements also served as an educational instrument. We trained (and checked) the participants to “recognize hunger” and to adjust food intake according to sensations mealby-meal with the reported diary. Five-month energy balance showed reliability of the reported “recognition of hunger”. Within this view, dieting represents a rough attempt to achieve an ideal weight without understanding and implementing the necessary meal-by-meal adjustments to expenditure.

Sufficient intake by “recognizing hunger” Trained HBG but not LBG subjects showed a cumulative balance that was negative during the 5 months, and the longitudinal difference was significant in comparison with control subjects. The significant decrease of body weight, BMI, and arm and leg skin-fold thickness in the HBG group

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and the stability of the LBG group confirmed a persistent implementation of “recognizing hunger” and associated adjustments to energy expenditure throughout the duration of this investigation. Another paper has detailed the effect of the “recognition of hunger” on body weight using a larger sample.5 The maintenance of previous physical activities in all trained subjects and the improvement in nutrition parameters in the HBG subgroup (Table 3) demonstrate that meals taken by trained subjects were sufficient to meet energy needs. This confirms earlier controlled, randomized studies in children with chronic nonspecific diarrhea, in which daily activity was preserved and body weight increased normally after 7 months, 4 years, and 12 years of complying with a pediatric adaptation of the present training.9-13

Diabetes prevention It is interesting that insulin production decreases with increasing noninsulin dependent diabetes (NIDD) duration and HbA1c level.18 In this study, the HBG control subgroup decreased insulinogenic index of beta cell function, whereas the HBG trained subgroup increased it. The difference between control and trained subgroups was significant; this implies higher insulin production, preservation of beta cell function, and the possibility of an innovative therapy designed to preserve or even improve functional beta cell mass by “recognizing hunger”.18 In a longitudinal investigation of 13,163 subjects, a fasting plasma glucose of ≥ 87 mg/dL (4.8 mmol/L) was found to be associated with an increased risk of NIDD in men compared with those whose fasting plasma glucose was < 81 mg/dL (4.5 mmol/L).22 Assessment and classification of meal habits allows correction toward metabolic risk decrease, as in Framingham studies.15

Diabetes treatment In this research, “recognizing hunger” prevented insulin resistance and NIDD in young, clinically healthy subjects with “normal” BG. The aim was to suppress subclinical inflammation (pro-inflammatory state) and the associated functional disorders and evolving vascular diseases.23-25 “Recognizing hunger” may also be helpful to some people with NIDD. Unfortunately, “recognizing hunger” contrasts the currently prevailing idea of constancy in time of daily energy intake. NIDD patients may have no hunger sensation at all. Absent arousal of hunger facilitates low energy intake. As an extreme example, two meals per day of 50 g of fish and salad, 100 kcal per meal, produced rapid and large weight loss and recovery of hunger sensations

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after adequate weight loss. Some of these people who lost weight show low estimation error of BG after training in “recognizing hunger”.4 The low error validates “recognizing hunger”, and prevents regaining body weight.5 Thus, adaptation of “recognizing hunger” to treating aged people with fully developed NIDD requires further investigation, and suggests that current treatment practices shall survive for some of these patients.

“Recognizing hunger” fading and overlapping HBG Mean BG had little absolute change (13.2% ± 10.1% of the range at recruitment in mean BG in the 120 investigated subjects: 64.5 mg/dL to 109.9 mg/dL) in control subjects over 5 months. The division of the 120 subjects into ten strata at recruitment was a classification of associated meal pattern. Subjects chose “recognizing hunger” at the lowest level of BG availability during the day. It is no surprise that “recognizing hunger” largely coincides with LBG meal patterns. The point of mean inversion was at 81.8 mg/dL. However, 27 out of 89 subjects persisted at HBG level at final investigation, although 15 out of 27 were within LBG limits after 7 weeks of training. Six subjects were engaged in heavy work during cool winters. The six subjects had a mean BG of 86.4 ± 4.0 mg/dL, which showed no difference from 87.1 ± 5.3 mg/dL in 21 out of 27 other subjects. IH developed in these outdoor heavy workers at higher levels than 81.8 mg/dL for high expenditure.

The division between compliance and noncompliance with “recognizing hunger” is statistically strong at 81.8 mg/dL, but some subjects may “recognize hunger” and overlap with HBG during transient or persistent conditions of high energy expenditure.

Conclusion “Recognizing hunger” showed a strong statistical association with LBG, with some overlapping with HBG in a few subjects with high energy expenditure and was associated with metabolic improvements as in previous investigations, although only in 55 out of 89 HBG trained subjects.4-6 A total of 38.3% of randomized trained subjects maintained LBG (to that at recruitment), and only decreased the SD of diary BG by “recognizing hunger”. This decrease in SD with the maintenance of the mean suggests that part of the untrained population often recognizes hunger before eating.

“Recognizing hunger” as a training method may be a rationalization of the use of physiological stimuli to eat in order to improve health.

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Acknowledgments The authors wish to thank: Laura Chiesi and Stefania Bini MD for dietary analyses; Riccardo Bianchi, David Lovell-Smith, Andrea Giommi (Statistics professor), and Stella Zagaria for technical support; and Stephen Buetow, Tim Kenealy, Chris Harshaw, Simon Thornton, Kent Berridge, James Gibbs, Charlotte Erlanson-Albertsson, and Michael Hermanussen for helpful insights on earlier drafts of this paper. This research was supported by the Italian Ministry of University, Research, Science and Technology grants for the years 1998-2002 and ONLUS Nutrizione e Prevenzione, Firenze for years 2003-2008.

Comment The 2010 version reports: “People who are most successful at achieving and maintaining a healthy weight do so through continued attention to consuming only enough calories from foods and beverages to meet their needs and by being physically active”. We found similar differences in about ten thousands diaries of children and adults. BG is correlated with post meal energy abundance for tissues and subsequently with either energy sufficiency or insufficiency. Single BG measurements allow poor comparison among people. In the article of this chapter, a weekly mean of pre-prandial BG measurements revealed that provision of energy to the body is habitual, personal (significantly different from mean BG of other people) and with low inter-personal variability (confidence limits of 3.84 mg/dL). Yet, provision of energy (BG) to body cells is an assessment that effectively characterizes subjects’ intake at the same metabolic moment in comparisons to that of subsequent months or other people and to homeostatic needs, insulin sensitivity and health (Chapter I).

Daily energy intake does not reveal any relation to physiology and allows poor interpersonal comparison. Part of investigated subjects spontaneously showed the mean LBG level of 76.6 ± 3.7 mg/dL at investigation start and spontaneously maintained the same level in subsequent months. This level was associated with the highest prevention of metabolic risk factors. These facts and the regression to the LBG level (and the associated regression to the LBG risk factors) of HBG group, the absence of signs of nutritional or energy deprivation and the absent development of anorexia nervosa during "recognizing hunger" suggest that the meal pattern associated with LBG is homeostatic. "Recognizing hunger" may be a tool for achieving homeostasis.

Recognizing hunger" is strongly associated with LBG with some overlapping

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over HBG. During "recognizing hunger", subjects with high energy expenditure require the high BG level. During or immediately after outdoor activity, energy provision (BG) is necessarily high. BG measurements must be done at least an hour after physical or outdoor activity.

LBG meal pattern by free choice In most investigations, we found a number of subjects with an LBG meal pattern already at recruitment. We grouped these subjects in the first column of data in table 5. The second column reports groups showing LBG only after training "recognizing hunger". In infants starting the training to "recognizing hunger", the prevalence of spontaneous LBG was 24.7% and in adults 38.3% of the totally recruited subjects. The existence of spontaneous LBG meal patterns in part of the population implies that training "recognizing hunger" and the associated acquisition of LBG is a reasoned regression to a (insulin sensitive, homeostatic!) condition that is naturally present in the healthiest part of the population, and is not a technological artifact like dieting. An LBG level of 76.6 Âą 3.7 mg/dL may easily be maintained by most people either spontaneously or after training [4]. This level for Initial Hunger may be easily maintained by humans between the ages of 18 and 60 years.

We adapted "recognizing hunger" to infants, and the initial request substituted Initial Hunger (Initial Request Meal Pattern, IRMP) [2]. In 73 infants [12], the cutoff at 81.2 mg/dL divided subjects with low mean BG from those with high mean BG at recruitment by the highest significance. By this division, 18 infants showed low mean BG and 55 infants showed high mean BG at recruitment. This cutoff in infants is quite similar to the cutoff (81.8 mg/dL) that we found in adults in the present chapter and to the cutoff found in prevention of non-insulin dependent diabetes in Israeli recruits [22].

In the same preliminary work [12], we reported a significant 15% â&#x20AC;&#x201C; 16% decrease in RMR by respiratory calorimetry and in total daily expenditure (TDE) by doubly labeled water in 24 infants from before training to during IRMP. IRMP decreases mean BG, RMR and TDE in infants. We interpreted the three decreases during IRMP (Vs. meal pattern at recruitment) as an elimination of forestalling IH, i.e. leaving behind meal by meal positive balance and acquiring null balance in blood. Taking together the investigations on children and adults, "recognizing hunger" decreased mean BG, RMR and TDE, meal by meal positive balance in blood, insulin resistance, intestinal disorders, and health risks (subclinical inflammation).

The following table has not been published, except for 6 groups reported in this and in the following article. There are findings from 9 different groups.

Here we selected subjects by their low mean BG from larger groups.

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Table 5. Occurrence of low mean blood glucose (LBG) either before or after training "recognizing hunger" in 7 different groups.

Training1 34 adults (BMI from 17 to 40) 12 adults, ctrl 18 diarrheic infants 9 normalweight adults, ctrl 26 normalweight adults, 8 overweight adults, ctrl 12 overweight adults 3 41 HBG adults 41 HBG infants4

Before 2 76.6 ± 3.7 76.9 ± 3.4 77.1 ± 3.8 77.3 ± 3.9 76.5 ± 3.9 77.4 ± 3.6 77,1 ± 3,1 91.7 ± 7.8 92,3 ± 7,7

After 77.2 ± 4.2 No training 75.2 ± 6.9 No training 76.7 ± 4.1 No training 77,2 ±4,8 78.5 ± 6.8 74,7 ± 5,1

1. Trained subjects show mean BG both before and after training. No training refers to subjects kept as control (ctrl).

2. Mean ± SD of mean diary of 21 pre-prandial BG in a week in mg/dL. 3. 41 of 55 adults of mixed body mass index (BMI) and mean BG > 81.8 mg/dL at recruitment who significantly decreased mean BG after training "recognizing hunger".

4. 41 of 55 infants recruited for diarrhea, who showed arm skin-fold thickness on 15th percentile of normal reference. They significantly decreased mean BG from > 81.1 mg/dL, the level at recruitment.

LBG and heavy outdoor working Twenty-seven of 89 trained subjects maintained HBG at the end of the investigation. We tried to find an explanation from data after 7 weeks training. Six of 27 subjects had 100 mg/dL, or over, at recruitment. Only three of 9 subjects who showed BG over 100 mg/dL at recruitment were able to lower BG below 81.8 mg/dL after training. A borderline condition to noninsulin dependent diabetes might reduce chances of effective training. Fifteen of 27 showed LBG after 7 weeks from recruitment, and regressed to HBG after 5 months from recruitment. Yet, subjects denied any drop in "recognizing hunger" and the regression might have been partly due to an intermediate lifestyle with the following group of six heavy outdoor workers.

These remaining six of 27 did heavy outdoor work all day long. One of these reported having no gastric sensations at all at recruitment, even long after consuming a meal. We exceptionally suggested meal start after BG decrease to below 81.8 mg/dL. The subject endured physical weakness for two hours before meal consumption, BG lowered from 92.5 ± 5.1mg/dL to 80.7 ± 5.7 mg/dL and body weight from 74.5 to 67.4 kg after 36 days. He coped with an

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open air heavy job during cold winter, his height was 189.5 cm (recruitment BMI = 20.75), and energy intake showed a decrease from 3613±615 kcal/d to 1817±394 kcal. We suggested this subject to use the sensation of physical weakness as IH and as an appropriate signal for meal onset. In the subsequent 40 days, the subject increased intake to 2380±459 kcal, BG to 85.6±4.7 and weight to 70.95 kg. In the meantime he had solved recruitment complaints (abdominal pain and dermatitis).

A cut point in BG for eating?

The results in the 6 heavy outdoor workers suggest that they developed IH at a significantly higher BG than subjects who were mostly employed in office or home work. Also after gym activity subjects recognized IH at high BG. Between expenditure and the cut point in BG for IH may exist a linear correlation. The 6 workers are at an extreme of this correlation. During Winter, walking or cycling people arrived hungry to home but found HBG at measurement. At home entry, energy expenditure decreased and BG increased. To assess the habit in personal energy availability, BG measurements require a standard time and condition as shown in Methods, Measurements. A psychological stress may maintain high BG and no intake need for days. Excluding these transient circumstances, the mean cut point for IH is 76.6 ± 3.7 mg/dL in healthy adults and other people (Table 5).

Further investigations may add precision to these conclusions.

Promotion of LBG meal pattern Many countries support a national system of assistance that pays physicians to provide gratuity assistance. The payment might be increased (doubled) for every patient who maintains HbA1c lower than 5.0%.

Physicians will thus take advantage from studying and counselling ways to promote nutritional health.

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Bini, S., Ciampolini, M., Chiesi, L., Vicarelli, D. Energy need and glycemia before the meals of 23 normal-weight IBS adults. Appetite. 1992;19:166.

Singer, DE., Nathan, DM., Anderson, KM., Wilson, PWF., Evans, JC. Association of HbA(1c) with prevalent cardiovascular disease in the original cohort of the Framingham Heart Study. Diabetes. 1992;41(2):202-208.

Morihara, K., Oka, T., Tsuzuki, H., Tochino, Y., Kanaya, T. Achromobacter protease I-catalyzed conversion of porcine insulin into human insulin.

BiochemBiophys Res Commun. 1980;92(2):396-402.

Matsuda, M., DeFronzo, RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp.

Diabetes Care. 1999;22(9):1462-1470.

Wiesli, P., Schäffler, E., Seifert, B., Schmid, C., Donath, MY. Islet secretory capacity determines glucose homoeostasis in the face of insulin resistance. Swiss Med Wkly. 2004;134(37-38):559-564.

Ciampolini, M., Vicarelli, D., Seminara, S. Normal energy intake range in children with chronic nonspecific diarrhea: association of relapses with the higher level. J Pediatr Gastroenterol Nutr. 1990;11(3):342-350.

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Godfrey, K. Comparing the means of several groups. New Engl J Med. 1985; 313(23):1450-1456.

Tirosh, A., Shai, I., Tekes-Manova, D., et al. Normal fasting plasma glucose levels and Type 2 diabetes in young men. New Engl J Med. 2005;353(14):1454-1462.

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23. Reaven, GM. The metabolic syndrome: is this diagnosis necessary? Am J Clin Nutr. 2006;83(6):1237-1247.

24. Festa, A., Dâ&#x20AC;&#x2122;Agostino, R. Jr,, Howard, G., Mykkänen, L., Tracy, RP., Haffner, SM. Chronic subclinical inflammation as part of the insulin resistance syndrome: the Insulin Resistance Atherosclerosis Study (IRAS). Circulation. 2000;102(1): 42-47.

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Research Signpost 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

The Meal by Meal Dynamic Energy Balance in Blood: Habits & Risks, 2011: 119-143 ISBN: 978-81-308-0457-6 Editor: Mario Ciampolini

8. “Recognizing hunger” (initial hunger meal pattern) and body weight Sustained self-regulation of energy intake.

Loss of weight in overweight subjects.

Maintenance of weight in normal-weight subjects 1

Mario Ciampolini1, David Lovell-Smith2 and Massimiliano Sifone3

Unit of Preventive Gastroenterology, Department of Paediatrics, Università di Firenze 50132 Florence, Italy; 2Department of General Practice and Primary Health Care University of Auckland, Auckland, New Zealand; 3Department of Statistics Università di Firenze, Florence, Italy

Abstract Background: Dietary restraint is largely unsuccessful for controlling obesity. As an alternative, subjects can easily be trained to reliably recognize sensations of initial hunger (IH) a set of physiological sensations which emerge spontaneously, not necessarily at planned mealtimes, and may be the afferent arm of a homeostatic system of food intake regulation. Previously we have reported that IH is associated with blood glucose concentration (BG) below 81.8 mg/dL (4.55 mmol/l), (low blood glucose, LBG), and that a pattern of meals in which IH is present premeal (IHMP) Correspondence/Reprint request: Dr. Mario Ciampolini, Unit of Preventive Gastroenterology, Department of Paediatrics, Università di Firenze, 50132 Florence, Italy. E-mail: mlciampolini@fastwebnet.it

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improved insulin sensitivity, HbA1c and other cardiovascular risk factors. Here we report the effect upon weight in overweight and normal weight subjects.

Objective: To investigate whether the IHMP is associated with sustained loss of weight in overweight subjects over a 5 month period.

Methods: Seventy four overweight subjects (OW: BMI > 25) and 107 normal weight (NW) subjects were randomly allocated to either trained (OW: N = 51; NW N = 79) or control (OW: N = 23; NW: N = 28) groups. All subjects were allocated postrandomization into either low or high mean pre-meal BG groups (LBG and HBG groups) using a demarcation point of 81.8 mg/dL. Results: A significant longitudinal decrease was found in body weight (trained NW: -2.5 ± 4.6 kg; OW -6.7 ± 4.5 kg; controls: NW +3.5 ± 4.0 kg and OW -3.4 ± 4.0 kg; P = 0.006 and 0.029) and in energy intake, mean BG, standard deviation of diary BG (BG as recorded by subjects’ 7-day diary), BMI, and arm and leg skin-fold thickness in (OW and NW) HBG subjects. OW LBG subjects significantly decreased body weight (trained: -4.0 ± 2.4 kg; controls: -0.4 ± 3.7 kg; P = 0.037). 26 NW LBG subjects showed no longitudinal difference after training as did 9 control subjects.

Conclusion: Over a 5 month period the IHMP resulted in significant loss of weight in OW subjects compared to controls practicing dietary restraint. NW subjects maintained weight overall, however NW HBG subjects also lost weight compared to controls.

List of abbreviations BG LBG HBG BG estimation After training and validation Mean BG Diary-BG SD

NW OW BMI

: Blood glucose : Low mean pre-meal blood glucose concentration (below 81. 8 mg/dL) : High mean pre-meal blood glucose concentration (over 81.8 mg/dL) : During training: writing the expected BG value just prior to measuring the blood sample by glucometer. : subjectively evaluating own current BG value without measurement : Mean pre-meal blood glucose as reported by seven day diary : Mean pre-meal blood glucose standard deviation as reported by seven day diary.

Seven day diaries were completed at baseline, 7 weeks and 5 months : Normal weight (BMI below 25.0) : Overweight (BMI over 25.0) : Body mass index

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: Initial hunger : â&#x20AC;&#x153;Recognizing hungerâ&#x20AC;? or initial hunger meal pattern (see chapter 7).

1. Introduction The adverse effects of obesity are well known and include cardiovascular disease, type 2 diabetes and hypertension as well as gall bladder disease, osteoarthritis, endocrine disorders, sleep apnoea, social exclusion and depression [1,2]. More than 1.1 billion adults world-wide are overweight, and 312 million of them are obese [2]. Ten per cent of school-aged children world-wide are estimated to be overweight, and of these, one quarter is obese [3]. With a prevalence of overweight children at over 35% and obese children over 13 % (2003-2004 figures) the United States population is among the most obese in the world [4]. The prevalence of overweight children is lower in developing countries but is rising [5].

In adults, the decision to eat depends upon conditioned responses to external cues such as set mealtimes, others eating and highly palatable, available food (conditioned eating) as well as on physiological bodily sensations that reflect changes in the concentration of blood nutrients, including blood glucose [6] (unconditioned eating). Because conditioned eating tends to predominate, the feasibility of self-regulation of energy intake in an obesogenic environment has been questioned [7-9]. Dietary regimes that attempt to restrain eating have been largely unsuccessful [1,2].

The homeostatic systems that ensure constancy in osmotic pressure and body temperature rely for afferent information on bodily sensations (thirst and the sensation of heat respectively) [10]. We have trained subjects to reliably recognize comparable eating-related sensations that we group under the term initial hunger (IH) [11]. The necessity for such interoceptive information in homeostatic regulation has been recognized elsewhere [12-15]. We train subjects to adjust their meal-by-meal energy intake to ensure the pre-meal attainment of IH and its associated low BG concentration, three times per day. We term this routine the Initial Hunger Meal Pattern (IHMP) [16]. We suggest that IH is not conditioned by mealtime or other external cue and that the IHMP thus represents unconditioned eating. This contention is supported by our observation that in the early days of training subjects find that IH arises unexpectedly, often occurring at times far from usual mealtimes.

Elsewhere we found the IHMP was significantly associated with mean BG lower than 81.8 mg/dL (LBG) in weekly self-report diaries, and with improved insulin sensitivity, HbA1c and other cardiovascular risk factors in

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mixed body weight groups (NW and OW). Moreover, not only OW but NW HBG subjects lost weight under the IHMP supporting the notion that HBG and insulin resistance are important in the development of overweight [16].

Since BG concentration is a reliable index of energy availability to body cells [6], we hypothesized that the IHMP might allow for meal by meal homeostatic energy balance and weight regulation, and might be more effective than dietary methods that rely on restraint based on weekly or monthly measurements of weight. We now report the effect of the IHMP upon weight in OW and NW subjects.

Methods Eligibility criteria A total of 181 subjects were recruited by the Paediatric Gastroenterology Unit of Florence University between 1995 and 2000 into two separate lists (Figures 1 and 2). Subjects showed no morphological, physical or biochemical signs of organic disease [17, 18]. Subjects with impaired glucose tolerance (fasting plasma-glucose > 115 mg/dL (6.4 mmol/l)), as well as subjects suffering from non-insulin dependent diabetes mellitus (NIDDM), celiac, inflammatory bowel, liver, heart, brain and kidney diseases were excluded from recruitment. Informed consent was obtained from all participants. The local Hospital Ethics Committee approved the study in compliance with the Helsinki Declaration.

The intervention Subjects were trained in the IHMP, first by identifying IH, which was guided by consistency in subjective sensations and the association of these sensations with BG measurement.

Identification of IH [11] The explorative search for a subjectâ&#x20AC;&#x2122;s own signalling system took place during two instruction visits and a variable number of phone calls over the following seven weeks. Subjects were asked to ignore meal times at first, and to attend only to their sensations of hunger. At the earliest spontaneous arousal of sensations of hunger (IH) subjects were instructed to take note of the identified sensation, measure glucose concentrations with a portable instrument and consume a meal [11]. Subjects reported IH as gastric pangs, sensations of emptiness and hollowness and mental or physical weakness [11]. In the first three training days, before the IHMP was established, IH

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typically arose spontaneously and unexpectedly during usual activity often far from usual meal times (up to 48 hours, mean 2 hours) supporting the idea that IH is physiological and is not conditioned by external stimuli.

Training in the IHMP IH was cultivated pre-meal by adjusting composition, portion size or timing of food intake. After a few days of trial and error, and sometimes irregular mealtimes, subjects were able to arrange their food intake so that IH appeared before the usual three mealtimes per day with an average error of half-an-hour in 80% of instances [19]. If they overate at a given meal, subjects received feedback within a few hours since initial hunger did not appear pre-meal at the subsequent mealtime. This immediate feedback allowed for compensation by delaying, skipping or reducing the subsequent meal(s) (portion size and composition) to ensure a return of pre-mealtime initial hunger three times a day. Subjects were instructed to start a meal within 1 hour of the appearance of IH, and were prohibited from sustaining hunger for longer than 1 hour, to avoid BG declines below 60 mg/dL. Telephone assistance was provided so that subjects could describe their hunger sensations and times of occurrence, and to report pre-prandial BG and meal composition. With respect to content, up to 1 kg of fruit/vegetables per day was recommended [19]. Physical exercise for half an hour a day was also

Figure 1. Consort flow chart of NW subjects and investigation design. Randomized and controlled 5-month clinical investigation (and drop outs) to study the effect of IHMP on normal body weight after training.

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Figure 2. Consort flow chart of OW subjects and investigation design. Randomized and controlled 5-month clinical investigation (and drop outs) to study the effect of IHMP on body weight over 25 BMI after training.

encouraged although we were unable to document any change in either physical exercise or time spent in bed. Energy intake decrease (via smaller portion size and slightly lower numbers of meals per day) and increase in vegetable intake were therefore the significant variables in achieving initial hunger as in other investigations [11,19-23], and were negatively correlated (see results). The generally consistent association between IH and low BG measurement gave confidence in the reliability of the sensations of IH although we found that BG measurements taken less than 1 hour after taking even a few grams of food, after changes in ambient temperature, after physical activity such as walking or cycling and when under psychic stress were misleading since they did not correlate well with IH. Subjects repeated and refined this procedure three times a day for at least two weeks, and became able to accurately estimate pre-meal BG by their experience of IH [11]. Training ended after the first 7 weeks to be resumed only at investigation end. Thus after the first 7 weeks, subjects relied upon the identified subjective sensation (IH) alone, as the signal to begin a meal.

Control and training subjects were visited at baseline, after the 7 weeks of training, and at investigation end 5 months from baseline. The visits included clinical assessment, measurement of weight and BMI, diary handing, suggestions on compliance where appropriate, and validation of BG measurements [19-23]. Each subject measured his or her own blood sample by portable glucometer calibrated against the hospital laboratory

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autoanalyzer. Seven-day home diaries reported BG measurements before the three main meal times. Subjects were also instructed to perform half an hour per day of physical exercise, and consume up to 1 kg fruit and vegetables.

This purpose of the vegetables was to pre-vent distress from excessive hunger when IH appeared half an hour or more before mealtimes.

Control groups Control subjects were given information on food energy content and on recommended vegetable intake and physical activity similar to the trained subjects. The control OW subjects were encouraged to lose weight.

Study objective We wished to investigate whether the IHMP is associated with loss of weight over a 5 month period.

Outcomes Primary endpoint The primary endpoint was weight (expressed as BMI) at 5 months from baseline compared to controls.

Secondary endpoints At investigation end the following additional variables were assessed: 1.

2.

3.

4.

Pre-meal BG and BG standard deviation (BG SD) Arm and leg skinfold thickness [13,19].

Fruit and vegetable intake.

Systolic and diastolic blood pressures.

The seven-day home diaries also recorded food intake, bedtime hours and outdoor and gym hours [19-23].

Sample size Preliminary work in similar patients found BMI in the intervention group to be 26.6 (SD 3.6) and in the control group 29.0 (SD 3.5) [19]. Based on these figures, our sample size calculations suggested that we need a minimum of 21 subjects in each comparison group to detect a difference of 2.0 in group means, with a power of 80.% and a 1 sided alpha of 0.05.

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Randomization A dietician assigned subjects to either NW or OW lists according to body mass index (BMI) either lower or higher than 25.0. Subjects were allocated into trained and control groups in blocks (3:1) randomised by random numbers (Figure 1 and 2) [24].

Statistical methods Values are expressed as means ± SD. Yates test and two-tailed Student’s t-test on paired or unpaired samples with different variances according to data requirements were used to analyze the statistical significance of differences and correlations. The significance was set at P < 0.05 for single measurements. The Bonferroni correction was applied when required in the evaluation of results from multiple comparisons. The Chi-square for trend assessed the global significance of improvements in these trials. In multiple analyses between the same groups, the “<” symbol indicates the analysis of least significant P. MANOVA was performed on multiple variables to assess the training effect and main factors in training [2 4]. Evaluation of model assumptions was always checked.

Custom-made software was used to tabulate data for statistical analyses.

Microsoft Excel (Microsoft Corp., USA) and SAS 8 (SAS Institute Inc., Cary, NC, USA) were used for data presentation and statistical analyses.

Results Flow of participants Figures 1 and 2 show the flow of participants through each phase of the study.

Baseline demographics Baseline (i.e. before training) values of mean age, school education years, body weight, height, BMI, skinfold thickness, arm and leg circumferences, systolic and diastolic blood pressure did not significantly differ between the trained and the control NW and OW groups (in subgroups also, see section on post-hoc analysis below). The lowest P value on baseline differences between control and trained groups was in leg quadriceps thickness for NW HBG comparison (P = 0.07; Tables 1, 2, 3).

No significant gender difference in baseline mean pre-meal BG concentrations was observed in the control group (females: 83.8 ± 9.2 mg/dL;

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Table 1. Over-weight groups at baseline and at investigation end: composition, compliance and effects of training (IHMP) on diary reports and anthropometry.

Values are expressed as means ± SD. 1, years at the beginning of the study. 2, Number of subjects who significantly decreased mean pre-meal diary BG. 3, Mean pre-meal of diary blood glucose, mg/dL, LBG = lower than 81.8 mg/dL. HBG = higher than 81.8 mg/dL 4, Number of subjects who fell into the LBG at end of the study. 5, grams/d. 6, Kcal/d. 7, Diary BG SD refers to the SD of 21 BG preprandial measurements reported in 7 d diary by each subject. 8, Body weight in kg/ square height in meters. 9, kg. 10, mm. Asterisks indicate significant differences (Student’s t-test or Yates test: *, P < 0.05; **, P < 0.01; ***, P < 0.001) vs. respective control group values based on “post pre” measurements (a), or vs. baseline values of the same group (b).

n = 21; and males: 87,2 ± 7,5 mg/dL; n = 24; Student’s t-test for unpaired data: P = 0.24) and in the training group (females: 85.0 ± 8,9 mg/dL; n = 58; and males: 87.2 ± 9.9 mg/dL; n = 46; P = 0.22). The measurements from both genders were thus pooled in each group (Table 1). Baseline mean pre-meal BG for the control subjects (85.6 ± 8.4 mg/dL; n = 45) did not differ from that of the training subjects (86.0 ± 9.4 mg/dL; n = 104; P = 0.80).

Number of participants Results were obtained from 149 subjects (79 females and 70 males) randomized into control and training groups (see Methods) and completing the study (Figures 1 and 2).

Summary of the results OW group The IHMP was associated with a significant decrease in body weight and BMI in OW subjects compared to controls, after 7-weeks of training and 3

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months of application. In the control group BMI significantly decreased from baseline 29.1 ± 5.6 to 28.2 ± 5.6 after 5 months (P = 0.023), however BMI decreased from 28.7 ± 3.5 to 26.5 ± 3.5 in the trained group (pre/post P = 0.0001; comparison in longitudinal differences, P = 0.004). The changes in body weight confirmed BMI results.

MANOVA revealed a significant association between training and both BMI (P = 0.004) and body weight (P = 0.002) variations in the whole OW group. After insertion of the division of this group into LBG and HBG, MANOVA also revealed a significant association between mean BG and both BMI (P = 0.016) and body weight (P = 0.015). An interaction term between division in LBG and HBG groups and training did not reveal any significant change. We analysed by MANOVA training components and their association with BMI and body weight. Mean BG (P = 0.002) resulted as significant factor most involved with the variations in BMI and body weight.

Table 2. Normal- and over-weight groups divided by low and high mean pre-meal diary blood glucose (BG): composition and compliance at baseline and at investigation end.

Values are expressed as means ± SD. 1, years at the beginning of the study. 2, Number of subjects who significantly decreased mean pre-meal diary BG. 3, Mean pre-meal of diary blood glucose, mg/dL, LBG = lower than 81.8 mg/dL. HBG = higher than 81.8 mg/dL 4 , Number of subjects who fell into the LBG at end of the study. 5, grams/d. Asterisks indicate significant differences (Student’s t-test or Yates test): *, P < 0.05; **, P < 0.01; ***, P < 0.001) vs. respective control group values based on “post - pre” measurements (a), or vs. baseline values of the same group (b).

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The pre-meal mean BG showed a significant pre-post increase in the whole control group (P = 0.039), in contrast with a significant decrease in the trained group (P = 0.0001 in the pre/post and longitudinal differences between control and trained groups). Diary BG SD remained constant in control group and significantly differed (P = 0.012) from the post-test decrease in the trained group (P = 0.001).

We found no significant difference in the pre/post decrease in energy intake (Student’s t-test for unpaired data: P = 0.057) and increase in vegetable intake between control and trained groups (P = 0.629).

NW Group MANOVA revealed a significant association between training and BMI (P = 0.000), body weight (P = 0.000), arm skinfold thickness (P = 0.001) and leg skinfold thickness (P = 0.008) variations in the NW group. Diary BG SD (P = 0.012) was the factor most significantly associated with variations in arm skinfold thickness.

Post-hoc analysis - subgroups Baseline BG mean concentrations were distributed over a wide range.

Our results showed substantial weight decreases at study end not only in OW subjects but also in many NW subjects. It appeared that those NW subjects with high baseline BG might account for most of the weight loss shown by NW subjects. It was of interest therefore to use the “cut-off” value (demarcation point) of mean BG concentration that most significantly divided HBG and LBG subgroups in the previous study [16] (81.8 mg/dL) to set apart four subgroups: two subgroups (OW and NW) with low baseline BG (LBG) and two subgroups (OW and NW) with high baseline BG (HBG). Similarly, the BG value of 81.8 mg/dL was used to divide control subjects into OW and NW LBG and HBG control subgroups.

In LBG NW and OW subjects (mean pre-meal BG < 81.8 mg/dL; n = 26 and 12; Table 2) mean pre-meal BG remained constant after training, whereas in HBG NW and OW subjects (mean pre-meal > 81.8 mg/dL; n = 40 and 26; Table 1) mean pre-meal BG significantly decreased. The longitudinal difference was significantly greater than in the control subgroups. In the control subgroups, the BG did not decrease during the study time interval in any of the four subgroups (Table 2).

After 5 months, the number of trained subjects whose mean pre-meal BG fell below 81.8 mg/dL was significantly higher in the two HBG subgroups and in the OW LBG subgroup than in control subjects (Table 2). On the other

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hand, 22 of 26 NW LBG subjects remained below the BG of 81.8 mg/dL. They did not differ from 7 of 9 control subjects.

The pre/post decreases after training in mean pre-meal BG, diary-BG SD, energy intake, body weight, body mass index (BMI), arm and leg skinfold thickness were all significantly greater in the trained NW HBG group than in the corresponding control subjects (Table 2 and 3). Mean pre -meal BG, diary-BG SD, body weight and BMI also decreased significantly in OW HBG trained subjects compared to controls. Control OW HBG subjects also showed a significantly lower energy intake, body weight and BMI (Table 3), but not mean pre-meal BG (Table 2), at investigation end compared to baseline. The discrepancy prompted us to analyze energy intake, BG and body weight at 7 weeks of investigation. At 7 weeks, daily energy intake was 1082 ± 290 kcal/d and BG 88.0 ± 6.2 mg/dL in control OW HBG subjects.

The two values were significantly lower than at investigation end (n = 13, P < 0.02 and 0.01). At 7 weeks, body weight was 72.8 ± 15.3 kg which was significantly lower than at baseline (P = 0.0001) but not than study end.

In the NW LBG group, only the decrease in diary-BG SD was significantly greater than in control subjects in the longitudinal comparison after training. In the OW LBG group, the training was associated with significant pre/post decrease in energy intake, diary BG SD, BMI, body Table 3. Effects of training (IHMP) on diary reports and anthropometry in normaland over-weight groups divided by low and high mean pre-meal BG.

1

Kcal/d. 2, mg/dL; diary SD refers to BG SD of 21 measurements reported by each of 7d diary.

3 body weight kg/square height meters. 4 Kg 5 mm. Asterisks indicate significant differences as in Table 1.

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weight, arm and leg skinfold thickness, and the decreases in body weight and BMI were greater than in the OW LBG control group.

Thus the training appeared to decrease weight in OW or HBG subjects while NW LBG subjects maintained normal weight. Moreover, trained OW LBG subjects showed significantly lower energy intake per meal and lower number of meals per day (279 ± 128 kcal per 3.4 ± 0.6; n = 285 meals, P = 0.001) than NW LBG subjects. (367 ± 116 kcal per 3.7 ± 0.7; n = 673 meals) (HBG NW and OW subjects showed no such differences after training).

Vegetable intake Vegetable and fruit intake increased significantly in trained NW HBG subjects compared to control subjects. Vegetable intake significantly increased in both trained and control OW HBG subjects without any longitudinal difference between the groups’ increases. The longitudinal correlation of vegetable intake vs. energy intake in all trained NW subjects (LBG and HBG together) was significant (ρ = -0.26; P = 0.007; n = 66) and vegetable intake was significant also vs. mean pre-meal BG in all trained OW subjects (ρ = -0.32; P = 0.05; N = 38).

Well-being, nutrition, and circulation trials NW subjects showed a non-significant increase in out-door hours and decrease in diastolic blood pressure compared to control subjects (Table 4).

Trained OW subjects showed a significant pre/post decrease in bedtime hours and systolic and diastolic blood pressure. These values decreased but not significantly compared to controls. Trained (NW and OW) LBG groups showed a significant decrease in bedtime hours and in systolic blood pressure, and the longitudinal difference in bedtime hours was significantly greater than in control subjects. The Chi-square analysis for trend toward improvement on the 16 comparisons in systolic and diastolic blood pressure between trained and control subjects (LBG and HBG) was highly significant (P = 0.0001).

Additional analyses We contacted 17 of 26 trained HBG OW subjects 9 - 15 years after protocol end. Three subjects decreased body weight from 88.0 ± 6.0 kg to 78.7 ± 7.2 kg after training but showed a mean weight of 96.0 ± 3.5 after 13.3 ± 2.2 years. Fourteen subjects decreased body weight from 78.5 ± 11.2 kg to 73.2 ± 11.4 kg after training. They maintained the IHMP and showed a

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Table 4. Effects of training on bed time, activity, and blood pressure in HBG groups.

1

hours/d; 2 mm Hg; *, **, ***, a and b symbols as in Table 2.

mean weight of 73.3 ± 13.2 (P = 0.001 Vs. pre-training value) after 10.6 ± 1.

8 years. Thus, after 10 years, trained subjects showed a bimodal pattern with most maintaining the IHMP and significant weight loss.

Adverse events As in the previous study [16], trained subjects reported few negative effects. Five of 40 NW HBG subjects reported intense hunger at slightly low BG (SLBG, below 60 mg/dL) before five of 840 meals in the diary after training but no fainting. This number of SLBG events was significantly lower than 10/546 meals in 26 OW HBG subjects (P = 0.03). The 10 SLBG events in OW subjects were associated with feelings of faintness in 7 events and transient syncope in 2.

During the first month of training, for 25 of 104 subjects (66 NW and 38 OW) the consumption of the prescribed amounts of fruit and vegetables was followed by diarrhoea in 6 subjects, abdominal pain in 16 and both symptoms in 3. For these subjects, pre-meal BG measured over the previous 6 meals was ≥ 88 mg/dL for one or more meals. When BG so measured over the previous 6 meals was lower than 82 mg/dL, these two symptoms did not follow the prescribed consumption (P < 0.002 for fruit and 0.0001 for vegetables).

Discussion Interpretation of results Synopsis of key findings A seven-week training program to establish the IHMP led to significant loss of weight in OW subjects and maintenance of weight in NW subjects.

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Post hoc analysis suggests the IHMP led to loss of weight in subjects who are either OW or who are of NW with HBG. In NW LBG subjects, weight was maintained.

Possible mechanisms and explanations We suggested above (background) that IH may begin an important afferent arm of a physiological regulation mechanism that provides meal-bymeal feedback on energy need thus optimizing energy intake. Subjects who are overweight and those who are normal-weight but have pre-meal HBG forestalled this homeostatic mechanism. Restoring the homeostatic mechanism would explain our finding that the IHMP leads to loss of weight in OW and NW HBG subjects but not in NW LBG subjects Comparison with previous findings The epigastric sensation of hunger involves motor and secretion activation in the intestine, transient BG drops and activation of anterior cingulate cortex [25-31]. The decrease in mean BG after training implies that before training, OW and NW HBG groups forestalled the activation of this complex function by premature intake and suggests that interoceptive awareness can be improved. With improved interoceptive awareness after training, NW and OW subjects chose to initiate food intake at significantly lower mean pre-meal BG concentrations and lower diary BG SD than before training. After 5 months, only four of 26 trained LBG NW subjects initiated food intake at a mean pre-meal BG of greater than 81.8 mg/dL (and only by few mg/dL). This suggests a pattern of meal intake had been attained that allowed tighter BG control, a pattern that persisted over three months.

Post hoc analysis of pre-meal BG revealed no change in energy-balance habits in subjects who had baseline pre-meal LBG and regression toward LBG after training in those who were OW or had pre -meal HBG. This implies a pre-meal LBG threshold below which hunger is signalled. Previous studies have indicated this thresh-old occurs at 77.2 Âą 4.2 in adults and 75. 2 Âą 6.9 in infants [11,16,23].

A comparison between children taught to initiate food intake according to either hunger sensation or regular mealtime has been carried out by Birch [32]. In the first group caregivers were instructed to help children become aware of their internal cues of hunger and satiety, and to discuss with the children the relation of such cues to intake regulation. In the second group, the children were obliged to eat on a fixed schedule, being deliberately focused on external cues. The authors found evidence that children who were

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focused on interoceptive cues later showed an ability to adjust their intake to the actual energy content of ingested foods whereas the children who were focused on exteroceptive cues showed no such ability.

Limitations of the study Modified intention to treat analysis The most important limitation of this study is the high number of subjects (n = 32) who did not complete the study (dropouts) after the first two months.

Twenty six of these 32 subjects were trained and confirmed that they had experienced improvements but left citing their busy schedule or no felt need for further instructions. In intention to treat analysis those subjects who do not follow a study protocol are included in the final analysis. We included all subjects who enrolled for the study and for whom we have end-point data, however a number of subjects were lost to follow-up so our findings represent a modified intention to treat analysis. The likely effect of those subjects who dropped out was assessed by sensitivity analysis.

Sensitivity analysis We have data on all 32 dropouts (26 trained and 6 control subjects) from the 7 week post-training visit (Figure 1 and 2). The data showed agreement with the group that fulfilled the protocol with respect to mean BG, energy intake, BMI and body weight in 7 LBG NW subjects and 6 HBG NW subjects. Three LBG OW subjects together with 10 HBG OW subjects showed significant decrease in mean BG, energy intake and body weight. The six control dropouts showed no change in these assessments. From these data we conclude that the dropout subjects are unlikely to represent a significantly different population in respect to the endpoint measures of this study and that the absence of final data from these subjects is unlikely to have significantly affected the result overall.

Training period and 7-day diaries Subjects were asked to identify IH and base their decision to eat on its presence. During training, BG concentration was used as an objective validation of the subjective experience immediately after the experience was identified. The intervention in this study is IH and the outcome is weight. BG is an intermediate variable and it must be acknowledged that in completing their diaries during the final week, trained subjects also measured BG

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concentration. However, before measurement they estimated BG on the basis of IH, an estimation they were able to perform accurately [11]. Glycated hemoglobin reflects the average BG over a 4 month period and the lowered glycated haemoglobin in the previous study [16] and significant weight loss observed in this study are unlikely to have occurred in the final week. These data suggest that awareness of IH indeed preceded BG measurement, and was not significantly affected by it.

Generalizability Our findings are upon subjects who attended a gastroenterology clinic over a 5 month period. Further investigation will be necessary to evaluate the effect of the IHMP in other populations and what “reminder” training might be necessary to ensure compliance with the IHMP and maintenance of body weight maintenance over years [21,22].

Clinical and research implications Advantages over conventional dieting Restraint approach Control subjects were encouraged to lose weight and can be considered to represent a conventional restraint approach to dieting. Although control OW HBG subjects significantly lost weight in the first two months they significantly increased their energy intake and BG during the last three months of the study and lost no further weight. This is consistent with a “restrained” eating pattern. Control OW LBG subjects showed a mean premeal BG just at 81.8 mg/dL at the end of the study indicating that without training, their meals remained partly conditioned, thus explaining firstly, their over-weight status, and secondly, their failure to lose weight. Thus the findings in the two control OW subgroups (LBG and HBG) are consistent with the fact that restraint-type dieting tends to give short term results that are not sustained.

Weight cycling is a well-described phenomenon [33]. In the first phase of the cycle intake is conditioned or non-homeostatic. This leads to positive energy balance and weight increase. In the second phase OW subjects restrain their eating to lose weight. Most likely, the OW LBG subgroup was in this second phase at baseline. In the post-absorptive state, OW subjects have been shown to mobilise greater amounts of energy from reserve tissues to blood

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compared to NW subjects [34]. By attending to preprandial arousal of IH, trained OW LBG subjects had to adjust meal energy intake downwards sufficiently to take into account the increased availability of energy owing to postabsorptive energy release, hence their lower energy intake (about 300 kcal per day) compared to trained LBG NW subjects. During established IHMP, OW subjects reported that, provided meals were not delayed, their hunger was of no greater intensity nor more prolonged than NW subjects.

Moreover, despite significantly higher body weight and lower energy intake than NW LBG subjects, trained OW LBG subjects showed the same mean preprandial BG as trained NW subjects (Table 2, 3). These findings have at least three important clinical and research implications: 1. Trained OW subjects do not need to endure more prolonged or more intense hunger than NW subjects in order to lose weight.

2. The IHMP allows loss of weight without compromising energy availability for day-to-day energy need. The input of fatty acids from fat tissues to blood is limited in the overweight. Diets with lower mean content than 900 kcal a day may yield insufficient energy for body functions. That preprandial BG in the OW LBG group was the same as the NW LBG group indicates that in the OW LBG group a sufficiently high BG concentration was maintained for immediate energy needs. SD of diary BG in trained OW groups significantly decreased and regressed to that of NW groups further suggesting that under the IHMP OW groups adapted energy intake to metabolic need. In the absence of energy deprivation, less cycling of intake among trained OW groups would be expected.

3. An important subgroup exists (NW HBG) who appear NW by BMI criteria but who may nevertheless be at risk of weight related complications since they lose weight and decrease BG to a concentration comparable to the LBG group when trained in unconditioned eating.

Food composition approach (increased vegetables) After 5 months, no significant difference was found in vegetable intake between control and trained subjects. At the end of the study controls did not attain significantly lower BG or body weight than the trained group although they had been encouraged to lose weight. This implies that high vegetable intake alone is insufficient in preventing conditioned meals and lowering high BG.

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Sleep and the IHMP Restriction of bedtime (4 hours per day per 6 days vs.12 hours per day per 6 days) has been associated with cardiovascular risk factors including impaired insulin sensitivity [35]. Our IHMP-trained subjects showed a small but significant decrease in sleep hours compared to controls yet in a previous study the IHMP was associated with improved insulin sensitivity [16]. We suggest therefore that the observed decrease in sleep hours do not represent sleep debt but rather a physiological lowered sleep requirement associated with homeostatic eating. The mechanism by which this might occur is not yet clear.

Advantages of immediate feedback Subjects following the IHMP receive meal-by-meal subjective feedback from physiological signals. These signals map closely to BG and allow subjects to eat in an unconditioned manner without self-imposed restraint or the necessity to seek any particular goal weight. The resulting improved energy balance leads to loss of weight. â&#x20AC;&#x153;Normal weightâ&#x20AC;? is an artificial construct based on population statistics and may not apply to a given individual.

Recommendations of goal weight may be unhelpful for some subjects to whom the goal may seem arbitrary and daunting especially if it is to be achieved by dietary restraint. The IHMP obviates the need for pursuit of a statistical norm and allows each individual to find his or her physiological norm.

This approach could thus prove useful in the clinical setting since it removes major obstacles to weight loss, -the need for restraint, the need for dietary change, and the need to attain an arbitrary weight goal.

General interpretation The IHMP is an easy learned and reliable method to promote and maintain unconditioned eating. Our findings suggest that patients can maintain this eating pattern without further training for months, that it leads to improved insulin sensitivity [16] and that it promotes weight loss in OW subjects. The IHMP could therefore be an important tool in the clinical management of overweight and obese patients and could have implications for health policy in the prevention of a wide range of metabolic and vascular disorders.

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Conclusion A three-times- daily meal pattern (IHMP) was associated with LBG and sustained regression of overweight. The method was more effective than restraint-type dieting in a 5 month trial. IH, validated by BG, may represent the recovery of a vital afferent arm of the bodyâ&#x20AC;&#x2122;s homeostatic energy regulation system allowing sustained self regulation of energy intake. Post hoc division of NW and OW subjects into subgroups with mean pre-meal BG either lower or higher than 81.8 mg/dL suggests body weight maintenance in NW subgroup with low mean BG and decrease in those who were either OW or HBG NW. The findings of this study and those of the accompanying study [16] suggest that the current epidemic of insulin resistance and overweight may have its origin in the non-cognizance of hunger - the physiological signals of energy insufficiency to body cells. This may owe to forestalling such signals in early life and subsequent reinforcement of this behaviour pattern. By restoring and validating hunger awareness, the IHMP could help in the prevention and treatment of diabetes and obesity and a range of associated disorders and thus lessen the high economic burden of health services in industrialized societies.

Comment The Gastroenterology Unit (UniversitĂ di Firenze) set out Initial Request Meal Pattern (IRMP for children) to cure malabsorption in infants (Chapter 7 for outlines) [36]. For about ten years we avoided training overweight subjects (OW) [19]. IHMP is not a dieting instrument to reduce fat and weight, but a long term adaptation to current abundance of intake possibilities to decrease intestinal immune stimulation [36]. We educated malnutrited infants to health [36]. The adaptation was rewarding both subjectively and objectively and equally effective in NW and OW subjects. Subjectively, adults obtained happy activity between meals, and objectively, they decreased risks and subclinical inflammation. IHMP nullified metabolic and subjective intake differences between OW and NW people. In Chapter 7, 30 of 120 investigated subjects were overweight at recruitment. The OW subjects revealed an LBG meal pattern in the same proportion of NW subjects. After training, insulin sensitive NW subjects, insulin resistant NW subjects and OW subjects had the same pre-prandial BG (LBG), and similarly attained null meal by meal balance. Meal by meal, null energy balance in blood and LBG attainment are common health targets for all and meal amount is a challenge for all, whatever the body weight.

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After the end of absorption, fat tissues of OW people deliver an amount of fatty acids to blood that is three - five times higher than that of NW people [34, 37, 38]. The fatty acid amount is part of what enters into blood dynamic balance of energy, and covers the last 1 – 4 hours after the end of absorption.

OW subjects do not have to endure hunger for body weight loss. They have to add this fatty acid amount either consciously, subconsciously or unconsciously to the meal amount that they believe to be necessary to cover the inter-meal interval, and wait for IH arousal. After this inclusion, OW subjects take away a small amount of fat from thick subcutaneous tissues until they achieve insulin sensitivity. OW subjects showed a BG estimation error that was significantly lower than that of NW subjects in a preliminary investigation [39]. On the other hand venturing IH arousal was successful only before 60% of meals as compared to 80% of meals by NW subjects, and the difference was significant. OW subjects show difficulty in venturing meal size for a meal by meal null balance. Training IHMP offers at least a way of recognizing either an actual attainment or a possibility for compensation at subsequent meal challenge. “Recognizing hunger” is a synonymous term for IHMP that emphasizes the need for a conscious evaluation of intake at every meal.

OW subjects tend to consume lower number of meals per day than NW subjects do. No energy consumption at a meal produces negative meal by meal balance in blood during inter-meal interval. Fatty acids influx into blood is insufficient to sustain LBG, normal activity and normal RMR without meals. Weakness arises as subjective counterpart of depressed blood glucose (SDBG, Table 1, Chapter 1) and low RMR. Non-feeding for 15 days to achieve rapid body weight decrease seems as an even heavier error than skipping a meal. The amount of beta cells in pancreas dictate meal size: at renewing feeding, OW people are unable to consciously oppose their strong impulse to eat (Chapter 1). OW people rapidly regain lost body weight. This regaining is associated with high risk of insulin resistance and diabetes [33].

Part of humans have high capability of producing insulin and storing big meals. These people have no feedback except for an esthetical deterioration.

Lack of scientific information allow them happy intake excesses for years.

Regression to healthy meal pattern is disturbed by an increased number of beta cells and by ignoring a subjective limit that is recognizable as the same for each meal (IH).

Infants with chronic diarrhea show thin skin-fold [20, 23]. They require only few days to acquire insulin sensitivity and do not lose any significant thickness of arm and leg skinfold during training [20, 23]. Instead, a NW person with insulin resistance may gain insulin sensitivity by losing a mean 2.5 kg in an interval from one week to one month. During dieting or

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practicing IHMP, OW subjects have a supply of copious fatty acids from thicker subcutaneous tissues for more hours than NW subjects, and this high supply persists for a longer period than NW subjects before recovering insulin sensitivity. Once the OW subject achieves insulin sensitivity, delivery of fatty acids exceeding into blood ceases, by definition of insulin sensitivity.

Achieving this, OW subject has BG and weight homeostasis and good health.

Persistence in IHMP becomes habitual in contrast to dieting, although still requiring the same attention to meal components to venture null meal by meal balance like during weight loss. The acceptance of this lifelong commitment is difficult before training and easy after training. Successful maintenance depends also on personal motivations in life. Further slow loss of weight may persist for slow decrease of adipocyte number [40].

Meal by meal positive balance corresponds to achieving pre-prandial HBG, and this condition reverts soon to LBG at IHMP adoption, and body weight decreases after few days. Null balance corresponds to achieving preprandial Initial Hunger and LBG, and to either maintenance of body weight in NW insulin sensitive subjects, or body weight decrease in OW subjects and in insulin resistant NW subjects. Copious fatty acids entering into blood in post-absorption period allow fat tissues and body weight decrease without hunger endurance. As for meal by meal negative balance, an example is given at the end of the previous Chapter (7). Negative balance is characterized by enduring hunger, decreasing body weight and frequent occurrence of SLDG. This classification corresponds better to findings than the comparison between subsequent pre-meal BGs. We suggested that BG measurements were higher during heavy outdoor work in cold climate and in the subsequent hour than in an indoor sedentary setting (Chapters 3 and 7). Excluding these BG measurements, attaining LBG is associated with null meal by meal balance. Except for heavy outdoor physical activity, pre-prandial attainment of the same HBG represents maintenance of positive balance and body weight increase.

The paper definitively shows that vegetable intake decreases energy intake but is insufficient in lowering mean BG (and body weight) when subjects take meals by overlooking IH arousal. In our opinion, fruit and vegetables, up to 1 kg per day are an indissoluble part of IHMP to contrast current abundance in energy rich food. Two apples were abundant in venturing to overcome a hospital night, but venturing an intake of a similar amount of calories (15 â&#x20AC;&#x201C; 20 grams, a table spoon) of a greasy sweet created difficulty to stop intake. Fruit and vegetables are associated with increased relapses of functional intestinal disorders in our investigations. Yet this effect developed only at high BG intake, and mostly in the first month of training.

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Acknowledgements The investigation was supported by the Italian Ministry of University, Research, Science and Technology grants for the years 1996-2002 and the draft of the Ms by the ONLUS Nutrizione e Prevenzione, Florence, for years 2003-2009.

The authors thank Laura Chiesi and Stefania Bini MD for dietary analyses and Stephen Buetow, Tim Kenealy, Chris Harshaw, Simon Thornton, Kent Berridge, James Gibbs, Charlotte Erlanson Albertsson and Michael Hermanussen for helpful insights on earlier drafts of this paper.

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Research Signpost 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

The Meal by Meal Dynamic Energy Balance in Blood: Habits & Risks, 2011: 145-166 ISBN: 978-81-308-0457-6 Editor: Mario Ciampolini

9. Systemic immune stimulation Attention to metabolic hunger and its effects on Helicobacter pylori infection Mario Ciampolini1, Lorenzo Borselli1 and Valerio Giannellini2 1

Department of Pediatrics, University of Florence, 50132 Florence, Italy 2 Department of scienze farmaceutiche 50 121 Florence, Italy

Abstract. A significant decrease in the bacterial count of small intestinal mucosa has been observed in children with recurrent diarrhea or abdominal pain in the time that has elapsed from the previous meal. Humans may be trained to recognize metabolic feelings of hunger that are associated with a steady and slightly lower glycemia than baseline, between 4.7 and 3.9 mmol/L (x 18 to get mg/dL). An eating habit associated with a decrease in preprandial glycemia prevented diarrhea relapses, and was expected to impair intestinal microflora growth, including Helicobacter pylori in the stomach. The development of Helicobacter pylori infection might be prevented during childhood, and recovery from infection may be expected with intervention. The improvement in attention to metabolic feelings consisted of acquiring a predictive ability of glycemia by distinction between unsolicited hunger feelings (metabolic hunger) and those associated with external cues.

Matching intake to the in between energy needs served to predict the subsequent emergence of the metabolic hunger. The matching was further compensated for the early or late emergence of metabolic hunger at the subsequent meals.

Correspondence/Reprint request: Dr. Mario Ciampolini, Department of Pediatrics, University of Florence, 50132 Florence, Italy. E-mail: mlciampolini@fastwebnet.it

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Fruit and vegetables were increased to avoid abrupt glycemia lowering. This intervention was trained in 5-month periods. Subjects (209, 44, and 58) completed their training during 4-year periods between 1982 and 1994, and were enrolled in a prospective, controlled, randomized, interventional, preventive, and cohort study. The “prevention” hypothesis was tested in a subgroup of 86 healthy infants who were recalled in the years 1996 to 1998. A “recovery” study of approximately a 1-year intervention was investigated in 47 healthy subjects between ages 5 and 25, who were positive for anti-H. pylori and had no need for an immediate antibiotic treatment at entry. The following behavioral factors were recorded in a 7-day home diary and calculated: the fraction of meals induced by metabolic hunger out of 21 main mealtimes; average preprandial glycemia (DAP glycemia); daily intakes, activity; and bedtime hours. The decrease in preprandial glycemia was the objective measure of compliance with the recognition of “metabolic” hunger. Anthropometric measures and blood tests were obtained for nutritional and functional verifications. Average preprandial glycemia was 8.5 and 8.6% lower in the intervention groups than the control groups in the “prevention” and “recovery” studies, respectively, at the end of follow-up (p < 0.05 and < 0.001, respectively). A 4.7% seroprevalence of H. pylori infection was observed in the intervention group, with 30.2% in the control group at a mean age of 10 years after approximately an 8-year follow-up in the “prevention” study (p < 0.0005). The seroprevalence decreased to 9 of 24 (37.5%) under intervention as opposed to 20 of 23 controls (87%) in the recovery study (p < 0.002). A significant positive correlation was found between DAP glycemia and the anti-H. pylori serum antibody concentration (r = 0.52; p = 0.0002). A decrease in the level of immune stimulation by H. pylori infection was observed due to the intervention, which may have a preventive and therapeutic role on the infection. © 2000 Elsevier Science Inc. All rights reserved.

1. Introduction Insulin sensitivity measures the individual current carbohydrate (and indirectly energy) storage rate from blood to the body cells. The measured value has a range as wide as three times the lower range limit in people with normal glucose tolerance [1-7], and even more in a mixed sample under our observation [8]. Vascular and ovary risks and progressive deterioration develop in association with the slowest rates (insulin resistance), despite absence of symptoms for many years [2,3,5-7,9,10]. A (cognitive) feeding based on recognition of both energy intake and current insulin sensitivity may improve insulin sensitivity and prevent all of these widespread risks. A feeding on demand (hunger) was proposed in infants to minimize immune stimulation by bacterial growth in intestine [8,11-13], and was revealed to be associated with insulin sensitivity increase [14]. The hunger expression by the infant was also associated with a decrease in preprandial glycemia, and followed by a decrease in resting metabolic rate, which suggests a metabolic origin [8,11-13,15,16]. The infant expresses the same manifestation of hunger

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as soon as he/she sits down at the table, at the sight of food, or even by the speech of older children. These external stimuli usually are more powerful than the metabolic hunger [17,18]. This distinction was learned by attentive caregivers whose infants were addressed to our unit to acquire subjective improvements, for example, prevention of mild intestinal complaints or increase in fitness [8,11-16,19]. The use of metabolic hunger as a guide in feeding is currently explored in infants in a controlled, randomized, followup, which has been maintained for about 18 years. This prospective study might show unknown effects of the intervention, for example, on intestinal microflora, including Helicobacter pylori (H. pylori) in the stomach. The development of this infection might be prevented during childhood, and recovery may be expected under intervention.

The “prevention” hypothesis was tested in a subgroup of the cohorts under recall in the years 1996 to 1998. Eighty-six children were negative for H. pylori antibody in the second year of life, and their frozen sera were available in the follow-up at various periods of time from enrollment. A final blood sample was obtained and analyzed for H. pylori infection.

The study was extended into the adult age range [8,20]. The metabolic hunger was ignored in older children and adults, and a training period was necessary for learning recognition. The metabolic hunger may be felt in the previous hour and remembered upon going to the meal table, whereas the “external” hunger appears only at events associated with food. The “recovery” hypothesis was investigated in newly enrolled subjects between 5 and 25 years of age, who were positive for anti-H. pylori and had no need for an immediate antibiotic treatment at baseline. A single blood test assessed the outcome after 6 to 18 months: either negative seroconversion or maintenance of seropositivity.

Preprandial glycemia measurement was used for apprehension of recognition of metabolic hunger, and for assessment of the compliance under intervention (causal factor). Home diaries reported foods and Yes or No hunger manifestation or perception with preprandial glycemia measurements, and documented subjects’ voluntary compliance with the intervention. Anthropometric measurements verified positive growth. The pre-post decrease in glycemia may both prove actual recognition of metabolic hunger and be associated with recovery from the H. pylori infection as assessed by seroconversion.

2. Materials and methods 2.1. Study design The intervention and the controlled follow-up were designed in 1980, and the intervention was reproducible by complying with a main variable and

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a support variable [8,11-16,19]. The main variable was dependent, and was assessed by both subjective evaluation and biochemical measurement. The assessment consisted of the recognition of the blood glucose level by body feelings of bearable hunger and preprandial glycemia measurement that was maintained between 3.9 and 4.7 mmol/L. The subjective evaluation served permanently after a period of training and glycemia measurements for periodical verification. The intervention predicted or manipulated a few independent variables to influence the dependent main variable. Snacks, climate, and energy density in the meal were independent. The decrease in energy intake reproduced a variable part of compliance, which might be substituted by an increase in physical exercise. All independent variables could be substituted by a variable acting in the same direction to comply.

Two independent variables with opposite effects on glycemia might be decreased or increased together to obtain the same blood glucose concentration. Therefore, all independent variables expressed only a variable part or negligible amount of compliance. The support variable is more understandable, and erroneously considered the only compliance. Abundant vegetable intake is necessary to prevent hypoglycemia events in hyperinsulinemic patients waiting for metabolic hunger. On the other hand, a high vegetable intake when glycemia is high is associated with the development of diarrhea, abdominal pain, or headache [8,12,15,19].

Compliance with only one of the two prescriptions was associated with these undesirable effects, whereas the two prescriptions together produced bearable hunger for about 3 h in adults, i.e., the possibility of taking the subsequent meal before glycemia drops [8,12,15,21-24].

Phone calls were repeated at least for 7 initial days. Detailed descriptions of metabolic hunger, food intake, and physical and social activity patterns were collected throughout the 5-month observation period. Seven-day home diaries, anthropometric measurements, and clinical evaluations were obtained at baseline, every 50 days for the 5-month initial apprehension, and every year during subsequent follow-up. Diaries reported hunger recognition, food intake, and also preprandial blood glucose measurements at baseline and after 8 year of age.

The intervention required a certain amount of motivation, attention, and discipline, and therefore, it recruited persons who were willing and able to fulfill the protocol after 1986. Willing caregiver-children pairs in which the children were in their second year of life were randomly assigned to two open cohorts for a controlled, prospective investigation, and were recalled in alphabetical (i.e., random) order every 4 years (Table 1). An equal number of consecutive subjects were matched for age and length of follow-up, and antibody to H. pylori were added to programmed tests between the years

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Table 1. Number of subjects who completed the 4-, 8-, and 12-year-follow-up of the subjects who completed the first 5-month period, which was educational in the intervention group.

Follow-up (years) 4-8a 8-12b >12c Under intervention 47/110 141/177 78/136 Controls 41/99 103/134 47/117 Dropouts in first 5 months Under intervention 6/47 (13%) 5/31 (16%) 89/199 (45%) Controls 2/19 (10%) 2/20 (10%) 51/150 (34%) a Forty-one children under intervention and 17 controls completed the 5-month follow-up between 1990 and 1994, and are added to the 1982-1990 input. b Twenty-six children under intervention and 18 controls completed the 5-month follow-up between 1986 and 1990, and are added to the 1982-1986 entries. c One hundred ten children under intervention and 99 controls completed the 5-month initial follow-up between 1982 and 1986.

1996 and 1998 [8,11,12]. The seroconversion to H. pylori was the outcome.

These were measured in 86 subjects with different lengths of follow-up.

Newly recruited subjects between 5 and 25 years were selected for the “recovery” study. The same recruitment and 1:1 random assignment were employed, and the same alphabetical (random) recall was used for end-trial assessment after 6 to 18 months under intervention.

2.2. Subjects In early 1987, the Pediatric Gastroenterology Unit of Florence University limited recruitment to patients who were addressed and prepared for the intervention by inter-personal relationships or their physician. The Hospital Gastroenterology Unit served the outpatients. Healthy subjects, 6 to 60 months of age were eligible. The clinical assessment of all patients consisted of a routine physical examination and of diagnostic biochemical and microbiological evaluations to rule out disorders such as celiac disease, lactose intolerance, cystic fibrosis, inflammatory bowel disease, liver disease, pancreatitis, and bacterial and parasitic infections [15,16,19]. Those who had organic diseases, acute or relapsing conditions, or were unmotivated or unreliable were excluded (see Validations). The subjects were healthy as judged from reactive C protein, white blood count, and absence of important intestinal or other organ complaints. The infants were concurrently assigned to the intervention or control group, i.e., the “external induction” or “ad lib” feeding group, by use of a concealed sequence prepared on a random-umber

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table at diagnosis between 1982 and 1994 [25]. The concealed sequence was prepared every 2 years, with an initial ratio of 2:1 between intervention and control subjects. This ratio was changed to 1:1 at the beginning of 1987, and again to 2:1 in 1991, for no-controlled research on resting metabolic rate.

Table 1 reports the number of examinations every 4 years in comparison to the number of subjects who completed the first 5-month period, which was educational in the intervention group. The difference shows the 4-year dropouts. Obtaining a diagnosis, medical verification, and psychological support motivated the caregivers of the control group. Dropouts in both groups were motivated by the absence of motivating illness, lack of time or money, and well-being. Sufficient apprehension or distrust to novelty caused renounce to follow-up in the intervention group. Eighty-nine children were alphabetically recalled for the last compliance and blood tests in both groups. Of these, 86 were examined.

The intervention and control group for the “recovery” investigation were formed in subjects aged from 60 months to 25 years by the same random method in a 1:1 proportion between 1991 and 1996. No antibiotic treatment was used for H. pylori elimination because of the absence of important dyspeptic symptoms. Four of 28 intervention subjects and 3 of 26 controls did not comply with instructions or follow-up in this study. The compliance was repeatedly assessed, and blood sampling was tested once in the 47 subjects 6 to 18 months after baseline. The hospital management works for profit under a newly implemented state law, and collection of data has stopped due to lack of immediate profit in 1998.

No child had had febrile disease, had used any drug or medication in the preceding 3 weeks, or was treated for H. pylori infection during the followup. The study was reviewed and approved by the departmental Human Trial Committee. Informed consent was obtained from the infants’ parents.

2.3. Intervention (recognition of “metabolic hunger”) The subjects or the caregivers, i.e., the mother and father of the child under 13 years of age, received verbal, written, and phone tutorial daily instructions for 1-2 weeks, and developed two mental habits at mealtimes: (1) evaluation of metabolic feelings (manifestations); (2) planning the next emergence of metabolic hunger to maintain previous habits and allow for change. The planning was carried out by matching energy-dense food in the meal to the needs for the planned time interval [11-16].

The subjects ignored the first mealtime at first training attempt. They waited for the emergence of the unexplored personal feeling(s) of metabolic hunger or for manifestations in children, and measured glycemia at first

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perception. Metabolic hunger and glycemia lower than 4.7 mmol/L allowed 100 to 200 g of low energy-dense food and about half of previous high energy-dense food intake for the first meals. The amount of low energy-dense food was increased in 2-3 days to arrive at the full prescription (see later).

High energy-dense food was increased in 1-2 days only after the third day to avoid intestinal complaints for high fiber intake. The metabolic hunger arose in unplanned moments in the first days of trials and errors. After the early days it became easier to let the metabolic hunger arise within the hour that the meal was cooked. There were concerns about how a situation could be created without the sight or smell of food, and the reflection on the behavior or feelings in the previous hour often was useful. The repetition of the same manifestation with the same blood glucose levels indicated the metabolic hunger. The emergence of these feelings or expressions was perceived at subsequent meals, and this became a habit. Ignoring the first signs of metabolic hunger, as well as loss of meals, was discouraged after the first early training days.

The mother (or father) often knew the all-day behavior of the infant, and easily developed the recognition of metabolic hunger. Crying in the first months of life, mood changes like loss of enthusiasm for playing, gestural or verbal requests, or searching for food without any â&#x20AC;&#x153;externalâ&#x20AC;? stimulus all were considered to be signs of metabolic hunger in infants [26]. The metabolic perceptions of older subjects consisted of gastric pangs, feelings of emptiness, or mental activity impairment (no enthusiasm, difficulty in sustained mental concentration, irritability). The caregivers described the type, intensity, and persistence of hunger, as well as the delay in food consumption. They reported the preservation of food type choices, social obligations, good mood, physical, and mental effectiveness, and the usual (or increased) day-to-day physical activity.

The social obligations like parties and school catering had to be included in planning the intake amount and timing of previous and subsequent meals.

The emergence of hunger at the midday communal eating was planned by matching energy intake to the needs for the interval at breakfast, and compensated by verification of the emergence at the subsequent dinner. After learning the recognition, no metabolic hunger before the meal was considered a factor, which prolonged the time before the next hunger emergence and suggested a decrease in energy-dense food. Avoiding snacks was suggested, but early hunger emergence had to be satisfied with fruit and adequate energy-dense food if needed. The prescribed intervention included the increase of energy expenditure because of the positive correlation between energy expenditure and lean body mass. Overheating and over clothing were decreased, while outdoors and gym activity increased [27]. The meal

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was planned again at subsequent mealtimes and consumed in large, small, or null amounts on the basis of metabolic hunger and planned activity for the next interval. Ignoring metabolic hunger, as well as loss of meals, was discouraged.

A few people expressed doubts about the intensity of the perception to be used as a signal for eating. Five adults were given two more specific verbal definitions on metabolic hunger in the following succession: work until emergence of feelings that disturb activity, and subsequently, work until initial emergence of feelings associated with glycemia under 4.7 mmol/L. The first definition was associated with four of five subjects with meals consumed when glycemia was as low as 2.5-3.3 mmol/L, physical and mental weakness for hours before feeding, and occasional fainting and bulimic behavior (very hungry) or abstinence from meals. The second was associated with glycemia between 4.2 and 4.7 mmol/L, not impairment of intermeal activity, mood changes, food abstinence, or excessive intake. This sensation was suggested as the appropriate meal signal. Four types of metabolic feelings were identified: (1) satiety or no thought of food; (2) appetite or consumption of available food at perception of it; (3) bearable hunger feelings between 3.9 and 4.7 mmol/L; and (4) unbearable or bulimic hunger under 3.6-3.3 mmol/L. High energy-dense food was considered to be food with over 60 kcal/100 g, and fruit and vegetables were low energy-dense foods. Fruit was defined as food under 45 kcal/ 100 g (apples, pears, and oranges) and vegetables under 30 kcal/100 g. Tables with the energy content of food items were provided [8,11-16,19]. Three hundred grams of leafy vegetables per meal were prescribed for children older than 8 years of age and adults. Fruit and vegetable intake was united under the name â&#x20AC;&#x153;Low energy-dense foodâ&#x20AC;?

(LEDF). Vegetable dishes could be fresh or cooked and savored with tomato, onion, pepper, oil, and mixed with other food. The mother evaluated the savor as pleasant. Fruits and vegetables were usually given to children as the first dish, except in presence of intense hunger. Tables with the energy content of food items were given out.

2.4. Clinical assessments and measurements 2.4.1. Clinical assessments Clinical assessments were performed for diagnostic purposes at baseline, one to three times within 5 months of initial instructions, and every following year. The purpose was to evaluate each subjectâ&#x20AC;&#x2122;s clinical condition and

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assess growth in children, changes in fat, and voluntary compliance with the study protocol.

Clinical assessments at baseline and at the end of protocol included standard hematological evaluations and urinalysis, urine culture, and examination of stools for occult blood, ova and parasites, antibodies to H. pylori, and bacterial cultures for potential pathogens. Children were examined to rule out other organic disorders, as previously noted.

Comprehensive biochemical profiles were obtained on all children.

Measurements included reactive C protein, serum albumin, hemoglobin, iron, transferrin, calcium, phosphorous, Cu, Zn, total and HDL cholesterol, triglycerides, alkaline phosphatase, ALT, AST, total Immunoglobulin, IgA and IgG antigliadin, and anti-Helicobacter pylori antibodies, and ferritin.

Plasma folates, B12, and IgE also were determined, as were red blood cell volume, platelet, and eosinophil counts [8,11-16,19].

2.4.2. Anthropometry Anthropometric measurements were obtained by standard techniques as described previously [11]. Children less than 2 years old were measured in length, while older children by height. Length and height were expressed as a percentage of median length (height) for age (NCHS, USA).

Weight was expressed as a percentage of the median weight for age (NCHS, USA). Weight for length/height was the individual weight divided by the median reference weight for the same height (NCHS, USA). Muscle area also was calculated [11].

2.4.3. Diary assessment Seven-day home diaries, which reported hunger type recognition and glycemia measurements, were used to estimate energy, fiber, fruit and vegetable intake, environmental effective temperature, and document the hours spent out-doors, in gym, and asleep.

All data were recorded on special forms supplied by the investigators.

Space was provided for reporting five meal events. Further occasional intake events were joined with the nearest meal. The meal was an event of energy intake separated by more than 2 h from similar events in a day. A dietitian instructed each caretaker in food measurement and weighing. Meal initiation by either metabolic or external hunger was evaluated in the quarter of an hour before breakfast, lunch, and dinner, and was reported in the diary by the caregiver. The type of hunger feeling was recorded (stomach, mood and mind, physical). Food intakes were estimated by weighing or measuring

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foods before and after cooking. Measurement utensils were provided to the caretakers by the investigators and all portions after cooking and leftovers were weighed or measured. Glycemia was then measured for adults in a drop of total blood from a warm finger with an automated portable blood glucose meter (Miles). It was also often measured on willing children to better understand their expressions. Care was taken to avoid sampling cold fingers.

The diary measurements made with the portable instrument were corrected by the ratio to the Hospital laboratory, and the same lot of strips was used in the individual diary succession (see Validations). The meter is based on measurement of the electrical potential produced by the reaction of glucose with the glucose oxidase reagents on the electrode. The capillary values are reported in this presentation, which are 0.2 mmol/L lower than the venous plasma glucose. The objective average compliance was calculated as the weekly mean of these glycemia measurements (DAP glycemia). Vegetable acceptance, which was the average percent of the recommended intake per meal in the examined week, was used in addition to vegetable weight to allow comparisons in subjects despite differences in age and type of vegetable intake.

Intake data were analyzed with a computer program containing the nutrient composition of 600 commonly consumed foods [28]. Additional details have been published previously [8,11-16,19].

The number of days with diarrhea, vomiting, abdominal pain, headache, and fever before enrollment was assessed retrospectively by interviewing caregivers at baseline. Records of these symptoms were kept daily using validated procedures for all subjects during the follow-up [8.11-16,19].

Records of school or work activity and of days off were kept for older children and adults.

2.4.4. Assessment of H. pylori infection H. pylori IgG antibodies were assayed in the serum from frozen samples by using a commercial enzyme-linked immunosorbent assay (ELISA); Helori test, Eurospital, Trieste, Italy [29]. Baseline and early frozen samples were available for all children. Concentration of the antibody was expressed in Units, which corresponded to a 1% point in a percentage index obtained by comparing the patientâ&#x20AC;&#x2122;s value with the positive control. Over 15 U in the antibody concentration was considered evidence of an H. pylori infection (see Validation). Serology, bacterium culture, the urea breath test, and histology have not been statistically different in establishing the diagnosis from Warthin-Starry staining of gastric biopsy specimens and the urease test in adults and children [30-34].

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2.5. Validations The cut point between positive and negative concentrations was investigated in 40 children undergoing upper gastrointestinal endoscopy.

Three antral biopsy specimens were taken for histology, culture, and the urease test. A positive diagnosis of H. pylori infection was made if the bacterium was isolated or both a positive urease test and histological gastritis were found. A cut point of 15 U in the antibody concentration gave no false negatives and one false positive of 21 negative subjects.

Fresh whole blood was drawn into heparin tubes at each diary. One sample was centrifuged immediately and analyzed in duplicate by a laboratory hexokinase method (Hospital autoanalyzer Synchron CX7). The allowed spread for this measurement was 2% from average, measured in 50 regional laboratories every month. The second sample was tested with the portable instrument 5 or 10 times. Care was taken for a simultaneous measurement with the laboratory [35].

The variation coefficient (SD/mean) was 2.6% in the measurements with the portable instrument, and 6.0% in the ratio between these measurements and the Synchron CX7 in 80 diaries. The diary measurements made with the portable instrument were corrected according to this ratio to Synchron CX7.

The comparison was repeated on another sample when the difference was higher than 10%. Twelve subjects were discarded as inaccurate, due to over 7% variation coefficients in the measurements with the portable instrument.

The subjectâ&#x20AC;&#x2122;s hunger and glycemia evaluation were obtained at the moment of blood sampling under intervention, and the mean difference between estimation and corrected measurement of blood glucose level had no significant difference from zero. The mean error in this estimation was 7.0 Âą 3.8% of mean measured blood glucose in adults and 9.9 Âą 5.3% in children (p< 0.05). Internal hunger was perceived in the range of 2.9 to 5 mmol/L. Planning the emergence of metabolic hunger was taught mainly through phone calls. Subjects were taught how to evaluate energy and vegetable intake, environmental temperature, humidity, wind, clothing, hours outdoors, physical activity and type of work, number of hours before meal consumption, and the possibility of snacks. Energy intake and glycemia measurements were reported daily, and a logical trial and error search for the best planning was developed in the subsequent phone calls. Interest and trustfulness were verified in these phone calls. Practitioners visited 47 homes during intervention and confirmed accurateness within 10% in reported item [8].

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2.6. Statistical analyses The DAP glycemia in a week and the serum concentration of antibody to H. pylori were investigated by factor analysis (principal components) and simple regression analyses. These were carried out on absolute values after joining the two groups in comparison in both studies at the follow-up end (cross-sectional analysis). The analyses also were performed on the pre-post intervention differences in the â&#x20AC;&#x153;recoveryâ&#x20AC;? study (intraindividual, longitudinal analysis). Communality is the proportion of the variances of the analyzed variables, which is communal in factor analysis, and may suggest a communal underlying factor. In this investigation, the communality of H. pylori antibody concentration and DAP glycemia was investigated by longitudinal factor analysis. One variable was added to the analysis at a time in search of potential confounders, which may change the communality. A selection was made of variables that showed a correlation coefficient of 0.45 or higher to the communality without decreasing the proportion of communality (potential cofactors or consequences). The fraction of the meals that were consumed after recognition of metabolic hunger was considered 0 at baseline, and absolute values under intervention were used in longitudinal analyses on intra individual difference of DAP glycemia and concentration of anti H. pylori serum antibody. Simple regression analyses were investigated between longitudinal differences and baseline on each anthropometric measure [25].

The size sample was calculated to obtain an approximate change of 2.02.5% in the mean and SD of results after entry of any further subject. Values are expressed as means Âą SD. The two-tailed t-test was used to detect significance of difference and correlation, and the level of interest was set at P < 0.05 [25].

3. Results The 5-month educational period was completed by 55-59% of patients in the general population until 1986, and by 84-90% of those who were thereafter addressed and pre-pared for the intervention by interpersonal relationships or their physician. The caregiver often missed the surveillance of one main meal per day, and a few subjects were motivated to drop out due to the inability to program other meals. Overprotection and unmotivated fear of insufficient eating and aversion to fruit and vegetables were widespread in the general population in 1982. Eleven of 78 subjects abandoned the followup in the first 5 months after this date. One could not be traced due to change

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of address. One refused vegetables, and nine compliant and grateful subjects were motivated to drop out due to well-being and lack of need for further verification. Control subjects also reported this motivation and showed a dropout rate similar to that of intervention subjects (Table 1). Relapses of symptoms were observed in approximately 10% of subjects under intervention, and were associated with transient lack of compliance with the waiting for hunger perception. Complication or un-toward effect was not reported. A difficulty in distinguishing hunger was observed in two adults.

These subjects predicted glycemia with a 5-6% error, despite no threshold hunger sensation. Hypoglycemia or fainting was not observed in children, and was associated with avoidance of fiber intake in three adults.

No significant difference was found in anthropometric or blood parameters, in intake estimates at baseline, or in length of follow-up in the selected subgroups for â&#x20AC;&#x153;prevention studyâ&#x20AC;? (Table 2). A mean follow-up of approximately 8 years was obtained. Maintenance of compliance was checked every year, and yearly results were comparable to those observed at final assessment. Recognition of metabolic hunger was reported in 72.0% of meals. Preprandial glycemia was measured in 19 subjects under intervention and in only four controls. A significant 8.5% lower glycemia was observed in the diary averages under intervention than in controls. Estimated energy intake was lower in the intervention than in control group, but the significance of the difference was marginal, and disappeared after adjustment for body weight. A significantly lower increase was observed in the mean weight for height under intervention than in control subjects, and the final value was significantly lower under intervention. A significant difference in fruit and vegetable intake also was observed between intervention and control group (Table 3).

No H. pylori seroconversion was observed in those who were under intervention for 8 years. The frozen sample of one subject was transiently positive after 8 years and negative after 12 years. This transiently positive subject was recalled with the 12-year cohort, and he was reported only here, without further mention in the 8-year cohort. Seven subjects were positive in the control subjects at the same time, and the difference from zero was significant. Three frozen samples were positive after 8 years, and came from positive subjects who were recalled with the 12-year control cohort.

These are reported in the 12-year group only. The complete comparison showed two positive seroconversions (plus a transient one) of 43 subjects under intervention and 13 of 43 controls. This difference was highly significant and corresponded to one infection every 176 years under intervention, and one infection every 26.5 years in control subjects in the follow-up (Table 4).

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Table 2. Group composition and characteristics in the “prevention” and “recovery studies”.

“Prevention” Intervention

a

“Recovery” b

Control

Interventiona

Controlb

Male

23

23

13

11

Female

20

20

11

12

Entry age

(m)

23.0 ± 12.3

24.7 ± 15.7

142.7 ± 69.1

152.2 ± 66.8

Age at last measurement

(m)

121.4 ± 42.2

121.2 ± 43.7

153.5 ± 65.6

164.5 ± 67.2

Average follow-up period

(m)

98.3 ± 44.4

96.5 ± 43.3

10.8 ± 5.1

12.3 ± 5.7

10.8 ± 4.5

9.6 ± 3.4

11.3 ± 4.4

10.8 ± 5.2

Parents’ school yearsc a

Recognition of “metabolic hunger.”

“External hunger,” i.e., ad lib. eating. m = months. c Sum of school years divided by 2. b

Table 3. Final outcomes of anthropometric measurements and average intakes and preprandial glycemia reported in home diaries for infants enrolled at the second year of age and negative for Hp (“prevention” study), and for subjects enrolled between the fifth and 25th year of age and positive for Hp (“recovery” study).

“Prevention” Intervention (n = 43)

a

“Recovery” b

Control (n = 43)

Interventiona (n = 24)

Controlb (n = 23)

Age (years)

10.1 ± 3.5

10.1± 3.6

12.8 ± 5.5

13.7 ± 5.6

Weight (kg)

32.7 ± 13.5

34.4± 13.6

43.6 ±19.5

46.1 ± 16.6

Weight for height (%)

96.1 ± 12.3

102.9 ± 13.0*

+3.1 ± 12.5

+10.3 ± 13.7*

-5.1 ± 10.2

-2.0 ± 11.2

9.1 ± 4.3

10.0± 3.9

10.9 ± 4.9

12.3 ± 6.6

Increase in the sum of skinf. thickn.

+7.0 ± 9.6

+10.4± 11.7

-5.1 ± 10.5

-2.9 ± 10.6

Daily energy intake (kcal)

1228 ± 419

1527 ± 478**

1267 ± 471

1485 ± 572

Daily energy intake per kg (kcal)

37.6 ± 16.1

44.4 ± 16.8

28.8 ± 14.4

32.2 ± 20.0

Daily vegetable intake (g/kg)

10.2 ± 7.9

2.3 ± 1.7**

11.8 ± 9.1

7.3 ± 6.7

5.0 ± 3.6

3.1 ± 2.2**

6.4 ± 5.0

3.7 ± 3.0

4.6 ± 0.6

5.0 ± 0.3*

4.4 ± 0.4

4.8 ± 0.3***

Increase in % weight for height a

Arm skinfold thickness (mm)

b

Daily fruit intake (g/kg) Mean preprandial glycemia (mmol/L)

c

103.2 ± 12.2 105.6 ± 19.0

* p , 0.05, t-test, **p , 0.01, t-test; ***p , 0.001, t-test. a The median reference (NHCS, USA), for female and male is 12-10 mm, respectively, for the age at the end of the “prevention” study, and 14-11 mm for the age in the “recovery” study. b Sum of tricipital and quadricipital skinfold thickness in mm. c Nineteen children under intervention and only 4 controls. The mean of these four diary average preprandial glycemia (DAP glycemia) is similar to larger series of children of the same age under ad lib eating condition. Capillary values, which are 0.2 mmol/L lower than venous plasma glucose.

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Table 4. “Prevention” study. Number of subjects with positive seroconversion of the tested subjects in the intervention and control groups after 4, 8, and 12 years.

Follow-upa 4 years 8 years 12 years Total % Cumulative follow-upc

Intervention 0/14 b 0/13*d 2/16 2/43** 4.7% 352f

Control 4/13 3/14 6/16e 13/43 30.2% 346g

a

The children were enrolled in the trial between 1982 and 1994.

The fractions represent the number of positive subjects of those recalled and tested. Frozen samples were available from previous examinations, and positive samples are mentioned d,e and not reported in the table. b Conversions of tested subjects. c Years × subjects followed in the group. d One child under intervention was positive after 8 and negative after 12 years for anti-H. pylori antibody, and he is included only in the 12-year group. e Three of 6 control children were positive in the frozen serum sample after 8 year follow-up, and remained positive after 12 years.

Their inclusion was only in this group. f One infection every 176 years under intervention, and g One infection every 26.5 years in control subjects in the follow-up (p < 0.001 vs. control, chisquare). * p < 0.02, and **p < 0.0005. Yates test on the cumulated subjects in the cohorts after 4 plus 8, and after 4 plus 12 years follow-up.

Consistent results were shown by the “recovery” study. The number of dropouts was four and three in the intervention and control groups, respectively, and were motivated by lack of interest for the follow-up.

Metabolic hunger was recognized in 71.2 ± 30.0% of diary assessments under intervention. The diary average preprandial glycemia (DAP glycemia) was 5.2 ± 0.5 mmol/L at baseline, and was 8.6% lower than this with intervention (Table 3). The control group at end of follow-up showed no difference from base-line (5.0 ± 0.4 mmol/L).

Fifteen of 24 (62.5%) subjects had lost seropositivity for H. pylori infection in the intervention group, whereas 3 of 23 (13%) control subjects had lost seropositivity (Table 5). The pre-post difference in the mean concentration of serum anti-H. pylori was significantly higher in the intervention than in the control group. Significant positive correlation was found between the serum concentration of anti-H. pylori and DAP glycemia in simple regression longitudinal analysis (Fig. 1). Three-quarters of the two variances were communal in longitudinal factor analysis, 0.87 being the

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Table 5. “Recovery” study.

Intervention group (n = 24) Control group (n = 23)

Entry

End-trial

48.7 ± 38.2a

29.6 ± 42.9b

End-trial prevalence of infectionc 9/24 (37.5%)

47.7 ± 40.8

56.5 ± 42.5*

20/23 (87.0%)**

Serum anti-H. pylori concentrations and prevalence of the infection in intervention and control youngsters, who were positive for H. pylori at baseline. a Serum anti-H. pylori concentration, units. b First testing after about 1 year. c > 15U; see Clinical Assessments and Measurements. * p < 0.001 ANOVA. ** p < 0.002; Yates test.

Figure 1. Positive correlation between serum concentration of anti-H. pylori and diary average preprandial glycemia. Values represent differences, first less second examination. Black and white dots show intervention and control subjects, respectively. n = 47, r = 0.52, p = 0.0002.

correlation coefficient of each variable to the communality. The fruit, vegetable, fiber, and energy intake and outdoors hours were intervention components. A significant positive correlation was found between energy intake adjusted for body weight and DAP glycemia. Significant negative correlation was found between the diary average fruit intake adjusted for body weight and the serum concentration of anti-H. pylori in simple longitudinal regression analyses (r = 0.37; p < 0.05, and r = −0.43; p < 0.01,

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respectively). Both relations shared all their variance with about half of the communal variance of DAP glycemia and of anti-H. pylori in factor analysis.

The search for confounding variables on this communality showed no effect by age or other investigated variables. Instead, the ratio between LDL and HDL cholesterol and serum IgA concentration showed a high positive correlation coefficient to the same communality. Outdoor hours and vegetable, fruit, and fiber intake showed a negative correlation. No relation to the communality was found by the following variables: body weight; body weight percent for height and for age; skinfold thickness; arm and leg muscle area; number of days with vomiting, headache, abdominal pain or diarrhea in the 90 days preceding end of follow-up; and parentsâ&#x20AC;&#x2122; sum of the number of school years. The following daily averages obtained from the 7-day home diary also showed no relation: fraction of meals induced by metabolic hunger; carbohydrate, protein, and fat intake adjusted for energy intake; effective home temperature; and hours spent in bed.

None of the groups showed any deterioration in intermeal behavior or in intellectual or physical school or work performance. There was no decrease in hours spent outdoors, no increase in bedtime hours, and no clinical deterioration in blood samples. The mean height and calculated muscle areas remained around the normal median reference for the same age (NCHS, USA) in all four groups.

4. Discussion Four metabolic feelings or conditions were distinguished: (1) satiety or indifference at the sight of food; (2) appetite or consumption of available food at perception of it; (3) bearable hunger feelings between 3.9 and 4.7 mmol/L glycemia, or search for food without activity disturbance; (4) unbearable or bulimic hunger under 3.6-3.3 mmol/L, which was associated with activity disturbance. The last two types emerged with threshold characteristics in most subjects. The bearable or transient perception of metabolic hunger represented a metabolic signal rather than the beginning of an unpleasant period. Slow glycemia decrease and mild hunger have been observed with high fiber intake [15,21-24], and fruit and vegetables were more than doubled in the meals under intervention compared to controls. On the other hand, the high fruit and vegetable intake in association with no metabolic hunger or glycemia over 5 mmol/L produced abdominal pain and/or diarrhea [12].

The reader may consider hunger feelings and intake decision a psychological event with psychological purposes and consequences, and may

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not know how to perceive metabolic hunger as it was described in this investigation. The explorative verification required a modest amount of responsible and intense mental work and important changes in eating behavior, including copious fruit and vegetable intake and glycemia measurements. This full understanding and achievement of emergence of metabolic hunger before 75% of the meals (as in present investigation) may be impossible for many readers. On the other hand “most people can follow the present intervention if properly informed” and “the intervention was less difficult than expected” were typical reports by the subjects in this intervention. The error in the prediction of glycemia by metabolic feelings was within 10% of the measured value in these subjects. The evaluation of metabolic feelings showed an independent association with a steadier and slightly lower glycemia in preliminary investigations on 7000 meals by stratified analysis [14-16]. The plasma glucose concentration represents a balance between in and out energy fluxes [3-7]. The prediction of the emergence of metabolic hunger within a tight glycemia range at the scheduled mealtimes required the evaluation of these fluxes and the manipulation of a few. The resting metabolic rate and energy fecal loss significantly decreased under intervention [15]. The physical activity and hours spent outdoors could be predicted. Fruit, vegetable, fiber, and energy intake could be manipulated [14-16]. The manipulated or predicted factors of energy balance acted on glycemia, which in turn affected the serum concentration of antibody to H. pylori. The effect on the outcome might, however, be independent from glycemia lowering. This issue was investigated in the subjects of the “recovery” study by simple regression and factor analyses. A negative correlation to the serum concentration of antibody to H. pylori (outcome) was shown by adjusted fruit intake, and this finding has been already reported [36]. The variance of this relation was in common with the larger variance of the relation between DAP glycemia to the outcome. This coincidence supports an inhibition of infection by fruit mediated by the maintenance of a lower glycemia. The reproduction of these investigations may confirm the role of the components, as well as conclude the demonstration.

The intervention was associated with prevention of H. pylori-positive seroconversion and recovery from it in the two studies. Longitudinal simple regression analysis showed a highly significant, positive correlation between the concentration of serum anti-H. pylori and DAP glycemia in the “recovery” study. The odd ratios were 6.5 times lower for positive seroconversion in the “prevention” study, and 4.8 times higher for negative seroconversion in the “recovery” study under intervention than in “ad lib,” control subjects. Lower weight for height increase was observed more in the

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group under intervention than in the control group in the “prevention study,” and this may confirm an actual compliance in recognizing metabolic hunger in the long period.

A dependence on age of H. pylori seroconversion is well documented [29], and was confirmed by the “prevention” study. The groups in this study were well matched for age at entry and length of follow-up to avoid any effect by this confounding variable. The modest and insignificant difference in age between the groups in the “recovery study” showed no relation to the concentration of serum anti-H. pylori in regression and factor analyses.

The bacteria number on duodenal normal mucosa decreased in time after the previous meal in children and the variation was significantly larger on flat mucosa [19]. Absorption acceleration has been observed in association with lower glycemia [3,36-38, 40-42]. This acceleration was the purpose of intervention, to decrease the immune stimulation by intestinal bacteria.

Present findings confirm the expectation for the stomach. Seroconversion is currently used for diagnosis of H. pylori infection [29]. This method has not been statistically different from bacterium culture, the urea breath test, histology, or Warthin-Starry staining of gastric biopsy specimens, and the urease test in establishing the diagnosis in adults and children [30-34, 43].

Improvements in gastric emptying and/or acid secretion might inhibit H. pylori proliferation. These gastric functions increase with insulin sensitivity increase and glycemia decrease [36-42].

The cohorts showed 10-15% dropout rates during the first 5-month learning period. Reasons for this were reported by phone; compliant persons who were satisfied with their present health did not feel the need to make a further visit. The same reasons or lack of time and money explained further dropouts at annual verification, and the dropouts were similar in the intervention and control groups. This similarity supports lack of bias in the dropouts from either cohort. This high compliance was, however, obtained in a selected population with different problems than most of the population.

The majority of the human population develops risks and organ deterioration associated with well-being and not paying attention to one’s own body or its changes. A flat small intestinal mucosa often has been observed in well-being celiac children during gluten feeding in our Unit. Vascular disease develops silently through years [9,10]. Inflammatory bowel disease may show anatomical lesions well after symptom regression [44]. Also, the H. pylori infection was not predictable by symptoms in this investigation. On the contrary, a minority of human patients has been described with excessive perception of or attention to their own body feelings in association with scanty anatomical alteration [45]. The investigated subjects were selected from this minority. These subjects considered the assessment of metabolic

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hunger feelings at meals and of physical fitness in the interval as an easy guide for all life. H. pylori infection was prevented or cured in these attentive subjects, and insulin resistance also improved in a preliminary report [14].

For prevention purposes, an increase in attention to own body feelings may also be useful to the vast majority, which develops vascular and ovary risks in association with no complaints.

Acknowledgment This work was supported by Local University grants for the years 1990-1999 and CNR grants for 1992 and 1994.

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Research Signpost 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India

The Meal by Meal Dynamic Energy Balance in Blood: Habits & Risks, 2011: 167-168 ISBN: 978-81-308-0457-6 Editor: Mario Ciampolini

10. Conclusions Mario Ciampolini

Preventive Gastroenterology Unit, Department of Paediatrics Università di Firenze, 50132 Florence, Italy

In the last paper (Chapter 9), “recognizing hunger” (i.e. Initial Hunger Meal Pattern, IHMP) prevented and cured H. pylori infection. We used the same training that we report in chapters 5 – 8, and the trained meal pattern achieved important, biomedical results. As regards the operative mechanism during “recognizing hunger” (IHMP), the paper of chapter 9 brings us back to the information in the year 2000. The training was reproducible, but subjects’ compliance remained unknown as well as the changes in energy balance factors. The four recent chapters provided us with the missing information.

People venture meal-size to cover expenditure in inter-meal interval even after training in “recognizing hunger” (IHMP). During IHMP, venturing is checked by recognizing spontaneous arousal of Initial Hunger (IH) three times a day (around mealtimes) and/or by measurements of the associated blood glucose (BG). Mean weekly BG assesses the purpose of eating, i.e., the provision of energy by blood to body. The assessment is standardized at the same metabolic times in the day, the three lowest BGs in the day. Mean weekly BG is habitual, i.e., stable (absolute change = 13.2% ± 10.1% of possibilities, chapter VII) over 5 months in control adults (without any training). In a cross-sectional investigation before any training, mean BG resulted to be stratified in ten strata. Mean BG assesses intake habits in general and after training. High mean BG (HBG, high strata) is associated with high energy intake, high resting metabolic rate, high total daily Correspondence/Reprint request: Dr. Mario Ciampolini, Preventive Gastroenterology Unit, Department of Paediatrics, Università di Firenze, 50132 Florence, Italy. E-mail: mlciampolini@fastwebnet.it

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expenditure, high insulin resistance, high risks (subclinical inflammation) and body weight increase, either below or over 25 of BMI. Without any training, a minority of population (20% - 40%) spontaneously maintains lower mean BG (LBG) than a mean cut off of 81.8 mg/dL, does not increase body fat, has high insulin sensitivity and high risk prevention. “Recognizing hunger” (IHMP) is ‘homeostatic’.

INDEX A Absorption

-

12,22,31,32,33,34,35,36, 37,38,39,41,43,44,51,52, 71,73,91,139,140,163

BG

-

BG measurement

-

BMI (body mass index)

-

1,2,3,4,5,6,37,38,40,41, 42,43,44,57,71,72,73,79, 80,81,82,83,84,88,89,90, 95,96,97,100, 101 44,72,73,82,95,96,97, 100,101,109,112,113, 115,122,124,125,135,140 6,7,58,63,80,83,84,85,86, 88,89,101,102,105,109, 114,115,120,124,125, 126,127,128,129,130, 131,134,136, 168

B

D Diarrhea

-

dynamic balance

-

4,12,13,14,20,21,22,24, 36,37,60,73,74,90,97, 100,108,110,114,139, 145,148,154,161 2,3,4,5,43,139

E energy balance in blood

-

3,6,23,42,52,73,90,91, 138

fatty acids

-

fattening

-

3,5,6,40,52,72,136,139, 140 4,43

F

G GTT

-

6,7,83,84,86,87,96,99, 100,101,106

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Index

H HBG (high blood glucose concentration)

-

HOMA Homeostasis

-

2,45,96,98,99,100,101, 102,104,105,106,107, 108,109,110,111,112, 113, 114,115,120,122, 126,127,128,129, 130, 131,132,133,134,138, 140,167 5 2,3,61,112,113,119,121, 122,133,135,137,138, 140,168

I IBS (irritable bowel syndrome)

-

IHMP

-

Initial Hunger (IH)

-

Insulin resistance (IR)

-

Insulin sensitivity

-

Intestinal bacteria

-

11,12,13,14,15,16,18,19, 20,22,24 2,73,74,79,80,81,82,85, 88,89,98,119,120,121, 122,123,125,127,130, 131,133,135,136,137, 138,139,140 2,38,58,59,60,62,70,79, 80,167 2,3,4,5,6,22,23,31,37,38, 39,40,41,42,43,45,72,73, 80,89,90,91,80,89,90,91, 96,97,105,108,110,113, 122,138,139,146,164, 168 2,4,5,22,42,79,80,81,83, 87,89,90,96,97,98,99, 401,104,106,108,112, 120,121,137,139,140, 146,163,168 23,163

L LBG

-

2,80,81,89.90,91,95,96, 98,99,101,102,103,104, 105,106,107,108,109, 110,111,113,114,115, 121,127,129,130,133, 135,136,138,139,168

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Index

M Mean BG

-

2,6,73,84,85,88,89,90, 95,96,97,99,102,103, 104,107,108,109,111, 112,113,114,120,121, 128,129,133,134,138, 140,167,168

-

2,81,110,111,122

-

6,13,23,24,39,40,41,43, 49,50,52,110,122

-

2,73,79,80,95,96,97,98, 99,103,105,109,110,111, 119,121,139,167

subclinical inflammation

-

Subjective Slightly Depressed BG Stress

-

6,23,24,39,41,44,45,49, 51,52,73,74,89,91,110, 113,138,168 1,43,59,80,81,82,83 6,88 23,43,44,45,49,51,52,82, 91,100,115,124,125

N Non Insulin Dependent Diabetes (NIDD) P Pro-inflammatory state R Recognizing hunger

S

T Training

-

1,7,43,44,57,58,59,60,67, 68,69,70,73,74,80,82,83, 84,85,86,87,88,89,91,95, 96,97,98,99,100,101,102, 104,105,106,107,108, 109,110,111,113, 115, 120,121,122,123,124, 126,127,128,129,130, 131,132,133,134,135, 137,138,139,140,146, 147,148,150,151,167