IJP: Israel Journal of Psychiatry: Vol' 51, issue 2 by MEDIC

israel journal of

psychiatry

Vol. 51 - Number 2 2014

ISSN: 0333-7308

Special section Gender and psychiatry: Part I 82

Editorial: Gender and Psychiatry Zipi Dolev et al.

Gender Differences in the Psychopathology of Emerging Psychosis Alexandre GonzĂĄlez-RodrĂguez et al.

Antidepressant Use in Pregnancy: An Evaluation of Adverse Outcomes Excluding Malformations Laura Lorenzo and Adrienne Einarson

106

Maternal Depression and Perception of Teratogenic Risk Gideon Koren

109

The Impact of Maternal Positive and Negative Affect on Fetal Physiology and Diurnal Patterns Gillian E. Hanley et al.

118

Gender Differences in the Prevalence and Correlates of Psychotropic Medication Use among Older Adults in Israel Tzvia Blumstein et al.

128

Postpartum Anxiety in a Cohort of Women from the General Population Inbal Shlomi Polachek et al.

135

Aripiprazole Combined with Other Psychotropic Drugs in Pregnancy: Two Case Reports Vesna Pirec et al.

137

Gender and Disordered Eating of Adolescents in Israel Bracha Katz

145

Disordered Eating and Cultural Distinctions: Exploring Prevalence and Predictors among Women in Israel Marjorie C. Feinson and Adi Meir

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israel journal of

psychiatry

The Official Publication of the Israel Psychiatric Association Vol. 51 - Number 2 2014

and related sciences EDitor

David Greenberg DEPUTY EDITORS

Doron Gothelf Yoav Kohn Ivonne Mansbach Ora Nakash Shaul Lev-Ran David Roe Rael Strous Book reviews editor

Yoram Barak

Special section: Gender and psychiatry: Part 1

82 > Editorial: Gender and Psychiatry

Zipi Dolev, Shaila Misri and Anita Riecher-Rössler

85 > Gender Differences in the Psychopathology of Emerging Psychosis

Founding Editor

Alexandre González-Rodríguez, Erich Studerus, Andrea Spitz, Hilal Bugra, Jacqueline Aston, Stefan Borgwardt, Charlotte Rapp and Anita Riecher-Rössler

Editorial Board

94 > Antidepressant Use in Pregnancy:

PAst Editor

Eli L. Edelstein Heinz Z. Winnik

Alean Al-Krenawi Alan Apter Omer Bonne Elliot Gershon Talma Hendler Ehud Klein Ilana Kremer ltzhak Levav Yuval Melamed Shlomo Mendlovic Ronnen Segman Eliezer Witztum Gil Zalsman Zvi Zemishlany International Advisory Board

Paul Appelbaum Dinesh Bhugra Yoram Bilu Boris Birmaher Aaron Bodenheimer Stephen Deutsch Carl Eisdorfer Michael First Helen Herrman Julian Leff Ellen Liebenluft John Mann Phyllis Palgi Soumitra Pathare Daniel Pine Bruce Pollock Dan Stein Robert Wallerstein Myrna Weissman Associate editor

Rena Kurs

Assistant Editor

Joan Hooper

Marketing: MediaFarm Group +972-77-3219970 23 Zamenhoff st. Tel Aviv 64373, Israel amir@mediafarm.co.il www.mediafarm.co.il

128 > Postpartum Anxiety in a Cohort of Women from the General Population: Risk Factors and Association with Depression during Last Week of Pregnancy, Postpartum Depression and Postpartum PTSD Inbal Shlomi Polachek, Liat Huller Harari, Micha Baum and Rael D. Strous

An Evaluation of Adverse Outcomes Excluding Malformations

135 > Aripiprazole Combined with Other Psychotropic Drugs in Pregnancy: Two Case Reports

106 > Maternal Depression and

137 > Gender and Disordered Eating of

Laura Lorenzo and Adrienne Einarson

Perception of Teratogenic Risk

Gideon Koren

109 > The Impact of Maternal Positive and Negative Affect on Fetal Physiology and Diurnal Patterns

Gillian E. Hanley, Dan Rurak, Ken Lim, Ursula Brain and Tim F. Oberlander

Vesna Pirec, Aarti Mehta and Sittanur Shoush

Adolescents in Israel

Bracha Katz

145 > Disordered Eating and Cultural Distinctions: Exploring Prevalence and Predictors among Women in Israel Marjorie C. Feinson and Adi Meir

118 > Gender Differences in the Prevalence and Correlates of Psychotropic Medication Use among Older Adults in Israel

Tzvia Blumstein, Yael Benyamini, Dov Shmotkin and Liat Lerner-Geva

Hebrew Section

156

> Abstracts

Manic-depression Artist: Anonymous Since 2010 the cover of the Israel Journal of Psychiatry has presented art works by patients. There is no single view of this art: whether a perception that is unique owing to the artist’s life experience, as an opportunity to express inchoate feeling and thoughts, or as a tribute to their quality, an expression of their contribution to society and life. The reader interested in a history of this field will enjoy: Beveridge A. A disquieting feeling of strangeness? The art of the mentally ill. J R Soc Med 2001;94:595-599.

Isr J Psychiatry Relat Sci - Vol. 51 - No 2 (2014)

Editorial: Gender and Psychiatry Gender differences of psychiatric disorders have long been recognized: prevalence rates in women exceed those of men for a number of disorders. Gender differences between men and women exist in the epidemiology, risk factors, presenting symptoms, course of illness, treatment response, and prognosis of psychiatric conditions (1). Not all differences can be explained by physiologic variation; for example, the greater frequency of eating disorders in women may represent a sociocultural effect, with body weight affecting a self-image to a far greater degree than a man (2). On the other hand, men may abuse substances to manage emotional response that are discouraged or viewed as unacceptable in men. Comorbid medical conditions are more likely in women, including thyroid disease, migraine and fibromyalgia (1). Sex differences in schizophrenia are one of the most consistently reported aspects of the disease. They are described in almost all features of the illness from prevalence, incidence and mean age at onset, clinical presentation and course, and in the response to treatment. Whether and how women and men with schizophrenia differ is one of the most interesting as well as clinically relevant topics in schizophrenia research (3). Evidence suggests sex differences in schizophrenia reflect differences in both neurodevelopmental processes and social effects on disease risk and course. Male: female incidence approximates 1.4:1 but at older onset women predominate, so prevalence differences appear smaller (4, 5) Gender differences have often been described regarding psychopathological symptoms in chronic schizophrenia and first-episode psychosis (FEP) patients, although methodologically sound studies could not always confirm this (6). In a new study from the Basel FePsy FrĂźherkennung von Psychosen â&#x20AC;&#x201C; early detection of psychosis clinic psychiatric symptoms were assessed not only in 87 FEP patients but also in 117 patients with an at risk mental state (ARMS) for psychosis (7). This is a novel approach, especially as most of them were antipsychotic free. In addition to observer-rated scales also a self-report scale was used. Results were controlled for the influence of age, medication and cannabis use. As often described in the literature, women had higher scores in positive psychotic symptoms, while men had higher scores in negative symptoms. However, the differences did not withstand correction for multiple testing. Thus, there do not seem to be 82

any major gender differences in psychopathology, either in ARMS or in FEP patients as regards self-reported or observer-rated symptoms when correction for multiple testing and potential confounders is performed (8, 9). Gender differences can be explained also by physiologic variation, as for example the influence of hormones on mood. Reproductive psychiatry is a specialty that helps women deal with psychiatric conditions that develop in relation to specific points in their reproductive life cycle, such as their menstrual cycle, pregnancy and menopause (1, 10) Pregnancy and postpartum related mental health issues continue to be a public health burden all over the world (11). Research shows that women are often distressed by depressive, anxiety and occasionally psychotic disorders in the perinatal period, thus challenging the notion that the child bearing experience is a time of uninterrupted joy, contentment and gratification. Despite the high rate of prevalence of depressive and anxiety disorders, estimated to be 12% (12) and 8.5% (13) respectively, in perinatal women, the associated stigma acts as a barrier which prevents afflicted women from seeking or receiving help. Women are reluctant to accept any psychiatric diagnosis in pregnancy or postpartum, owing to the shock, fear, rejection and dishonor that accompanies mental illness. Hence, delay in diagnosis and late intervention appears to be the rule. In some cultures, denial of this illness in the mother is widespread. Resultant chronicity of the condition with ongoing disability in overall functioning is commonly encountered. The morbidity and mortality associated with maternal mental illness is of significance as it can result in complicated mother-infant attachment (14). Sophisticated research on antenatal psychiatric disorders and its adverse impact in utero is presently of particular interest to researchers. Biological and psychological markers have been shown to be altered in the fetuses exposed to severe antenatal mood and anxiety disorders (15). Oberlanderâ&#x20AC;&#x2122;s paper on fetal physiology and maternal affect denotes an important milestone in the advancement of maternalfetal medicine as it relates to mental health issues (16). Psychiatric illness during the perinatal period has been shown to exert short- as well as long-term negative effects on the developing baby, the newborn and the child (17). Research in this particular area seems to be evolving speedily over the past two decades.

Zipi Dolev et al.

The transition into motherhood with its attendant anxiety can be overwhelming to the mother and often masks the underlying pathological perinatal mental illness. Early identification and screening is advocated at many centers whereby women at risk can be closely monitored. Among the several risk factors that have been thus far recognized, genetic, biological and psychosocial vulnerabilities appear to play an important role in the onset and perpetuation of perinatal psychiatric disorders. Additional risk factors include: unwanted pregnancy, lack of partner and family support, low socioeconomic class, chronic medical conditions and substance abuse (18). Prior trauma and birthrelated complications such as difficult labor or surgical interventions can trigger flashbacks, intrusive memories, negative perceptions and anxiety/ mood changes. Shlomi Polachek and colleagues describe postpartum depression and Post Traumatic Stress Disorder in their paper which requires careful attention (19). The obvious concern that arises after a psychiatric diagnosis has been established is the availability of safe, effective and affordable interventions for the anguished mother. Involving a significant other in the treatment plan and dealing with the woman’s concerns compassionately will aid compliance. Another essential way in which the communication between the clinician and the woman can be enhanced is by establishing mutual consensus, thus sharing the process of management. The treatment issue has been in the forefront of treating physicians’ minds, particularly in the last ten years with controversial research on the use of psychotropic medications in pregnancy and the postpartum. The Federal Drug Administration and Health Canada advisories have triggered apprehension. Women are reluctant to access suitable pharmacological interventions despite severity of their illness. Women’s perception of teratogenic effects is also an important area as described by Koren (20); it has been developing rapidly as research in this field gains momentum. Long term studies on biobehavioral teratogenecity with antenatal medication exposure show positive results (21). While research demonstrates relapse of symptoms with medication discontinuation (22). prescribing psychotropic medications to pregnant and lactating women appears to be weighed down with concern and hesitation. Current research in relation to perinatal medication use is conflict-ridden at best. Lorenzo and Einarson’s paper (23) therefore will serve as guide to physicians and boost confidence in reinstating medications when deemed appropriate. The exposure of the developing fetus to the medications versus the maternal mental illness continues to be a clinical conundrum for the treating clinician.

Comorbid disorders such as Obsessive Compulsive Disorder or Generalized Anxiety Disorder in their severe forms appear to be resistant to conventional treatment and require multiple modalities of management. Polypharmacy, although not recommended, is often necessary to control severe Anxiety Disorders or psychotic symptoms in pregnancy. In addition to the use of antidepressants, the use of atypical antipsychotics in complex, comorbid psychiatric conditions is not uncommon. Pirec and colleagues (24) describe the use of an atypical antipsychotic medication in antenatal women, an area with sparse data. It is ideal to combine psychological as well as pharmacological therapies for an optimal outcome in moderateto-severe psychiatric conditions. More knowledge exists at present with regards to the effectiveness of individual psychotherapy (25). Although not extensive, the data on group therapy appears to show successful results if administered in an appropriate manner (26, 27). Bowen et al.’s paper introduces innovative group therapy techniques for perinatal women in Saskatchewan, Canada (28). Several perinatal centers in Canada are embracing group intervention with excellent outcome. This gender specific perinatal mental health issue will require a massive campaign to bring it into the limelight. It remains a neglected medical reality in many parts of the world. Public awareness and education are the key to minimize shame and promote early intervention. In the light of rapidly accumulating data on the adverse effects of persistent, relapsing mental illness on the mother and her child, maintaining emotional stability in the perinatal period is absolutely mandatory. While the gap between recognition and treatment still remains wide, increased understanding, improved clinical care, growing research and investment of funds by appropriate agencies in some countries appears to offer hope and optimism in the lives of mentally ill mothers. Gender differences have been noted also in pharmacodynamics of medications. The optimal dose range of a therapeutic medication may not be the same for women as for men. “Standard” treatment, when applied to women, works less well than for men because it has largely been tested on male animals in the laboratory and on male research subjects in the clinic (29). Women may require lower doses of medications than men, even when adjusted for body weight, due to hormonal influences on blood drug levels. The use of exogenous hormones (oral contraceptive, hormone replacement therapy) may additionally influence levels of medications. 83

Editorial: Gender and Psychiatry

Men and women differ also in the side effects of medications (30). We need to understand that beyond the need to better understand psychiatric disease is the clinical responsibility to provide individualized, optimally effective, genderspecific care to all patients (31). Only recently, medical research has started to understand the importance of taking gender into account as the symptoms and responses to medical treatment may be very different between sexes. Gender-based medicine is the field of medicine that studies the biological and physiological differences between the human sexes and how that affects differences in disease (32). References 1. Kornstein SG, Clayton AH, editors. Women’s mental health: A comprehensive textbook. New York: Guilford, 2002. 2. Bean P, Maddocks MB, Timmel P, Weltzin T. Gender differences in the progression of co-morbid psychopathology symptoms of eating disordered patients. Eat Weight Disord 2005;10:168-174. 3. Abel KM, Drake R, Goldstein JM. Sex differences in schizophrenia. Int Rev Psychiatry 2010;22:417-428 4. Aleman A, Kahn RS, Selten JP Sex differences in the risk of schizophrenia: Evidence from meta-analysis. Arch Gen Psychiatry 2003;60:565-571. 5. Häfner H, Maurer K, Löffler W, Riecher-Rössler A The influence of age and sex on the onset and early course of schizophrenia. Br J Psychiatry 1993;162:80-86. 6. Riecher-Rössler A, Pflueger MO, Borgwardt S. Schizophrenia in women. In: Kohen D, editor. Oxford textbook of women and mental health (ed. D. Kohen). Oxford: Oxford University, 2010: pp. 102-114. 7. González-Rodríguez A, Studerus E, Spitz A, Bugra H, Aston J, Borgwardt S, Rapp C, Riecher-Rössler A. Gender differences in the psychopathology of emerging psychosis. Isr J Psychiatry Relat Sci 2014, 51:85-93. 8. González-Rodríguez A, Studerus E, Spitz A, Rapp C, Bugra H, Aston J, Borgwardt S, Riecher-Rössler A. Gender Differences in the Psychopathology of Emerging Psychoses. Eur Psychiatry 2013;28:1. 9. Riecher-Rössler A, Häfner H. Gender aspects in schizophrenia: Bridging the border between social and biological psychiatry. Acta Psychiatr Scand 2000;102:58-62. 10. Riecher-Rössler A, de Geyter C The forthcoming role of treatment with oestrogens in mental health. Swiss Med Wkly 2007;137:565-572. 11. Riecher-Rössler A, Steiner M, editors. Perinatal stress, mood and anxiety disorders: from bench to bedside. Bibliotheca Psychiatrica, vol. 173. Basel: Karger, 2005 12. O’Hara MW, Swain AM. Rates and risk of postpartum depression—a meta-analysis. Int Rev Psychiatry 1996;8:37-54. 13. Ross LE, McLean LM. Anxiety disorders during pregnancy and the postpartum period: A systematic review. J Clin Psychiatry 2006;67: 1285-1298. 14. Weikum WM, Mayes LC, Grunau RE, Brain U, Oberlander TF. The impact of prenatal serotonin reuptake inhibitor (SRI) antidepressant exposure and maternal mood on mother–infant interactions at 3 months of age. Infant Behav Dev 2013;36:485-493. 15. Monk C, Spicer J, Champagne FA. Linking prenatal maternal adversity to developmental outcomes in infants: the role of epigenetic pathways. Dev Psychopathol 2012;24:1361-1376. 16. Hanley GE, Rurak D, Lim K, Brain U, Oberlander TF. The impact of

maternal positive and negative affect on fetal physiology and diurnal patterns. Isr J Psychiatry Relat Sci 2014, 51:109-117. 17. Sandman CA, Davis EP, Glynn LM. Prescient human fetuses thrive. Psychol Sci 2012;23:93-100. 18. Lancaster CA, Gold KJ, Flynn HA, Yoo H, Marcus SM, Davis MM. Risk factors for depressive symptoms during pregnancy: a systematic review. Am J Obstetrics Gynecology 2010;202:5-14. 19. Shlomi Polachek I, Huller Harari L, Baum M, Strous RD. Postpartum anxiety in a cohort of women from the general population: Risk factors and associations with depression during the last weeks of pregnancy, postpartum depression and postpartum PTSD. Isr J Psychiatry 2014, 51:128-134. 20. Koren G. Maternal depression and perception of teratogenic risk. Isr J Psychiatry Relat Sci 201451:106-108. 21. Misri S, Reebye P, Kendrick K, Carter D, Ryan D, Grunau R, et al. Internalizing behaviors in 4-year-old children exposed in utero to psychotropic medications. Am J Psychiatry 2006;163:1026-1032. 22. Cohen LS, Altshuler LL, Harlow BL, Nonacs R, Newport DJ, Viguera AC, et al. Relapse of major depression during pregnancy in women who maintain or discontinue antidepressant treatment. JAMA 2006;295:499-507. 23. Lorenzo L, Einarson A. Antidepressant use in pregnacy: an evaluation of adverse outcomes excluding malformations. Isr J Psychiatry Relat Sci 2014,51:94-105. 24. Pirec V, Mehta A, Shoush S. Aripiprazole combined with other psychotropic drugs in pregnancy: Two case reports. Isr J Psychiatry 2014, 51:135-136. 25. Grote N, Swartz H, Geibel S, Zuckoff A, Houck P, Frank E. A randomized controlled trial of culturally relevant, brief interpersonal psychotherapy for perinatal depression. Psychiatr Serv, 2009;60:313-321. 26. Reay R, Fisher Y, Robertson M, Adams E, Owen C. Group interpersonal psychotherapy for postnatal depression: a pilot study. Arch Womens Ment Health 2006;9:31-39. 27. Frisch U, Hofecker Fallahpour M, Stieglitz RD, Riecher-Rössler A. Group treatment for depression in mothers of young children: A controlled study. Psychopathology 2012;46:94-101. 28. Bowen A, Baetz M, Schwartz L, Balbuena L, Muhajarine N. Antenatal group therapy improves worry and depression symptoms. Isr J Psychiatry Relat Sci 2014, in press. 29. Bigos KL, Pollock BG, Stankevich BA, Bies RR. Sex Differences in the pharmacokinetics and pharmacodynamics of antidepressants: An updated review. Gender Med 2009, 6:522-543. 30. Clayton AH. Gender differences in clinical psychopharmacology. J Clin Psychiatry 2005;66:1191. 31. Burt VK, Hendrick VC. Clinical manual of women’s mental health. Arlington, Virgina: American Psychatric Press, 2005. 32. Baggio G, Corsini A, Floreani A, Giannini S, Zagonel V. Gender medicine: A task for the third millennium. Clin Chem Lab Med 2013; 51:713-727.

Guest Editors: Dr. Zipi Dolev

Psychiatrist, Women’s Mental Health Private practice, Herzlia, Israel. Zipora1@netvision.net.il

Dr. Shaila Misri

Clinical Professor, Psychiatry and Obstetrics/Gynecology University of British Columbia, P1-228, 4500 Oak Street Vancouver, BC, Canada V6H 3N1 smisri@cw.bc.ca

Prof. Anita Riecher-Rössler

MD, PhD, Head of Center for Gender Research and Early Detection Psychiatric University Clinics Basel Anita.Riecher@upkbs.ch

Isr J Psychiatry Relat Sci - Vol. 51 - No 2 (2014)Alexandre González-Rodríguez et al.

Gender Differences in the Psychopathology of Emerging Psychosis Alexandre González-Rodríguez, MD, Erich Studerus, PhD, Andrea Spitz, MSc, Hilal Bugra, MSc, Jacqueline Aston, MD, Stefan Borgwardt, MD, Charlotte Rapp, MSc, and Anita Riecher-Rössler, MD University of Basel Psychiatric Clinics, Center for Gender Research and Early Detection, Basel, Switzerland

Abstract Background: Gender differences have often been found in psychopathological symptoms among chronic schizophrenia and first-episode psychosis (FEP) patients. However, many of these studies suffer from methodological problems and show inconsistent results. Furthermore, very few studies have investigated gender differences in individuals with an at-risk mental state (ARMS) for psychosis. Methods: Psychopathological symptoms were assessed in 117 ARMS and 87 FEP patients by two observer-rated scales, namely, the expanded version of the Brief Psychiatric Rating Scale (BPRS) and the Scale for the Assessment of Negative Symptoms (SANS), and by one self-report scale, the Frankfurt Complaint Questionnaire (FCQ). Gender differences were investigated by applying Analyses of Variance using the BPRS, SANS and FCQ subscales as dependent variables, and group and sex as between-subject factors - in a second step by including age, antipsychotic, antidepressant and cannabis use as covariates. Results: There were no significant gender × patient group interactions, suggesting that gender effects did not differ between patient groups. Women had higher scores in positive psychotic symptoms (BPRS Psychosis/ Thought Disturbance) while men had higher scores in negative symptoms (BPRS negative symptoms, SANS total score, as well as subscales Affective Flattening, Avolition-Apathy and Asociality-Anhedonia). However, the differences did not withstand correction for multiple testing. The results did not change when corrected for potential confounders.

Conclusions: There do not seem to be any gender differences in psychopathology, neither in ARMS nor in FEP patients, as regards self-reported or observerrated symptoms, when corrected for multiple testing and potential confounders.

Introduction The analysis of gender differences in schizophrenia has been of interest for many decades. Kraepelin had already observed, on the basis of medical histories of 225 men and 449 women, that the classical picture of schizophrenia with early manifestation, deficits in premorbid development, affective flattening and social anhedonia seems to occur much more often in men than in women (1). The empirical data collected since then appear to confirm this, especially the gender differences with regards to an earlier manifestation age of psychosis in men than in women (for review, see 2, 3-5). Many studies have also reported that men have poorer premorbid adjustment and present with more negative, but fewer depressive symptoms than women (for review, see 6, 7, 8). Furthermore, women seem to have a better response to antipsychotics than men (9, 10). However, the problem of many studies conducted in this area is that frequently the examined populations were neither representative, nor restricted to first contact patients or first admissions, or important covariates were not considered (11-13). Furthermore, the diagnostic concept applied is important. Thus, Addington et al. (14), in a study on 113 inpatients meeting DSM-III-R criteria

Address for Correspondence: Prof. A. Riecher-Rössler, University of Basel Psychiatric Clinics, Center for Gender Research and Early Detection, University Hospital Basel, Petersgraben 4, CH-4031 Basel, Switzerland Anita.Riecher@upkbs.ch

Gender Differences in the Psychopathology of Emerging Psychosis

for schizophrenia, reported that gender differences in negative and affective symptoms disappear when the sample is restricted to narrowly defined schizophrenia. Empirical studies that were clearly restricted to first episode psychosis (FEP) patients are rather inconclusive. Thus, for instance Szymanski et al. (15) reported more anxiety, illogical thinking, inappropriate affect, and bizarre behavior in women than in men. No gender differences in FEP were found in Barajas et al. (16). Häfner et al. (4), who carried out a representative study of all 276 first hospitalized FEP patients from a well-defined catchment area with a population of about 1.5 million inhabitants in and around Mannheim, Germany, did not find many gender differences. Especially with respect to psychotic symptoms after correction for multiple testing, no statistically significant gender differences were found anymore. They rather found differences in illness behavior with more self-neglect and cannabis abuse in men and more over-adaptive behavior in women (17, 18). These authors noted that methodological problems (see above), but possibly also the higher prevalence of substance abuse in men, could have contributed to gender differences found in other studies (19). More recent studies investigating gender differences regarding symptoms in clearly representative samples of first episode patients were conducted by Salokangas and Stengård (20), Thorup et al. (21), Koster et al. (22), Cotton et al. (23) and Bertani et al. (24). The most commonly reported findings in these studies were more negative, but less affective symptoms, poorer social functioning and more social isolation in men than in women (20, 21, 24, 25) and also more substance abuse in men (21, 23, 25). There are only few studies about psychopathological gender differences in individuals with a so-called at-risk mental state for psychosis (ARMS). All of these reported no gender differences regarding symptoms at baseline (26-28). When baseline and follow-up time points were considered collectively, Willhite et al. (26) found significantly higher levels of negative symptoms and marginally lower levels of social functioning in men. To our knowledge, the present study is the first to investigate gender differences in psychopathology in a largely representative sample of both ARMS individuals and FEP patients, considering important potential confounders such as age, duration of untreated illness (DUI), antipsychotic and antidepressant medication, and cannabis use. The goal of the study was to elucidate whether gender differences in psychopathology in fact do exist in ARMS or FEP, in order to provide clinical 86

evidence to improve the early detection of psychosis. We hypothesized that the gender differences in psychopathology in ARMS and FEP found in some of the previous studies could be explained by potential confounders such as higher substance use in men compared to women. Material and Methods Setting and study population

Participants were recruited via the Früherkennung von Psychosen (FePsy) Clinic, a specialized clinic for the early detection of psychosis at the Department of Psychiatry, University Hospital in Basel, Switzerland, from March 1, 2000, to September 1, 2012. The present study is a part of an ongoing study on the early detection of psychosis. The ARMS and FEP groups were identified using the Basel Screening Instrument for Psychosis (BSIP), a 46-item instrument based on variables that have shown to be risk factors and early indicators of psychosis (29). This instrument allows the rating of individuals with beginning psychosis in the atypical early stages of the disease with a good reliability and validity (29, 30) according to the criteria of Yung and co-workers (31). Inclusion criteria

Subjects were included as ARMS individuals if they met the following inclusion criteria based on our screening instrument (29) and the Brief Psychiatric Rating Scale (BPRS) (version Lukoff et al. [32] and Ventura et al. [33]): i. Prepsychotic category (according to Yung et al. [31] and BPRS version/scale Lukoff et al. [32]). “Attenuated” psychotic symptoms: psychotic symptoms below transition cut-off (BPRS scales: hallucinations 2–3, unusual thought content 3–4, suspiciousness 3–4) at least several times per week, in total persisting for >1 week; or Brief Limited Intermittent Psychotic Symptoms (BLIPS): psychotic symptoms above transition cut-off (BPRS scales: hallucinations ≥4, unusual thought content ≥5, suspiciousness ≥5, conceptual disorganisation ≥5), but each symptom <1 week before resolving spontaneously. ii. Genetic risk category: first or second degree relative with psychotic disorder and at least two further risk factors according to screening instrument. iii. Unspecific risk category: minimal amount and combination of certain risk factors according to screening instrument. Precondition for all categories: criteria of transition to psychosis not fulfilled.

Alexandre González-Rodríguez et al.

Criteria i) and ii) correspond to those of Yung et al. (31). Criterion iii) additionally permits the inclusion of individuals at lower risk, i.e., of patients without prepsychotic symptoms or genetic risk who only exhibit a combination of certain unspecific risk factors and indicators such as prodromal symptoms or marked social decline (unspecific risk group).

More detailed descriptions of the study design, recruitment and inclusion criteria have been provided elsewhere (30, 34). All aspects of the study were approved by the Ethics Committee of Basel (EKBB), Switzerland, and written informed consent was obtained from each study participant.

Transition criteria

At the time of study inclusion, psychopathological symptoms were assessed with the expanded version of the Brief Psychiatric Rating Scale (BPRS) (32, 33), the Scale for the Assessment of Negative Symptoms (SANS) (35) and the Frankfurt Complaint Questionnaire (FCQ) (36). The BPRS consists of 24 items and is one of the most frequently used research instruments for evaluating psychopathological symptoms in patients with schizophrenia (37). Although there is no widely accepted factorial structure of the BPRS, several authors have proposed a four factorial structure. In the present study, we used the BPRS total score and the four subscales (i.e., Depression/Anxiety, Psychosis/Thought Disturbance, Negative Symptoms, and Activation) derived from the factorial structure of Velligan et al. (37), as their study was based on the largest sample size. The SANS is a well-recognised rating scale for the assessment of negative symptoms in schizophrenia. It consists of 19 items, which are grouped into five domains or factors (Affective Flattening, Alogia, Avolition-Apathy, AnhedoniaAsociality, and Inattention). In the present study, we used the SANS total score and the five original subscales. The FCQ is a self-rating scale that is composed of 98 yes/ no questions. It is one of the most widely used procedures for systematic investigation of non-psychotic subjective experiences (i.e., so-called basic symptoms) in emerging psychoses and has been adapted to several languages (38). Basic symptoms are subjective subclinical disturbances in avolition, affect, thought, speech, perception and stress tolerance, which can occur at every stage of psychotic disorders, in ARMS individuals, in prodromes of relapse, and during psychotic episodes (39). FCQ items are grouped into ten categories according to phenomenological similarities. Exploratory factor analyses, however, suggest only 2-4 underlying factors (40). In this study, we used the four scales derived from the factorial structure of Süllwold and Huber (41) (i.e., Disturbances of automated responses, Perceptual disturbances, Depression and Overinclusion) and the FCQ total scale. The duration of untreated illness (DUI) was defined as the time period between first self-perceived signs or symptoms and first contact with our specialized early

Inclusion criteria for FEP patients and criteria for transition to psychosis: FEP patients were those who at intake already fulfilled the criteria for transition to psychosis as defined by Yung et al. (31): • At least one of the following symptoms: Suspiciousness (BPRS ≥5): says others are talking about him/her maliciously, have negative intentions or may harm him/her (incidents more than once a week OR partly delusional conviction). Unusual thought content (BPRS ≥5): full delusion(s) with some preoccupation OR some areas of functioning disrupted (not only ideas of reference/ persecution, unusual beliefs or bizarre ideas without fixed delusional conviction). Hallucinations (BPRS ≥4): occasional hallucinations or visual illusions >2/week or with functional impairment (not only hearing of own name, non-verbal acoustic or formless visual hallucinations/illusions). Conceptual disorganization (BPRS ≥5): speech difficult to understand due to circumstantiality, tangentiality, neologisms, blockings or topic shifts (most of the time OR three to five instances of incoherent phrases). • Symptoms at least several times a week. • Change in mental state lasting >1 week. The patients were only included in the study if they had not received antipsychotic treatment for more than a maximum of three weeks. If the patients fulfilled the inclusion criteria, they were asked to participate in the FePsy study, an open, prospective clinical study on the early recognition of schizophrenic psychosis. Exclusion criteria

Exclusion criteria were age <18 years, insufficient knowledge of German, IQ <70, psychosis clearly due to organic brain disease or substance abuse (except cannabis), psychotic symptomatology within a clearly diagnosed affective psychosis or borderline personality disorder, or lifetime antipsychotic treatment for more than a maximum of three weeks (total chlorpromazine equivalent dose ≥2500 mg) (34).

Clinical data and psychopathological assessment

Gender Differences in the Psychopathology of Emerging Psychosis

detection clinic. The duration of untreated psychosis (DUP) was defined as the time period between the appearance of first psychotic symptoms and first contact with our FePsy Clinic. The DUI and DUP were determined by using the Basel Interview for Psychosis (BIP) ) (42), a structured and specifically developed interview for the early detection of psychosis. The DUI was assessed both for ARMS and FEP patients at first contact, but the DUP was only assessed in FEP patients since ARMS patients per definition did not have psychotic symptoms yet.

Demographic and clinical characteristics of the ARMS, FEP and total groups are presented in Table 1. No statistically significant univariate differences were found between men and women with regard to age, years of education, cannabis use, antipsychotic and antidepressant use, neither within the total sample nor within the FEP and ARMS groups. The DUP and the DUI did not differ between male and female ARMS and FEP patients, and within the total group. Furthermore, there were no statistically significant DUI × gender × group interactions.

Data analysis All data were analyzed by using SPSS for Windows (version 19). Univariate differences in socio-demographic and clinical characteristics between male and female patients within each patient group (i.e., ARMS, FEP, and combined group) were tested with t-tests, Mann-Whitney U tests, χ2 and Fisher’s exact tests. These tests were two-tailed with a significance level of 0.05. Multivariate differences in psychopathology were investigated by applying a one-way analysis of variance (ANOVA) for each of the 16 clinical variables (i.e., 5 BPRS scales, 6 SANS scales and 5 FCQ scales). The clinical variables served as the dependent variables, and gender and patient groups (ARMS or FEP) were included as between-subject factors. In case of a significant group by gender interaction, ANOVAs were followed up by subgroup analyses. Moreover, to investigate whether gender differences were biased by confounding variables, age, DUI, use of antipsychotic, antidepressant and cannabis were introduced into the models in a stepwise manner. Specifically, cannabis use was included in the multiple regression models as a categorical variable represented by four dummy variables. Due to the large number of comparisons, p-values of the gender effects in the ANOVA models were corrected by the Benjamini-Hochberg method that controls for the false discovery rate (43).

Gender differences in psychopathology

Results Sample characteristics

Of the ARMS and FEP patients recruited into FePsy study, in 117 ARMS (men/women 1.72) and 87 FEP patients (male/female 1.81) at least one of the analysed rating scales was completed. The BPRS ratings were obtained in 114 ARMS and 86 FEP patients, the SANS ratings in 110 ARMS and 81 FEP patients, and the FCQ was completed in 69 ARMS and 55 FEP patients. 88

Table 1 also shows the univariate comparisons of the BPRS, SANS and FCQ subscales between men and women within each patient group. Mean scores and 95% confidence intervals of these psychopathological symptom scales within ARMS and FEP patients are additionally presented in Figure 1. When uncorrected for multiple testing, within the total group men had higher scores than women in the BPRS subscale “negative symptoms”, in the SANS total score as well as the SANS subscales “Affective Flattening,” “Alogia” and “Asociality-Anhedonia,” Within the ARMS group, women had significantly higher scores than men in the BPRS subscale “Depression/Anxiety,” whereas men had higher scores than women in the SANS total score as well as the SANS subscales “Alogia” and “AsocialityAnhedonia. Within the FEP group, higher scores in the BPRS subscale “negative symptoms” were found in men compared to women. In multivariate analyses, there were no statistically significant gender × group interactions for any of the 16 dependent variables. Hence, all multivariate analyses were performed in the total group only. Regression coefficients, uncorrected p-values and p-values corrected by BenjaminiHochberg adjustment for multiple testing are shown in Table 2. Negative values of the regression coefficients mean that women had lower scores on the assessed scales. The main effect of gender was significant for the BPRS subscales “Psychosis/Thought disturbance” and “Negative symptoms”, in the SANS total score as well as the SANS subscales “Affective Flattening, “Avolition-Apathy” and “AsocialityAnhedonia. This means that women had more positive psychotic symptoms and thought disturbances, but fewer negative symptoms than men and that there were no gender differences in other domains such as affective symptomatology (see Table 2). However, these differences were no longer significant when p-values were corrected for multiple

Alexandre GonzĂĄlez-RodrĂguez et al.

Table 1. Socio-demographic and clinical characteristics of ARMS and FEP patients All

ARMS

Women N=74

Men N=130

p-value N

Age

28.1(9.8)

26.8(6.8)

0.301

Years of education

11.4(3.0)

11.4(3.1)

0.904

Women N=43

FEP

Men N=74

p-value N

Women N=31

Men N=56

p-value

204 26.7(9.5)

25.3(6.4)

0.395

117

30.1(9.9)

28.7(6.9)

0.508

204 11.8(3.1)

11.8(3.2)

0.943

117

10.9(2.9)

11.0(3.1)

DUP [months] DUI [months]

56.8(68.2)

54.7(63.9)

Current cannabis use

0.848

150

0.089

204

67.9(73.7)

51.0(55.1)

0.264

0.244

117

0.888

25.4(39.7) 47.9(74.5)

0.106

39.5(56.0) 58.9(73.5)

0.244

0.207

0.962

1.000

None

58(78.4%) 80(61.5%)

35(81.4%)

50(67.6%)

23(74.2%) 30(53.6%)

Rarely

3(4.1%)

11(8.5%)

1(2.3%)

3(4.1%)

2(6.5%)

8(14.3%)

Several times per month

3(4.1%)

3(2.3%)

2(4.7%)

2(2.7%)

1(3.2%)

1(1.8%)

Several times per week

4(5.4%)

15(11.5%)

1(2.3%)

10(13.5%)

3(9.7%)

5(8.9%)

Daily

6(8.1%)

21(16.2%)

4(9.3%)

9(12.2%)

2(6.5%)

12(21.4%)

Antipsychotics currently

0.542

204

0.133

117

65(87.8)

119(91.5%)

41(95.3%)

74(100%)

24(77.4%) 45(80.4%)

Yes

9(12.2%)

11(8.5%)

2(4.7%)

0(0.0%)

7(22.6%)

61(82.4%)

106(81.5%)

34(79.1%)

58(78.4%)

Antidepressants currently No Yes

1.000

204

1.000

11(19.6%)

117 27(87.1%) 48(85.7%)

13(17.6%)

24(18.5%)

9(20.9%)

16(21.6%)

4(12.9%)

8(14.3%)

BPRS Depression/Anxiety

2.6(1.0)

2.4(1.0)

0.252

199

2.6(0.9)

2.2(0.9)

0.034*

113

2.6(1.0)

2.7(1.1)

0.646

BPRS Psychosis/Thought Disturbance

2.3(1.0)

2.1(0.9)

0.145

201

1.8(0.7)

1.6(0.6)

0.229

115

3.1(0.9)

2.8(0.9)

0.139

BPRS Negative symptoms

1.8(0.9)

2.1(1.0)

0.011*

200 1.8(0.9)

2.1(1.0)

0.123

114

1.7(0.8)

2.1(1.0)

0.033*

BPRS Activation

1.6(0.7)

1.5(0.7)

0.494

200 1.4(0.7)

1.4(0.5)

0.768

114

1.9(0.7)

1.7(0.8)

0.473

BPRS total score

1.9(0.5)

0.731

200 1.7(0.5)

1.7(0.4)

0.573

114

2.2(0.5)

0.989

SANS Affective Flattening

0.7(1.0)

1.0(1.0)

0.039*

189

0.7(1.1)

1.1(1.0)

0.120

108 0.7(0.9)

1.0(1.1)

0.176

SANS Alogia

0.6(0.8)

0.9(1.1)

0.035*

189

0.6(0.8)

0.9(1.0)

0.049*

109 0.7(0.8)

0.9(1.1)

0.359

SANS Avolition-Apathy

1.7(1.2)

2.0(1.0)

0.051

191

1.7(1.0)

1.9(1.0)

0.214

110

1.7(1.4)

2.2(1.1)

0.141

SANS Asociality-Anhedonia

1.7(1.4)

2.2(1.3)

0.011*

186

1.7(1.4)

2.3(1.3)

0.049*

106 1.7(1.3)

2.1(1.3)

0.110

SANS Inattention

0.9(1.2)

1.2(1.2)

0.178

172

0.8(1.0)

1.1(1.1)

0.166

1.1(1.5)

1.3(1.3)

0.545

SANS total score

1.0(0.8)

1.4(0.9)

0.006*

191

1.0(0.8)

1.4(0.9)

0.027*

110

1.1(0.8)

1.4(0.9)

0.109

FCQ Disturbances of automated responses

0.3(0.3)

0.694

124

0.3(0.2)

0.826

0.4(0.3)

0.792

FCQ Perceptual disturbances

0.2(0.2)

0.984

125

0.1(0.1)

0.492

0.2(0.2)

0.3(0.3)

0.621

FCQ Depression

0.4(0.2)

0.4(0.3)

0.841

125

0.3(0.2)

0.668

0.4(0.2)

0.4(0.3)

0.845

FCQ Overinclusion

0.4(0.2)

04(0.3)

0.339

124

0.4(0.2)

0.3(0.2)

0.195

0.5(0.2)

0.5(0.3)

0.968

FCQ total score

0.3(0.2)

0.704

124

0.3(0.2)

0.2(0.2)

0.521

0.4(0.2)

0.4(0.3)

0.909

*P<0.05 ARMS= At-risk mental state; FEP= First episode of psychosis; DUP= Duration of untreated psychosis; DUI= Duration of untreated illness; BPRS= Brief Psychiatric Rating Scale; SANS= Scale for the Assessment of Negative symptoms; FCQ= Frankfurt Complaint Questionnaire. Values of continuous variables are given as means with standard deviations in parentheses.

testing by using the Benjamini-Hochberg adjustment (see Table 2). Furthermore, the results did not change when age, DUI, cannabis use, antipsychotic and antidepressant use were included into the models as covariates.

Discussion The aim of this study was to investigate gender differences in psychopathology in a sample of 117 ARMS individu89

Gender Differences in the Psychopathology of Emerging Psychosis

Fig. 1. Symptomology in At-Risk Mental State and First Episode Psychosis Patients in the FePsy-Study Means and 95% confidence intervals of subscales of the Brief Psychiatric Rating Scale (BPRS), Scale for the Assessment of Negative Symptoms (SANS) and Frankfurt Complaint Questionnaire (FCQ) within the groups of at-risk mental state (ARMS) and first episode psychosis (FEP) patients. All scales were z-transformed based on means and standard deviations of the total group. Women N = 74; Men N = 130.

als and 87 FEP patients. We conducted a cross-sectional analysis as part of the FePsy study (34), an open longitudinal prospective and observational study, which aims to improve the early detection of psychosis. We examined the hypothesis that gender is associated with different psychopathological patterns in at-risk mental states for psychosis and at the first onset of psychosis. In a further step, we included potentially confounding factors such as age, duration of untreated illness, cannabis use, antipsychotic and antidepressant use. As regards potentially influencing factors of psychopathology, no statistically significant gender differences were found regarding age at the time of study inclusion, years of education, antipsychotic and antidepressant use, neither within the total sample nor within the FEP and 90

ARMS groups. Within the ARMS group, our findings are in line with previous studies (26, 44) that found no significant gender differences in demographic factors and psychiatric medication intake. Within the FEP group, our results on demographic features are supported by recent findings by Bertani and colleagues (24) who carried out the PICOS study, a representative study of all FEP patients from a catchment area of nearly 3.3 million inhabitants in northeastern Italy. These authors found no statistically significant differences in educational levels between male and female FEP patients. In our study, a tendency to gender differences regarding cannabis use was shown. Within the ARMS and FEP groups, men had higher cannabis use rates compared to women. This finding is in line with the above mentioned

Alexandre González-Rodríguez et al.

Table2. Symptomatology in AtRisk Mental State and First Episode Psychosis Patients - multiple regression models with gender, patient group, cannabis use (categorical) and gender × group interaction. Coefficient

p-value p-value (corrected (uncorrected) by BH adj.2)

BPRS Depression/Anxiety

0.065

0.382

0.634

BPRS Psychosis/Thought Disturbance

0.104

0.082

0.195

BPRS Negative symptoms

-0.188

0.010**

0.103

BPRS Activation

0.042

0.420

0.634

BPRS total score

0.009

0.817

0.873

SANS Affective Flattening

-0.171

0.038*

0.151

SANS Alogia

-0.136

0.084

0.195

SANS Avolition-Apathy

-0.148

0.085

0.195

SANS Asociality-Anhedonia -0.245

0.019*

0.103

SANS Inattention

-0.123

0.219

0.438

SANS total score

-0.170

0.014*

0.103

FCQ Disturbances of automated responses

0.013

0.610

0.813

FCQ Perceptual disturbances

-0.004

0.795

0.873

FCQ Depression

0.000

0.984

FCQ Overinclusion

0.019

0.436

0.634

FCQ total score

0.004

0.819

0.873

ARMS women: N = 43; ARMS men: N = 74; FEP women: N = 31; FEP men: N = 56; Total N = 204 *p<0.05; **p<0.001 1 Negative values of the regression coefficients mean that women had lower scores on the assessed scales. 2 BH adj= Benjamini-Hochberg adjustment for multiple testing.

ABC study that found higher substance abuse in men than women in the early phases of psychoses (4, 19). There were no statistically significant DUI or DUP and gender × group interactions in our study. For this reason, gender differences in psychopathology do not seem to be influenced by the duration of untreated illness or psychosis in our ARMS and FEP samples. These findings are consistent with the PICOS study (24), which reported that DUP did not differ significantly by gender and had no confounding effect on psychopathological symptoms in FEP patients. As regards psychopathology in our study, when uncorrected for influencing factors and multiple testing, we found that male ARMS individuals had significantly higher negative symptom scores, whereas women had higher scores in depressive symptoms. Also within the FEP group, men were more likely to present negative

symptoms than women. Despite this tendency, statistically significant differences in psychopathological symptoms could not be confirmed between men and women, in both ARMS individuals and FEP patients, when p-values were corrected for multiple testing. Within the ARMS group, these findings are in agreement with Willhite and colleagues (26) who found no significant gender differences in ratings of any of the symptoms of the Scale of Prodromal Symptoms (SOPS) (45) at baseline. Within the FEP group, this is in agreement with the most representative study carried out by Häfner et al. (12), and a recent systematic review (8), which reported no gender differences in psychopathological symptoms in emerging psychoses. Also in the ABC study (19), prior to the correction for Type I error, male FEP patients had shown higher scores in loss of interest, self-neglect, slow speech, obsessional thoughts, alcohol and drug abuse. Women were more likely to present delusions of guilt and incongruity of affect. However, these gender differences were no longer present when p-values were adjusted for multiple testing (12), similar to what was shown in our study. Furthermore, Bertani et al. (24) found no significant gender differences in psychopathology assessed by the PANSS scale and subscales (positive, negative and general subscales) in FEP patients. Our findings on gender differences in psychopathology did not change when age, duration of untreated illness (DUI), cannabis use, antidepressant and antipsychotic use were included into the models as covariates. These findings are consistent with Bertani et al. (24) who controlled gender differences in FEP patients for age. To the best of our knowledge, this is the first study to examine gender differences in psychopathology concomitantly in both ARMS and FEP patients by using both observer-rated scales and a self-report scale, and including age, DUI, cannabis, antidepressant and antipsychotic use as potential confounders together. So far there are only few studies on gender differences in psychopathology of ARMS individuals and results of studies investigating FEP patients are inconsistent. This might be due to several reasons. Methodological differences between studies such as different study designs, and a lack of a systematic and homogenous assessment of psychopathological symptoms could have contributed to the inconsistencies. Many studies have recruited patients from chronic populations, inpatient units or private clinics, that cannot be considered a representative population of a catchment area. Furthermore, the sample sizes in many studies were small. Häfner et al. (4) were the first 91

Gender Differences in the Psychopathology of Emerging Psychosis

to specifically control selection and diagnostic bias in the ABC study. Patients included in our study also seem to be fairly representative for our catchment area as our early detection clinic FePsy is the only one in our area. A further strength of our study is that we investigated gender differences in psychopathological symptoms with two well established observer-rated scales (BPRS and SANS) (32, 35) and a self-report scale (FCQ) (36). A limitation is that the FCQ scale could not be obtained in half of the patients, which limited the statistical power. In conclusion, the present study could not confirm significant gender differences in psychopathology in ARMS individuals or FEP patients. Nevertheless, further studies to examine gender differences in ARMS and FEP patients in larger populations controlling for important confounding factors such as age, medication and cannabis use are warranted. Contributions Alexandre González-Rodríguez was involved in the analysis and interpretation of data, and wrote the first draft of the manuscript. Erich Studerus supported statistical analyses and reviewed the paper. Charlotte Rapp, Andrea Spitz, Hilal Bugra, Jacqueline Aston and Stefan Borgwardt critically revised the manuscript. Anita Riecher-Rössler designed the study, supervised the whole project and revised the paper. References 1. Lewine RRJ. Gender and schizophrenia. In: Nasrallah HA, editor. Handbook of schizophrenia. Amsterdam, New York, Oxford: Elsevier; 1988: pp. 379-397. 2. Bardenstein KK, McGlashan TH. Gender differences in affective, schizoaffective, and schizophrenic disorders: A review. Schizophr Res 1990;3:159-172. 3. Angermeyer M, Kühnz L. Gender differences in age at onset of Schizophrenia. Eur Arch Psychiatr Neurol Sci 1988;237:351-364. 4. Häfner H, Riecher A, Maurer K, Fätkenheuer B, Löffler W, an der Heiden W, et al. Sex differences in schizophrenic diseases. Fortschr Neurol Psychiatr 1991;59:343-360. 5. Riecher-Rössler A, Häfner H. Gender aspects in schizophrenia: Bridging the border between social and biological psychiatry. Acta Psychiatr Scand Suppl 2000;407:58-62. 6. Abel KM, Drake R, Goldstein JM. Sex differences in schizophrenia. Int Rev Psychiatry 2010;22:417-428. 7. Leung A, Chue P. Sex differences in schizophrenia, a review of the literature. Acta Psychiatr Scand Suppl 2000;401:3-38. 8. Ochoa S, Usall J, Cobo J, Labad X, Kulkarni J. Gender differences in schizophrenia and first-episode psychosis: A comprehensive literature review. Schizophr Res Treatment 2012;916198:doi 10.1155/2012/916198. 9. Riecher-Rössler A, Kulkarni J. Estrogens and gonadal function in schizophrenia and related psychoses. Curr Top Behav Neurosci 2011;8:155-171.

10. Riecher-Rössler A, Häfner H. Schizophrenia and oestrogens - is there an association? Eur Arch Psychiatry Clin Neurosci 1993;242:323-328. 11. Goldstein JM. Sampling biases in studies of gender and schizophrenia - a reply. Schizophr Bull 1993;19:9-14. 12. Häfner H, Riecher A, Fatkenheuer B, Hambrecht M, Löffler W, Heiden Wad, et al. Sex differences in schizophrenia. Psychiatria Fennica 1991;22:123-156. 13. Riecher-Rössler A, Pflüger M, Borgwardt S. Schizophrenia in women. In: Kohen D, editor. Women and Mental Health. New York: Oxford University, 2010. 14. Addington D, Addington J, Patten S. Gender and affect in schizophrenia. Can J Psychiatry 1996;41:265-268. 15. Szymanski S, Lieberman JA, Alvir JM, Mayerhoff D, Loebel A, Geisler S, et al. Gender differences in onset of illness, treatment response, course, and biologic indexes in first-episode schizophrenic patients. Am J Psychiatry 1995;152:698-703. 16. Barajas A, Banos I, Ochoa S. Age of onset of a first psychotic episode: Are there any clinical differences between men and women? Psiquiatria Biologica 2007;14:136-141. 17. Häfner H, Maurer K, Löffler W, Riecher-Rössler A. The influence of age and sex on the onset and early course of schizophrenia. Br J Psychiatry 1993;162:80-86. 18. Häfner H, Riecher-Rössler A, An Der Heiden W, Maurer K, Fätkenheuer B, Löffler W. Generating and testing a causal explanation of the gender difference in age at first onset of schizophrenia. Psychol Med 1993;23:925-940. 19. Häfner H, Maurer K, Löffler W, an der Heiden W, Munk-Jørgensen P, Hambrecht M, et al. The ABC Schizophrenia Study: A preliminary overview of the results. Soc Psychiatry Psychiatr Epidemiol 1998;33:380-386. 20. Salokangas RKR, Stengård E. Gender and short-term outcome in schizophrenia. Schizophr Res 1990;3:333-345. 21. Thorup A, Petersen L, Jeppesen P, Ohlenschlaeger J, Christensen T, Krarup G, et al. Gender differences in young adults with first-episode schizophrenia spectrum disorders at baseline in the Danish OPUS study. J Nerv Ment Dis 2007;195:396-405. 22. Koster A, Lajer M, Lindhardt A, Rosenbaum B. Gender differences in first episode psychosis. Soc Psychiatry Psychiatr Epidemiol 2008;43:940-946. 23. Cotton SM, Lambert M, Schimmelmann BG, Foley DL, Morley KI, McGorry PD, et al. Gender differences in premorbid, entry, treatment, and outcome characteristics in a treated epidemiological sample of 661 patients with first episode psychosis. Schizophr Res 2009;114:17-24. 24. Bertani M, Lasalvia A, Bonetto C, Tosato S, Cristofalo D, Bissoli S, et al. The influence of gender on clinical and social characteristics of patients at psychosis onset: A report from the Psychosis Incident Cohort Outcome Study (PICOS). Psychol Med 2012;42:769-780. 25. Koster A, Lajer M, Lindhardt A, Rosenbaum B. Gender differences in first episode psychosis. Soc Psychiat Epidemiol 2008;43:940-946. 26. Willhite RK, Niendam TA, Bearden CE, Zinberg J, O'Brien MP, Cannon TD. Gender differences in symptoms, functioning and social support in patients at ultra-high risk for developing a psychotic disorder. Schizophr Res 2008;104:237-245. 27. Lemos-Giraldez S, Vallina-Fernandez O, Fernandez-Iglesias P, Vallejo-Seco G, Fonseca-Pedrero E, Paino-Pineiro M, et al. Symptomatic and functional outcome in youth at ultra-high risk for psychosis: A longitudinal study. Schizophr Res 2009;115:121-129. 28. Ziermans TB, Schothorst PF, Sprong M, van Engeland H. Transition and remission in adolescents at ultra-high risk for psychosis. Schizophr Res 2011;126:58-64. 29. Riecher-Rössler A, Aston J, Ventura J, Merlo M, Borgwardt S, Gschwandtner U, et al. The Basel Screening Instrument for Psychosis (BSIP): development, structure, reliability and validity. Fortschr Neurol Psychiatr 2008;76:207-216. 30. Riecher-Rössler A, Pflueger MO, Aston J, Borgwardt SJ, Brewer WJ, Gschwandtner U, et al. Efficacy of using cognitive status in predicting psychosis: A 7-year follow-up. Biol Psychiatry 2009;66:1023-1030.

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31. Yung AR, Phillips LJ, McGorry PD, McFarlane CA, Francey S, Harrigan S, et al. Prediction of psychosis. A step towards indicated prevention of schizophrenia. Br J Psychiatry Suppl 1998;172:14-20. 32. Lukoff D, Nuechterlein KH, Ventura J. Manual for the expanded brief psychiatric rating scale. Schizophr Bull 1986;12:594-602. 33. Ventura J, Lukoff D, Nuechterlein KH, Liberman RP, Green M, Shaner A. Training and quality assurance with the brief psychiatric rating scale: "The Drift Busters"; Appendix 1 The Brief Psychiatric Rating Scale (expanded version). Int J Meth Psychiatric Res 1993;3:221-224. 34. Riecher-Rössler A, Gschwandtner U, Aston J, Borgwardt S, Drewe M, Fuhr P, et al. The Basel early-detection-of-psychosis (FEPSY)-study design and preliminary results. Acta Psychiatr Scand 2007;115:114-125. 35. Andreasen NC. The Scale for the Assessment of Negative Symptoms (SANS): Conceptual and theoretical foundations. Br J Psychiatry Suppl 1989;7:49-58. 36. Süllwold L. Manual zum Frankfurter Beschwerde-Fragebogen (FBF). Berlin: Springer, 1991. 37. Velligan D, Prihoda T, Dennehy E, Biggs M, Shores-Wilson K, Crismon ML, et al. Brief psychiatric rating scale expanded version: How do new items affect factor structure? Psychiatry Res 2005;135:217-228. 38. Mass R, Haasen C, Krausz M. Dimensional structure and diagnostic

specificity of the Frankfurt Complaint Questionnaire. Eur Psychiatry 1997;12:117-123. 39. Schultze-Lutter F. Subjective symptoms of schizophrenia in research and the clinic: The basic symptom concept. Schizophr Bull 2009;35:5-8. 40. Loas G, Yon V, Brien D. Dimensional structure of the Frankfurt Complaint Questionnaire. Compr Psychiatry 2002;43:397-403. 41. Süllwold L, Huber G. Frankfurter Beschwerde-Fragebogen (FBF). Schizophrene Basisstörungen. Berlin: Springer, 1986: pp. 1-36. 42. Ackermann T. Basler Interview zur Früherkennung von Psychosen - BIP: Interrater-Reliabilität, Struktur und Validität. Faculty of Psychology, University of Basel. [Unpublished Master's Thesis]. 2012. 43. Benjamini Y, Hochberg Y. Controlling the false discovery rate - a practical and powerful approach to multiple testing. J Royal Statistical Society Series B-Methodological 1995;57:289-300. 44. Amminger GP, Leicester S, Yung AR, Phillips LJ, Berger GE, Francey SM, et al. Early-onset of symptoms predicts conversion to non-affective psychosis in ultra-high risk individuals. Schizophr Res 2006;84:67-76. 45. Miller TJ, McGlashan TH, Woods SW, Stein K, Driesen N, Corcoran CM, et al. Symptom assessment in schizophrenic prodromal states. Psychiatr Q 1999;70:273-287.

Isr J Psychiatry Relat Sci - Vol. 51 - No 2 (2014)

Antidepressant Use in Pregnancy: An Evaluation of Adverse Outcomes Excluding Malformations Laura Lorenzo, MD,1 and Adrienne Einarson, RN2 1

Psinapsys Psychiatric Private Center, Buenos Aires, Argentina The Motherisk Program, The Hospital for Sick Children, Toronto, Canada

Abstract Background: To date, many studies have been published regarding the safety of antidepressant use in pregnancy. However, most have been regarding a possible association with major malformations and there have been relatively few studies that have examined other infant outcomes specifically.

required, as untreated depression is also associated with adverse effects on the infant. However, further research needs to be conducted where it is possible to control for maternal depression, in order to evaluate whether these adverse events are due to the underlying maternal illness, the antidepressant, or possibly a combination of both.

Objective: To evaluate possible adverse effects of antidepressant use in pregnancy. Methods: We searched the literature, using Medline, PUBMED, Embase, and Reprotox , and retrieved key articles and reviews of the topic. We examined all outcomes with the exception of major/minor malformations. Results: We did not find an overall increased risk associated with lower mean birthweight, small for gestational age or long-term neurodevelopmental adverse outcomes. However, there does appear to be a significantly increased risk for spontaneous abortion, preterm birth and low birthweight less than 2,500gm. In addition, a possible increased risk for Persistent Pulmonary Hypertension of the Newborn (PPHN) and evidence of Poor Neonatal Adaptation Syndrome (PNAS) following use in late pregnancy. All of the observed risks were of a very low magnitude and the clinical significance of these results is unknown. Conclusions: This information should not preclude a pregnant women from being treated for depression if

Adrienne Einarson/The Motherisk Program is a recipient of an unrestricted educational grant from Eli Lilly Inc. Canada, to examine the safety of duloxetine (CymbaltaÂŽ) during pregnancy. Laura Lorenzo has no possible conflicts of interest.

Background Women are twice as likely than men during their lifetime to experience both anxiety and depression, most of which occur during their years of reproductivity (1). During pregnancy, the period prevalence rate for a major depressive episode is 18.4% (2). A study from the National Birth Defects Prevention from ten U.S. states (3), documented that among 6,582 mothers included in the study, 298 (4.5%) reported use of an antidepressant during pregnancy. The authors reported that antidepressant use at any time during pregnancy had increased from 2.5% in 1998 to 8.1% in 2005 and is probably higher since this data was compiled, as overall use of antidepressants in the general population has increased exponentially (4). Although these numbers are from the U.S., it likely reflects prevalence throughout the world, as the World Health Organisation ranks depression as the leading cause of disability worldwide and estimates an effect on approximately 120 million individuals (5). Due to fears of teratogenicity, it is not an unusual occurrence for women to discontinue their medication, especially psychotropic drugs, upon diagnosis of pregnancy. Data from a large U.K. database of primary care information

Address for Correspondence: Adrienne Einarson, RN, The Motherisk Program, The Hospital for Sick Children, 555 University Avenue, Toronto ON M5G 1X8, Canada â&#x20AC;&#x2020; einarson@sickkids.ca

Laura Lorenzo and Adrienne Einarson

reported that although antidepressants prescribing in pregnancy increased almost 4-fold between 1992 and 2006, pregnancy was a major determinant for antidepressants discontinuation (6). It should be noted that pregnant women who discontinue their medication are exposed to possible relapse of illness. In one study (7), of 36 women who were contacted following this decision, 26 (70.3%) of the women reported physical and psychological adverse effects, with 11 reporting psychological effects only, 11 reported suicidal ideation and four were admitted to hospital. Prior to discontinuing their antidepressant, all of the women were euthymic. Another group (8) reported that among 82/201 depressed women who continued to take their antidepressant throughout pregnancy, 21 (26%) relapsed, compared with 44 (68%) of the 65 women who discontinued medication. Untreated maternal depression Few studies have been conducted specifically to examine the risk of untreated maternal depression and the rates of preterm birth. A recent metanalysis (9) reported that depression during pregnancy was associated with modest significant risks of preterm birth (RR=1.13; 95% CI, 1.061.21) and low birth weight (RR=1.18; 95% CI, 1.07-1.30), although possible effects of antidepressants could not be excluded. Another review (10) did focus exclusively on non-medicated antenatal depression and offspring outcomes. Despite the heterogeneity of outcome measures, findings from this review suggested that prenatal depression negatively impacted a developing fetus, with implications extending into childhood (i.e., shorter length of gestation, fetal growth restriction and/or lower birth weight). In addition, newborns of depressed mothers showed a biochemical/ physiological profile that mimics their mothersâ&#x20AC;&#x2122; prenatal biochemical/physiological profile including elevated cortisol, lower levels of dopamine and serotonin, greater relative right frontal EEG activation and lower vagal tone (11). These findings were thought to reflect more general developmental issues that may impact the individual throughout adulthood. Untreated depression during pregnancy may also cause women to use other substances, that can adversely affect pregnancy outcomes which was confirmed in a recent study, where researchers followed 195 women throughout pregnancy to evaluate the use of medicinal agents and habit-forming substances, and prenatal depression was associated with decreased prenatal vitamin compliance and increased use of hypnotics and tobacco (12). Regarding

obstetric outcomes, another study reported that depression in late pregnancy was associated with increased risk of epidural analgesia (33% vs. 19%, p =.01, adjusted RR = 2.56, 95% CI 1.24-5.30), caesarean sections and instrumental vaginal deliveries (39% vs. 27%, p =.02, adjusted RR = 2.28, 95% CI 1.15-4.53), as well as more admission to neonatal intensive care units (24% vs. 19%, p =.03, adjusted RR = 2.18, 95% CI 1.02-4.66) (13). The impact of antidepressant treatment on pregnancy outcomes has been explored mainly focused on major malformations. Other outcomes, like fetal growth, spontaneous abortion, perinatal events or infant neurodevelopment, have received relatively less attention. However, these outcomes could be affected by untreated depression. Hence, the following is a summary of outcomes following depression in pregnancy, treated pharmacologically with antidepressants. Fetal growth The growth of the fetus provides information about the course of pregnancy and may anticipate the health aspects of postnatal development. Methods to estimate fetal growth, birth weight, and timing of delivery are outcomes frequently used in epidemiological studies (14). A child born weighing less than 2,500 grams is considered low birthweight, and if the birth occurred prior to 37 weeks gestation, both outcomes involve an increased risk of morbidity and mortality of the newborn but do not represent different endpoints. A low-birthweight baby can be born full term, and a premature baby may not be low birth weight. A measure used to combine these aspects is intrauterine growth retardation, known as â&#x20AC;&#x153;small for gestational ageâ&#x20AC;? (SGA) and is a baby whose birth weight is below the 10th percentile, based on birth weight reference curves and stratified by infant gender and gestational age (15). The impact of antidepressants on fetal growth has been evaluated (16-37) with a diversity of outcome measures. Using different data sources, and with different results, most of the studies lacked an adequate control group of women with untreated depression. Also lacking in many of the studies is antidepressant dose, duration of exposure and the severity of depression. In summary, despite heterogeneity of outcomes, we did not find an overall increased risk associated with lower birth weight or small for gestational age. However, there does appear to be a significantly increased risk for preterm birth and infants born less than 2,500gm (Table 1). 95

Antidepressant Use in Pregnancy: An Evaluation of Adverse Outcomes Excluding Malformations

Table 1. Fetal Growth First author and year

Drugs studied

Study design

Chambers 199616

Fluoxetine

Prospective cohort

Exposed n

Comparison group n

Source of data

Primary outcome

228

254

TIS California

Birth size, gestational age

Results: Higher rates of premature delivery (RR 4.8; 95% CI 1.1-20.8) and lower birth weight (188 gr. ;p .02) with late pregnancy exposure Simon 200217

TCAs SSRIs

Prospective cohort

TCAs = 209 SSRIs = 185

Matched controls for each exposure (209; 185)

Prepaid health plan (USA)

gestational age, birth weight, head circumference at birth

Results: No difference in any outcome for TCAs exposed vs. non-exposed. For SSRIs exposed, decreased gestational age (≤ 36 weeks, OR 4.38 [1.57-12.22]) Oberlander 200618

SSRIs

Prospective cohort

SSRIs prescriptions = 1451

Depressed without SSRIs prescriptions = 14234 Non-depressed controls = 92192

Administrative database

birth weight <10th percentile for gestational age, gestational age <37 weeks

Results: infants of mothers with SSRIs prescriptions had more incidence of birth weight <10th percentile for gestational age (p .02) than those of mothers with untreated depression (propensity score matched). No differences in other outcomes Davis 200719

SSRIs, TCAs and other AD

Retrospective cohort

SSRIs = 1047 TCAs = 221 Other AD = 173

Control = 49667

Administrative database

Perinatal adverse events

Results: Increased risk of preterm delivery for SSRIs exposed (RR 1.45; 95%CI 1.25, 1.68) and TCAs exposed (RR 1.67; 95%CI 1.25, 2.22). Suri 200720

SSRIs, TCAs and other AD

Prospective cohort

Depressed mothers using AD = 49 (group 1)

Depressed mothers not using AD = 22 (group 2) Healthy controls = 19 (group 3)

Outpatients of UCLA Women’s Life Center clinic

gestational age at birth, birth weight

Results: Groups 1, 2 and 3 differed in gestational age at birth (38.5 weeks, 39.4 weeks, 39.7 weeks, respectively; p .004) and rates of preterm birth (14.3%, 0%, 5.3%, respectively; p .05). No differences found in birth weight. Outcomes not affected by pregnancy depression. Oberlander 200821

SRIs

Prospective case-control

Early exposure = 1575

Late exposure = 1925

Administrative database

birth weight <10th percentile for gestational age, gestational age <37 weeks

Results: No significant differences between early and late exposure after propensity-score matching. Only low birth weight in the limit of significance (p .05). (30gm difference between groups) Toh 200922

SSRIs Non-SSRIs

Retrospective cohort

SSRIs = 192 (first trimester = 106; beyond first trimester = 86) non-SSRIs = 59

5710 unexposed to AD

Slone Birth Defects Center Epidemiological Study

Preterm delivery SGA

Results: No greater risk of preterm delivery (OR 1.12 [0.64-1.95]) in SSRIs exposed. Compared to non exposed, there were more premature births in non-SSRI exposed (OR, 2.23; 95% CI 1.02-4.88) and more SGA offsprings among women who maintained SSRIs beyond the first trimester (OR, 3.0; 95% CI, 1.7-5.5). Maschi 200823

SSRIs TCAs

Prospective cohort

Paroxetine = 58 Fluoxetine = 32 Amitriptyline = 26

Non exposed = 1200

Drug and Health Information Centre, Italy

Neonatal adverse events and Special Care Unit admission rate

Results: Exposed women had more premature births than unexposed (OR 2.31 95% CI 1.14-4.63). Adjusting for time of exposure, the association remained significant only in the group who had received antidepressants throughout pregnancy Lund 200924

SSRIs alone or in combination

Prospective cohort

SSRIs = 329

Positive psychiatric history/ No SSRI Use = 4902 No Psychiatric History = 51 770

Aarhus Birth Cohort (Denmark)

Gestational age Preterm birth Birth weight Head circumference

Results: Mean gestational age was 4.5 days (95% CI, −6.2 −2.8) shorter in children born to SSRI exposed mothers vs. non exposed, and 3.8 days (95% CI, −5.6 −2.0) shorter vs. women with history of psychiatric illness. Risk of preterm birth was twice that of women of the other two groups (vs. women without history of psychiatric illness: adjusted OR, 2.02; [95%CI, 1.29-3.16]; vs. women with a history of psychiatric illness: OR, 2.05 [95% CI, 1. 28-3.31]). No differences in head circumference. Einarson 200925

SSRIs Other AD

Prospective cohort

928

TIS Motherisk Program

Fetal growth

Results: 82 (8.8%) preterm deliveries in the antidepressant group and 50 (5.4%) in the comparison group. OR: 1.7 (95% CI: 1.18–2.45). and 89 (9.6%) SGA in the exposed group and 76 (8.2%) in the comparison group; OR: 1.19 (95% CI:0.86–1.64). Mean birth weight in the antidepressant group was 3,449±7591 g and 3,455±7515 g in the comparison group (P=.8)

Laura Lorenzo and Adrienne Einarson

First author and year

Drugs studied

Study design

Wisner 200926

SRIs

Prospective cohort

Exposed n

Comparison group n

Source of data

Primary outcome

Continuous SSRI exposure = 48 Partial SSRI exposure = 23

No SSRI, no depression = 131 Continuous depression, no SSRI = 14 Partial depression, no SSRI =22

Outpatients

infant birth weight and preterm birth

Results: Continuous SSRI and continuous depression groups had a 20% increase in premature births compared with the others three groups (partially exposed and control). Continuos depression RR 3.71 [0.98–14.13]). Continuous SSRIs RR 5.43 [1.98–14.13]. Association between continued use of SSRIs and preterm delivery was strengthened when adjusting for age and race Lewis 201027

SSRIs SNRIs

Prospective cohort

Obstetrical clinic in Melbourne

gestational age at birth, neonatal growth outcomes at birth and then at 1 month postpartum

Results: Children of mothers exposed to antidepressants were more likely to be born prematurely (mean gestational age 38.86 vs 39.86; p .005) and were of shorter length (49.30 vs. 51.44 cm; p .001) and lower birth weight (3273 vs. 3671 gr.; p .010) than children of non-exposed mothers. Reis 201028

TCAs SSRIs SNRIs

Prospective

14821 women and 15017 neonates (3 groups: early, late and both)

1 062 190 women with 1 236 053 infants in the population

Swedish Birth Registry

maternal delivery diagnoses, infant neonatal diagnoses

Results: Increased preterm birth for all exposures (TCAs OR 2.36 [1.89–2.94]; SSRIs OR 1.46 [1.31–1.63]; SNRIs OR 1.98 [1.49–2.63]). SNRI exposure showed a higher risk for low birthweight than SSRI and a significant SGA effect, not present in the other two groups. Ramos 201029

SSRIs TCAs other ADs

Casecontrol

Cases = 404 pregnancy sub analysis cases = 128.

Controls = 2302 Sub analysis controls = 810

3 administrative databases (Canada) Sub analysis with questionnaire about potential confounders

SGA

Results: prescriptions of ADs other than SSRI and co-administration of two or more classes of ADs were associated to SGA only during 2nd trimester (aRR 2.25 [1.30–3.92]; aRR 3.48 [1.56–7.75] respectively). In sub analysis of questionnaire respondents associations remained significant (aRR 2.41 [1.07-5.43]; aRR 3.28 [1.28-8.45] respectively). Roca 201130

SSRIs

Casecontrol

Women with depressive or anxiety disorder = 84

Matched controls = 168

General teaching hospital

Obstetrical and neonatal outcomes

Results: Rates for preterm birth were higher in the exposed group (OR=3.44, 95% CI=1.30-9.11). Following stratification, exposure to a high-dose was associated with lower gestational age (p=.009) and higher rates of prematurity (OR=5.07, 95% CI=1.34-19.23). KliegerGrossmann 201231

Escitalopram SSRIs Other ADs

Prospective cohort

Escitalopram = 213

Other AD = 212 Nonteratogens = 212

TIS Motherisk Program Swiss TIS Florence TIS

pregnancy outcomes

Results: Higher rate of low birth weight (<2500 g) in the escitalopram group (9.9%) compared with those exposed to other ADs (3.6%, P = .038) and nonteratogens (2.1%, P = .003). No differences in other outcomes Nordeng 201232

TCAs SSRIs

Prospective cohort

Pregnancy exposed = 699

Non-exposed = 61648 Prior pregnancy exposed = 1048

Norwegian Mother and Child Cohort Study. Medical Birth Registry of Norway

Birth weight Preterm birth

Results: Adjusting for maternal level of depression and a wide range of other potentially confounding factors, exposure to antidepressants during pregnancy was not associated with increased risk of preterm birth (adjusted OR, 1.21; 95% CI, 0.87-1.69) or low birth weight (adjusted OR, 0.62; 95% CI, 0.33-1.16). Grzeskowiak 201233

SSRIs

Retrospective cohort

With SSRIs prescriptions and psychiatric illness = 221

No prescriptions, no psychiatric illness = 32004 No prescriptions, psychiatric illness = 1566

Administrative databases (Women’s and Children’s Health Network, South Australia)

preterm delivery, low birth weight, small-for-gestational age

Results: Infants of women with pregnancy prescription of SSRIs had a twice increased risk of preterm delivery (aOR, 2.68; 95% CI, 1.83-3.93), low birth weight (aOR, 2.26; 95% CI, 1.31-3.91), but not small-for-gestational age (aOR, 1.13; 95% CI, 0.65-1.94) compared with infants of mothers with psychiatric illness but no SSRI use during pregnancy. Data collection of women with psychiatric illness couldn’t account for severity. So, confounding by maternal illness cannot be ruled out

Antidepressant Use in Pregnancy: An Evaluation of Adverse Outcomes Excluding Malformations

First author and year

Drugs studied

Study design

Hayes 201234

SSRIs TCAs Other ADs

Retrospective cohort

Exposed n

Comparison group n

Source of data

Primary outcome

Depressed with 1-2 prescriptions = 10,700 Depressed >3 prescriptions = 6196

Not classified as depressed = 195,079 Depressed, no prescriptions = 16,901

Administrative database (TennesseMedicaid)

Pregnancy outcomes

Results: Most women (75%) discontinued prescriptions before or during first trimester. Filling 1, 2, and 3 antidepressant prescriptions during the second trimester was associated with shortened gestational age by 1.7 (95% CI 1.2–2.3), 3.7 (95% CI,2.8–4.6), and 4.9 (95% CI, 3.9 –5.8) days, when controlled for potential confounders including diagnosis of previous depression, comorbid psychiatric diagnosis and multiple psychiatric medications. Yonkers 201235

SRIs

Prospective cohort

Depressive episode and use of SRIs = 55 No depressive episode but use of SSRI = 238

No depressive episode no SRI use (control) = 2194 Depressive episode and not use of SRI = 167

Obstetrical practice and hospital-based clinics

Preterm birth Early preterm birth (< 34 completed weeks’ gestation) Late preterm birth (34-36 completed weeks’ gestation)

Results: Using SSRIs with or without depression in pregnancy was not associated with elevated risk of preterm birth in general. The risk for early preterm birth) was similar for all the groups. After adjustment, significant risk for late preterm birth emerge in both groups exposed to SSRIs, with (OR 3.14; 95%CI 1.5–6.8) or without (OR 1.93; 95% CI 1.2–3.2) depression in pregnancy but not for depression only exposure (OR 1.34, 95% CI 0.71–2.5). El Marroun 201236

SSRIs

Population-based Prospective cohort

Women using SSRIs = 99

No SSRIs, no depression (control) = 7027 No SSRIs and clinically relevant depressive symptoms = 570

Generation R Study (Netherlands)

Birth outcomes Fetal body and head growth

Results: SSRI-exposed children had higher risk for preterm birth (OR 2.14 [1.08-4.25]). Children of mothers with depressive symptoms not using SSRIs showed a slower rate of fetal weight gain (−4.4 g/week; p .001) and head growth (−0.08 mm/wk; p .003), while children in the SSRI-using group did not. Both groups showed a reduction in fetal head circumference, more pronounced in SSRIs exposed children (−0.18 mm/week; p .003). Dubnov-Raz 201237

SRIs

Prospective cohort

Sheba Medical Center

growth parameters

Results: No differences regarding bone density, but infants exposed to SSRIs had a smaller head circumference (33.8±1.2 vs 34.4±1.1 cm, p=0.005). ADs: antidepressants; SSRIs: selective serotonine reuptake inhibitors; SRIs: serotonine reuptake inhibitors (includes SSRIs and venlafaxine); Other ADs: other antidepressants except SSRIs and tricyclics; TCAs; tricyclics antidepressants

Spontaneous abortion Spontaneous abortion is a common adverse pregnancy outcome, estimated to occur in up to 15% of all viable pregnancies, but is difficult to estimate the precise incidence, as it is usually unknown when conception occurred. For example, early pregnancy losses are more frequent but could be misidentified as a delayed menstrual period if a woman is unaware of being pregnant (14). Recently, two studies designed specifically to evaluate this outcome (38, 39) found an increased risk of spontaneous abortion in those women who received antidepressants. Despite differing methodology, results were similar in both studies. However, the major limitation is that neither group was able to effectively control for maternal depression. Former studies included miscarriage as secondary outcome (40-45) and found no increased risk except for bupropion (43) (Table 2). In summarizing the data on spontaneous abortion, there does appear to be a small but significantly increased risk for spontaneous abortion associated with antidepressant use in early pregnancy. 98

Poor neonatal adaptation syndrome (PNAS) Exposure to an SSRI during pregnancy has been associated with neonatal symptoms including: jitteriness, difficulty feeding, respiratory problems, low blood sugar, and neurological symptoms (sleep disturbances and increased motor activity) (46) and it was unclear if this was the consequence of withdrawal or toxicity. In 2005, a report (47) documented an association between third trimester SSRIs exposure and neonatal signs described as “withdrawal syndrome” (convulsions, irritability, abnormal crying and tremor). Furthermore, gastrointestinal and neurological signs could also represent withdrawal, as they are similar to those described in adults following discontinuation of SSRIs treatment, while respiratory difficulties appear to be related with toxicity as observed in animal models (48). Subsequently, further studies have since been published reporting on varying degrees of these symptoms (49-57) (Table 3). In summarizing the data regarding this outcome, the occurrence of these symptoms has been reported to be from 10-30%, with no apparent dose response. Most importantly, the symptoms resolve within a week with no apparent long term adverse effects.

Laura Lorenzo and Adrienne Einarson

Table 2. Spontaneous Abortion (SA) First author and year

Drugs studied

study design

Exposed n

Comparison group n

Source of data

Primary outcome

Pastuzsak 199340

Fluoxetine TCAs

Prospective cohort

Fluoxetine = 128 TCAs = 74

Controls = 128

TIS Motherisk Program

Malformations, miscarriage

Results: Fluoxetine exposed had a nonsignificant risk for miscarriage when compared with women exposed to nonteratogens (RR 1.9 [0.92 -3.92]). The rate of miscarriages in the fluoxetine group was comparable with the TCAs group (13.5% and 12.2% vs 6.8% in the nonteratogens). Kulin 199841

SSRIs

Prospective cohort

267

TIS Canada and USA

Malformations miscarriage

Venlafaxine = 150

SSRIs = 150 Nonteratogens controls = 150

TIS Motherisk

Malformations, miscarriage

TIS Motherisk

Pregnancy outcomes

Results: No differences in miscarriage Einarson 200142

Venlafaxine SSRIs

Prospective case-control

Results: No differences in miscarriage (12% exposed versus 7% non-exposed, p .24) Chun-Fan-Chan 200543

Bupropion Other ADs

Prospective cohort

Bupropion = 91

Other ADs = 89 Nonteratogens controls = 89

Results: Bupropion exposure had more miscarriages compared to non teratogenic exposures (14.7% vs. 4.5%, p 0.009), but similar to other AD Sivojelezova 200544

Citalopram

Prospective cohort

132

Other ADs = 132 Nonteratogen controls = 132

TIS Motherisk Program

Birth outcomes

TIS from Canada, Israel, Italy, UK and Australia

Abortions, pregnancy outcomes

TIS Motherisk Program

Spontaneous abortion

Results: No differences in miscarriage: 11% vs 10% for other SSRIs and 10% for non teratogenic exposure Djulus 200645

Mirtazapine

Prospective case-control

Mirtazapine exposed = 104

Other AD = 104 Nonteratogens controls = 104

Results: No significant differences in miscarriages (19% vs 17% other AD and 11% for controls) Einarson 200938

SSRIs SNRIs Other ADs

Prospective cohort

937

Results: Increased risk of SA in those women who received antidepressants (RR 1.63 95% CI 1.24-2.14), representing a rate of 13% in exposed vs. 8% in the unexposed Nakhai-Pour 201039

SSRIs SNRIs TCAs Other ADs

Nested case-control

Cases = 5124

Controls = 51240

Administrative database (Canada)

Spontaneous abortion

Results: Out of 5124 cases of SA, 5.5% of the women had at least one prescription of antidepressants during pregnancy, compared with 1401 (2.7%) of controls (OR 1.68 95% CI 1.38-2.06). SSRIs: selective serotonine reuptake inhibitors; SNRIs: serotonine and noradrenaline reuptake inhibitors; Other ADs: other antidepressants except SSRIs and tricyclics; TCAs; tricyclics antidepressants

Persistent pulmonary hypertension (PPHN) Persistent pulmonary hypertension of the newborn is defined as a failure of the normal relaxation in the fetal pulmonary vascular bed during the circulatory transition. This occurs shortly after birth, with varying degrees of severity, in approximately 2-6 cases per 1,000 live births (58). It is a syndrome characterized by marked pulmonary hypertension that causes right-to-left extra-pulmonary shunting of blood (59). There have been six published studies reporting on the possible association with an increased risk for PPHN associated with antidepressant use in late pregnancy (28, 60-64) (Table 4). However, because of small sample sizes and quality issues in studies, the absolute risk cannot be determined, although it is probably less than 1%. It also appears that other factors such as performing a caesarean section, may play a larger role than SSRI use (60).

QTc prolongation in the newborn Prolongation of the QT interval is a risk factor for malignant arrhythmias and sudden death with some researchers examining the possibility that unknown, symptom free and untreated QTc prolongation in the newborn may result in the sudden death of a seemingly healthy adolescent (65). There is only one study reporting on this outcome, where researchers performed electrocardiograms on 52 newborn infants exposed to SSRIs in utero as well as 52 healthy control newborns and the two groups were matched for gestational age (66). The mean QTc was significantly longer in the group of newborns exposed to antidepressants as compared with control subjects (409 +/- 42 vs 392 +/- 29 milliseconds). Five (10%) newborns exposed to SSRIs had a markedly prolonged QTc interval (>460 milliseconds) compared with none of the unexposed newborns. However, all of the 99

Antidepressant Use in Pregnancy: An Evaluation of Adverse Outcomes Excluding Malformations

Table 3. Poor Neonatal Adaptation Syndrome (PNAS) First author and year

Drugs studied

Study design

Chambers 199616

Fluoxetine

Prospective cohort

Exposed n

Comparison group n

Source of data

Primary outcome

228

254

TIS California

Neonatal adaptation

Results: Third trimester had higher rates admission to special-care nurseries (RR 2.6; 95% CI 1.1-6.9), and poor neonatal adaptation, including respiratory difficulty, cyanosis on feeding, and jitteriness (RR 8.7; 95% CI 2.9-26.6) Costei 200249

Paroxetine

Prospective cohort

3rd trimester exposure = 55

1st/2nd trimester exposure = 27 Nonteratogens controls = 27

TIS Motherisk Program

Discontinuation syndrome in neonates

Results: Neonatal complications (respiratory distress, hypoglycemia, jaundice) more frequent in third trimester exposed (p .03). Only third trimester exposure associated with neonatal distress (OR 9.53 [1.14-79.1]) Casper 200350

SSRIs

Prospective cohort

Children of depressed mothers using SSRIs = 31

Children of depressed mothers not using SSRIs = 13

Women’s Wellness Clinic

Bayley Scales of Infant Development Birth outcomes

Results: No significant differences on most birth outcomes and follow-up measures. SSRIs exposed infants had low 5 min APGAR score (p<.00) Laine 200351

Citalopram Fluoxetine

Prospective cohort

Non-exposed = 20

Outpatients

Neonatal symptoms and cord blood monoamine concentration

Results: SSRIs exposed neonates had lower APGAR score at 15 min (p .02), lower cord blood 5HIAA concentrations (p .02) and more serotonergic symptom score during first 4 days after born (p .008). No differences at 2 weeks and 2 months. Zeskind 200452

SSRIs

Prospective cohort

Non-exposed = 17

Carolinas Medical Center (USA)

Neonatal behavior, motor activity

Results: Exposed neonates were more tremorous (p .038), had less changes in behavioral states (p .05), fewer different behavioral states (p .009) and more periods of active (REM) sleep (p .001), compared with non-exposed newborns. Sivojelezova 200544

Citalopram

Prospective cohort

132

Other ADs = 132 Nonteratogen controls = 132

TIS Motherisk Program

Birth outcomes

Administrative database (Finland)

Treatment in SCU or NICU

Results: Increased risk for NICU admission (RR 4.2 [1.71-10.26]). No further differences in other outcomes Malm 200553

SSRIs

Prospective cohort

SSRIs purchases = 1782 (1, 2 and 3 trimester)

Matched Controls = 1782

Results: compared with infants exposed only during the 1st trimester, exposed in the 3rd trimester were more often treated in SCU or NICU (P .009, adjusted OR 1.6, [1.1-2.2]) LevinsonCastiel 200646

SRIs

Prospective cohort

SRIs exposed = 60

Non exposed = 60

Tertiary care center

Neonatal abstinence symptoms (Finnegan Score)

Non exposed = 1200

Drug and Health Information Centre, Italy

Neonatal adverse events and SCU admission rate

Non exposed controls = 73

secondary and tertiary care facilities

adverse effects on the neonates

Results: Abstinence symptoms in 18 exposed neonates vs. no controls Maschi 200823

SSRIs TCAs

Prospective cohort

Paroxetine = 58 Fluoxetine = 32 Amitriptyline = 26

Results: No differences in PNAS or admission to SCU. Boucher 200854

SSRIs SNRIs TCAs Other ADs

Case control

AD exposed = 73

Results: Exposed neonates had increased risk of alertness alteration (OR 37 [8–174]), altered muscular tone (OR 20 [5–71]), feeding and GI problems (OR 3.8 [1.7–8.1]), tachypnea (OR 2.5 [1.1–5.3]), and neurological problems (8/73 vs 0/73; P .006). Lund 200924

SSRIs alone or in combination

Prospective cohort

SSRIs = 329

Positive psychiatric history/No SSRI Use = 4902 No Psychiatric History = 51 770

Aarhus Birth Cohort (Denmark)

5-minute Apgar score, and admission to NICU.

Results: SSRIs exposed neonates had increased risk for NICU admissions (adjusted OR 2.39; 95% CI, 1.69-3.39 vs. control group, and OR 2.04; 95% CI, 1.42-2.94 vs. infants of mothers with psychiatric history) and for low 5 min APGAR scores (adjusted OR, 4.44; 95% CI, 2.58-7.63 and adjusted OR, 6.58; 95% CI, 3.39-12.74, respectively).

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First author and year

Drugs studied

Study design

Reis 201028

Tricyclics SSRIs SNRIs

Prospective

Exposed n

Comparison group n

Source of data

Primary outcome

14821 women and 15017 neonates (3 exposure groups: early, late and both)

1 062 190 women with 1 236 053 infants in the population

Swedish Birth Registry

Infant neonatal diagnoses

Results: Increased neonatal complications in late vs. early exposure and higher with both exposures: hypoglycaemia (OR 1.56 [1.36–1.79]), respiratory diagnoses (OR 1.65 [1.46–1.85]) and low Apgar score (OR 2.34 [1.96–2.79]). The OR is significantly increased for these outcomes primarily after the use of TCAs but also of SNRIs and SSRIs. Increased risk for jaundice after the use of TCAs and SNRIs. Casper 201155

SSRIs

Prospective cohort

Whole pregnancy exposure = 23

1st trimester exposure = 14 2nd/3rd trimester exposure = 18

Women’s Clinic at Stanford University

Pregnancy outcomes

Results: Increased length of prenatal exposure to SSRIs was associated with low APGAR scores at 1 and 5 min (OR 3.0 [CI 1.2, 7.8] and 5.2 [CI 1.0,26.8] respectively) and specifically on activity subscale (OR for a low score (<2) on this scale were 3.8 and 6.0 at 1 and 5 min, respectively). Also, longer exposure associated with more admission to NICU (p<.03) Kallen 201256

Central nervous system (CNS) active drugs

Prospective

15045 live born infants of mothers who redeemed prescription of CNS-active drugs during 2nd/3rd trimester

Rest of the population

Swedish Birth Register and the Prescribed Drug Register (between 2006-2008)

Neonatal symptoms

Results: Increased risk of neonatal symptoms in newborns of mothers receiving various types of CNS-active drugs, used alone: respiratory diagnoses (OR, 1.51; 95% CI, 1.41-1.63), hypoglycemia (OR, 1.49; 95% CI, 1.36-1.63) and low Apgar score (OR, 1.33; 95% CI, 1.17-1.53), more marked with benzodiazepines. The OR for any neonatal symptom after maternal use of only an SSRI was 1.82 (95% CI, 1.62-2.05), and after use of SSRI combined with 1 or more other drug was higher (OR, 2.46; 95% CI, 2.06-2.93). Hayes 201234

SSRIs SNRIs TCAs Other ADs

Retrospective cohort

Depressed with 1-2 prescriptions = 10,700 Depressed >3 prescriptions = 6196

Not classified as depressed = 195,079 Depressed, no prescriptions = 16,901

Administra-tive database (TennesseMedicaid)

Respiratory distress and convulsions

Results: Respiratory distress was 1.1 (95% CI, 0.9 –1.3), 1.4 (95% CI, 1.1–1.8), and 1.6 (95% CI, 1.2–2.0) times more common among infants born to women who filled 1, 2, and 3 prescriptions during the second trimester Grzeskowiak 201233

SSRIs

Retrospective cohort

With SSRIs prescriptions and psychiatric illness = 221

No prescriptions, no psychiatric illness = 32004 No prescriptions, psychiatric illness = 1566

Administrative databases (Australia)

Neonatal hospitalization and length of hospital admission

Results: Infants of women with pregnancy prescription of SSRIs had a twice increased risk of admission to hospital (adjusted OR, 1.92; 95% CI, 1.39-2.65), and length of hospital stay longer than 3 days (adjusted OR, 1.93; 95% CI, 1.11-3.36) compared with infants of mothers with psychiatric illness but no SSRI use during pregnancy, who had only an slight increased risk of neonatal hospital admission (adjusted OR, 1.21; 95% CI, 1.07-1.38). Smith 201257

SSRIs

Prospective cohort

No pregnancy depression, SSRIs use 3rd trimester = 6

No pregnancy depression, no SSRIs use = 61

Yale Pink and Blue cohort

Neonatal outcomes and behavior, sleep, motor activity

Results: Exposed newborns had shorter gestational age (1 week, p .02), lower 5 min APGAR score (p .01) and less motor activity, with marginal difference (p .05). No differences were found in sleep patterns. SSRIs: selective serotonine reuptake inhibitors; SNRIs: serotonine and noradrenaline reuptake inhibitors; Other ADs: other antidepressants except SSRIs, SNRIs and tricyclics; TCAs; tricyclics antidepressants. SCU: special care unit. NICU: neonatal intensive care unit

drug-associated abnormalities normalized in subsequent electrocardiographic tracings. The authors concluded that “although these infants were free of serious adverse effects, additional research is necessary to determine whether antenatal use of SSRIs is associated with malignant arrhythmias in the first days of life.” Long-term neurodevelopment The use of antidepressants medications throughout pregnancy exposes the fetal brain at a time of maximum central nervous system (CNS) development, therefore

may potentially influence neurotransmitter binding in an immature brain. Long-term outcomes could be influenced not only by serotonergic but also by dopaminergic and noradrenergic neurotransmitter systems, such as attention, impulse control, aggression, affect regulation, cognition and motor performance (67). There remains a paucity of studies examining neurodevelopmental outcomes of children exposed to prenatal use of antidepressants, probably due to the numerous methodological issues associated with conducting these types of studies (68-76) (Table 5). In summarizing the data, despite these limitations, the majority of studies found no 101

Antidepressant Use in Pregnancy: An Evaluation of Adverse Outcomes Excluding Malformations

Table 4. Persistent Pulmonary Hypertension of Neonate (PPHN) First author and year Chambers 200661

Drugs studied Fluoxetine

study design

Exposed n

Comparison group n

Source of data

Nested case-control

infants with PPHN = 377

Matched controls = 839

Slone Epidemiology Center Birth Defects Study

Primary outcome PPHN

Results: Maternal use of SSRI after week 20 associated with PPHN (OR 6.1 [2.2–16.8]) Absolute risk with SSRI use in late pregnancy: 6 – 12 per 1000. Andrade 200962

SSRIs

Retrospective cohort

Exposed = 1104

Matched controls = 1104

Medical records

Prevalence of PPHN

Results: Similar prevalence exposed vs. non exposed (2.14 per 1000 vs. 2.72 per 1000) Wichman 200963

SSRIs

Retrospective cohort

Exposed = 808 (53 in 3rd trimester, 119 in 2nd and 3rd trimester)

Non exposed = 24406

PPHN

Results: No increased risk for PPHN in SSRIexposed infants Reis 201028

TCAs SSRIs SNRIs

Prospective

14821 women and 15017 neonates, early and late exposure

1 062 190 women with 1 236 053 infants in the population

Swedish Birth Registry

Neonatal diagnoses

Madigan Army Medical Center

PPHN

National Health registries from Denmark, Finland, Iceland, Norway, and Sweden

PPHN

Results: PPHN in late pregnancy exposure RR 2.56; [1.17– 4.85]. Early exposure RR 2.30 [1.29– 3.80]. Wilson 201160

SSRIs

Case-control

20 cases

Case/Controls ratio 1:6

Results: cesarean delivery (CD) prior to the onset of labor increased the risk for PPHN: OR 4.9 [1.7-14.0] Kieler 201264

SSRIs

Retrospective populationbased cohort

SSRIs exposed = 30115

All birth in population

Results: PPHN OR 2.1 [1.5-3.0], similar for each type of SSRIs. SSRIs: selective serotonine reuptake inhibitors; SNRIs: serotonine and noradrenaline reuptake inhibitors; TCAs; tricyclics antidepressants

Table 5. Neurodevelopment First author and year

Drugs studied

study design

Exposed n

Comparison group n

Source of data

Nulman 199768

TCAs Fluoxetine

Prospective cohort

TCAs = 80 Fluoxetine = 55

Non-exposed controls = 84

TIS Motherisk Program

Primary outcome and measurement Bayley Scales of Infant Development, McCarthy Scales of Children’s Abilities, Reynell Developmental Language Scales.

Results: No differences were seen in terms of IQ and language in infants between 16 and 86 months of age exposed during at least the first trimester Nulman 200269

TCAs Fluoxetine

Prospective cohort

TCAs = 46 Fluoxetine = 40

Non-exposed controls = 36

TIS Motherisk Program

Bayley Scales of Infant Development, McCarthy Scales of Children’s Abilities and Reynell Developmental Language Scales.

Results: No significant differences in IQ, language, behavior and temperament in infants between 15 and 71 months of age after controlling for maternal illness. Negative association between maternal depression and IQ, and number of postnatal depressive episodes and language. Casper 200350

SSRIs

Prospective cohort

Children of depressed mothers using AD = 31

Children of depressed mothers not using AD = 13

Women’s Wellness Clinic

Bayley Scales of Infant Development Birth outcomes

Results: No significant differences on most birth outcomes and follow-up measures. SSRIs exposed infants had low scores on psychomotor development index (p. 02) and motor quality (p. 05). Oberlander 200470

SSRIs

Prospective cohort

Non-exposed controls = 23

British Columbia Women’s Hospital

Bayley Scales of Infant Development at 2 and 8 months

Results: No developmental differences in infants exposed to SSRIs during the 2nd and 3rd trimester compared to unexposed, and also between those with or without transient neurobehavioral symptoms at birth Misri 200671

SSRIs

Prospective cohort

Children of anxious/ depressed mothers medicated = 22

Non-exposed controls = 14

British Columbia Women’s Hospital

Child Behavior Checklist and Child-Teacher Report Form

Results: No differences in childhood internalizing behavior at age 4 between exposed or unexposed children. Increased parental reports of child internalizing behaviors associated with maternal symptoms of depression (F=5.43, df=1,36, p<0.05) and anxiety (F=6.88, df=1,36, p<0.05).

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First author and year Oberlander 200772

Drugs studied

study design

SSRIs

Prospective cohort

Exposed n Children of anxious/ depressed mothers medicated = 22

Comparison group n

Source of data

Primary outcome and measurement

Non-exposed controls = 14

British Columbia Women’s Hospital

Child Behavior Checklist and direct observations

Results: No differences in externalizing behavior in exposed vs non-exposed. More report of internalizing behaviors in mothers with higher levels of stress, anxiety, and depressed mood. Pedersen 201073

ADs

Prospective cohort

407 infants exposed to SSRIs 479 infants of untreated depressed mothers

79189 infants of non-depressed untreated mothers

Danish National Birth Cohort

Developmental milestones at 6 and 19 months reported by the mother

Results: Children with second- or third-trimester exposure to antidepressants were able to sit 15.9 days (95% CI 6.8 –25.0) and to walk 28.9 days (95% CI: 15.0–42.7) later than children of women not exposed to ADs but still within the normal range of development. Klinger 201174

SSRIs

Prospective cohort

Children with PNAS (30) vs. children without (52)

Schneider Children’s Medical Center of Israel

Neurodevelopmental evaluation at the age of 2 to 6 years

Results: No difference in mean cognitive ability (106.9±14.0 vs 100.5±14.6, P 0.12) and developmental scores (98.9±11.4 vs 95.7±9.9, P 0.21). PNAS associated with increased social-behavior abnormalities (OR 3.03, P 0.04) and advanced maternal age (OR 1.12, P 0.04). Galbally 201175

ADs

prospective casecontrolled

Non exposed controls = 19

Mercy Hospital for Women and private psychiatrists

Bayley Scales of Infant Development at 23.09 (SD 3.82) months (control) and 28.53 (SD 6.22) months (exposed)

Results: Children exposed to ADs in pregnancy scored lower on motor subscales in particular on fine motor scores than non-exposed children without statistical significance. No association found between maternal depression and neurodevelopment. Casper 201155

SSRIs

Prospective cohort

Whole pregnancy exposure = 23

1st trimester exposure = 14 2nd/3rd trimester exposure = 18

Women’s Clinic at Stanford University

Bayley Scales of Infant Development at 14 months

Results: Longer SSRIs exposure associated with increased risk for lower Psychomotor Developmental Index and Behavioral Rating Scale scores in infancy (p=0.012 and p=0.007, respectively) Croen 201176

ADs

Populationbased casecontrol study

298 case children with ASD

1507 randomly selected control children

Medical records

Autism spectrum disorders (ASD)

Results: increased risk of ASD associated with treatment with SSRIs by the mother during the year before delivery about 3%. No increase risk for mothers with history of mental health treatment in the absence of prenatal exposure to SSRIs. ADs: antidepressants; SSRIs: selective serotonine reuptake inhibitors; TCAs; tricyclics antidepressants. PNAS: poor neonatal adaptation symdrom

differences between those exposed and the controls on any of the neurodevelopmental outcomes that were measured. conclusion Following an extensive review of the literature, in order to evaluate whether antidepressants are associated with adverse pregnancy and infant outcomes, excluding major malformations, we did not find appreciable increases in any of the outcomes we examined. We did not find an overall increased risk associated with low birthweight, small for gestational age or long-term neurodevelopemental adverse outcomes. However, there does appear to be a significantly increased risk for spontaneous abor-

tion, preterm birth and infants born less than 2,500 gm. In addition, a possible increased risk for Persistent Pulmonary Hypertension of the Newborn (PPHN) and evidence of Poor Neonatal Adaptation Syndrome (PNAS) following use in late pregnancy. The observed risks were of a very low magnitude and the clinical significance of these results is unknown. When a woman suffers from depression during pregnancy, this information will assist her and her health care provider when weighing the benefits and/or risks of treatment with an antidepressant. It should be kept in mind when making this important decision, that untreated depression is also associated with adverse effects on the infant. Many of those effects have been associated too with antidepressants expo103

Antidepressant Use in Pregnancy: An Evaluation of Adverse Outcomes Excluding Malformations

sure. Further research needs to be conducted where it is possible to control for maternal depression, in order to evaluate whether these adverse events are due to the underlying maternal illness, the antidepressant, or possibly a combination of both. References 1. Grigoriadis S, Robinson GE. Gender issues in depression. Ann Clin Psychiatry 2007;19:247-255. 2. Gavin NI, Gaynes BN, Lohr KN, Meltzer-Brody S, Gartlehner G, Swinson T. Perinatal depression: A systematic review of prevalence and incidence. Obstet Gynecol 2005;106:1071-1083. 3. Alwan S, Reefhuis J, Rasmussen SA, Friedman JM, National Birth Defects Prevention S. Patterns of antidepressant medication use among pregnant women in a United States population. J Clin Pharmacol 2011;51:264-270. 4. Mojtabai R. The public health impact of antidepressants: An instrumental variable analysis. J Affect Disord 2011;134:188-197. 5. World Health Organization (WHO). Available at: wwwwhoint/research/ en [Accessed 20th Oct 2011]. 6. Petersen I, Gilbert RE, Evans SJ, Man SL, Nazareth I. Pregnancy as a major determinant for discontinuation of antidepressants: An analysis of data from the Health Improvement Network. J Clin Psychiatry 2011;72:979-985. 7. Einarson A, Selby P, Koren G. Abrupt discontinuation of psychotropic drugs during pregnancy: Fear of teratogenic risk and impact of counselling. J Psychiatry Neurosci 2001;26:44-48. 8. Cohen LS, Altshuler LL, Harlow BL, et al. Relapse of major depression during pregnancy in women who maintain or discontinue antidepressant treatment. JAMA 2006;295:499-507. 9. Grote NK, Bridge JA, Gavin AR, Melville JL, Iyengar S, Katon WJ. A meta-analysis of depression during pregnancy and the risk of preterm birth, low. Arch Gen Psychiatry 2010;67:1012-1024. 10. Davalos DB, Yadon CA, Tregellas HC. Untreated prenatal maternal depression and the potential risks to offspring: A review. Arch Womens Ment Health 2012;15:1-14. 11. Field T, Diego M, Hernandez-Reif M. Prenatal depression effects on the fetus and newborn: A review. Infant Behav Dev 2006;29:445-455. 12. Newport DJ, Ji S, Long Q, et al. Maternal depression and anxiety differentially impact fetal exposures during pregnancy. J Clin Psychiatry 2012;73:247-251. 13. Chung TK, Lau TK, Yip AS, Chiu HF, Lee DT. Antepartum depressive symptomatology is associated with adverse obstetric and neonatal outcomes. Psychosom Med 2001;63:830-834. 14. Savitz DA, Hertz-Picciotto I, Poole C, Olshan AF. Epidemiologic measures of the course and outcome of pregnancy. Epidemiol Rev 2002;24:91-101. 15. Wilcox AJ. On the importanceâ&#x20AC;&#x201C;and the unimportanceâ&#x20AC;&#x201C;of birthweight. Int J Epidemiol 2001;30:1233-1241. 16. Chambers CD, Johnson KA, Dick LM, Felix RJ, Jones KL. Birth outcomes in pregnant women taking fluoxetine. N Engl J Med 1996;335:1010-1015. 17. Simon GE, Cunningham ML, Davis RL. Outcomes of prenatal antidepressant exposure. Am J Psychiatry 2002;159:2055-2061. 18. Oberlander TF, Warburton W, Misri S, Aghajanian J, Hertzman C. Neonatal outcomes after prenatal exposure to selective serotonin reuptake inhibitor antidepressants and maternal depression using populationbased linked health data. Arch Gen Psychiatry 2006;63:898-906. 19. Davis RL, Rubanowice D, McPhillips H, et al. Risks of congenital malformations and perinatal events among infants exposed to antidepressant medications during pregnancy. Pharmacoepidemiol Drug Saf 2007;16:1086-1094. 20. Suri R, Altshuler L, Hellemann G, Burt VK, Aquino A, Mintz J. Effects of antenatal depression and antidepressant treatment on gestational age

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at birth and risk of preterm birth. Am J Psychiatry 2007;164:1206-1213. 21. Oberlander TF, Warburton W, Misri S, Aghajanian J, Hertzman C. Effects of timing and duration of gestational exposure to serotonin reuptake inhibitor antidepressants: population-based study. Br J Psychiatry 2008;192:338-343. 22. Toh S, Mitchell AA, Louik C, Werler MM, Chambers CD, Hernandez-Diaz S. Antidepressant use during pregnancy and the risk of preterm delivery and fetal growth restriction. J Clin Psychopharmacol 2009;29:555-560. 23. Maschi S, Clavenna A, Campi R, Schiavetti B, Bernat M, Bonati M. Neonatal outcome following pregnancy exposure to antidepressants: A prospective controlled cohort study. BJOG 2008;115:283-289. 24. 24. Lund N, Pedersen LH, Henriksen TB. Selective serotonin reuptake inhibitor exposure in utero and pregnancy outcomes. Arch Pediatr Adolesc Med 2009;163:949-954. 25. Einarson A, Choi J, Einarson TR, Koren G. Adverse effects of antidepressant use in pregnancy: An evaluation of fetal growth and preterm birth. Depress Anxiety 2009;27:35-38. 26. Wisner KL, Sit DK, Hanusa BH, et al. Major depression and antidepressant treatment: impact on pregnancy and neonatal outcomes. Am J Psychiatry 2009;166:557-566. 27. Lewis AJ, Galbally M, Opie G, Buist A. Neonatal growth outcomes at birth and one month postpartum following in utero exposure to antidepressant medication. Aust N Z J Psychiatry 2010;44:482-487. 28. Reis M, Kallen B. Delivery outcome after maternal use of antidepressant drugs in pregnancy: An update using Swedish data. Psychol Med 2010;40:1723-1733. 29. Ramos E, St-Andre M, Berard A. Association between antidepressant use during pregnancy and infants born small for gestational age. Can J Psychiatry 2010;55:643-652. 30. Roca A, Garcia-Esteve L, Imaz ML, et al. Obstetrical and neonatal outcomes after prenatal exposure to selective serotonin reuptake inhibitors: The relevance of dose. J Affect Disord 2011; 135:208-215. 31. Klieger-Grossmann C, Weitzner B, Panchaud A, et al. Pregnancy outcomes following use of escitalopram: A prospective comparative cohort study. J Clin Pharmacol 2012;52:766-770. 32. Nordeng H, van Gelder MM, Spigset O, Koren G, Einarson A, EberhardGran M. Pregnancy outcome after exposure to antidepressants and the role of maternal depression: Results from the Norwegian Mother and Child Cohort Study. J Clin Psychopharmacol 2012;32:186-194. 33. Grzeskowiak LE, Gilbert AL, Morrison JL. Neonatal outcomes after late-gestation exposure to selective serotonin reuptake inhibitors. J Clin Psychopharmacol 2012;32:615-621. 34. Hayes RM, Wu P, Shelton RC, et al. Maternal antidepressant use and adverse outcomes: A cohort study of 228,876 pregnancies. Am J Obstet Gynecol 2012;207:49. 35. Yonkers KA, Norwitz ER, Smith MV, et al. Depression and serotonin reuptake inhibitor treatment as risk factors for preterm birth. Epidemiology 2012;23:677-685. 36. El Marroun H, Jaddoe VW, Hudziak JJ, et al. Maternal use of selective serotonin reuptake inhibitors, fetal growth, and risk of adverse birth outcomes. Arch Gen Psychiatry;69:706-714. 37. Dubnov-Raz G, Hemila H, Vurembrand Y, Kuint J, Maayan-Metzger A. Maternal use of selective serotonin reuptake inhibitors during pregnancy and neonatal bone density. Early Hum Dev 2012:88:191-194. 38. Einarson A, Choi J, Einarson TR, Koren G. Rates of spontaneous and therapeutic abortions following use of antidepressants in pregnancy: Results from a large prospective database. J Obstet Gynaecol Can 2009;31:452-456. 39. Nakhai-Pour HR, Broy P, Berard A. Use of antidepressants during pregnancy and the risk of spontaneous abortion. CMAJ 2010;182:1031-1037. 40. Pastuszak A, Schick-Boschetto B, Zuber C, et al. Pregnancy outcome following first-trimester exposure to fluoxetine (Prozac). JAMA 1993;269:2246-2248.

Laura Lorenzo and Adrienne Einarson

41. Kulin NA, Pastuszak A, Sage SR, et al. Pregnancy outcome following maternal use of the new selective serotonin reuptake inhibitors: a prospective controlled multicenter study. JAMA 1998;279:609-610. 42. Einarson A, Fatoye B, Sarkar M, et al. Pregnancy outcome following gestational exposure to venlafaxine: A multicenter prospective controlled study. Am J Psychiatry 2001;158:1728-1730. 43. Chun-Fai-Chan B, Koren G, Fayez I, et al. Pregnancy outcome of women exposed to bupropion during pregnancy: A prospective comparative study. Am J Obstet Gynecol 2005;192:932-936. 44. Sivojelezova A, Shuhaiber S, Sarkissian L, Einarson A, Koren G. Citalopram use in pregnancy: Prospective comparative evaluation of pregnancy and fetal outcome. Am J Obstet Gynecol 2005;193:2004-2009. 45. Djulus J, Koren G, Einarson TR, et al. Exposure to mirtazapine during pregnancy: A prospective, comparative study of birth outcomes. J Clin Psychiatry 2006;67:1280-1284. 46. Levinson-Castiel R, Merlob P, Linder N, Sirota L, Klinger G. Neonatal abstinence syndrome after in utero exposure to selective serotonin reuptake inhibitors in term infants. Arch Pediatr Adolesc Med 2006;160:173-176. 47. Sanz EJ, De-las-Cuevas C, Kiuru A, Bate A, Edwards R. Selective serotonin reuptake inhibitors in pregnant women and neonatal withdrawal syndrome: A database analysis. Lancet 2005;365:482-487. 48. Belik J. Fetal and neonatal effects of maternal drug treatment for depression. Semin Perinatol 2008;32:350-354. 49. Costei AM, Kozer E, Ho T, Ito S, Koren G. Perinatal outcome following third trimester exposure to paroxetine. Arch Pediatr Adolesc Med 2002;156:1129-1132. 50. 50. Casper RC, Fleisher BE, Lee-Ancajas JC, et al. Follow-up of children of depressed mothers exposed or not exposed to antidepressant drugs during pregnancy. J Pediatr 2003;142:402-408. 51. Laine K, Heikkinen T, Ekblad U, Kero P. Effects of exposure to selective serotonin reuptake inhibitors during pregnancy on serotonergic symptoms in newborns and cord blood monoamine and prolactin concentrations. Arch Gen Psychiatry 2003;60:720-726. 52. Zeskind PS, Stephens LE. Maternal selective serotonin reuptake inhibitor use during pregnancy and newborn neurobehavior. Pediatrics 2004;113:368-375. 53. Malm H, Klaukka T, Neuvonen PJ. Risks associated with selective serotonin reuptake inhibitors in pregnancy. Obstet Gynecol 2005;106:1289-1296. 54. Boucher N, Bairam A, Beaulac-Baillargeon L. A new look at the neonateâ&#x20AC;&#x2122;s clinical presentation after in utero exposure to antidepressants in late pregnancy. J Clin Psychopharmacol 2008;28:334-339. 55. Casper RC, Gilles AA, Fleisher BE, Baran J, Enns G, Lazzeroni LC. Length of prenatal exposure to selective serotonin reuptake inhibitor (SSRI) antidepressants: Effects on neonatal adaptation and psychomotor development. Psychopharmacology (Berl) 2011;217:211-219. 56. Kallen B, Reis M. Neonatal complications after maternal concomitant use of SSRI and other central nervous system active drugs during the second or third trimester of pregnancy. J Clin Psychopharmacol 2012;32:608-614. 57. Smith MV, Sung A, Shah B, Mayes L, Klein DS, Yonkers KA. Neurobehavioral assessment of infants born at term and in utero exposure to serotonin reuptake inhibitors. Early Hum Dev 2013;89:81-86. 58. Lakshminrusimha S, Steinhorn RH. Pulmonary vascular biology during neonatal transition. Clin Perinatol 1999;26:601-619.

59. Dakshinamurti S. Pathophysiologic mechanisms of persistent pulmonary hypertension of the newborn. Pediatr Pulmonol 2005;39:492-503. 60. Wilson KL, Zelig CM, Harvey JP, Cunningham BS, Dolinsky BM, Napolitano PG. Persistent pulmonary hypertension of the newborn is associated with mode of delivery and not with maternal use of selective serotonin reuptake inhibitors. Am J Perinatol 2011;28:19-24. 61. Chambers CD, Hernandez-Diaz S, Van Marter LJ, et al. Selective serotonin-reuptake inhibitors and risk of persistent pulmonary hypertension of the newborn. N Engl J Med 2006;354:579-587. 62. Andrade SE, McPhillips H, Loren D, et al. Antidepressant medication use and risk of persistent pulmonary hypertension of the newborn. Pharmacoepidemiol Drug Saf 2009;18:246-252. 63. Wichman CL, Moore KM, Lang TR, St Sauver JL, Heise RH, Jr., Watson WJ. Congenital heart disease associated with selective serotonin reuptake inhibitor use during pregnancy. Mayo Clin Proc 2009;84:23-27. 64. Kieler H, Artama M, Engeland A, et al. Selective serotonin reuptake inhibitors during pregnancy and risk of persistent pulmonary hypertension in the newborn: Population based cohort study from the five Nordic countries. BMJ 2012;344:d8012. 65. Hobbs JB, Peterson DR, Moss AJ, et al. Risk of aborted cardiac arrest or sudden cardiac death during adolescence in the long-QT syndrome. JAMA 2006;296:1249-1254. 66. Dubnov-Raz G, Juurlink DN, Fogelman R, et al. Antenatal use of selective serotonin-reuptake inhibitors and QT interval prolongation in newborns. Pediatrics 2008;122:e710-715. 67. Stokes AH, Hastings TG, Vrana KE. Cytotoxic and genotoxic potential of dopamine. J Neurosci Res 1999;55:659-665. 68. Nulman I, Rovet J, Stewart DE, et al. Neurodevelopment of children exposed in utero to antidepressant drugs. N Engl J Med 1997;336:258-262. 69. Nulman I, Rovet J, Stewart DE, et al. Child development following exposure to tricyclic antidepressants or fluoxetine throughout fetal life: A prospective, controlled study. Am J Psychiatry 2002;159:1889-1895. 70. Oberlander TF, Misri S, Fitzgerald CE, Kostaras X, Rurak D, Riggs W. Pharmacologic factors associated with transient neonatal symptoms following prenatal psychotropic medication exposure. J Clin Psychiatry 2004;65:230-237. 71. Misri S, Reebye P, Kendrick K, et al. Internalizing behaviors in 4-year-old children exposed in utero to psychotropic medications. Am J Psychiatry 2006;163:1026-1032. 72. Oberlander TF, Reebye P, Misri S, Papsdorf M, Kim J, Grunau RE. Externalizing and attentional behaviors in children of depressed mothers treated with a selective serotonin reuptake inhibitor antidepressant during pregnancy. Arch Pediatr Adolesc Med 2007;161:22-29. 73. Pedersen LH, Henriksen TB, Olsen J. Fetal exposure to antidepressants and normal milestone development at 6 and 19 months of age. Pediatrics 2010;125:e600-608. 74. Klinger G, Frankenthal D, Merlob P, et al. Long-term outcome following selective serotonin reuptake inhibitor induced neonatal abstinence syndrome. J Perinatol 2011;31:615-620. 75. Galbally M, Lewis AJ, Buist A. Developmental outcomes of children exposed to antidepressants in pregnancy. Aust N Z J Psychiatry 2011;45:393-399. 76. Croen LA, Grether JK, Yoshida CK, Odouli R, Hendrick V. Antidepressant use during pregnancy and childhood autism spectrum disorders. Arch Gen Psychiatry 2011;68:1104-1112.

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Maternal Depression and Perception of Teratogenic Risk Gideon Koren, MD, FRCPC Motherisk Program, Division of Clin Pharmacology-Toxicology, Department of Pediatrics, Hospital for Sick Children and University of Toronto, Toronto, Canada

Abstract Depression in pregnancy is characterized by unrealistically heightened perception of teratogenic risk. Appropriate counseling regarding the exposure at hand can assist in reducing maternal concerns. Addressing depression during pregnancy and, in parallel, providing evidencebased counseling and reassurance regarding different antidepressants in pregnancy may avert major health risks.

The majority of pregnant women are exposed to medications during pregnancy. Since the thalidomide disaster of the 1950-60s, medicine is commonly practiced with blatant over estimation of the potential teratogenic effects of various exposures in pregnancy (1-4). We have shown that women tend to assign an unrealistically high teratogenic risk to medications even when they are not known to be teratogenic, as well as to drugs that have been proven to be safe to the fetus (1-2, 4). This misperception of teratogenic risk may lead to serious consequences such as discontinuation of medication for life threatening disorders as well as consideration of pregnancy termination of an otherwise wanted pregnancy (1-5). In the case of psychotropic drugs, abrupt discontinuation of medications may lead to exacerbation of depression (6). In a large multicenter trial Cohen et al. (7) explored the effects of medication discontinuation on pregnancy course. The authors followed up a group of women suffering from major depression treated with antidepressants in pregnancy. A proportion of these women decided to discontinue their antidepressants while others elected to continue. The risk of major depression

relapse was 70% in the group that discontinued therapy, as compared to only 25% among those who continued. This study and similar others highlight the dangers of discontinuation of important medications during pregnancy. In the case of antidepressants, this can be associated with increased suicidality. Perception of Teratogenic Potential of Pregnant Women In 1989 we studied for the first time the perception of teratogenic risk in a group of 80 women attending our Motherisk antenatal counseling service (2). These women were exposed to medications not known to be teratogenic, yet they assigned high teratogenicity potential to their exposures (mean 25%), and expressed a high rated likelihood of pregnancy termination. The good news was that these unrealistic perceptions and intentions changed following an evidence-based counselling session. We recently published additional work exploring maternal perception of teratogenic potential (8). Our results corroborated the earlier findings regarding the heightened perception of teratogenic potential among pregnant and planning women, exposed to a variety of fetal-safe agents. As expected, women exposed to proven teratogens (such as anticonvulsants or anticoagulants) exhibited an even higher risk perception and likelihood of pregnancy termination (8). Measuring Maternal Perceptions In different teratology centers, women are counseled in the early stages of pregnancy or in the planning phase. Typically these women are exposed to a variety of medications, some may constitute teratogens, or are suffering from medical disorders that may have adverse fetal impact on

Address for Correspondence: Gideon Koren, MD FRCPC, Motherisk Program, Division of Clin Pharmacology-Toxicology, Hospital for Sick Children and University of Toronto, 555 University Ave., Toronto M5G 1X8, Canada â&#x20AC;&#x2020; gidiup_2000@yahoo.com

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the pregnancy course and or outcome. The components of a typical counseling session include a detailed demographic and medical questionnaire followed by evidence-based counselling on safety/risk of the specific context of the women. In an attempt to capture maternal perceptions and intentions prior to, and following the counselling session, we have developed a specific Visual Analog Scale (VAS) (2, 8). This VAS was validated for quantification of maternal teratogenic risk perception and the rated likelihood of pregnancy termination in pregnant women. The first item of the visual analog scale quantifies maternal tendency to terminate the present pregnancy (on a scale of 1 to 100). The second item refers to the woman’s perception of her unborn baby’s risk for birth defects, and the third refers to the risk of birth defects in the general population. As one would expect, the first and second items of the VAS are significantly inter-correlated. In other words, women who perceive their personal risk of having a child with a birth defect to be high are more likely to consider pregnancy termination. Some maternal characteristics have been shown by us to have a significant effect on maternal intention to terminate the pregnancy, such as age and marital status (8). Despite depression being so prevalent in pregnancy, very few studies have been conducted on the possible impact of undiagnosed maternal depression on these perceptions and intentions. Depression in Pregnancy Major depression is the most common mood disorder with high prevalence among women of reproductive age (9). The lifetime incidence of major depression among women is as high as 15% (10, 11). Unfortunately, only half of these women ever seek care. The risk for major depression peaks during the childbearing years and is twice as high in women than in men, both in the childbearing years and during the post-menopausal period (12, 13). Pregnancy is a major life stressor, and thus may precipitate or exacerbate depressive symptoms. During pregnancy, the risk for active major depression is at least 10% (14), and is associated with a variety of adverse outcomes including poor maternal health; longer hospitalization; suicide ideation and attempt; postpartum depression; higher miscarriage rate in the first trimester and higher rates of pre-term birth (15-18). Maternal depression during pregnancy is therefore a condition that must be screened for and appropriately managed. In reality, depression in pregnancy is often undiagnosed and undertreated, thereby exposing women and their untreated fetuses to a variety of risks (19).

Screening for Depression in General and Obstetric Practices The Edinburgh Postnatal Depression Scale (EPDS) was originally published by Cox et al. in 1987 in an attempt to screen for postpartum depression (20). It consists of 10 items in a self-rated questionnaire. The maximum score is 30. A score of 10 or more is suggestive of a minor depressive disorder, while a score of 13 or more is suggestive of major depression. It is important to remember that this is a screening tool that should never replace full diagnostic workup. Although originally developed for postpartum depression, the EPDS was later validated also for depression during pregnancy (21-24). In Toronto’s Motherisk program we have integrated the EPDS as part of the counseling session in an attempt to screen for maternal depression in our clinic population. In a sample of over 400 women counseled at the Motherisk Clinic, a quarter of the women scored 13 or more on the EPDS, highly suggestive of major depression (25). A third of the women who had a previous diagnosis of depression scored 13 or more on the EPDS as well. This finding in itself is suggestive of under-treatment in this depressed sub-population. Importantly, a significant number of women coming to the clinic admitted occasional suicide ideation (EPDS question number 10) (25). Maternal Depression and Perception of Teratogenic Risk Perception of teratogenic risk and maternal decisions are influenced by multiple factors including maternal emotional state. We have recently shown that an EPDS score ≥ 13 (i.e., most probably major depression) is an independent predictor of an heightened perception of teratogenic risk and that EPDS score is significantly and positively correlated with the rated likelihood of pregnancy termination (8). In other words, using the EPDS as a surrogate of the level of depression, a depressed woman (compared to a non-depressed woman with the same exposure) is more likely to have an unrealistically high perception of the risk of having a baby with a birth defect and, possibly as a result, is more likely to consider pregnancy termination. The Effect of Evidence-Based Counselling Repeating the three VAS items following the counselling session allows a comparison of maternal perceptions and 107

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intentions prior to, and following, counseling and determining whether the session had a significant impact on the patient. Measuring by differences in the maternal assigned risk for having a baby with a birth defect before and after the counseling session, the counselling session has been shown by us to have a significant impact (8). In fact, the assigned risks for all three components of the validated VAS (described above) drop significantly following counseling. Even more important, the rated likelihood of pregnancy termination was shown to significantly decline following a single exposure directed counselling session (2, 3, 8). This effect was shown both for women with high EPDS, as well for those with lower ones. Thus, appropriate counselling assists in lowering maternal fears, misperceptions, and even the tendency to terminate pregnancy. SUMMARY Depression is common in women in general and even more so during pregnancy. Maternal depression and its association with the perception of teratogenic risk is a critical, yet neglected, issue. Depressive symptomatology is correlated with both elevated teratogenic risk perception as well as the rated likelihood of pregnancy termination. Appropriate counselling regarding the exposure at hand may assist in reducing maternal concerns. Addressing depression during pregnancy and, in parallel, providing evidence based counselling and reassurance regarding different exposures in pregnancy may avert major health risks. References 1. Bonari L, Koren G, Einarson TR, et al. Use of antidepressants by pregnant women: evaluation of perception of risk, efficacy of evidence based counseling and determinants of decision making. Arch Women Ment Health 2005;8:214-220. 2. Koren G, Bologa M, Long D, et al. Perception of teratogenic risk by pregnant women exposed to drugs and chemicals during the first trimester. Am J Obstet Gynecol 1989;160:1190-1194. 3. Koren G, Bologa M, Pastuszak A. Women’s perception of teratogenic risk. Can J Public Health 1991;82:S11-4-S33-37. 4. Nordeng H, Ystrøm E, Einarson A. Perception of risk regarding the use of medications and other exposures during pregnancy. Eur J Clin Pharmacol 2010;66:207-214. 5. De Santis M, De Luca C, Quattrocchi T, et al. Use of the Internet by women seeking information about potentially teratogenic agents. Eur J Obstet Gynecol Reprod Biol. 2010;151:154-157.

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6. Einarson A, Selby P, Koren G. Abrupt discontinuation of psychotropic drugs during pregnancy: Fear of teratogenic risk and impact of counseling. J Psychiatry Neurosci 2001;26:44-48. 7. Cohen LS, Altshuler LL, Harlow BL, et al. Relapse of major depression during pregnancy in women who maintain or discontinue antidepressant treatment. JAMA 2006;295:499-507. 8. Walfisch A, Sermer C, Matok I, Einarson A, Koren G. Perception of teratogenic risk and the rated likelihood of pregnancy termination: Association with maternal depression. Can J Psychiatry 2011; 56:761-767. 9. Hirth JM, Berenson AB. Racial/ethnic differences in depressive symptoms among young women: The role of intimate partner violence, trauma, and posttraumatic stress disorder. J Women Health (Larchmt) 2012;21:966-974. 10. Vesga-López O, Blanco C, Keyes K, Olfson M, Grant BF, Hasin DS. Psychiatric disorders in pregnant and postpartum women in the United States. Arch Gen Psychiatry 2008;65:805-815. 11. Marcus SM, Flynn HA, Blow FC, Barry KL. Depressive symptoms among pregnant women screened in obstetrics settings. J Women Health 2003;12:373-380. 12. Kessler RC, McGonagle KA, Swartz M, et al. Sex and depression in the national comorbidity survey. I: Lifetime prevalence, chronicity and recurrence. J Affect Disord 1993;29:85-96. 13. Ahokas A, Kaukoranta J, Aito M. Effect of oestradiol on postpartum depression. Psychopharmacology 1999;146:108. 14. Dennis CL, Ross LE, Grigoriadis S. Psychosocial and psychological interventions for treating antenatal depression. Cochrane Database Syst Rev 2007;3:CD006309. 15. Pagel MD, Smilkstein G, Regen H, et al. Psychosocial influences on new born outcome: A controlled prospective study. Soc Sci Med 1990;30:597-604. 16. Hedegaard M, Henriksen TB, Sabroe S, et al. Psychological distress in pregnancy and preterm delivery. BMJ 1993;307:234-239. 17. Teixeira JMA, Fisk NM, Glover V. Association between maternal anxiety in pregnancy and increased uterine artery resistance index: Cohort based study. BMJ 1999;318:153-157. 18. Muzik M, Marcus SM, Heringhausen JE, et al. When depression complicates childbearing: Guidelines for screening and treatment during antenatal and postpartum obstetric care. Obstet Gynecol Clin North Am 2009;36:771-788. 19. Alder J, Fink N, Urech C, et al. Identification of antenatal depression in obstetric care. Arch Gynecol Obstet 2011;284:1403-1409. 20. Cox JL, Holden JM, Sagovsky R. Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale. Br J Psychiatry 1987;150:782-786. 21. Eberhard-Gran M, Eskild A, Tambs K, et al. Review of validation studies of the Edinburgh Postnatal Depression Scale. Acta Psychiatr Scand 2001;104:243-249. 22. Murray D, Cox JL. Screening for depression during pregnancy with the Edinburgh depression scale (EPDS). J Reprod Infant Psychol 1990;8:99107. 23. Thorpe K. A study of the Edinburgh postnatal depression scale for use with parent groups outside the postpartum period. J Reprod Infant Psychol 1993;11:119-125. 24. Beck AT, Ward CH, Mendelson M, et al. An inventory for measuring depression. Arch Gen Psychiatry 1961;4:561-571. 25. Walfisch A, Sermer C, Matok I, Koren G, Einarson A. Screening for depressive symptoms. Can Fam Physician 2011;57:777-778.

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Gillian E. Hanley et al.

The Impact of Maternal Positive and Negative Affect on Fetal Physiology and Diurnal Patterns Gillian E. Hanley, PhD, 2,4 Dan Rurak, PhD,2,3 Ken Lim, MD, FRCSC,2,3 Ursula Brain, BA,1,2 and Tim F. Oberlander, MD, FRCPc1,2 1

Department of Pediatrics University of British Columbia, Vancouver BC, Canada Child & Family Research Institute, University of British Columbia, Vancouver BC, Canada 3 Departments of Obstetrics & Gynecology, University of British Columbia, Vancouver BC, Canada 4 School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada 2

Abstract Background: While research has shown that maternal mood (depression and/or anxiety) can have effects on the fetus, little is known about whether maternal positive and negative affect influences the fetus. Method: We examined fetal vascular and heart rate changes at 36 weeks gestation in 53 euthymic mothers according to their Positive and Negative Affect Scale (PANAS) scores. Results: Mothers who reported high levels of negative affect showed reduced uterine artery flow, decreased fetal heart rate (fHR) variability, an altered diurnal pattern, and decreased uterine artery cross-sectional area compared to mothers who reported low levels of negative affect. Mothers with low positive affect had a steeper diurnal pattern in fHR accelerations and decreased uterine artery mean velocity flow than mothers with high positive affect. Limitations: Our observational study suffers from a small sample size. Conclusion: Even in the absence of an Axis I Major Depressive Disorder (MDD), variations in maternal affect appear to be associated with variations in fetal and uterine physiology.

Address for Correspondence: toberlander@cw.bc.ca

Introduction The notion that a mother’s mood during pregnancy shapes the developing fetal brain, which influences risks for mental and physical health across the life span has been a part of popular beliefs for millennia (1). Exposure to maternal mood disturbances during pregnancy is among the earliest of adverse experiences and has long-term effects on the offspring (2). While substantial evidence points to how early life adversity predisposes to poor mental health and stress adaptation across the life span (3) little is known about how such affect disorders, whether postive or negative, influence fetal development during a typical pregnancy. An individual’s affective state is now known to be correlated with their health status (4, 5), but why some are more prone than others to feel anxious, neurotic and threatened by life’s stressors remains unclear. These tendencies, known as negative affect (NA), are generally maintained as relatively stable characteristics, with individuals expressing feelings like anger, contempt, shame, fear and depression (6). On the other hand, individuals with high positive affect (which reflects an individual’s enthusiasm, activity, control and commitment) seem able to maintain a positive outlook over both time and in various situations (7). Funding Source: G.E.H. is supported by the Canadian Institutes for Health Research, the Michael Smith Foundation for Health Research, Women’s Health Research Institute and Neurodevnet. T.F.O. is the R. Howard Webster Professor in Early Child Development at the University of British Columbia and his work is supported by the Child and Family Research Institute and the Canadian Institutes for Health Research. This study was supported by the Child and Family Research Institute (UBC) and the Canadian Institutes of Health Research [MOP-57837].

Tim F. Oberlander, MD, Child & Family Research Institute, F605 4480 Oak St., Vancouver, BC V6H 3V4, Canada

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Impact of Maternal Positive and Negative Affect on Fetal Physiology and Diurnal Patterns

With respect to mother’s mood, research examining maternal mood disturbances (depression and/or anxiety) during pregnancy has suggested that it is an independent risk factor for operative delivery (8), preterm birth (9) and low birth weight (9). Studies comparing the infants born to mothers with higher depression scores have noted that they are at increased risk for decreased motor tone, more abnormal reflexes, lower activity levels, less robustness and endurance, increased irritability, and inferior orientation compared to infants born to mothers with low depression scores (10, 11). Antenatal depressed mood during pregnancy has been associated with atypical frontal EEG patterns, reduced vagal tone, elevated cortisol and norepinephrine, and lower dopamine and serotonin levels in the offspring (12). Prenatal maternal anxiety predicts infant temperament and attention regulation during the first year of life (12, 13), even when accounting for postnatal maternal psychological state, consistent with a fetal progamming hypothesis. Fetuses of mothers who are depressed display a higher baseline fetal heart rate (fHR), a slower fHR reaction to an external stimulus, and a longer period to return to fHR baseline levels after the stimulus compared with fetuses in a control group (14). Previous work examining how maternal psychological state affects the fetus has shown that fetuses of mothers who reported greater daily stress showed significantly lower fHR variability than the low stress group. Fetuses of depressed and/or anxious mothers also show significantly different reactivity to acute maternal stress and a significantly higher increase in fHR when the mother was introduced to a lab-induced stressor (15-17). Thus, there is reason to believe that maternal affect may also influence fetal physiology and behavior; however, very little is known on the association between positive and negative maternal affect and human fetal physiologic functions during a typical pregnancy. Our aim was to investigate whether there is an association between maternal affect and fHR variability and Doppler blood flow velocity variables in the fetal middle cerebral artery (MCA), umbilical artery, and the uterine artery at 36 weeks gestation in euthymic mothers. Method Participants were 53 healthy, pregnant women and their singleton fetuses. Mothers were recruited during their second trimester (at 26 weeks gestation) from community midwife clinics and family physician clinics in metropolitan Vancouver. Informed consent was obtained from all mothers and the study was approved by the University of British 110

Columbia Research Ethics Board and the BC Women’s Hospital Research Review Committee. Inclusion criteria for this study were singleton pregnancy, confirmed gestational age, ability to give informed consent, lack of substance abuse, and no known fetal anomalies. Exclusion criteria were bipolar disorder, use of psychotropic medications, and significant maternal medical, obstetrical, or fetal conditions. Maternal affect and characteristics

We assessed maternal affect using the Positive and Negative Affect Scale (PANAS). We measured the study participants daily for 7 days at 36 weeks gestation. This was done to increase the reliability of the assessment, as it takes into account fluctuations in mood and provides more robust estimate of typical levels of positive and negative affect (18). The PANAS instrument estimates the degree of both negative and positive “affectiveness.” We used the mean PA and NA scores for the 7-day period. The PANAS instrument has been validated in many samples (7, 18-20) and it has been shown that positive and negative affect are not significantly correlated implying that there is divergent validity between the two measures. We also calculated the Pearson correlation coefficients between PA and NA scores in our sample and found that PA and NA were not strongly correlated (ρPA,NA= -0.21). Thus, each participant was categorized once according to their NA score and then again according to their PA score. Maternal characteristics and health history were obtained from a combination of maternal interviews and medical records. Mothers were also assessed for depression using the Edinburgh Postnatal Depression Scale (EPDS), a 10-item self-rated questionnaire intended to assess existence and severity of depression symptoms that was designed for use in pregnant women (21). The Hamilton Rating Scale for Depression (HAM-D) is a 21-item clinician rated scale that measures the severity of depression in adults with a range from 0-63. A trained research assistant administered the clinician rated HAM-D assessments (22). Experimental protocol

The data collection for this protocol occurred between January 2007 and March 2010. Study recruits were healthy women, without any known significant medical conditions. The pregnancies were considered low risk at the time of the study. Study participants were asked to eat and drink normally before they arrived. Women were scanned as close to 36 weeks and 0 days as possible (sample mean was 36 weeks and 1 day) in an attempt to avoid risk of delivery in healthy women. They were placed in a semi-recumbant,

Gillian E. Hanley et al.

left lateral decubitus position throughout the ultrasound and the fHR monitoring. The study protocol involved two 2-hour monitoring sessions, a morning session (starting at approximately 8:15 am) and an afternoon session (starting at approximately 1:00 pm) on the same day. Fetal and placental positions were documented by ultrasound. Amniotic fluid assessment was done to rule out oligohydramnios and polyhydramnios prior to the start of the study period. The Doppler ultrasound vascular studies were performed with an Aloka ProSound 5500 with a curvilinear 4-7 MHz probe using B mode, color flow and pulse wave Doppler. All scans were performed by a single Obstetrician/Gynecologist (KL) who was blinded to the mothersâ&#x20AC;&#x2122; PANAS results. In the first monitoring session, high resolution B mode and pulse wave Doppler ultrasound was used to measure blood flow velocity variables (diameter, pulsatility index, peak velocity, blood flow) in three arterial vessels: umbilical, uterine and fetal middle cerebral arteries (23). Each variable was measured five times with the mean being used for analysis. Following the ultrasound portion of the session, the fHR characteristics were recorded using computerized cardiotocography (Oxford Sonicaid 8002; Oxford Instruments, U.K.). The Sonicaid system was used for 50 minutes to collect data on baseline fHR, accelerations, decelerations, short- and long-term variation, minutes of high episode, as well as maternally perceived fetal movements. These fHR variables are commonly used in fetal monitoring procedures to identify fetuses at risk of metabolic compromise (24, 25). This protocol was repeated in the afternoon sessions. Between the two sessions, participants were provided a standard lunch and mothers were encouraged to get up and move around during the break. Data analysis

We separated mothers into low and high negative and positive affect groups using a median split for each dimension. We then used repeated measures analysis of variance (ANOVA) to examine time (morning versus afternoon) by group (low or high negative or positive affect) differences in physiological parameters. Univariate analysis of variance was used to determine differences in maternal group characteristics. A p-value of <0.05 was considered significant. All statistical analyses were carried out using Stata version 12.0 (StataCorp, College Station, Texas). Results This study sample is drawn from a cohort that included women who were depressed and/or exposed to selective

serotonin reuptake inhibitor (SSRI) antidepressants; 156 women were contacted and 92 of those women met study inclusion criteria and were enrolled - 39 of these women were experiencing depression or were using SSRI antidepressants and were thus excluded from this study. Our final study sample included 53 healthy, pregnant women and their singleton fetuses. Maternal and fetal/neonatal characteristics

Table 1 illustrates maternal and fetal characteristics according to positive and negative affect. There were no differences in maternal age at birth across any affect groups. Mothers with high negative affect were more likely to be nulliparous than mothers with low negative affect (68.0% versus 55.6%); however, differences were not statistically significant. The same was true of mothers with high positive affect (65.4% versus 57.7%). Education levels also differed slightly according to affect with mothers reporting high negative affect indicating they had some postsecondary or less, more often than mothers reporting low negative affect (30.7% versus 18.5%). The opposite was true for mothers reporting high positive affect - 19.3% of those mothers reported having some postsecondary education or less compared to 29.6% of mothers reporting low positive affect. However, there were no statistically significant differences in education level across affect groups and all mothers were highly educated relative to the general population. Not surprisingly, there were significant differences across affect groups in mean Edinburgh Postnatal Depression Scale (EPDS) scores and Hamilton Depression Scale (HAM-D); however, mean scores were significantly below the cut-off values for a positive screen for depressive symptomatology in all groups (relevant cutoff values are 13 or more for the EPDS and 18 or more for the HAM-D) (26, 27). There were no significant differences in neonatal outcomes across the groups. Fetal movements, heart rate and heart rate variability

Figure 1 illustrates fetal movements, heart rate and heart rate variability across low and high negative affect groups. Fetal movement counts (as perceived by the mother) did not differ between low and high negative affect groups (F=0.21, P=0.65), nor did they differ across the day (F=0.00, P=0.95) (Fig. 1F). Basal heart rate at the onset of each study session was also not significantly different between high and low negative affect groups (F=0.57, P=0.45), and again there were 111

Impact of Maternal Positive and Negative Affect on Fetal Physiology and Diurnal Patterns

Table 1. Maternal and neonatal characteristics according to positive and negative affect N=53 Negative affect Variables

Low (n=27)

High (n=26)

Positive affect P-value

Low (n=27)

High (n=26)

P-value

Maternal characteristics, mean (sd) or count (%) Gestational age on fetal study day, weeks

36.2 (0.15)

36.0 (0.10)

0.16

36.1 (0.14)

36.1 (0.12)

0.76

Age, yrs

34.2 (4.5)

33.9 (5.2)

0.80

34.6 (5.1)

33.5 (4.6)

0.41

15 (55.6)

17 (68.0)

15 (57.7)

17 (65.4)

10 (37.0)

8 (32.0)

2 (7.4)

0 (0.0)

8 (29.6)

2 3 4

Number of previous live births 10 (38.5)

8 (30.8)

1 (3.9)

10 (40.0)

8 (30.8)

10 (38.5)

11 (40.7)

10 (40.0

11 (42.3)

10 (38.5)

3 (11.1)

4 (16.0)

4 (15.4)

3 (11.5)

5 (18.5)

1 (4.0)

3 (11.5)

0.21

0.63

Number of pregnancies

0.21

0.68

Maternal education High school or less

1 (3.7)

3 (11.5)

3 (11.1)

1 (3.9)

Some postsec

4 (14.8)

5 (19.2)

5 (18.5)

4 (15.4)

Postsec completed

10 (37.0)

12 (46.1)

11 (44.0)

10 (38.5)

Post-graduate

11 (40.7)

6 (23.1)

7 (28.0)

10 (38.5)

0.72

EPDS score

2.7 (3.2)

6.8 (4.7)

<0.01

6.3 (5.1)

3.0 (2.9)

0.01

HAM-D score

5.0 (4.7)

9.8 (5.9)

<0.01

9.6 (3.4)

5.0 (4.1)

<0.01

3450.96 (432.3)

3621.4 (643.0)

0.16

3556.7 (426.4)

3509.2 (442.0)

0.69

0.54

Neonatal characteristics Birth weight (grams) Birth length (cm)

51.9 (2.6)

51.9 (2.4)

0.99

52.2 (2.7)

51.6 (2.2)

0.38

Head circ, (cm)

35.0 (1.3)

35.4 (1.3)

0.25

35.3 (1.3)

35.2 (1.4)

0.77

Gestational age at birth, (weeks)

39.9 (1.2)

40.2 (1.1)

0.38

40.2 (1.1)

39.9 (1.2)

0.39

1 min Apgar

8.6 (0.8)

8.5 (1.2)

0.80

8.5 (1.2)

8.6 (0.8)

0.89

5 min Apgar

9.0 (0.4)

9.0 (0.3)

0.95

9.0 (0.4)

8.9 (0.3)

0.42

no significant differences between morning and afternoon (F=0.59, P=0.44) (Fig. 1A). However, differences in fHR variability indices emerged between groups and across the day. There was a significant time-by-group interaction regarding short-term variations across the day (F=3.89, P=0.05) (Fig. 1B). There was little or no change across the day among the high NA group whereas among the low NA group, short-term variations increased significantly from morning to afternoon. The number of fHR accelerations in the high NA group was significantly higher than in the low NA group (F=6.40, P=0.01) (Fig. 1C). Similar to short-term variations, durations of high-HR variability episodes remained unchanged in the high NA group, while it increased significantly in the low NA group between the morning and afternoon sessions (F=7.36, 112

P=0.009) (Fig. 1E). Long-term variations did not differ between NA groups (F=0.54, P=0.46) (Fig. 1D). Figure 2 illustrates fetal movements, heart rate and heart rate variability across low and high positive affect groups. Once again there were no statistically significant differences in fetal movements or basal heart rate between groups (Fig. 2A and 2F). There were also no statistically significant differences in short-term variability, long-term variation, and duration of high variability (Fig. 2B, 2D, 2E). However, there were significant time-group interactions in fHR accelerations (F=10.5, P=0.002). The high PA group showed very little change between morning and afternoon sessions, while the low PA group showed a statistically significant increase in fHR accelerations between the morning and afternoon session (Fig. 2C).

Gillian E. Hanley et al.

Figure 1. Means of: basal fetal heart rate (A); short-term variability (B); fetal heart rate accelerations (C); long-term variation (D); duration of high variability (E); and fetal movements/h (F) in the low and high NA group

*p<0.05; **Group-time interaction significantly different from corresponding AM value

Table 2. Mean and standard deviations for: umbilical artery pulsatility index (PI); mean uterine artery (UtA) PI; Middle Cerebral Artery (MCA) PI; MCA mean flow velocity (MVC); MCA vessel cross-sectional area; and MCA artery blood flow, in the low and high negative and positive affect groups. Negative affect

Positive affect

Variable

Low

High

P-value

Low

High

P-value

Umbilical artery PI

0.93 (0.13)

0.90 (0.17)

0.40

0.93 (0.13)

0.90 (0.17)

0.54

MCA PI

1.73 (0.35)

1.74 (0.30)

0.97

1.73(0.35)

1.74 (0.30)

0.63

MCA MVC (cm/s)

27.9 (.6)

26.4 (5.8)

0.28

27.9 (6.6)

26.4 (5.8)

0.67

MCA area (cm2)

0.10 (0.05)

0.10 (0.03)

0.93

0.10 (0.05)

0.10 (0.03)

0.36

MCA flow

167.6 (114.4)

158.9 (78.9)

0.60

167.6 (114.4)

158.9 (78.9)

0.66

Middle cerebral, umbilical and uterine artery flow characteristics

Table 2 presents mean middle cerebral artery (MCA) pulsatility index, MCA flow velocity, MCA vessel crosssectional area, and MCA total artery blood flow. There were no significant differences in any of these measures across groups, nor were there any significant time-group interactions. Table 2 also illustrates the umbilical artery pulsatility index. There were no significant differences

in any of these measures across groups, nor were there any significant time-group interactions (P>0.05). Figure 3 illustrates uterine artery mean blood flow velocity, volume flow, pulsatility index and vessel crosssectional area. In fetuses of mothers with high PA mean uterine artery blood flow velocity was significantly higher than in fetuses of mothers with low PA (F=6.03, P=0.02), and the decrease in UtA mean velocity flow between morning and afternoon was significantly different in 113

Impact of Maternal Positive and Negative Affect on Fetal Physiology and Diurnal Patterns

Figure 2. Means of: basal fetal heart rate (A); short-term variability (B); fetal heart rate accelerations (C); long-term variation (D); duration of high variability (E); and fetal movements/h (F) in the low and high PA group

Note: * p<0.05; ** Group-time interaction significantly different from corresponding AM value

mothers with high PA (F=6.03, P=0.04) (Fig. 3B). Fetuses of mothers with low NA had significantly higher UtA volume flow than mothers with high NA (F=3.83, P=0.05), and in both groups this appeared to decrease slightly between morning and afternoon (Fig. 3C). Overall uterine blood flow in the low and high NA groups when normalized to birth weight averaged 691.1Âą59.1 ml/kg and 345.5Âą27.0 ml/kg, respectively and were significantly different (p<0.01). There was no difference in the uterine artery pulsatility index by negative or positive affect (Fig. 3E, 3F). UtA vessel cross-sectional area (calculated from the vessel diameter) was significantly lower in the high NA group compared with the low NA group (P=0.04) (Fig. 3G). There was no significant difference in UtA vessel cross-sectional area between PA groups (P=0.70). Discussion We report that in a non-clinical cohort (i.e., non-psychiatric setting) a motherâ&#x20AC;&#x2122;s affect, measured using the Positive and Negative Affect Scale (PANAS), was associ114

ated with differences in fHR characteristics and uterine flow measures at 36 weeks gestation. Among fetuses of mothers reporting high levels of negative affect, there were higher rates of accelerations compared with fetuses of mothers who reported low NA. Although the higher rates of accelerations were not associated with an increase in fetal movements as perceived by the mother, this measure may underestimate fetal movements (28). Among fetuses of high NA mothers, there were no increases in fHR variability from morning to afternoon that had occurred in the low NA groups. This included measures of short-term variability and the duration of high variability episodes. Among fetuses of mothers reporting high levels of positive affect, there was also less variability between morning and afternoon for fHR accelerations, than among fetuses whose mother reported low positive affect. Among mothers reporting high NA, uterine artery mean volume flow was lower and stayed lower across the day. Mothers with high PA had higher UtA mean velocity flow across the day and showed a larger change from morning to afternoon session than mothers with low PA.

Gillian E. Hanley et al.

Figure 3. Uterine artery mean blood flow velocity according to NA (A) and PA (B), mean volume flow according to NA (C) and PA (D), uterine pulsatility index according to NA (E) and PA (F), and mean vessel cross-sectional area presented as a mean according to NA (G) and PA (H)

*p<0.05; **Group-time interaction significantly different from corresponding AM value

Uterine artery cross-sectional area was also significantly lower in mothers with high NA compared to mothers reporting low NA. Our finding of increased fHR variability across the study day in the fetuses whose mothers reported low NA is consistent with the typical diurnal variation in fHR that has been previously reported in the near-term human fetus (23, 29). While an exact mechanism involved in humans is not evident, in pregnant sheep the maternal melatonin rhythm influences fetal rhythms in activity, behavior and cardiovascular function via placental transfer (30, 31). It

is unclear why the fHR variables in the high NA group did not show the same morning to afternoon pattern; however, we have long known that there is a link between mood disorders that present with high levels of negative emotions and circadian rhythm disturbances (32, 33). The lower value of uterine blood flow in the high NA group compared to the low NA group was due to reduced values of both mean uterine artery blood flow velocity and uterine artery cross-sectional area, the two determinants of volume flow. These differences may be related to the changes in uterine blood flow during pregnancy. Although 115

Impact of Maternal Positive and Negative Affect on Fetal Physiology and Diurnal Patterns

total uterine blood flow increases progressively during gestation, uterine blood flow normalized to fetal weight decreases progressively from at least 20 weeks gestation (34). This decline in relative blood flow is associated with progressive decreases in pro-angiogenic (placental growth factor) and increases in anti-angiogenic (soluble endoglin and soluble VEGF receptor-1) factors in maternal blood with advancing gestation (35), suggesting a decrease in placental angiogenesis. Fowles et al. (36) have reported that maternal serum levels of VEGF (another pro-angiogenic factor) had a negative relationship with Center for Epidemiologic Studies â&#x20AC;&#x201C; Depression scale in low income women. Furthermore, Helbig et al. (37) found a reduction in fetal weight normalized umbilical venous volume flow with no change in umbilical arterial pulsatility index in relation to increasing maternal psychological distress. They also found no changes in uterine artery pulsatility index, suggesting the volume flow rather than vascular resistance indices is a more important variable to measure in such studies. In the current study the lower value of uterine blood flow in the high NA group was not associated with a lower birth weight. However, birth weight is a poor indicator of fetal growth; rather it is the extent to which individual fetuses meet their growth potential that is more important (38). A number of key limitations need mentioning. First, we assumed the mood differences were the main independent variables, and randomization between the groups was not possible. As a result, not accounting for unmeasured maternal illness characteristics may have contributed to an ascertainment bias. Second, our sample size was small and there were frequently differences between the groups that did not reach statistical significance. Further research should examine the effect of maternal affect on fetal vascular and fHR in a larger sample. Finally, we did have two mothers who delivered before 37 weeks, but their blood flow measures were not significantly different from the mothers who delivered after 37 weeks, making it unlikely that we observed early signs of preterm labor. It is possible that the PANAS measurements may suffer from some social desirability bias; however, as there is considerable variation in scores, and many mothers who reported high negative affect and low positive affect, we consider the possibility of social desirability bias unlikely. While we excluded mothers who suffered from significant maternal, obstetrical and fetal conditions, it is possible that there were differences in maternal health status across the affect groups. Finally, we were also unable to examine neonatal short- and long-term outcomes in this study. 116

In summary, even in euthymic mothers, those who report high levels of negative affect showed reduced uterine artery flow, decreased fHR variability, an altered diurnal pattern, and decreased uterine artery cross-sectional area. These findings suggest that even in the absence of an Axis I MDD, maternal affect may impact on fetal and uterine physiology. Further studies are needed to examine the mechanisms that link maternal affect and fetal cardiovascular function, as well as to investigate all of the potentially relevant and interacting physiologic variables. While we report no difference in birth weight, birth length, head circumference, gestational age, and 1- and 5-minute Apgar scores of infants according to maternal affect groups (Table 1), further research should examine alternative neonatal outcomes. Implications for maternal care during gestation remain to be determined. References 1. Murphy PA. Origins: How the nine months before birth shape the rest of our lives. New York: Free Press, 2010. 2. Vesga-Lopez O, Blanco C, Keyes K, Olfson M, Grant BF, Hasin DS. Psychiatric disorders in pregnant and postpartum women in the United States. Arch Gen Psychiatry 2008;65:805-815. 3. Charney DS. Psychobiological mechanisms of resilience and vulnerability: Implications for successful adaptation to extreme stress. Am J Psychiatry 2004;161:195-216. 4. Pressman SD, Cohen S. Does positive affect influence health? Psychol Bull 2005;131:925. 5. Veenhoven R. Healthy happiness: Effects of happiness on physical health and the consequences for preventive health care. J Happiness Stud 2008;9:449-469. 6. Watson D, Pennebaker JW. Health complaints, stress, and distress: Exploring the central role of negative affectivity. Psychol Rev 1989;96:234. 7. Bood SĂ&#x2026;, Archer T, Norlander T. Affective personality in relation to general personality, self-reported stress, coping, and optimism. Indiv Diff Res 2004;2:26-37. 8. Chung TKH, Lau TK, Yip ASK, Chiu HFK, Lee DTS. Antepartum depressive symptomatology is associated with adverse obstetric and neonatal outcomes. Psychosom Med 2001;63:830-834. 9. Grote NK, Bridge JA, Gavin AR, Melville JL, Iyengar S, Katon WJ. A meta-analysis of depression during pregnancy and the risk of preterm birth, low birth weight, and intrauterine growth restriction. Arch Gen Psychiatry 2010;67:1012-1024. 10. Field T, Diego M, Hernandez-Reif M. Prenatal depression effects and interventions: A review. Infant Behav Dev 2010;33:409-418. 11. Misri S, Oberlander TF, Fairbrother N, Carter D, Ryan D, Kuan AJ, et al. Relation between prenatal maternal mood and anxiety and neonatal health. Can J Psychiatry 2004;49:684-689. 12. Talge NM, Neal C, Glover V. Antenatal maternal stress and long-term effects on child neurodevelopment: How and why? J Child Psychol Psychiatry 2007;48:245-261. 13. Austin MP, Hadzi-Pavlovic D, Leader L, Saint K, Parker G. Maternal trait anxiety, depression and life event stress in pregnancy: Relationships with infant temperament. Early Hum Dev 2005;81:183-190. 14. Allister L, Lester BM, Carr S, Liu J. The effects of maternal depression on fetal heart rate response to vibroacoustic stimulation. Dev Neuropsychol 2001;20:639-651. 15. Monk C, Fifer WP, Myers MM, Sloan RP, Trien L, Hurtado A. Maternal

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stress responses and anxiety during pregnancy: effects on fetal heart rate. Dev Psychobiol 2000;36:67-77. 16. Monk C, Myers MM, Sloan RP, Ellman LM, Fifer WP. Effects of women’s stress-elicited physiological activity and chronic anxiety on fetal heart rate. J Dev Behav Pediatr 2003;24:32. 17. Monk C, Sloan RP, Myers MM, Ellman L, Werner E, Jeon J, et al. Fetal heart rate reactivity differs by women’s psychiatric status: An early marker for developmental risk? J Am Acad Child Adolesc Psychiatry 2004;43:283-290. 18. Steptoe A, Wardle J. Positive affect and biological function in everyday life. Neurobiol Aging 2005;26:108-112. 19. Archer T, Adolfsson B, Karlsson E. Affective personality as cognitiveemotional presymptom profiles regulatory for self-reported health predispositions. Neurotox Res 2008;14:21-44. 20. Norlander T, Bood SAK, Archer T. Performance during stress: Affective personality, age, and regularity of physical exercise. Soc Behav Pers 2002;30:495-508. 21. Cox J, Holden J, Sagovsky R. Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale. Br J Psychiatry 1987;150:782-786. 22. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960;23:56-62. 23. Rurak D, Lim K, Sanders A, Brain U, Riggs W, Oberlander TF. Third trimester fetal heart rate and Doppler middle cerebral artery blood flow velocity characteristics during prenatal selective serotonin reuptake inhibitor exposure. Pediatr Res 2011;70:96. 24. Dawes GS, Moulden M, Redman CW. Improvements in computerized fetal heart rate analysis antepartum. J Perinat Med 1996;24:25-36. 25. Hamilton EF, Warrick PA. New perspectives in electronic fetal surveillance. J Perinat Med 2013;41:83-92. 26. Matthey S, Henshaw C, Elliott S, Barnett B. Variability in use of cutoff scores and formats on the Edinburgh Postnatal Depression Scale - implications for clinical and research practice. Arch Womens Ment Health 2006;9:309-315. 27. Cusin C, Yan H, Yeung A, Fava M. Rating scales for depression. In: Bair

L, Blais MA, editors. Handbook of clinical rating scales and assessment in psychiatry and mental health. New York: Humana, 2010: pp. 7-35. 28. Hijazi ZR, East CE. Factors affecting maternal perception of fetal movement. Obstet Gynecol Surv 2009 quiz 499; 64:489-497. 29. Visser G, Goodman J, Levine D, Dawes G. Diurnal and other cyclic variations in human fetal heart rate near term. Am J Obstet Gynecol 1982;142:535. 30. Houghton D, Walker DW, Young IR, McMillen IC. Melatonin and the lightdark cycle separately influence daily behavioral and hormonal rhythms in the pregnant ewe and sheep fetus. Endocrinology 1993;133:90-98. 31. Zemdegs I, McMillen IC, Walker W, Thorburn G, Nowak R. Diurnal rhythms in plasma melatonin concentrations in the fetal sheep and pregnant ewe during late gestation. Endocrinology 1988;123:284-289. 32. Wirz-Justice A. Chronobiology and mood disorders. Dialogues Clin Neurosci 2003;5:315. 33. Wirz-Justice A. Biological rhythm disturbances in mood disorders. Int Clin Psychopharmacol 2006;21:S11. 34. Konje JC, Kaufmann P, Bell SC, Taylor DJ. A longitudinal study of quantitative uterine blood flow with the use of color power angiography in appropriate for gestational age pregnancies. Am J Obstet Gynecol 2001;185:608-613. 35. Romero R, Nien JK, Espinoza J, Todem D, Fu W, Chung H, et al. A longitudinal study of angiogenic (placental growth factor) and antiangiogenic (soluble endoglin and soluble vascular endothelial growth factor receptor-1) factors in normal pregnancy and patients destined to develop preeclampsia and deliver a small for gestational age neonate. J Matern Fetal Neonatal Med 2008;21:9-23. 36. Fowles ER, Murphey C, Ruiz RJ. Exploring relationships among psychosocial status, dietary quality, and measures of placental development during the first trimester in low-income women. Biol Res Nurs 2011;13:70-79. 37. Helbig A, Kaasen A, Malt UF, Haugen G. Does antenatal maternal psychological distress affect placental circulation in the third trimester? PLoS ONE 2013;8:e57071. 38. Bukowski R. Fetal growth potential and pregnancy outcome. Semin Perinatol 2004;28:51-58.

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Isr J Psychiatry Relat Sci - Vol. 51 - No 2 (2014)

Gender Differences in the Prevalence and Correlates of Psychotropic Medication Use among Older Adults in Israel Tzvia Blumstein, MA,1 Yael Benyamini, PhD,2 Dov Shmotkin, PhD,3 and Liat Lerner-Geva, PhD, MD1,4 1

The Gertner Institute for Epidemiology and Health Policy Research, Tel Hashomer, Sheba Medical Center, Ramat Gan, Israel Bob Shapell School of Social Work, Tel Aviv University, Tel Aviv, Israel 3 The Herczeg Institute on Aging, Tel Aviv University, Tel Aviv, Israel 4 Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel 2

Abstract Background: This study evaluates gender differences in the prevalence of psychotropic medications use among elderly Israelis and the socio-demographic, physical and mental health correlates of their use. Method: Data were taken from a national survey that sampled the community-dwelling Jewish population aged 65-94 in Israel. Psychotropic medications were assessed from the list of all medications recorded during a faceto-face interview. The current analysis focused on three medication groups: anxiolytics, sedatives/hypnotics and antidepressants. Results: A significantly higher use of anxiolytics was observed among women compared to men after taking into account their worse physical and mental health. Age, not being married, sleeping problems and depressive symptoms were significant correlates among men while number of non-psychotropic medications, any life trauma and being married correlated with use of anxiolytics and sedatives/hypnotics among women. The use of antidepressants was low in men and women and was related mainly to disability in ADL. Conclusions: This study points to possibly overprescribing of anxiolytics among women and low detection and treatment of depression among the elderly in general.

Introduction The proportion of the population aged 65 years and over in Israel, estimated around 10.0% in 2011, has remained steady since 1995, and is expected to grow to 14.6% by 2035 (1). People in this age group are high users of prescription and nonprescription medications because of increasing levels of chronic comorbidities (2, 3). Consequently, this increase includes higher use of psychotropic medications as compared to younger age groups (4). An Israeli national health survey conducted in 2003-2004 showed that 6.9% of the adult population (over the age 20) report using psychotropic drugs; this rate increased to 12.6% for age group 60-69, and 22.9% for age 70 and over (5). Similar findings were published by another Israeli community study of older adults aged 75-94, where rates increased from 24% in the early 1990s to 28% in the early 2000s (6). The literature reports potentially adverse consequences in the long-term use of benzodiazepines, which is the main ingredient in most sedative, hypnotic and antianxiety medications. Recently, among older people with dementia, use of central nervous system medications was linked to a high number of drug-related problems such as syncope, fatigue, delirium, falls and fractures (7). Other adverse consequences among the general older population include reduced cognitive function (8, 9), increased risk of falls (10) leading to hip-fractures (11, 12), increased depressed affect (13) and lower subjective and objective sleep quality (14). Cross-sectional comparisons of use of psychotropic medications consistently showed a higher use of psychotropic medications among women in all adult age groups (15, 16), among old and old-old people (17-19) and across

Address for Correspondence: Tzvia Blumstein, MA, Women and Childrenâ&#x20AC;&#x2122;s Health Research Unit, The Gertner Institute, Sheba Medical Center, Tel Hashomer, Ramat Gan 52621, Israel â&#x20AC;&#x2020; tzviabl@gertner.health.gov.il

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numerous countries (20). Similar results were observed in studies focusing on the use of benzodiazepines in the general population (21) and in older age groups (22). Findings were less consistent when specific classes of medications were analyzed. In several studies the gender gap was shown for anti-anxiety agents and sedative/hypnotics combined (17,18, 23). In another study of older adults, women had a significantly higher risk of using all psychotropic, antidepressant and antianxiety drugs, but use of sedatives was not significantly different across gender (24). These findings were shown after taking into account gender differences in sociodemographics as well as physical and mental health measures. The current study aimed to evaluate gender differences in the prevalence of psychotropic medications in community dwelling adults aged 65-94, and to compare factors associated with psychotropic medications use among elderly women and men. Methods Participants and Procedure

The sample used for this research was the Israeli Multidisciplinary Aging Study (IMAS). The IMAS conducted a multidimensional assessment of a random sample of the older Jewish population in Israel stratified by age group (65-69, 70-74, 75-79, 80-84, 85-89, 90-94), gender, and place of birth (Israel, the Middle East or North Africa, and Europe or America). The sample was drawn from the National Population Registry (NPR) in December 1999. Out of 1,757 sampled individuals, 825 individuals were fully interviewed during 2000-2002 (15.1% were not located, 32.3% refused, and 5.7% could not be fully interviewed): 721 (87%) in person and 104 (13%) by proxy. Proxy interviews were not included in the current study because cognitive and emotional correlates of medication use were not assessed for proxy interviewees. Thus, the current study included all participants living in the community at the time of the baseline interview and personally interviewed (n=721). The study was approved by the Institutional Review Board of the Sheba Medical Center and all participants signed an informed consent form before the interview. A description of the IMAS study design and results have been published elsewhere (6, 25). Measures

Psychotropic medications were assessed from the list of all medications recorded by the interviewer. Interviewees were asked if they were currently taking prescribed or

self-prescribed drugs for a specified list of medical conditions (heart disease, hypertension, diabetes, kidney disease, sleeping difficulties, depression, etc.). They were requested to display the containers of all medications they were taking, and the name, frequency, and duration of use were recorded. A coding system was developed whereby each drug was given a four digit code: the first two digits represented the therapeutic class according to the classification by the Monthly Ethical Drug Indexed Compilation (26) (a bi-monthly publication of all products according to their indications), and the next two served for assigning a number for every drug in the group. For the purpose of the present analysis, a clinician reviewed only drugs in the following CNS therapeutic groups, namely, hypnotics and sedatives, tranquillizers and antidepressants (as classified in the original coding system described above), and the generic name was retrieved through the Medic and converted into the Anatomical Therapeutic and Chemical (ATC) classification system (27). A detailed description of the original coding system and the process of conversion to ATC categories have been published in a previous paper devoted to a comparison of psychotropic medication use between two cohorts, 1989 vs. 1999 (6). Variables from three domains of interest were examined as correlates of use of psychotropic medications: sociodemographic characteristics, physical health and functioning, and mental health and life events indicators. Socio-demographic variables included age, gender, place of birth (born in Israel, Asia-Africa, Europe-America), education (number of school years), marital status (married versus currently unmarried), income (having only a National Insurance pension versus additional income resources), and religiousness (self-defined as religious, traditional, or secular). Physical health and functioning variables included: Number of diseases (comorbidity) was measured by the number of ever diagnosed diseases reported by the respondent out of a list of 18 chronic diseases (e.g., hypertension, diabetes, cardiac disease, stroke, arthritis, cancer). Number of other (non-psychotropic) medications was categorized into four categories: none, 1-2, 3-5, and 6+ medications. Physical functioning was measured by a modified version of the Katz activities of daily living (ADL) scale (28). The ADL indicator was defined as a need for human assistance in performing one or more of seven activities: crossing a small room, washing, dressing, eating, grooming, transferring from bed to chair, and toileting. 119

Gender Differences in Psychotropic Medication Use among Older Adults in Israel

Difficulty in physical robustness was measured by a scale that assessed activities requiring physical robustness (29, 30), consisting of seven items, each rating the difficulty of performing a certain activity (pushing or pulling heavy objects, bending, crouching or stooping, walking up to 1 km, climbing 10 stairs, lifting or carrying weight up to 5 kg, and stretching the right or left arm above the shoulder) on a scale of 0 (no difficulty), 1 (some difficulty), 2 (much difficulty) and 3 (cannot do). The measure’s sum score ranged from 0 to 21 was recoded to a three-level variable; low, moderate and high difficulty. The number of monthly visits to a family physician was recoded as a three-level variable: no visits (0), one visit (1), and 2 or more visits (2). Mental health and life events variables included: Sleeping problems were defined as a positive answer to one or both of the following questions: (a) Do you have difficulties falling asleep? and, (b) Do you wake up early in the morning and cannot fall asleep again? Affective functioning was measured by the Center for Epidemiological Studies - Depression scale (CES-D) (31), consisting of 20 items depicting depressive symptoms experienced in the last month and scored each on a scale from 0 (not at all), 1 (sometimes), 2 (most of the time), to 3 (almost every day). The Cronbach alpha coefficient of internal reliability was 0.87 in the full sample. The summary score of all responses (ranged 0-60) was then categorized to a three-level variable; low depressive symptoms (0-10), moderate (11-16), and high (17+), which corresponds to an accepted cut-off point for the definition of high depressive symptoms. Cognitive functioning was measured by the OrientationMemory-Concentration Test (32). This measure includes six test items referring to basic cognitive functions such as knowing the current date and time, remembering a name and an address, and counting backwards (α=0.72). As initially suggested, the total scores (range 0-28) were categorized into three levels: normal cognitive status estimated by a score of 0-8, slight impairment 9-19, and significant impairment 20-28. Holocaust survivorship was defined according to (a) the participant’s report that during 1939-1945 he or she had been in any European country occupied or dominated by the Nazi regime, and (b) a positive answer to the question “Do you define yourself as a Holocaust survivor?” Traumatic life events - the number of traumatic events was measured by the question, “Have you ever undergone a traumatic event that has influenced your entire life?” with an option to list up to three such events. The response 120

was recoded into a dichotomous variable denoting no report of such events (0) or one or more events (1). Statistical Analysis

Differences in the level of psychotropic medication use across categories of independent variables and between men and women were tested by using chi-square tests for categorical variables. The final multivariate logistic regression models included those indicators found to be significantly related to the combined anxiolytics and sedatives/hypnotics medication group within a set of univariate analyses. Age, gender and origin (the stratification variables in the sampling design) were included irrespective of their association with use of medications. The analysis for the combined anxiolytics and sedatives/hypnotics group was also performed separately for anxiolytics and for sedatives/hypnotics. The analysis for antidepressants group included the same correlates of interest as assessed for the combined anxiolytics and sedatives/hypnotics group. All analyses were performed using SPSS 15.0. Results The comparison of sociodemographic characteristics and other study variables between men (n=374; 51.9%) and women (n=347; 48.1%) is presented in Table 1. Although the sample was stratified by age group, gender and place of birth, the comparison of age group distribution and mean age showed that men were significantly older, probably due to a higher response rate among older men. Men had significantly higher education, more sources of income, and a higher rate of being married. On the other hand, women had significantly higher comorbidity, used more non-psychotropic medications and reported lower levels of physical functioning. The comparison of mental health indicators also showed that women reported more sleeping problems, impaired cognitive status, depressive symptoms, and past trauma than men. Table 2 presents the crude rates of psychotropic medications use. Women used significantly more anxiolytics (19.9%) and sedatives/hypnotics (12.7%) as compared to men (8.0% and 8.6%, respectively). No significant gender differences were observed for antidepressants, antipsychotics or antiepilectics. The last two therapeutic groups were not analyzed any further in the current analysis due to their very low use in this community sample. Anxiolytics and sedatives/hypnotics were analyzed both separately and as a combined outcome group

Tzvia Blumstein et al.

Table 1. Descriptive Characteristics of the Participants by Gender: The Israeli Multidisciplinary Aging Study Characteristic

Men (n=374) %

Women (n=347) %

Chi Square

Characteristic

Men (n=374) %

Women (n=347) %

Sociodemographic characteristics

Number of non- psychotropic drugs

Age

None

17.0

10.8

χ²=(3)8.99*

65-69

17.9

23.9

1-2

27.0

25.6

70-74

17.9

23.9

3-5

33.4

75-79

21.9

19.3

22.6

30.2

80-84

18.7

14.1

Need of assistance with ADLs

85-89

13.9

12.4

84.5

74.9

90-94

9.6

6.3

Yes

15.5

25.1

Mean age

78.7±7.7

76.8±7.7

Place of birth

χ²(3)=11.09*

χ²=(2)10.25**

Difficulty in physical robustness χ²=(2)3.47

χ²=(2)38.53***

Low

48.7

27.1

Asia-Africa

36.9

31.4

Moderate

27.2

32.3

Europe-America

32.4

32.0

High

24.2

40.6

Israel

30.7

36.6

School years

Monthly number of physician visits χ²(3)=11.81**

χ²=(2)5.53

None

71.4

64.0

0-4

10.9

20.1

One

19.0

21.6

5-8

24.6

24.5

Two or more

9.6

14.4

9-12

35.0

28.9

Mental health & life events

13+

29.4

26.4

Sleeping problem

Missing (n)

(17)

(29)

Marital status

χ²=(1) 69.76***

χ²=(1)34.77***

38.8

18.8

Yes

61.2

81.2

Married

72.6

41.8

Cognitive status

Not married

27.4

58.2

Normal

71.3

60.9

Missing (n)

(6)

(2)

Moderate

26.3

28.4

Impaired

2.4

10.7

(5)

(9)

Sources of income

χ²=(1)8.55**

Only social security

16.0

24.9

Missing

Additional income

84.0

75.1

Depressive symptoms

Missing (n)

(12)

(10)

Religious identification

χ²=(2)1.78

χ²=(2)21.81***

χ²=(2)29.06***

Low

42.2

25.3

Moderate

32.7

32.6

Religious

20.7

19.5

High

25.1

42.1

Traditional

38.9

43.7

Missing (n)

(57)

(27)

Secular

40.5

36.7

Any life trauma

Missing (n)

(6)

(4)

72.5

58.2

Yes

27.5

41.8

Health and physical functioning Number of diseases

χ²(4(=19.20**

Chi Square

χ²=(1)16.19***

Holocaust survivor

χ²=(1)0.14

None

10.4

9.9

85.9

86.2

19.8

13.1

Yes

14.1

13.8

2-3

37.2

30.9

Missing (n)

(10)

(3)

4-5

19.3

21.6

24.5

***p<0.0001; **p<0.01; *p<0.05 Note: Age, gender and place of birth served as stratification variables in the sampling design

121

Gender Differences in Psychotropic Medication Use among Older Adults in Israel

Table 2. Patterns of Psychotropic Medications Use among Participants of the Israeli Multidisciplinary Aging Study (age 65-94) Type of Drugs

Total (n=721) %

Men (n= 374) %

Women (n=347) %

Statistical tests¹ χ²

65-79 (449) %

80-94 (n-272) %

Statistical tests¹

Anxiolytics

13.7

8.0

19.9

χ²=21.39***

14.0

13.2

χ²=0.09

Sedatives/Hypnotics

10.5

8.6

12.7

χ²=3.25*

6.7

16.8

χ²=18.8***

Antidepressants

4.0

3.7

4.3

χ²=0.16

3.6

4.8

χ²=0.65

Antipsychotics²

1.1

0.5

1.7

χ²=2.34

1.6

0.4

χ²=2.19

Antiepileptic²

1.7

1.6

1.7

χ²=0.017

2.2

0.7

χ²=2.30

Anxiolytics & Sedatives/hypnotics (Benzodiazepines only)

21.6 (20.2)

15.0 (13.9)

28.8 (28.1)

χ²=20.35***

18.7

26.5

χ²=6.02**

¹ Chi Square test for differences between men and women and between two age groups (Degree of freedom=1) ² These categories were excluded from further analysis due to very low use in both gender groups. ***p<0.0001; **p<0.01; *p<0.05

since this last group contained over 90% benzodiazepines. Comparing the use of these psychotropic medication groups by two age groups (65-79 vs. 80-94) showed a significant higher use of sedatives/hypnotics among the old-old (Table 2). The tests for the associations of each characteristic with the use of the two groups of psychotropic medications, based on the full sample, showed that increasing age, gender (women), place of birth (Europe/America) and marital status (not married) were significantly associated with a higher use of anxiolytics and sedatives/hypnotics. Use of antidepressants was unrelated to gender (data not shown). The univariate analysis also showed that health status measures, physical functioning variables and depressive symptoms were associated significantly with both antidepressants and anxiolytics and sedatives/ hypnotics combined, while sleeping problems and past traumas were associated positively and significantly only with use of anxiolytic & sedatives/hypnotics. Multivariate analysis for use of anxiolytics and sedatives/hypnotics in the full sample (Table 3) showed a significant increased odds for use with each advancing year (O.R.=1.06; 95%CI =1.02-1.09) in all participants and in men but not in women. Women had a significantly higher risk compared to men (O.R.=1.86; 95% CI=1,182.93). Other measures positively and significantly related to the use of anxiolytics and sedatives/hypnotics were the number of other medications, sleeping problems, and depressive symptoms. Age, sleeping problems and depressive symptoms were significantly related to the use of this group of medications only among men while the number of non-psychotropic medications and any life trauma were significantly related only among women. The results of the tests for estimating an interaction effect of gender with each predictor for anxiolytics and 122

sedatives/hypnotics are not shown since only marital status interacted significantly with gender (p=0.001). The multivariate analysis stratified by gender showed that being married was associated with increased odds (with borderline significance) of use of these medications among women, but with significantly lower odds among men. In a set of multivariate logistic regression analyses performed separately for anxiolytics and for sedatives/hypnotics, the results showed that gender differences remained significant only for anxiolytics. Sleeping problems were a significant predictor for both groups of medications while depressive symptoms were a significant predictor for use of sedatives/hypnotics but not for use of anxiolytics (data not shown). Multivariate analysis for the use of antidepressants showed no significant difference in the level of use of these medications between men and women (Table 4). High depressive symptoms were associated with an over two-fold risk for use of antidepressants only among men (although with no statistical significance). Those disabled in ADL showed higher odds of use compared to those not disabled (with borderline significance in men and the full sample). Discussion Gender differences in rates of psychotropic medications

The findings in the current study point to a significantly higher use of anxiolytics, as well as anxiolytics and sedatives/hypnotics combined, among women compared to men, after taking into account women’s worse physical and mental health. These findings are in line with findings from Australia and Britain on benzodiazepine use (19, 33),

Tzvia Blumstein et al.

Table 3. Multivariate Logistic Regression Models for Use of Sedatives/Hypnotics & Anxiolytics Medications by Gender All Characteristics

Men

Women

O.R.

95% CI

p-value

O.R.

95% CI

p-value

O.R.

95% CI

p-value

Age (continuous)

1.06

1.02-1.09

0.001

1.09

1.04-1.14

<0.0001

1.03

0.99-1.08

0.17

Gender (women vs. men)

1.86

1.18-2.93

0.008

Sociodemographic characteristics

Place of birth

0.137

0.33

0.34

Asia-Africa vs. Israel

0.76

0.45-1.30

0.32

0.87

0.35-2.12

0.75

0.66

0.33-1.32

0.24

Europe-America vs. Israel

1.29

0.78-2.10

0.32

1.56

0.68-3.62

0.30

1.08

0.57-2.05

0.82

Married vs. not married

1.06

0.68-1.67

0.80

0.49

0.25-0.97

0.04

1.74

0.96-3.16

0.07

Number of diseases

1.05

0.93-1.19

0.41

1.17

0.93-1.48

0.18

1.02

0.87-1.19

0.80

Number of non-psychotropic medications

1.18

1.11-1.29

0.003

1.09

0.90-1.31

0.40

1.20

1.05-1.37

0.008

Need of assistance with ADLs - Yes vs. No

1.46

0.80-2.67

0.22

2.34

0.80-6.80

0.12

1.06

0.5-2.26

0.89

Difficulty in physical robustness

0.92

0.65-1.30

0.63

0.82

0.48-1.43

0.50

1.07

0.68-1.69

0.77

Sleeping problems - Yes vs. No

2.69

1.48-4.87

0.001

3.57

1.48-8.61

0.005

2.00

0.86-4.63

0.11

Moderate vs. low

1.15

0.65-2.05

0.63

1.26

0.52-3.03

0.61

1.25

0.55-2.84

0.60

High vs. low

1.98

1.07-3.64

0.03

3.26

1.28-8.28

0.01

1.84

0.77-4.4

0.17

Any life trauma

1.18

0.77-1.80

0.45

0.78

0.36-1.68

0.53

1.60

0.93-2.75

0.09

Depressive symptoms

0.042

0.106

0.32

O.R. = Odds Ratio; CI = Confidence Interval

and with a U.S. study, where elderly women were more likely than elderly men to use all psychotropic agents, and one and a half times more likely to use anti-anxiety and antidepressants but not more likely to use sedatives (24). Data from two national health surveys of U.S. adults (17+) showed significant age-adjusted gender differences in the same direction for any psychotropic medication use, antidepressant use and the use of anxiolytics/sedatives/ hypnotics combined (34). The current study did not show significant gender difference in use of antidepressants unlike the findings in the above cited studies. This could be due to the lack of statistical power in detecting gender differences in a low level outcome variable such as the use of antidepressants (3.7% in men; 4.3% in women). Several explanations were suggested in the literature for the gender gap in the use of psychotropic medications. First, this gap was naturally linked to higher levels of anxiety and depressive disorders observed among women (35-37). Yet, this argument cannot explain the gender gap in studies that, similar to ours, showed higher female use independent of psychiatric morbidity (38, 39) and higher use of benzodiazepines in women with no diagnosed disorder of anxiety or insomnia (21). A second explanation is related to patientsâ&#x20AC;&#x2122; health behavior. It has been suggested that women more commonly complain of psychological symptoms, more frequently

seek professional help, and consequently are more likely to be prescribed a psychotropic medication (38). In the current investigation, however, the frequency of monthly visits to the family physician was not related to the use of psychotropic medications and did not reduce gender differences in use of anxiolytics and sedatives/hypnotics when adjusted for within the multivariate model (data not shown). The observed gender gap was also viewed and studied as a gender bias from the perspective of the primary care providers who may be less stringent when prescribing these medications for women (21, 38). Lay people are also more likely to identify mental health disorders among women (40), which can also lead to gender differences in health care seeking for symptoms of mental ill-health. In a body of research devoted to assessing inappropriate drugs prescription, findings indicated that older women were more likely to be prescribed inappropriate drugs in community-based settings (41-43). In several studies, the inappropriate prescriptions included psychotropic drugs (20, 41, 44, 45) or benzodiazepines (46) . These findings reflect the importance of further understanding the sources of the gender differences in the use of psychotropic medications. If women tend to complain more of depressive symptoms and therefore receive more medical treatment, it may then be important to encour123

Gender Differences in Psychotropic Medication Use among Older Adults in Israel

Table 4. Multivariate Logistic Regression Models for Use of Antidepressants by Gender All Characteristics

O.R.

Men

Women

95% CI

p-value

O.R.

95% CI

p-value

O.R.

95% CI

p-value

1.05

0.96-1.14

0.32

0.94

0.85-1.03

0.18

Sociodemographic characteristics Age (continuous)

0.99

0.93-1.05

0.72

Gender (women vs. men)

0.90

0.37-2.16

0.81

Asia-Africa vs. Israel

0.64

0.24-1.72

0.37

0.36

0.08-1.69

0.20

1.15

.28-4.75

0.85

Europe-America vs. Israel

0.68

0.26-1.78

0.43

0.41

0.10-1.71

0.22

0.91

.23-3.65

0.89

Married vs. not married

1.84

0.71-4.80

0.21

1.82

0.44-6.60

0.41

1.65

0.46-5.93

0.45

Number of diseases

1.11

0.83-1.36

0.40

1.18

0.79-1.74

0.43

1.18

0.83-1.67

0.35

Number of non-psychotropic medications

1.05

0.85-1.28

0.67

1.03

0.74-1.43

0.87

1.01

0.76-1.34

0.94

Need of assistance with ADLs - Yes vs No

3.03

0.97-9.52

0.06

6.36

0.86-47.0

0.07

2.76

0.58-13.1

0.20

Difficulty in physical robustness

1.11

0.55-2.23

0.77

0.54

0.17-1.72

0.30

1.62

0.64-4.09

0.31

Sleeping problems -Yes vs. No

0.89

0.33-2.42

0.82

1.47

0.34-6.3

0.60

0.46

0.11-1.87

0.28

High vs. Low & Moderate Depressive symptoms¹

0.95

0.36-2.48

0.92

2.49

0.62-9.92

0.20

0.47

0.12-1.91

0.29

Any life trauma

1.37

0.59-3.17

0.46

1.56

0.41-5.95

0.51

1.79

0.57-5.65

0.32

Place of birth

0.60

0.32

O.R. = Odds Ratio; CI = Confidence Interval; ¹Depressive symptoms was collapsed in this table from three to two categories (0-16, 17+).

age men’s reporting of depressive symptoms and seeking care for themselves (47). Thus, health care providers may need to ensure that reporting mental health problems is perceived as legitimate by male patients and does not threaten their identity or masculinity (48, 49). On the other hand, it is possible that health providers are more inclined to attribute somatic complaints in women to mental health conditions and therefore over-prescribe an inappropriate treatment. In the latter case, steps should be taken to reduce excessive prescribing to older women. Gender-specific risk factors for use of anxiolytics & sedatives/hypnotics

In our study, no significant interactions were observed between the studied correlates of medication use and gender, except for marital status. Thus, our findings support some research findings showing that physical and mental health risk factors are associated similarly with use of long term benzodiazepines among men and women (22) or with use of any psychotropic drug (50). In contrast, other findings demonstrate gender differences in the associations of office visits to general practitioners with anxiolytic, antidepressant and benzodiazepines use (21, 45). As stated above, marital status varied significantly in its association with use of anxiolytics and sedatives/hypnotics combined across gender groups. Married men were at a significantly lower risk and women at a borderline higher 124

significant risk than unmarried elderly to use anxiolytics and sedatives/hypnotics. This finding is not in line with results from a Swedish investigation where divorced or widowed women were more extensive psychotropic drug users than married women, with no di respective marital categories (50). However, in that study, both single men and women were at the lowest risk. In our sample, less than 2% of participants were single, and therefore could not be studied separately from widowed/ divorced elderly. The proposition that a woman spouse can facilitate access to medical treatment by encouraging the husband to consult a physician or specialist (51) was not supported in this study. On the contrary, among men, a spouse was associated with significantly less use of anxiolytics and sedatives, after taking into account men’s lower rate of sleeping problems and depressive symptoms, thus suggesting a higher sense of psychological wellbeing among married men in comparison to those widowed or divorced. Several studied indicators (age, number of non-psychotropic medications, sleeping problems and depressive symptoms) showed differential trends of associations among men and women. High depressive symptoms and sleeping problems were associated with a significant three-fold risk of using anxiolytics and sedatives combined among men, while among women the almost two-fold risk was not significant. Also, the number of other medications was a significant risk factor for women

Tzvia Blumstein et al.

and not for men. These variations only partly resemble findings from a U.S. study, where psychotropic drug use was strongly correlated with depressive symptoms in both genders, yet correlated with sleeping problems only in men and with medical conditions only in women (23). The adjusted risk for any life trauma was a borderline significant risk factor among women (but not among men), in line with other findings relating women’s depression to a wide range of life events while men’s depression is more closely linked to their own health status (52). As shown previously, the use of sedatives/hypnotics was significantly higher among the old-old (80+), while age was actually related to use of these medications only among men. These findings suggest that current medication use among old-old women may continue to reflect past prescribing habits whereas, among old-old men, increasing age and consequently sleeping problems seem to determine a higher medication use. Use of antidepressants

Due to the statistical limitation in assessing significant multivariate results for use of antidepressants, only trends in the associations of the studied correlates with the use of this kind of medications can be discussed. The high odds for use of antidepressants in both women and men with ADL disability has been observed previously in an analysis for all psychotropic drugs using IADL disability as an indicator of functioning (24). These findings indicate that depression often co-occurs with multiple health, functioning and psychosocial problems, and is not always perceived by the elderly and their physicians as high priority (53). A second observation in the current analysis relates to the surprising lack of association between high depressive symptoms and use of antidepressants among women. Men with high depressive symptoms had a non-significant, over two-fold risk for use of antidepressants, but women showed non-significant odds in the opposite direction. This observation strengthens the concern that physician’s attitudes toward women’s mental health complaints are different from their attitudes toward men’s complaints. It is likely that past prescribing of benzodiazepines for women was not updated in response to potential changes in women’s complaints along the aging process. As a result, women were at a higher risk of not being properly treated. Limitations One of the limitations in this study concerns a lack of clinical diagnosis of depression and other specific

mental disorders. For assessment of depression, we used an accepted cut-off point on the CES-D depressive symptoms scale. However, since only cognitivelynormal respondents, who were able to answer the self-report questions, were included in this study, one may assume that self-reports in this study were reasonably accurate. Another limitation is the time that has passed since the data were collected, which raises a question as to more recent changes in prescribing psychotropic medications, particularly antidepressants. Thus, according to empirical evidence in Western countries, the use of antidepressants has increased in the last two decades (34). However, the current findings can serve as a basis for evaluating future changes in prescribing these medications. Another limitation relates to the exclusion of proxy participants and residents of old-age homes, which presents a bias in the representation of the original national sample. Nevertheless, since the focus of this investigation concerns gender differences, the estimation of crude rates of medication use among men and women was performed employing the full sample (including proxies), and the results indicated similar gender gap in using anxiolytics and sedatives/hypnotics combined (15% among men and 29.6% among women). In addition, all stratification variables were included in the multivariate analyses as accepted in population surveys for stratified sampling design (54). Conclusions The gender differences in the use of anxiolytics and sedatives/hypnotics as well as in correlates of their use observed in this study raise a concern with regard to disparities in mental health care quality between men and women. In order to develop guidelines to increase clinicians’ awareness of differential reporting of psychological symptoms and attitudes to psychotropic medications between gender groups, it is important to study these issues and report findings separately for men and women. Targeted efforts to avoid excessive prescribing of anxiolytics to older women should be considered by clinicians. In general, this study also points to a possibly low detection of depression among the elderly and a need to study further medical treatment practices of depression among both men and women. Acknowledgement The Israeli Multidisciplinary Aging Study (IMAS) was funded by the Israel National Institute for Health Policy (Grant A/2/1998 and Grant R/2/2004).

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Gender Differences in Psychotropic Medication Use among Older Adults in Israel

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Isr J Psychiatry Relat Sci - Vol. 51 - No 2 (2014)

Postpartum Anxiety in a Cohort of Women from the General Population: Risk Factors and Association with Depression during Last Week of Pregnancy, Postpartum Depression and Postpartum PTSD Inbal Shlomi Polachek, MD,1 Liat Huller Harari, MD,2 Micha Baum, MD,3 and Rael D. Strous, MD1,4 1

Beer Yaakov–Ness Ziona Mental Health Center, Beer Yaakov, Israel Ramat Chen Community Mental Health Center, Ramat Hatayasim, Tel Aviv, Israel 3 Sheba Medical Center at Tel Hashomer, Ramat Gan, Israel 4 Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel 2

Abstract Background: In contrast to postpartum depression, postpartum anxiety receives less attention, especially in the general population. Acknowledging the phenomenon is important, as it may lead to significant distress and impair maternal functioning. Objectives: To explore the phenomenon in a cohort of women in the general population and to investigate possible associated factors. Methods: Within the first days after childbirth, women at Chaim Sheba Medical Center maternity ward were interviewed. Questionnaires included psychosocial variables, feelings and fears during pregnancy and childbirth, and the Edinburgh Postnatal Depression Scale (EPDS) (referring to the last week before delivery). A month later, subjects completed the EPDS, a modified Spielberger Anxiety Scale and the Posttraumatic Stress Diagnostic Scale via telephone. Results: 40.4% had high anxiety scores. A significant association was noted between postpartum anxiety and depression during the last week of pregnancy, postpartum depression, as well as postpartum PTSD. Anxiety scores were almost 50% higher in those who suffered from postpartum PTSD compared to those who experienced postpartum depression. Associations were also found

with fear of the birth, fear of death during delivery (mother and fetus), feeling lack of control during labor and less confidence in self and medical staff. Of women who developed postpartum anxiety, 75% reported feeling anger, fear or emotional detachment during childbirth. No association was found with birth complications. Conclusions: Anxiety symptomatology appears to be a common manifestation after childbirth. It is therefore important to inquire about depression and fears during pregnancy and childbirth and subjective experience in order to anticipate postpartum anxiety symptoms, even by means of a brief screening test. The finding that postpartum PTSD was associated with the severity of postpartum anxiety may be used in the future as a potential identifier of PTSD symptoms in women with high anxiety scores.

Approximately 13% of women will suffer from symptoms of depression during pregnancy and/or the postpartum period (1, 2). What however is less commonly known is that anxiety is also prominent in the postpartum period. While a vast database on postpartum depression has accumulated over the past 20 years, in contrast, anxiety in the perinatal period has received less research and attention. Several studies have shown that the postpar-

Address for Correspondence: Address for Correspondence: Inbal Shlomi Polachek, MD, Beer Yaakov – Ness Ziona Mental Health Center, POB 1, Beer Yaakov 70350, Israel inbalshlomi@gmail.com

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Inbal Shlomi Polachek et al.

tum period clearly elevates the risk of experiencing an exacerbation of anxiety-related symptoms in women who are already vulnerable to such experience. Initial case reports on the impact of pregnancy and the postpartum period on the severity of panic disorder suggested that pregnancy protects against panic attacks while the postpartum period is a time of increased risk and severity of panic disorder (3, 4). However, other evidence suggests that the most common effect of perinatal status on panic disorder may be no change in symptom severity (5, 6). Williams and Koran (7) assessed the course of OCD across the perinatal period. They report that the majority of women reported no change in symptomatology during pregnancy with 29% reporting postpartum exacerbation of symptoms. Not many studies have examined postpartum anxiety in the general population. Stuart et al. (8) reported a point prevalence of anxiety of 8.7% at 14 weeks postpartum and 16.8% at 30 weeks postpartum in a community sample. In this study, the Edinburgh Postnatal Depression Scale was found to have a strong correlation with the State Anxiety Scale of the State-Trait Anxiety Inventory, suggesting that the Edinburgh Postnatal Depression Scale may be a good screening instrument for anxiety as well as depression. Several studies found that the rate of OCD (2.7%- 3.9%) (9, 10) and GAD (4.4%- 8.2%) (9, 11, 12) are higher in postpartum women than in the general population. The rate of panic disorder however was not noted to be different from that in the general population. These observations are not surprising since the mean age of onset of many anxiety disorders is in the early 20s - a time during which many women are contemplating childbirth (13). Thus postpartum anxiety appears to be a common experience in part because of its prevalence among women in this age, as well as the fact that childbirth is a well established stressor related to a higher incidence of anxiety disorder than what would be expected by chance (14). It is thus understandable that the postpartum period would be a time of vulnerability predisposing to the development and onset of anxiety disorder, as women are often overwhelmed by changing roles, multiple demands and lack of sleep (6). While the phenomenon has been noted, not many have explored which women will suffer from postpartum anxiety symptomatology. Attention to the phenomenon of postpartum effects of maternal anxiety is important since anxiety in this context impairs maternal functioning, leads to significant distress and may seriously disturb mother-infant interaction,

with consequences ranging from maternal neglect and failure to thrive to infanticide (15). Since depression and anxiety frequently co-occur, it is likely that women who report depressive symptoms in the postpartum period also experience clinically significant symptoms of anxiety (16). For example, Wenzel et al. (10) noted that approximately 20% of postpartum mothers in a community sample reporting dysphoria also endorsed subsyndromal panic and obsessive compulsive symptoms. Austin et al. (17) in a cohort study of 1,549 women found that 20.4% of the women who demonstrated anxiety disorder had comorbid depression. Furthermore, 37.7% of the women with a major depressive episode (MDE) exhibited comorbid anxiety disorder. Since postpartum anxiety is poorly understood including knowledge of risk and predisposing factors, the aim of this study was to explore the phenomenon in a cohort of women in the general population and to investigate factors associated with the development of the condition Materials and Methods Study Population

Criteria for inclusion included women of any age who gave birth at the hospital during the study and who were able to sign the informed consent form. The study was approved by the Chaim Sheba Medical Center Helsinki Committee Ethical Review Board. Study Design and Study measurements

Within the first few days after childbirth (2 days for natural delivery and 5 days for caesarian section), women who were hospitalized in the Chaim Sheba Medical Center (a large academic general hospital) maternity ward were approached for study participation. Every woman who agreed to participate in the study answered a specially designed package of questionnaires with the assistance of the researcher. The study inventory inquired about demographic and socioeconomic variables, history of trauma, previous childbirth, fears during pregnancy and childbirth, mode of delivery, discomfort with the undressed state, feeling control during labor, confidence in self and medical staff, breastfeeding and future plans regarding pregnancy. In addition the Edinburgh Postnatal Depression scale (EPDS) was administered. The EPDS referred to a report of the last week before delivery, aiming to measure depressive symptoms at the end of pregnancy. A month later, these women were contacted via telephone and requested to complete once again the study questionnaires consisting 129

Postpartum Anxiety in a Cohort of Women from the General Population

of questions exploring subjective experience of obtaining sufficient postpartum help, emotional detachment from husband, desire for more children and breastfeeding , as well as the EPDS, the modified Spielberger Anxiety Scale and the Posttraumatic Stress Diagnostic Scale (PDS).

PDS analysis was used to indicate presence or absence of DSM-IV criteria of PTSD. All tests were set with a two-tailed significance level of 5%. Analyses were performed by SPSS software (version 16).

Background for Study Questionnaires

Results

1. The Edinburgh postnatal Depression scale (EPDS) was developed as a screening test for postnatal women. It has been validated (as has its Hebrew version) (18) and is widely used around the world. A score > 10 indicates symptoms of depression and a score > 12 indicates significant depressive symptoms (19, 20). In our analysis we referred to EPDS > 10. 2. The Posttraumatic Diagnostic Scale (PDS) provides an indication of whether DSM-IV criteria for PTSD have been met, the severity of the symptoms, the number of symptoms and the severity of dysfunction. It has been validated in those who have undergone a traumatic event in the month previous to the test (21). 3. The modified Spielberger Anxiety Scale is an adaptation of the Spielberger Anxiety Scale aimed at identifying current anxiety state. The questionnaire consists of statements regarding mental state, such as “I am stressed,” “I am disturbed.” The patient is requested to note the intensity of the experienced emotion: “very much,” “medium,” “little,” “not at all.” The questionnaire is intended for use when use of the full questionnaire is impossible (due to lack of time, for example). The questionnaire combines elements found to be most correlated with anxiety in the expanded version. A version of the short questionnaire has been found to be reliable and valid (22). Statistical Analysis

The analysis examined the relationships between the characteristics of postpartum anxiety, depression during the last week of pregnancy and postpartum and demographic characteristics of previous pregnancies, current pregnancy, birth process and various factors after birth. Associations were calculated using of chi-square and t-tests as appropriate according to variables nature. Scores on the modified Spielberger Anxiety Scale showed a biased distribution, with mainly low scores. Therefore, scores were categorized according to a median split into low (0-4) or high (5-20) anxiety groups. This approach to analysis of scores is similar to that of Shindel et al. (23) where scores were divided into quartiles for subsequent analysis. EPDS scores were analyzed using the conventional cut-point of EPDS>10 as indicating postpartum depression. 130

Demographics

The demographic characteristics of the cohort have been described elsewhere (24). In summary, 102 women agreed to participate and were interviewed; 89 of the group completed the one month follow-up interview. Mean age was 32 years (range 20-40 years). For 29% of the study sample this was their first delivery. Mean parity=1.3. 95.5% percent of the women surveyed were married, 3.3% with partners and 1% was divorced. Mean number of years of educations =14.7; 84% percent of the women reported that they work, with 12.4% describing their income as significantly above average, 38.2% as slightly above average, 34.8% average, 9% less than average and 5.6% significantly less than average. With respect to religious orientation, 49.4% described themselves as secular, 29.2% as traditional, 9% as national religious and 11.2% as ultra-orthodox. Demographic associations with anxiety and depression

Among demographic variables only anxiety was significantly associated with mean education years (14.3 years in low anxiety group vs. 15.6 years in high anxiety group) (t test, p=0.045). Clinical associations with postpartum anxiety

1. Modified Spielberger Anxiety Scale results Most women, n=53 (60%), showed low scores of 4 or less on a modified version of the Spielberger Anxiety Scale while the remaining n=36 (40%), showed high scores. Therefore it was deemed inappropriate to use the anxiety score as a continuous variable and scores were categorized by means of the median split to separate the sample into low (0-4) or high (5-20) anxiety groups. 2. EPDS results With a score of at least 10 on the EPDS indicating possible depression, 22 (24.7%) subjects scored above 10 during their last week of pregnancy and 4 (4.5%) subjects above 10 postpartum. There was a significant association between depression during last week of pregnancy (EPDS>10) and postpartum anxiety (chi test, p<0.01) as well as postpartum depression (EPDS>10) and postpartum anxiety (chi test, p<0.05).

Inbal Shlomi Polachek et al.

Figure 1. Incidence and association of postpartum anxiety, depression during the last week of pregnancy, postpartum depression and PTSD pregnancy depression n=22 24.7% postpartum anxiety n=36 40.4%

Table 1. Mean Anxiety Scores

postpartum PTSD n=7 7.8%

postpartum women n=89

3. PDS results The PTSD scores of the cohort have been described elsewhere by our team (23). In summary, results as expressed by means of the PDS questionnaire analysis indicated that 3 (3.4%) women fulfilled the full criteria of PTSD one month after birth. The results were analyzed including women with full PTSD criteria and women missing one or two criteria, providing a total of 7 (7.8%) women. As expected, a significant association with presence of anxiety was found in the subgroup of patients who developed postpartum PTSD (chi test, p<0.001). All the women in the PTSD group had high anxiety scores as defined by the median split. In addition, it is important to note that women in the PTSD group had almost twice the mean anxiety scores than women with depression during their last week of pregnancy and 50% higher than women with post-partum depression. See Figure 1 for summary of incidence and association of postpartum anxiety, depression during last week of pregnancy, postpartum depression and PTSD See Table 1 for comparison of mean anxiety score of women with depression during last week of pregnancy, postpartum depression and postpartum anxiety. 4. Prior history No significant associations were found between depression during last week of pregnancy, postpartum anxiety

Mean Anxiety Score

Depression during last week of pregnancy

EPDS<10

4.1791

EPDS>10

7.0455

Postpartum depression

EPDS<10

4.6706

EPDS>10

9.5000

NO PTSD

4.1707

Yes PTSD

13.2857

Postpartum PTSD postpartum depression n=4 4.4%

Number

or depression and previous psychological or psychiatric treatment, family psychiatric disorders, drug use, past traumatic events, sexual abuse, previous birth experience, and report of sadness or anxiety during or after previous pregnancies. 5. Current pregnancy Unplanned pregnancies were associated with depression during last week of pregnancy (chi test, P=0.038). No associations were found to waiting time for pregnancy, fetal medical problems, fertility treatment or to duration and methods of preparation for birth (birthing course, books, Internet, etc.). However, as expected an association was noted between crises during pregnancy and depression during last week of pregnancy (chi test, P=0.024). 6. Birth expectations Women with high postpartum anxiety had higher mean of fear of birth during pregnancy (t test, P=0.018); 50% of women who were depressed during last week of pregnancy reported a high fear of birth compared to 27.3% of those without depression (chi test, P=0.05). No association was found to severity of pain expectations. 7. Delivery No associations were found with delivery week, mode of delivery, use of analgesia, or intensity of pain experienced during delivery. 8. Feelings during childbirth Women with high postpartum anxiety reported higher levels of â&#x20AC;&#x153;feeling of danger to their lives or health or health of the fetus during laborâ&#x20AC;? compared with those with low anxiety (t test, P=0.053, P=0.005). Postpartum anxiety was also associated with reports of feeling less confidence in themselves and staff during labor (t test, P=0.04, P=0.04). The women were asked about feeling anger, fear or emotional detachment during childbirth. More women with depression during last week of pregnancy, postpartum depression and postpartum anxiety reported at least one of these negative feelings (chi test P=0.05, P=0.081, P = 0.012). An association between 131

Postpartum Anxiety in a Cohort of Women from the General Population

depression at the end of pregnancy and discomfort with the undressed state during labor was found (chi test, P=0.013). A tendency towards significance was noted in women with high anxiety (chi test, P=0.082). 9. Immediate postpartum factors No significant associations were found with mother and baby complications, mother pain after birth or to Apgar scores. In addition no significant associations were found with reports of desire for more children or breastfeeding. 10. One-month postpartum factors More women who had depression during the last week of pregnancy reported feeling emotional detachment from their husbands after delivery (chi test, P=0.051). In women with high postpartum anxiety this did not reach statistical significance (chi test P=0.196). Fewer women with postpartum depression (EPND>10) or postpartum anxiety reported that they had desire for future pregnancies, but the finding did not reach statistical significance (chi test, P=0.085, P=0.146). No association was found between anxiety and breastfeeding one-month postpartum, although a tendency was noted in women with depression at the last week of pregnancy or post-partum (chi test p=0.092, p=0.135). Discussion Observations from this epidemiological study â&#x20AC;&#x201C; to the best of our knowledge the first of its kind in Israel indicate that approximately 40% of women postpartum experienced severe anxiety. Considering that we studied a cohort of subjects from the general population, this is remarkable since results from this study indicate that such anxiety symptomatology appears to be very high in the community. It should be noted, however, that this finding by nature included all subjects with PTSD, many with postpartum depression and many with anxiety disorder who would have remained undiagnosed and untreated. Postpartum anxiety was associated with postpartum PTSD. This finding is not surprising given that PTSD has been classified according to the DSM-IV as an anxiety disorder. In contrast Maggioni et al. (25), by means of the State Trait Inventory rating scale, noted that 3-6 months after delivery 19% of women investigated suffered from state anxiety and 23.7% from trait anxiety with no association between PTSD and anxiety. However, Czarnocka and Slade (26) did note an association between PTSD and anxiety. Differences between these study results may be explained by the use of different rating and evaluation scales. 132

The study observation that postpartum anxiety was correlated with depression during pregnancy and postpartum depression indicates the close relationship between the two disorders; 60% of the women who suffered from depression during their last week of pregnancy and 75% of the women who were depressed after childbirth also suffered from postpartum anxiety. However, severity scores of anxiety were almost twice the level of those who suffered from postpartum PTSD compared to those who experienced depression during last week of pregnancy and 50% higher in women who experienced postpartum depression. It appears from study results that women with higher educational status suffered more from postpartum anxiety. This is in some ways in contrast to what is generally believed about the relationship between education and anxiety (27). Similar to our findings, Bener et al. (28) in a study of 2,091 women noted that young mothers and those with higher education were more depressed, anxious, and under stress. Similar to previous studies (29, 30), we noted that unplanned pregnancies were associated with depression during pregnancy â&#x20AC;&#x201C; a finding which did not extend to anxiety. It thus appears that unplanned pregnancies did not increase anxiety and women in such situations deal with the unplanned experience by responses of painful depression rather that increased anxiety. We did not find a significant association between postpartum anxiety and fertility problems even though a tendency was noted. Our findings are similar to the Warmelink et al. (31) study of 907 women who conceived via medically assisted conception or conceived naturally. He did not find significant differences in the prevalence of PTSD, anxiety and depression between women who conceived via medically assisted conception and those who conceived naturally. It is important to note that among the most important findings of the study were the associations that were not observed. No association was noted between postpartum anxiety and/or depression and any objective risk factors during pregnancy and after. Thus no association was found with difficult childbirth or birth complications. This finding is similar to the Adams et al. (32) study which found no association between mode of delivery and maternal postpartum emotional distress in a prospective study of 55,814 women, unlike other studies such as that of Mei and Huang (33) which noted an association between labor complications and postpartum depression. However, we did note associations with several subjective factors. These women reported higher fear of birth

Inbal Shlomi Polachek et al.

during pregnancy. During childbirth these individuals reported feeling less control, more fear, anger and emotional detachment, a greater feeling of danger to their and the fetus’ lives or health and thus less reliance upon themselves and on the staff. The observation of increased “fear of childbirth” and fears during childbirth being associated with increased postpartum anxiety is not surprising and it supports the consideration that anxiety may be a trait that endures and is expressed in several different manifestations and situations in a person’s life and which may be exacerbated around pregnancy, childbirth and the postpartum period. The finding of heightened expectations of fear of childbirth being associated with depression at the end of pregnancy and one month postpartum is consistent with previous research among 98 primaparous women recruited from antenatal classes and who evaluated their expectations and experiences of pregnancy and delivery before and after birth. In this study the most consistent predictors of depression in the days immediately after birth were trait anxiety and fear of birth assessed during pregnancy (34). We found no significant association between anxiety and breastfeeding immediately after birth and one month postpartum. In contrast to our findings, Zanardo et al. (35), in a study of 204 women in the third to fourth day postpartum, found that increased state anxiety levels impaired success rates of breastfeeding (measured by the state-trait anxiety inventory). Similar to our previous finding of an association between discomfort with the exposed state during labor and PTSD, we noted an association between discomfort from exposure during labor and postpartum anxiety and depression – a finding which did not extend to a significant association with postpartum anxiety. Study limitations include the sample size which while useful could yield more generalized findings in a bigger sample. In addition, future studies of this nature should consider longer time to follow-up, exploration of the various subtypes of anxiety and increasing the sensitivity of the evaluation by conducting the follow-up in person rather than by telephone. In addition, further similar studies on the subject should document study subject refusal rates and comparisons with national demographic data in order to better generalize study findings. Finally, evaluation of pregnant women in the final stages of pregnancy for mood changes and expectations of childbirth was retrospective in this study. Future studies may want to consider evaluation of these factors in real time in order to exclude potential bias of memory recall.

In conclusion, findings from this study indicate a high incidence of self-reported postpartum anxiety symptoms and high comorbidity between depression during the end of pregnancy, postpartum depression, postpartum PTSD and anxiety. Since postpartum anxiety may be expressed in several forms including PTSD as noted in our previous study, it may be cost effective to evaluate postpartum anxiety in general by means of a brief screening test postpartum. Only if positive for anxiety would it then be valuable to probe for the specific nature of the anxiety. The finding that postpartum PTSD was associated with the severity of postpartum anxiety could be used in the future as a potential “red flag” to identify PTSD symptoms in women with high anxiety scores. Anxiety after childbirth was found to be associated with fears during pregnancy and childbirth and not to the delivery process itself. It was related to fear of the birth, fear to her life and to the fetus during delivery, to feeling lack of control during labor and to less self-confidence in her ability to deal with labor and less confidence in the medical staff. Therefore it is important to inquire about depression during pregnancy and about fears during pregnancy and childbirth in order to anticipate anxiety symptoms after childbirth. It appears that more of a focus on the subjective experience during childbirth is indicated in order to predict anxiety development. Future studies with larger samples would be important in order to replicate these findings and further our understanding of these common and important phenomena during the postpartum period. Current knowledge on this subject

• In contrast to postpartum depression, anxiety in the perinatal period has received little attention and research. • Several studies have shown that the postpartum period elevates the risk of experiencing an exacerbation of anxiety-related symptoms in women. • Attention to the phenomenon of postpartum effects of maternal anxiety is important since anxiety in this context impairs maternal functioning, leads to significant distress and may seriously disturb mother-infant interaction, with consequences ranging from maternal neglect, failure to thrive and even to infanticide. What this study adds

• Observations from this epidemiological study indicate that approximately 40% of women postpartum experienced severe anxiety. Considering that we studied a cohort of subjects from the general population, this is 133

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• • •

•

remarkable since results from this study indicate that such anxiety symptomatology appears to be very high in the community. A significant association was found between postpartum anxiety and depression during last week of pregnancy, postpartum depression as well as postpartum PTSD. Postpartum PTSD was found to be associated with the severity of postpartum anxiety. Anxiety after childbirth was found to be associated with fears during pregnancy and childbirth and not to the delivery process itself. No association was found with birth complications. It is important to inquire about fears during pregnancy and childbirth and subjective experience in order to anticipate postpartum anxiety symptoms, even by means of a brief screening test.

References 1. O’Hara MW, Swain AM. Rates and risk of postpartum depression. Int Rev Psychiatry 1996;8:37-54. 2. Bennett HA, Einarson A, Taddio A, Koren G, Einarson TR. Prevalence of depression during pregnancy:Systematic review. Obstet Gynecol 2004;103:698-709. 3. George DT, Ladenheim JA, Nutt DJ. Effect of pregnancy on panic attacks. Am J Psychiatry 1987;177:144:1078-1079. 4. Northcott CJ, Stein MB. Panic disorder in pregnancy. J Clin Psychiatry 1994;55:539-542. 5. Wisner KL, Peindle KS, Hanusa BH. Effects of childbearing on the natural history of panic disorder with comorbid mood disorder. J Affect Disord 1996;41:173-180. 6. Ross LE, McLean LM. Anxiety disorders during pregnancy and the postpartum period: A systematic review. J Clin Psychiatry 2006;67:1285-1298. 7. Williams KE, Koran LM. Obsessive-compulsive disorder in pregnancy, the puerperium, and the premenstruum. J Clin Psychiatry 1997;58:330-334. 8. Stuart S, Couser G, Schilder K, O’Hara MW, Gorman L. Postpartum anxiety and depression: Onset and comorbidity in a community sample. J Nerv Ment Dis 1998;186:420-424. 9. Wenzel A, Gorman LL, O’Hara MW, Stuart S. The occurance of panic and obsessive compulsive symptoms in women with postpartum dysphoria: A prospective study. Arch Women Mental Health 2001;4:5-12 10. Wenzel A, Haugen EN, Jackson LC, Brendle JR. Anxiety symptoms and disorders at eight weeks postpartum. J Anxiety Disord 2005;19:295-311. 11. Wenzel A, Haugen EN, Jackson LC, Robinson K. Prevalence of generalized anxiety at eight weeks postpartum. Arch Women Ment Health 2003;6:43-49. 12. Ballard CG, Davis R, Cullen PC, Mohan RN, Dean C. Postpartum anxiety in mothers and fathers. Eur J Psychiatry 1993;7:117-121. 13. Kessler RC, McGonagle KA, Nelson CB, Hughes M, Swartz M, Blazer DG. Sex and depression in the national comorbidity survey. J Affect Dis 1993;29:85-96. 14. Sholomskas DE, Wickamaratne PJ, Dogolo L, O’Brien DW, Leaf PJ, Woods SW. Postpartum onset of panic disorder: a coincidental event? J Clin Psychiatry 1993;54:476-480.

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15. Spinelli M. Psychiatric disorders during pregnancy and postpartum. JAMWA 1998;53:165-169. 16. Maser J, Cloninger R. Co morbidity of mood and anxiety disorder. Washington DC: American Psychiatric Press, 1990. 17. Austin MP, Hadzi-Pavlovic D, Priest SR, Reilly N, Wilhelm K, Saint K, Parker G. Depressive and anxiety disorders in the postpartum period: How prevalent are they and can we improve their detection? Arch Womens Ment Health 2010;13:395-401. 18. Glasser S, Barell V. Depression scale for research in and identification of postpartum depression. Harefuah 1999;16:136:764-768. 19. Cox JL, Holden JM, Sagovsky R. Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale. Br J Psychiat 1987;13:782-786. 20. Murray L, Carothers AD. The validation of the Edinburgh Post-natal Depression Scale on a community sample. Br J Psychiatry 1990;13:288-290. 21. Foa EB, Cashman L, Jaycox L, Perry K. The validation of a self report measure of PTSD: The posttraumatic diagnostic scale. Psycholog Assess 1997;9:445-451. 22. Marteu T, Bekker M. The development of a six-item short-form of the state scale of the Spielberger State-Trait Anxiety Inventory (STAI). Brit J Clin Psychobiology 1992;31:301-306. 23. Shindel AW, Eisenberg ML, Breyer BN, Sharlip ID, Smith JF. Sexual function and depressive symptoms among female North American medical students. J Sex Med 2011;8:391-399. 24. Polachek IS, Harari LH, Baum M, Strous RD, et al. Postpartum posttraumatic stress disorder symptoms: The uninvited birth companion. Isr Med Assoc J 2012;14:347-353. 25. Maggioni C, Margola D, Filippi F. PTSD, risk factors, and expectations among women having a baby: A two-wave longitudinal study. J Psychosom Obstet Gynaecol 2006;27:81-90. 26. Czarnocka J, Slade P. Prevalence and predictors of post-traumatic stress symptoms following childbirth. Brit J Clin Psychol 2000;39:35-51. 27. Kaplan, Sadock’s. Anxiety disorders. In: Synopsis of psychiatry. Tenth edition 2007:578-634. 28. Bener A, Gerber LM, Sheikh J. Prevalence of psychiatric disorders and associated risk factors in women during their postpartum period: A major public health problem and global comparison. Int J Womens Health 2012;4:191-200. 29. Redshaw M, Henderson J. From antenatal to postnatal depression: Associated factors and mitigating influences. J Womens Health 2013;22:518-525. 30. Yanikkerem E, Ay S, Piro N. Planned and unplanned pregnancy: Effects on health practice and depression during pregnancy. J Obstet Gynaecol Res 2013;39:180-187. 31. Warmelink JC, Stramrood CA Paarlberg KM, Haisma HH, Vingerhoets AJ, Schultz WC, van Pampus MG. Posttraumatic stress disorder, anxiety and depression following pregnancies conceived through fertility treatments: The effects of medically assisted conception on postpartum well-being. J Reprod Med 2012;57:115-122. 32. Adams SS, Eberhard-Gran M, Sandvik ÅR, Eskild A. Mode of delivery and postpartum emotional distress: A cohort study of 55,814 women. BJOG 2012;119:298-305. 33. Mei ZX, Huang M. Association of psychological factors with post-partum hemorrhage and labor duration. J Southern Med Univ 2006;26:1203-1204. 34. Knight RG, Thirkettle JA. The relationship between expectations of pregnancy and birth, and transient depression in the immediate postpartum period. J Psychosom Res 1987;31:351-357. 35. Zanardo V, Gasparetto S, Giustardi A, Suppiej A, Trevisanuto D, Pascoli I, Freato F. Impact of anxiety in the puerperium on breast-feeding outcomes: Role of parity. J Pediatr Gastroenterol Nutr 2009;49:631-634.

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Vesna Pirec et al.

Aripiprazole Combined with Other Psychotropic Drugs in Pregnancy: Two Case Reports Vesna Pirec, MD, PhD,1 Aarti Mehta, MD,2 and Sittanur Shoush, MD3 1

Insight Behavioral Health Centers and Women’s Mental Health, University of Illinois at Chicago, Chicago, Illinois, U.S.A. General Adult and Reproductive Psychiatrist, Chicago, Illinois, U.S.A. 3 Women’s Mental Health and Women’s Mental Health Fellowship,University of Illinois at Chicago, Chicago, Illinois, U.S.A. 2

Abstract Maternal exposure to second generation antipsychotics during pregnancy has been associated with some negative effects for both mothers and infants. Aripiprazole is becoming more readily used, although data regarding its use in pregnancy are limited. Additionally there are limited data with regards to the impact of polypharmacy on pregnancy outcomes. Given the relative paucity of information related to aripiprazole use in pregnancy it is difficult to counsel women on potential risks or side effects. We present two cases that illustrate the use of aripiprazole as a part of a polypharmacy regimen in pregnancy and describe the pregnancy outcomes in an effort to help clinicians facing complex treatment decisions in pregnancy.

While the study of antidepressant use in pregnancy has received substantial attention in the past decade, both in research and in the media, less is known about the use of second generation antipsychotics (SGA). Despite this, the use of SGAs in pregnancy is steadily increasing. While there is literature on the use of SGAs as a class, there is limited information on specific SGAs use in pregnancy, especially newer ones such aripiprazole (1, 2). Aripiprazole is one of the newer SGAs that has unique pharmacological activities: partial agonist at dopamine 2 receptors and antagonist at serotonergic 5HT1A receptors. Aripiprazole has demonstrated its efficacy in stabilizing symptoms of psychosis and mania, as well as augmenting antidepressive effect of other medications. It has been prescribed more commonly due to novel mechanism of action and what was thought (3) to be a relatively lower risk for metabolic syndrome. However, aside from a few published case reports, its use in pregnancy has not been well studied.

Lack of available data makes it difficult to counsel women on potential risks or side effects. Additionally, there is limited data with regards to the impact of polypharmacy on pregnancy outcomes (4). While the goal is to limit polypharmacy in pregnancy, this is not always possible. We present two cases that illustrate the use of aripiprazole and polypharmacy in pregnancy and describe the pregnancy outcomes in an effort to help clinicians facing complex treatment decisions while medicating expecting mothers. Case 1: Ms. M was a 26 year–old woman who presented at 36 weeks gestational age into her first pregnancy for management of her bipolar illness. She had diabetes mellitus type II and hypothyroidism, both well controlled with insulin and levothyroxine respectively. She did not use illicit substances. Ms. M has had multiple hospital admissions most of which were for mania with psychotic features. Prior to conceiving she was stable on aripiprazole 15 mg daily, but self-discontinued upon discovering pregnancy around 4 weeks gestational age. Due to partial response to aripiprazole, lamotrigine was added and slowly titrated up to 150 mg daily at 25 weeks gestational age. Despite medication adjustment, Ms. M developed another manic psychotic episode and was admitted to inpatient psychiatry at 31 weeks gestational age. In the hospital lamotrigine was discontinued and clonazepam and haloperidol were added. On discharge from the hospital she was taking aripiprazole 15 mg daily and clonazepam 1 mg at bedtime. Due to remaining hypomanic symptoms aripiprazole was titrated up to 10 mg twice daily and clonazepam 1 mg at bed time was continued. Ms. M’s symptoms were stabilized on this regimen. She delivered a term infant by cesarean due to breech presentation. The infant was 5-10th percentile with APGARs of 9/9. Although initially vigorous the infant developed

Address for Correspondence: Vesna Pirec, MD, PhD,Chief Medical Director, Insight Behavioral Health Centers, Women’s Mental Health 333 North Michigan Avenue, Suite 1900 Chicago, IL 60601, U.S.A. vpirec@insightillinois.com

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Aripiprazole Combined with Other Psychotropic Drugs in Pregnancy: Two Case Reports

poor feeding and hyperbilirubinemia of unknown etiology and on day two was admitted to the neonatal intensive care unit with nasogastric tube for feeding supplementation. The hyperbilirubinemia resolved spontaneously after a couple of days and the infant’s feeding improved. They were discharged from the hospital on day five. Ms. M chose to bottle feed the infant. On subsequent pediatrician follow up for three months the infant was developing well, apart from having an umbilical hernia and hemangioma on the thigh. Case 2: Ms. J was 23-year-old female with an atrial septal defect who was pregnant for the fifth time and had two live children, initially presented to an outside hospital two months post-partum and six weeks pregnant. She had prior history of bipolar disorder with psychotic features and was off all medication. On admission to the first hospital she presented with psychotic mania in the context of cocaine, marijuana and benzodiazepine use. Her initial medication regimen was ziprasidone 80 mg twice daily and oral haloperidol 10 mg twice daily. Her symptoms persisted and she was transferred to the second hospital. Per collateral history Ms. J’s prior episode of post-partum psychosis was stabilized on aripiprazole. Initial medication regimen was discontinued and aripiprazole and lithium were initiated. Ms. J’s medications were slowly titrated up to 25 mg of aripiprazole daily and lithium 300 mg three times per day. At approximately 10 weeks gestational age Ms. J improved significantly and was discharged from the hospital in stable condition. Due to feeling overly sedated, Ms. J self-discontinued lithium at approximately 12 weeks gestational age without consulting her psychiatrist. She continued to be stable and monotherapy with aripiprazole 25 mg daily was continued throughout the pregnancy. Ms. J denied use of any illicit drugs after her initial presentation. Ms. J gave birth to a term infant by vaginal delivery, with Apgar’s of 9/9. The infant was in the 26th percentile for weight, 53rd percentile for length but <3rd percentile for head circumference. It was also noted that the baby had hypospadias. Ms. J chose not to nurse. Discussion In both cases infants were exposed to multiple medications during various gestational stages. Thus it is difficult to draw any direct conclusion related to the infant outcomes and aripiprazole exposure. In both cases the women had term infants that were discharged from the hospital within five days 136

from delivery and initial development was unremarkable. In Case 1 the infant’s poor feeding may have been a result of antipsychotic withdrawals or neonatal benzodiazepine toxicity. It is unclear if the hyperbilirubinemia was related to medication exposure; however, it was time limited and did not require intervention. The infant in Case 2 had microcephaly and hypospadias. These malformations could have been attributed to any of the individual medications or a result of polypharmacy. However, since no previously published case reports of intrauterine exposure to aripiprazole showed any structural malformation in newborns (1, 2, 5, 6), it is more likely that fetal malformations in the second case were related to the exposure to polypharmacy. Additionally, in every pregnancy there is always a 1-3% chance of giving birth to an infant with major malformation regardless of medication exposure. And lastly, the fact that both women discontinued some of their medication without consulting their doctor, and possibly by doing that exacerbated their symptoms for a time period, could have contributed to infants’ outcomes. The debate over using psychotropic medication in pregnancy continues. Whenever possible, polypharmacy is discouraged in this patient population. Data regarding in utero exposure to some relatively newer medications such as aripiprazole alone or in the context of polypharmacy are sparse. Only one case report describes placental transfer of aripiprazole to be similar to that of risperidone or haloperidol (7). Meanwhile clinicians struggle to achieve stabilization of patients’ symptoms while providing as safe an environment as possible for a growing fetus. Presented cases further highlight the need for more studies on the use of aripiprazole as well as on the potential impact of polypharmacy in pregnancy in order to help guide clinicians and patients in making informed treatment decisions. References 1. Gentile S, Tofani S, Bellantuono C. Apiprazole and pregnancy: A case report and literature review. J Clin Psychopharmacol 2011;31:531-532. 2. Watanabe N, Kasahara M, Sugibayashi R, Nakamura T, Nakajima K, Watanabe O, Murashima A. Perinatal use of aripiprazole: A case report. J Clin Psychopharmacol 2011;31:377-379. 3. Newcomer JW. Second-generation (atypical) antipsychotics and metabolic effects: A comprehensive literature review. CNS Drugs 2005;19:1-93. 4. Einarson A, Choi J, Koren G, Einarson T. Outcomes of infants exposed to multiple antidepressants during pregnancy: Results of a cohort study. J Popul Ther Clin Pharmacol 2011;18:e390-396. 5. Lutz UC, Hiemke C, Wiatr G, Farger G, Arand J, Wildgruber D. Aripiprazole in pregnancy and lactation: A case report. J Clin Psychopharmacol 2010;30:204-205. 6. Mervak B, Collins J, Valenstein M. Case report of aripiprazole usage during pregnancy. Arch Women Ment Health 2008;11:249-250. 7. NguyenT, Teoth S, Hacket P., Illett K. Placental transfer of aripiprazole. Aust NZ J Psychiatry 2011;45:500-501.

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Bracha Katz

Gender and Disordered Eating of Adolescents in Israel Bracha Katz, PhD Department of Criminology, Western Galilee College, Israel

Abstract Background: Studies from recent decades indicate that the ideal of thinness can be discerned in a growing dissatisfaction with weight and an increase of the prevalence of disordered eating at an earlier age of onset. Objective: The purpose of this study is to evaluate the prevalence of disordered eating (above the cutoff point of 30 on the EAT-40) among a normal population of school students in Israel. Methods: The study sample was composed of Israeli (Jewish) adolescents in grades 7 to 12 from four schools. Of 326 students approached (181 females and 142 males), 323 completed the self-report EAT-40 and a structured questionnaire that provided socio-demographic and other information. Results: 41.5% of adolescents were not satisfied with their weight and 45.3% want to lose weight. A third of the sample engages in dieting behavior frequently; 6.1% of the adolescents have pathologic EAT-40 scores, with about three times as many girls as boys exhibiting disordered eating; 8.2% of the girls and 2.8% of the males show disordered eating (Ø=0.115, p<0.05). Among adolescents who are dissatisfied with their weight there are 7.6 times more with pathologic EAT scores than those who are satisfied with their weight (Ø=0.220; p<0.01). There are 10.8 times more pathologic EAT scores among adolescents who wish to lose weight than among those who do not wish to reduce their weight (Ø=0.237; p<0.01). No significant differences in pathologic EAT scores were found among adolescents from different ethnic backgrounds or levels of religious observance.

Address for Correspondence:

Conclusion: The prevalence of disordered eating among adolescents in Israel is higher than other countries in general, and among males in particular. There is a need for increased efforts to detect adolescents at risk for developing eating disorders, with the assistance of clinical tools. In addition an educational policy for disordered eating prevention should be instituted.

Background The past decades have witnessed the development of a cult of the body and the glorification of the ideal of thinness in modern Western society (1). Some of the side effects of this ideal can be discerned in a growing dissatisfaction with the body. A study in the U.S.A. reported that 80% of the girls stated they would like to weigh less (2). Israel, like other Western countries, is also influenced by the cult of the body. A national study reported that 60% to 80% of Israeli female adolescents are dissatisfied with their weight and body shape, although the vast majority of these youngsters are of normal or even low weight (3). In a study undertaken in 2001-2002, Israel ranked second among 33 Western countries, with 26% of Israeli girls engaged in dieting behavior (4). Previous international studies revealed an even high proportion of disturbed eating among Israeli girls, around 34.5% (3) and 28% (5). As for males, a national survey (3) revealed that 11% of the Israeli boys showed disturbed eating. This rate is higher than the rate reported in a previous study (5) of 8.9%. The desire for thinness leads adolescents to use different behaviors to reduce weight. Some behaviors, such as controlled eating or supervised physical exercise, are considered positive or harmless methods of weight loss, while others,

Bracha Katz, PhD, Western Galilee College, POB 2125, Acco 24121, Israel

ksbracha@gmail.com

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such as fasting or the overuse of laxatives, are liable to have serious health consequences (6-8). This study evaluates eating attitudes and behaviors among adolescents in Israel. However, body dissatisfaction is not only related to ideal body perception but also to being overweight (9). The desire for weight loss is more pronounced among adolescents with higher weight than among those of normal weight. Self-perception of overweight was found to be the most important factor leading to attempts to lose weight in nationally representative samples of adolescents from over 30 countries (9). Various studies have found that adolescentsâ&#x20AC;&#x2122; satisfaction with their weight and their attitudes regarding their appearance are related to dieting behavior and other methods of weight control (10, 11). Significant differences were also found, however, in the body satisfaction of girls compared to boys (12). Whereas boys perceive the ideal body as muscular girls prefer a thinner body, and perceive the ideal feminine body as very slim (13). Even so, children and adolescents from different ethnic groups might choose a heavier and broader ideal body (14), although the findings are not systematic. A study in Israel found that Jewish college females were less satisfied with their current figures than Arab females (15). Some studies show that gender differences in body image develop at early ages of 8-10 years old (6, 16) although some studies reported that these differences can occur even as early as age 6 (14). Disordered eating is a broad construct that includes subclinical eating disorders not otherwise specified (EDNOS) as well as aberrant preoccupations, attitudes and behaviors related to shape, weight, body image and food, that do not reach the levels of EDNOS (4, 16). Studies of the prevalence of disordered eating attitudes and behavior based on the Eating Attitudes Test (above the cutoff point of 30 on the EAT-40) show that disordered eating ranges from 5% to 22% (2, 17-19) and one study of males (20) found high scores of EAT-26 in 6% of high school boys. There are a few studies regarding disordered eating in Israel. Most of these studies focus on girls in various settings. Two studies of 12-18-year-old Jewish girls in Israel in several educational settings such as urban-secular, kibbutz and boarding schools reported that around 20% of the students of the secular boarding school had the most pathological EAT-26 (21) and EDI-2 (22) scores. The researchers suggest that eating-related pathology may increase when there are adverse conditions for growing up. One earlier study (23) reported higher rates of pathologic EAT-26 scores among girls from kibbutzim compared to girls in five urban high schools; 27% of the girls from kib138

butzim had pathologic EAT-26 scores compared to 16.2% of the urban high school girls (23). Another study of native Israeli and Russian immigrant females (24) reported that 19.6% of the native Israeli females had pathological levels of disturbed eating attitudes and behaviors as assessed with the EAT-26. A similar rate (18.8%) was found among the Russian female immigrants living in Israel for a longer period of time. On the other hand, only 7.9% of the Russian female immigrants living in Israel for three years or less had pathological levels as assessed with the EAT-26. The researchers (24) attribute these findings to the inclination among veteran immigrants to adopt Western cultural norms in order to bring them closer to native Israelis. Recently a national study of 2,978 Israeli Jewish and Arab schoolgirls from grades 7 through 12 (25) found that 30% of these girls can be defined as having disordered eating behavior according to the 4-points adapted SCOFF questionnaire. The study also found that being underweight reduces the probability of disordered eating, but that dieting, early onset of menarche, being overweight or obese and suffering from constipation increases the risk. Arab girls were more likely to have disordered eating than Jewish girls. Interestingly, a previous study of Arab girls from different ethnic backgrounds reported that the highest EAT-26 scores (>20) were found among Bedouin (19.4%) and Muslim (18.6%) adolescents (23). The drive to diet or involve themselves in disordered eating is related mainly to media influence, particularly television. In the Western world, the television and media convey the message that â&#x20AC;&#x153;thin is beautiful/intelligentâ&#x20AC;? and have permeated the entire social fabric so that teenage girls are equally influenced to diet irrespective of their SES background. Specifically for Arab girls it is suggested that the degree of exposure to the Western body ideal and to the presence of a conflict between what is the supposedly modern and the traditional feminine role is also considered to affect the high rate of eating disorder among those girls (23). A few studies in Israel addressed disordered eating among males. A study of 360 students in northern Israel (26) found that 5% of the boys (and 20.8% of girls) had pathological EAT-26 scores. Another study (27) reported that 6.8% of boys (and 20% of the girls) had pathologic EAT-26 scores. The current study seeks to provide an additional look at the prevalence of disordered eating among adolescence in Israel. The objectives of this study are to evaluate the prevalence of disordered eating attitudes and behaviors by an Eating Attitudes Test (EAT-40) above the cutoff

Bracha Katz

point of 30 (28, 29) in a random sample of 323 students of four large school base populations in Israel. METHOD Participants

The study was conducted in four schools in the northern and central regions of Israel. Each school has approximately 500 students. The four schools therefore comprise a total of 2,000 Jewish pupils. In each school we sampled randomly three classes. In each class about 25-30 students answered the questionnaires. The final sample included 323 students. The sample consists of 56% (n=181) females and 44% (n=142) males. The mean age was 14.4 (SD =1.25, n=322). 60.3% (n=195) were born to Israeli fathers, 28.1% were born to fathers of different countries, 10.5% (n=34) had fathers who came from Russia and 0.9% (n=3) fathers who came from Ethiopia. Measures

The Eating Attitude Test questionnaire (EAT-40) (28) was used to evaluate disordered eating. The EAT-40 consists of 40 items that relate to different dimensions of eating behavior, such as dieting, bulimia, a desire to be thin, excessive preoccupation with food and social pressures to eat (29). For example, the behavioral dimension of dieting is represented by statements such as: “Avoid eating when I am hungry,” “Engage in dieting behavior” and “Like my stomach to be empty.” The dimension of bulimia is represented by statements such as: “Have gone on eating binges where I feel I may not be able to stop” and “Vomit after I have eaten.” The aspiration for thinness is represented by statements such as: “Am terrified about being overweight” and “Am preoccupied with a desire to be thinner.” Food preoccupation is represented by statements such as: “Eat the same foods day after day” and “Feel that food controls my life.” Finally, the dimension of social pressure to gain weight is represented by statements such as: “Feel that others would prefer if I ate more” and “Feel that others pressure me to eat.” The respondents’ answers for each item in the questionnaire are on a Likert scale from 1 to 5 (1=always, 2=often, 3=sometimes, 4=rarely, 5=never). Each respondent’s final score is based on the total number of points accumulated from the answers to the questionnaire. The original questionnaire was translated into Hebrew for the purposes of this study. A test of the Hebrew-language questionnaire’s internal consistency showed it to have a high level of reliability (α=0.85), close to that of the original questionnaire (α=0.87).

The respondent’s score on the EAT-40 is calculated by the 40 items in this questionnaire. The eat cutoff point is 30. A final score above the cutoff point (>30) indicates disordered eating (17, 28, 30). A structured questionnaire was administered to obtain information about each participant regarding the followings: gender (male or female), age (in years), weight (kg) and height (cm) as reported by each respondent and the father’s country of birth. Religiosity was measured by the question: “How do you define yourself in terms of religion?” with possible answers: religious, traditional and secular, which are considered as levels of religious observance. Desired weight loss was measured in kilograms, with possible answers: 0.5kg, 1kg, 2kg, 3kg, 4kg, 5kg, more than 5kg. Weight perception was measured by the statement: “I define myself as” (a) very thin (b) thin (c) full-figured (d) fat (e) very fat. Weight satisfaction was measured by the statement: “I am satisfied with my body,” with the possible answers: “Yes” or “No.” Desire to lose weight was measured by the statement: “I desire to lose weight,” with the possible answers: “Yes” or “No.” Those questions are not part of the EAT-40. Thus the answers to them do not affect the EAT-40. Procedure

Each questionnaire contains the EAT-40 in part A and a structured questionnaire which obtains socio demographic and other information about each participant in part B. The questionnaires were approved by the Ministry of Education and the school principals. The questionnaires were delivered and distributed by two research assistants who explained to the students how to fill out the questionnaires, and who emphasized that the questionnaire is anonymous and that the students’ names do not appear on it and asked them to answer honestly. Of 326 students approached, 323 completed the questionnaire and three students refused to participate. Statistical and Data Analysis

Four statistical measurements were used (31): Spearman’s rho (signified by rs) for testing for correlations between ordinal variables. The Spearman test is a version of Cramer’s correlation. The Phi measurement (signified by the letter Φ) for testing associations between variables, one or two of which are nominal; for the comparison of continuous variables, student’s t-test was used. The values were presented as the mean plus the standard deviation (SD) and as percentages. For proportion comparison between the groups, the chisquare test was used. Differences are considered statistically 139

Gender and Disordered Eating of Adolescents in Israel

significant at a P value of <.01 or <.05. Data were calculated with the use of the Statistical Package for Social Sciences software (SPSS v. 15.0; SPSS Inc., Chicago, IL, USA). RESULTS The respondents’ average weight was 53kg (SD=11.8; n=256), and their average height was 1.64m (SD=0.87; n=256); 60.2% had Israeli-born fathers, while the fathers of 39.8% had been born outside Israel. About a half of the students were secular, about 40% were traditional, and only 10% were religious. Other characteristics are presented in Table 1 Among adolescents who wish to reduce weight (n=148), we found a positive correlation (rs=.348) between the number of kg each wished to lose and weight satisfaction, as presented in Table 2. Table 3 presents the frequency of selected eating attitudes and behaviors among the sample. Our findings show that 6.1% of the sample scored above the EAT-40 cutoff (>30). There is a correlation between Table 1. Weight satisfaction, weight perception and desire to reduce weight in the study sample of Israeli (Jewish) adolescents aged 12-18 Variable

Total

percentages

Weight perception

310

100.0

Very thin

4.2

Thin

151

48.7

Full-figured

123

39.7

Fat

5.5

Very fat

1.9

Weight satisfaction

313

100.0

Satisfied

183

58.5

Not satisfied

130

41.5

Desire to reduce weight

322

100.0

Yes

146

45.3

gender and pathologic EAT-40 scores, with 8.2% of the females scoring above the EAT-40 cutoff (>30), compared to 2.8% of the males (Ø=0.115, p<0.05). Another finding relates to the age of those with disordered eating. A t-test of the differences between age groups revealed significant differences between the age of those above the EAT-40 cutoff and below it (t=2.586, df=320, p<0.01). Those above the EAT-40 cutoff were relatively older than the rest, with an average age of 15.1 years (SD=1.2), compared to the average age of those below the eat cutoff (14.4 years; SD=1.2). We also found little association between weight satisfaction among the sample and pathologic EAT-40 scores (Ø=0.220). In addition, we discovered little association between the subjects’ desire to lose weight and pathologic EAT-40 scores (Ø=0.237), as presented in Table 4. However, no significant differences were found between those who wish to lose several or only a few kg with regards to their representation in the group with pathologic EAT40 scores, as shown in Table 5. DISCUSSION The present study provides some interesting findings regarding the eating behavior and attitudes of adolescents in Israel and explores some important characteristics of Israeli students, especially toward body dissatisfaction, body perception and desire to reduce weight. An important asset of the study is that it provides information from a normal population of Israeli adolescents. Relatively few studies have been done in this population group. This study reveals that the ideal of thinness is very prominent among these teenagers, as evinced by 41.5% of them who admitted that they were not satisfied with Table 2. Israeli (Jewish) adolescents aged 12-18 who wish to lose weight, by the number of kg they wish to reduce and by their weight satisfaction (n=148) Weight satisfaction

176

54.7

Number of kg wish to lose

Number of kg would like to lose*

148

100.0

Total

148 (100.0)

19.6

80.4

6 (100.0)

50.0

Total

Satisfied

Not satisfied

0.5 kg

4.1

0.5 kg

1 kg

2.7

1 kg

5 (100.0)

60.0

40.0

11 (100.0)

27.3

72.7

2 kg

8.1

2 kg

3 kg

10.1

3 kg

15 (100.0)

40.0

60.0

16 (100.0)

18.7

81.3

4 kg

10.1

4 kg

5 kg

25.0

5 kg

36 (100.0)

16.7

83.3

39.9

More than 5 kg

59 (100.0)

8.5

91.5

More than 5 kg

*Relevant only to those who wish to lose weight

140

(p<0.05)

Bracha Katz

Table 3. Selected eating attitudes and behaviors in the study sample of Israeli (Jewish) adolescents aged 12-18 (n=323) Frequency (%) No. 1

Selected statements

Always, often and sometimes

Rarely

Never

Average Score (Eat-40) mean

s.d.

Like eating with other people

86.8

10.2

3.1

2.49

1.023

Am terrified about being overweight

46.4

17.9

35.7

3.40

1.530

Avoid eating when I am hungry

19.9

21.5

58.5

4.29

1.013

Find myself preoccupied with food

43.4

26.9

29.7

3.63

1.208

Have gone on eating binges where I feel that I may not be able to stop

16.0

21.3

62.7

4.38

0.968

Aware of the calorie content of foods that I eat

49.4

19.1

31.6

3.40

1.413

Particularly avoid foods with a high carbohydrate content

16.4

21.4

62.2

4.39

0.931

Feel that others would prefer if I ate more

41.9

19.6

38.5

3.63

1.389

Vomit after I have eaten

4.6

9.0

86.4

4.77

0.692

Feel extremely guilty after eating

15.9

15.0

69.2

4.45

0.977

Am preoccupied with a desire to be thinner

38.7

19.5

41.8

3.67

1.433

Eat the same foods day after day

43.1

35.0

21.9

3.65

1.000

Think about burning up calories when I exercise.

49.5

17.5

32.9

3.41

1.438

Am preoccupied with the thought of having fat on my body

35.3

22.3

42.4

3.77

1.360

Take longer than others to eat my meals

48.0

31.2

20.9

3.42

1.207

Eat diet foods

35.2

24.3

40.5

3.85

1.191

Feel that food controls my life

24.3

20.2

55.5

4.13

1.198

Display self-control around food

69.6

9.9

20.4

2.82

1.443

Give too much time and thought to food

16.8

25.2

58.1

4.33

0.963

Suffer from constipation

6.2

18.8

75.0

4.65

0.738

Engage in dieting behavior

32.3

17.9

49.8

4.00

1.200

Like my stomach to be empty

25.8

20.2

54.0

4.13

1.162

Enjoy trying new rich foods

68.1

17.3

14.7

2.80

1.370

Have the impulse to vomit after meals

6.9

10.7

82.4

4.70

0.775

the statement number as it appears in the EAT-40 questionnaire.

Table 4. The study sample of Israeli (Jewish) adolescents aged 12-18, by their desire to lose weight and by EAT-40 cutoff (n=313) EAT-40 cutoff Desire to lose weight

Pathologic [cutoff score > 30]

Not Pathologic [cutoff score< 30]

0.0

100.0

Yes

10.8

89.2

(p<0.01)

their weight and 45.3% who declared that they want to reduce weight. Body dissatisfaction is particularly prevalent among 81% to 91% of the adolescents who want to reduce more than 4 kg of their body weight. Those findings are compatible with the findings of a national study in Israel (3), which reported that 60% to 80% of Israeli youth are dissatisfied with their weight. Interestingly, although such a high percentage of the

Table 5. Israeli (Jewish) adolescents aged 12-18 who wish to reduce weight, by the number of kg they wish to lose and by EAT-40 cutoff (n=129) EAT-40 cutoff Number of kg wish to lose

Total

Pathologic [EAT score > 30]

Pathologic [EAT score < 30]

Total

147 (100.0)

12.8

87.2

0.5 kg

6 (100.0)

16.7

83.3

1 kg

4 (100.0)

100.0

2 kg

12 (100.0)

8.3

91.7

3 kg

14 (100,0)

6.7

93.3

4 kg

15 (100.0)

13.3

86.7

5 kg

37 (100.0)

16.2

83.8

More than 5 kg

59 (100.0)

13.6

86.4

youths are not satisfied with their weight, just 5.5% of the subjects defined themselves as fat and 1.9% as very fat. 141

Gender and Disordered Eating of Adolescents in Israel

However it should be noted that those rates are low compared to the findings of a national health and nutrition survey among 7th-12th grade Jewish students which reported that 10.3% are overweight (BMI 88% to 97%) and 1.9% obese (BMI 98% and above) (32). The gap between those findings could be due to the fact that the adolescentsâ&#x20AC;&#x2122; weights in our study are based on the subjectsâ&#x20AC;&#x2122; self-reporting and not on their BMI. So this finding indicates that about 3%-5% of the adolescents who are overweight or obese do not define themselves in those terms and have a distorted weight image. Concerning the eating behavior and attitudes of the sample, our study reveals that a third of the adolescents frequently engage in dieting behavior (32.3%; Table 3, item 36). These findings are compatible with the study of Harel et al. (3), which reported that 34.5% of Israeli girls engaged in dieting behavior. We also found that 13.6% admitted that they vomit after meals (Table 1, item13). This finding is compatible with the study of Kaluski et al. (25), which found that 14% of the schoolgirls reports ever having made themselves vomit when they had a feeling of fullness. We also discovered that almost half of the sample admitted that food controls their life (44.5%; Table 1, item 30). This finding is compatible with Kaluski et al. (25), who found that 45% of the girls reported sometimes worrying that they will lose control over the quantity of food they eat. Our main finding indicates that 6.1% of the Israeli Jewish adolescent boys and girls have disordered eating. This conclusion can be generalized, as it is based on a sample drawn from a large population base from four schools in various parts of Israel and consists of normal adolescent boys and girls. The eating attitudes and behaviors questionnaire (EAT-40) (28-30) that we used as the research tool is appropriate for measuring disordered eating (above the cutoff point of 30 on the EAT-40), as it was designed as a psychometric tool for the initial diagnosis of symptoms of eating disorders and for acquiring a profile of the psychological, attitudinal and behavioral traits of those observed with EDs. The EAT-40 has been used in many studies as a scale for evaluating a wide range of behaviors and attitudes generally observed in EDs (17). We used this version of the EAT-40, even though there is also a shorter version that consists of 26 items (EAT-26) (33). Both versions have been used in research in different studies (4, 16-21, 23, 24, 26, 32) and as screening instruments to measure symptoms and characteristics of EDs. Compared to some studies, which reported 5.5% (17) or 4% (32) pathologic EAT-40 scores among boys and girls, the rate of adolescents with disordered eating in Israel found in 142

this study (6.1%) is slightly higher. However, it should be noted that other studies in Israel also reported higher rates of pathologic EAT scores among their subjects, compared to other countries, although those studies used the shorter version of the EAT questionnaire (EAT-26) (21-24). Regarding the age of adolescents with disordered eating, our findings indicate greater prevalence among adolescents with an average age of 15. This finding joins other studies that reported eating disorders to be more common at age 14 and over (35-36) and is compatible with the findings of Gur et al. (27) in Israel, who found that 16-year-old girls had higher rates of pathological EAT-26 scores than younger girls. No significant differences were found in this study between the adolescents with pathologic EAT-40 scores and the rest of the sample with respect to their ethnicity; whether first- or second-generation Israelis; or in relation to their levels of religious observance. However, it should be noted that the four schools sampled in this study were secular schools. Thus the religious students who attend them may be atypical of the more conservative religious population who attends religious schools. Other studies in Israel (4) have also found no correlation between immigrant status or religiosity and anorexia among Jewish youth. The current study gives special consideration to the issue of disordered eating among male teenagers. This group has rarely been studied in studies in Israel and abroad. Our study found disordered eating among 2.8% of boys. This rate is quite high, compared to the study of Abbate-Daga et al. (17) in Italy (0.4%). In Israel Maor et al. (26) found that 5% of the males (and 20% of the females) had pathologic EAT-26 scores, and Gur et al. (27) reported that 6.8% of boys (and 20% of the girls) had pathologic EAT-26 scores. The ratio of females to males in these studies is 4 to 1 (20% of the females vs. 5% males) in Maor et al. (26) and 2.9 to 1 in Gur et al. (27) (20% of the females vs. 6.8% males). These ratios are compatible to our study, which found that girls are nearly three times as likely to have disordered eating (8.2% vs. 2.8%) than boys. Another conspicuous finding of the present study is that 8.2% of the girls show disordered eating. This rate is slightly higher than reported by Abbata-Daga et al. (17) in Italy (7.4%) or other countries (2, 37). Other studies in Israel that used the shorter version of the EAT questionnaire (EAT-26) also revealed a higher incidence of females (around 20%) with pathological EAT-26 scores (cutoff score> 20) compared to other countries (4, 21-24). Our findings which show that disordered eating is approximately three times more frequent in girls than boys is a surprisingly low ratio, given that the literature generally

Bracha Katz

claims that around 85% of eating disorder patients are women. However, a common feature of those teenagers with disordered eating is that they are 7.6 more likely to be dissatisfied with their weight than other teens. A possible explanation for these findings – as other researchers in Israel also noted (23-25) – is that adolescents in Israel are affected by the Western modern culture which glorifies the ideal of thinness (1).These models are often conjoined with different personality traits which are presented by the media, including television and film actors, celebrities mentioned in the press, magazines, and the Internet. For example fatness is represented as symbolizing negative features, such as lack of control, laziness and addiction to various pleasures and cravings; feminine thinness is presented with attractiveness, autonomy, ambitiousness and control. Studies show (38) that identification with these models has an impact in shaping the adolescents’ self-image, when they compare themselves to them. Practical implications

There is a need for increased efforts to detect adolescents at risk for developing eating disorders. The detection of atrisk adolescents should be conducted with the assistance of clinical tools, taking into account more variables like BMI. Future studies should also refer to the participants’ body mass index. To date this variable has been little investigated in relation to disordered eating and body satisfaction. Considering that the current results indicate 41.5% of adolescents were not satisfied with their body weight, the design of a policy for prevention of disordered eating among youth is essential, since body dissatisfaction is considered one of the risk factors for disordered eating and might also increase the risk of psychological disturbances (6, 12). Since adolescents spend much of their day in school it can be a suitable framework for the implementation of primary prevention programs, aimed to promote healthy eating habits and satisfaction with the body image. A school food policy based on the availability of food items, school food rules, nutrition education program has a positive impact on adolescents’ food habits (39). In Israel there is a program that focuses on nutrition education, personal hygiene and development among children. This is operated in cooperation with the Ministry of Health and Ministry of Education through professional staff that received training in nutrition (http://www.tafuralay.co.il). However new and modern tools for adolescents’ health promotion should rely on the assumption that they need a food culture based on foods to eat, rather than foods to avoid, and an understanding of suitable weight-control measures (40). The adolescents’ age in

these programs should be addressed, since younger students were found to be more ignorant of these issues compared to older adolescents (41). Professional staff from different disciplines (42) should also be included in the program. A model of a comprehensive school-based program suggested that these programs should relate to a variety of factors, such as cognitive, behavioral, social, and cultural. The model proposes to combine knowledge about nutrition along with developing critical thinking about social messages glorifying unrealistic body shapes and decreasing the body dissatisfaction of adolescents (43). Improvement of the body image can be done using a combination of exercises and informal messages that encourage acceptance of different body shapes, and learning methods that encourage healthy relationships, critical thinking, social skills and empowerment (2, 43) through group work, play, drama, etc. (44(. A new interactive approach recommends focusing on the concept of self-esteem and positive aspects of the self, the adolescents’ expectations and feelings and social pressures held against them (2, 45). In addition, it is recommended increasing the adolescents’ understanding regarding the influence of cultural factors on the body image and encouraging them to use critical thinking regarding social norms that glorify unrealistic body shapes (43). Limitations of the study

The EAT- 40 is used in general as the first part of a twopart diagnostic screen (45, 46) and the present study addresses this initial stage. Future studies should use a sequential procedure in which those identified with disordered eating (in the first stage) will be diagnosed in the second stage via clinical interviews. An important study limitation lies in the fact that the weight of the subjects was not tested, so it was not possible to calculate their body mass index, and its relation to disordered eating and body satisfaction. Since this study is based on adolescents’ self-reported eating behaviors, there is a possibility that some subjects were not interested in providing true answers, especially if the respondents practice some kind of disordered eating. However, since the questionnaires were anonymous there is reason to believe that the participants answered openly and truthfully. Nevertheless, future research in large and representative samples of Israeli boys and girls can strengthen the conclusions of this study. Acknowledgement *I would like to express my gratitude to two anonymous readers of the IJP for their helpful comments to this article. *This study was supported by a grant from the research fund of the Western Galilee College.

143

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Isr J Psychiatry Relat Sci - Vol. 51 - No 2 (2014)

Marjorie C. Feinson and Adi Meir

Disordered Eating and Cultural Distinctions: Exploring Prevalence and Predictors among Women in Israel Marjorie C. Feinson, PhD, and Adi Meir, MA Falk Institute for Behavioral Health Studies, Jerusalem, Israel

Abstract Background: Cultural differences in serious eating problems among adult women have important treatment and prevention implications yet remain relatively unexplored. This is the first study to examine these issues among Israel’s multi-cultural adult population. Method: Disordered eating behaviors (DEB) are assessed with 14 DSM-related symptoms (including binge eating) in a multi-cultural sample of 485 women. Prevalence rates and clinical predictors of DEB severity are examined for three culturally distinct groups of Jews. Results: Second generation Israeli-born and first generation Israelis of Sephardic and Ashkenazi origins differ significantly in DEB prevalence (19.4%, 11.4%, 13.9%, p<.05). Regarding clinical predictors, self-criticism is strongest predictor for second generation while weight is strongest predictor for both first generation groups. Conclusions: Prevailing wisdom largely attributes eating disturbances to cultural thinness norms. However, substantial differences between culturally distinct groups of Israeli Jews, similarly exposed to westernized norms, challenge the prevailing wisdom. Culturally sensitive interventions warrant additional research and more illuminating explanatory models than “one size fits all.”

Introduction Socio-cultural explanations attribute many eating problems to westernized norms that glorify and promote a Address for Correspondence: Israel Falk1@012.net.il

thin body ideal. This perspective assumes that females are exposed to and pressured by thinness norms, internalize them, and develop unhealthy eating behaviors in an attempt to conform to such norms. The influence of thinness norms, however, has been challenged by findings of eating problems among ethnic groups with larger body sizes that do not conform to thin body ideals, such as African Americans (1-5) with the implication that other socio-cultural factors are involved. For example, Black women who frequently interacted with White individuals (presumably with more exposure to thinness norms) were no more likely to meet criteria for binge eating disorder (BED) than Blacks with low exposure (6). Striegel-Moore and colleagues concluded, that “… the amount of exposure to white social norms may be irrelevant for an understanding of risk for BED” (6). This observation also may apply to adult women with out-of-control eating behaviors such as binge eating and compulsive overeating (6, 7). Perhaps more germane to adult women is a sociocultural explanation that highlights bi-cultural conflict (8). When the values, beliefs and practices of particular ethnic/racial groups diverge from dominant cultural norms, the disparity can produce tensions, pressures, and emotional distress (8). Women may turn to food for comfort, as a way of coping with conflicting demands of a bi-cultural existence. A related explanation focuses on changing societal norms and transitions that contribute to conflicting gender role expectations, especially for women from more traditional backgrounds (9, 10). Changing circumstances and expectations may trigger an increased vulnerability to a range of mental health problems for more traditional groups and possibly account for an increase in eating disorders, as found among Japanese women following World War II (11). A recent analysis

Marjorie C. Feinson, PhD, Falk Institute for Behavioral Health Studies, Kfar Shaul, Givat Shaul, Jerusalem 91060,

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Disordered Eating and Cultural Distinctions: Exploring Prevalence and Predictors among Women in Israel

of disordered eating and religious observance revealed no significant differences between the most and least traditional respondents, specifically ultra-Orthodox and Secular women in Israel (12). In brief, studies of sociocultural factors other than beauty ideals and thinness norms are needed (13) and may be particularly pertinent to understanding cultural aspects of eating disturbances among adult women. Accordingly, the present study addresses some of these issues by focusing on the relationship between cultural origin and disordered eating with a multicultural sample of adult women in Israel spanning a broad age range (21 to 80). The heterogeneity of the Israeli population provides a unique opportunity for such an exploration. This analysis compares prevalence and clinical predictors across three distinct cultural origin groups: second-generation Israel-born Jews, and two groups of first generation Israeli Jews – those whose parents were born in North African or Middle Eastern countries (i.e., Sephardic) and those whose parents were born in Europe or the Americas (Ashkenazi). Methods Study Sample

The sample was recruited from primary health care clinics located in Jerusalem metropolitan areas and surrounding suburban neighborhoods. Clinics in specific neighborhoods were selected in order to achieve a socio-economically and culturally diverse sample broadly reflective of the adult female population (e.g., neighborhoods consisting primarily of Russian immigrants, a rural population, Arab Muslims, Ultra-Orthodox Jews, etc.), Under Israel’s universal health care, neighborhood clinics provide services without charge and utilization rates are relatively high (14, 15). Inasmuch as many visits are for routine tests by nurses, prescription refills, or referral forms, the sample is more broadly reflective of the community than a clinical population. This was substantiated by a majority of interviewees reporting no treatment for any health problems in the previous year. While clinics were specifically selected according to socio-demographic considerations, the recruitment of women within clinics was random. To maximize randomness and demographic diversity, interviewers entered the clinics at different hours of the day and on different days of the week. All women at least 20 years of age were invited to complete a self-report screening questionnaire (SQ) after receiving an explanation that it was part of 146

a community study of eating behaviors, that participation was voluntary, and responses were anonymous and confidential. SQs in Hebrew, Russian or English took 3 to 5 minutes to complete. A final SQ question asked about participating in a 30-40 minute telephone interview. Those interested provided contact information (first name, phone number, best time to call) and signed the SQ indicating consent to be called. This procedure, of briefly meeting interviewers in person, but the full interview being done by telephone, was successful in encouraging participation while also providing a degree of anonymity for those reluctant to answer questions in face-to-face interviews. All procedures and instruments were reviewed and approved by the appropriate review boards in addition to approval by the medical directors of each participating clinic. Measures

Disordered Eating Behaviors (DEB) is a term frequently used in the literature and refers to a broad range of binge eating, out-of-control eating and related problematic behaviors. DEB is distinguished from psychiatric diagnoses of anorexia and bulimia, which are less prevalent among adults. Although self-report screening questionnaires (SRQs) tend to yield higher scores than interview assessments, they are considered effective research instruments where clinical diagnoses are not required (16, 17). They may be particularly appropriate for assessing secretive or shameful behaviors, such as out-of-control eating behaviors (16, 18). Accordingly, an easily administered screening questionnaire (SQ) with clinically relevant symptoms that could be easily translated into Hebrew and Russian was developed for this study. Specifically, more than half of the 14 DEB-SQ items are consistent with DSM-IV symptoms, particularly the proposed category of binge eating disorder (BED). All items are unambiguous and devoid of confusing or unfamiliar terms. For example, the terms “binge eating” or “bingeing” are not used. Even “loss of control,” a central feature of binge eating, was avoided by asking: “Once you begin eating, do you have a hard time stopping?” To minimize the potential for recall bias, all SQ items are in the present tense and answered with a five-item Likert scale: always, often, sometimes, rarely, not at all. Three DEB categories, arrayed along a severity continuum, reflect both the number and frequency of symptoms: serious disordered eating (DE) requires answers of “often” or “always” to more than one-third of the 14 symptoms, and suggests a clinically meaningful condition; “considerable” DEB includes answers of “sometimes” or

Marjorie C. Feinson and Adi Meir

“often” to more than one-third of the symptoms and is suggestive of sub-threshold conditions; minimal DEB contains answers of “rarely” or “never.” DEB alpha reliability for the total sample is .80 with similar alphas for each cultural group. (Additional data for all measures available upon request.) Weight: Numerous studies reveal that self-reported height and weight correlate well with actual heights and weights and are “sufficiently valid to use in epidemiological and survey studies” (19), although a recent analysis raises some concerns (20). Interviewees were asked: For your age and height, do you consider yourself to be a healthy weight? Those answering “no” specified whether they were underweight (slightly or very) or overweight (slightly or very) and categorized accordingly as healthy weight, overweight or obese. Inasmuch as studies show that obesity is consistently underestimated by self-report (21, 22), the current findings are likely to under-estimate the true prevalence of obesity among respondents. Emotional well-being: A significant relationship between psychiatric problems and disordered eating symptoms has been documented in numerous studies (23-28). Two different but related aspects of emotional well-being are measured in this study: self-criticism and psychological distress. The Rosenberg Self-Esteem scale is a well established and widely-used 10-item measure of global self-esteem (29). A modified version adapted for this study reflects a more nuanced dimension, namely, self criticism (e.g., feeling critical of yourself, not good enough, much of what you do is inadequate, etc.) with three response categories (most of the time, sometimes, rarely). Higher scores reflect more self-criticism. Alpha reliability for the full sample was .74 with similar alphas for cultural groups. Psychological distress was measured with the Brief Symptom Inventory (BSI), an 18-item questionnaire with well-established reliability and validity (30). Alpha reliability for the full sample was .87 with similar cultural group alphas, consistent with alphas in previous Israeli studies (31). More than one standard deviation above the mean defined psychological distress. Socio-demographic variables: Cultural origin group is defined according to parents’ place of birth. First generation respondents of Sephardic origin have parents who were born in North African or Middle Eastern countries (PBA/S: Parents born abroad/Sephardic origin). First generation respondents of Ashkenazi origin are women with parents born in Europe or the Americas (PBA/A: Parents born abroad/Ashkenazi origin). (The majority of

first generation respondents were born in Israel; a small proportion within each group was born abroad but have lived most of their lives in Israel.) Second generation respondents are women born in Israel to Israeli-born parents (PBI). Interviewees excluded from these three cultural origin groups are missing cultural information or with parents from contrasting cultural origin groups or Muslims or Christians. A single question assessed income sufficiency: Does the family income (total income of all family members) cover most of the basic daily needs and expenses (food, rent, clothing, transportation, etc.)? Three response categories (does not cover most expenses; covers part, covers all or most) classify respondents accordingly. Age and education groups conform to categories of Israel’s Central Bureau of Statistics. Widowed and divorced respondents were combined into a category of previously married Statistical Analyses

Pearson’s chi-square and t-tests were used for sociodemographic comparisons. Correlations were calculated using Pearson’s r for continuous variables and Spearman’s rho for ordinal variables. Hierarchical regression for the full sample was computed with DEB as the dependent variable. Three clinical variables, weight, self-criticism (CSS) and psychological distress (BSI), were entered into the regression after the demographic variables (age, education, marital status). All possible interactions were checked, only the marital status-CSS interaction was significant and entered into the model. The regression for the full sample includes a cultural group variable which was significant. Accordingly, separate hierarchical regressions for each cultural group were computed, with variables entered in the same order as previously described. Results Demographic Description: Table 1 contains demographic characteristics for the full community sample and three cultural origin groups. The full sample is demographically diverse (column 1) and broadly representative of the Israeli adult female population (age 20+) regarding age, education, and marital status (32). Overall, close to 90% of respondents are age 25 and older and well educated (mean of 13.7 years). Cultural group comparisons reveal significant demographic differences: second generation respondents (PBI) are significantly younger and more likely to be single; Sephardic respondents (PBA/S) reported less education and less income compared to others. 147

Disordered Eating and Cultural Distinctions: Exploring Prevalence and Predictors among Women in Israel

Table 1. Characteristics of Jewish Respondents according to Cultural Origin Group Origin group Community samplea

Israel (PBI)c

Sephardic origin (PBA/S)d

n=567b

n=108

n=175

n=202

F / x2

<25

11.3

25.0

3.4

7.4

x2=80.58***

25-44.5

43.7

56.5

42.3

32.7

45-64.5

35.6

13.9

48.6

43.6

>=65

8.8

4.6

5.7

16.3

Mean (sd)

43.0

Variables

Ashkenazi origin (PBA/A)e

Age (yrs)

(15.1)

34.6

(14.0)

45.6

(12.2)

48.5b

(16.0)

F=34.66***

Education (yrs) <12

17.6

7.4

34.3

9.5

25.4

25.9

36.6

14.0

13-15

25.2

33.3

16.6

27.5

16+

30.0

33.3

12.6

49.0

Mean (sd)

13.7

(3.3)

14.4

(2.7)

11.9

(3.1)

15.1a

x2=106.64***

(3.1)

F=55.51***

Income Sufficiency Insufficient

18.2

15.9

30.5

11.7

Partially

33.2

31.8

39.7

26.4

Sufficient

46.0

52.3

29.9

61.9

Single

18.3

38.7

9.5

13.3

Previously married

18.3

12.3

22.0

22.4

Married

59.6

49.1

68.5

64.3

Obese

18.5

17.1

22.5

16.3

Overweight

27.9

25.7

30.1

31.6

Healthy

51.5

57.1

47.4

52.0

Self Critical

18.9

15.7

14.5

20.7

Not Self Critical

81.1

84.3

85.5

79.3

Mean (sd)

1.56

x2=42.91***

Marital Status x2=43.19***

Weight n.s

Self Criticism (CSS)

(0.40)

1.53

(0.38)

1.51

(0.40)

1.59

n.s (0.41)

n.s

Psychological Distress (BSI) Distressed

15.2

11.1

14.9

11.4

Not Distressed

84.8

88.9

85.1

88.6

Mean (sd)

1.74

(0.61)

1.64

(0.53)

1.77

(0.67)

1.64

n.s (0.57)

n.s

Disordered Eating Behaviors (DEB) Serious

15.9

19.4

11.4

13.9

Considerable

27.5

36.1

27.4

24.9

Minimal

56.4

Mean (sd)

2.38

44.4 (0.58)

2.51a

61.1 (0.54)

Community sample includes respondents with missing cultural information, Muslim-Arabs and Christians b Categories do not total 100% due to missing values. c PBI respondents are 2nd generation Israelis. d PBA/S respondents are 1st generation Israelis whose parents come from a

148

2.28b

x2=10.33*

61.2 (0.58)

2.33b

(0.55)

F=6.38**

North Africa or the Middle East. e PBA/A respondents are 1st generation Israelis whose parents come from Europe, North or South America. DEB = Disordered Eating Behavior, CSS = Critical Self Scale, BSI = Brief Symptom Inventory, *p< 0.05, **p < 0.01, ***p< 0.001

Marjorie C. Feinson and Adi Meir

Frequency of Clinical Correlates

second generation respondents and less strongly related for Sephardic and Ashkenazi respondents (r=.32 p<.001 vs. .19 p.<05, .23 p.<.01 respectively). Weight and selfcriticism were not significantly correlated, as one might expect to find more self-criticism among overweight and obese women. The absence of a significant relationship between DEB and income warranted excluding it from further consideration in multivariate analyses.

Frequency of DEB

Multivariate Analyses: Independent Variables associated with DEB severity

In contrast to demographic differences, there were no significant group differences regarding the three clinical correlates: weight, self criticism and psychological distress (Table 1, middle panel). Overall, almost half of the sample reported being obese or overweight (18.5%, 27.9% respectively) while almost one-fifth are self-critical (18.9%) and 15% are distressed. Among the 1,194 women who completed a screening questionnaire (data not shown), 14.5% have serious disordered eating behaviors. Among telephone interviewees (n=567), there are slightly higher rates of serious DEB, 15.9%, as shown in Table 1 (bottom panel). Also, there are significant DEB differences by cultural origin group: 19.4% for PBI; 11.4% for PBA/S; 13.9% for PBA/A (p<.05). Mean score comparisons with Sheffe post-hoc tests reveal that second-generation Israelis have significantly higher DEB scores than both Sephardic and Ashkenazi respondents (p<.01). Bivariate Relationships: DEB and Independent Variables

Correlations within each cultural origin group reveal substantial variations (Tables 2a, 2b). For second generation Israelis (Table 2a), DEB is not significantly correlated with weight; in contrast, weight is the strongest correlation with DEB for both first generation groups (Table 2b) (r=.31, .27 p<.001 respectively). Another contrast is the DEB-selfcriticism relationship; it is the strongest correlation for Table 2a. Bivariate Correlation Analysis: PBI Cultural Origin Group DEB

Age Education Income▪ Weight▪ CSS

Disordered Eating (DEB) Age

-.23*

Education

-.01

.00

Income Sufficiency▪

.02

.14

Weight▪

.17◊

.25* -.04

.32*** .11

Self Criticism .32*** -.01 (CSS)

.18◊

.04

-.07

Psychological .23* Distress (BSI)

-.05

.08

.09

.01

BSI

Hierarchical regression analysis for the full sample (available upon request) reveals that weight makes the largest contribution (8.2%) followed by self-criticism (3.9) while psychological distress (BSI) is not a significant predictor. After controlling for variations in demographic and clinical variables and entering all interaction terms, the unique effect of cultural origin group is significant (.008) contributing 1.2% to the explained variance of 20.5% (adjusted). Hierarchical regressions for three cultural groups (Table 3) reveal substantially different patterns of predictors of DEB severity. Beginning with second generation Israelis (top panel), weight is not a significant correlate. However, self criticism and the interaction of self-criticism with marital status make significant contributions. In contrast, for both first generation groups (middle and bottom panels), weight is the strongest predictor followed by self-criticism. There also are considerable differences regarding the amount of explained variance; for second generation Israelis, the model accounts for almost 30% Table 2b. Bivariate Correlation Analyses: Two Cultural Origin Groups DEB Disordered Eating (DEB) Age

-.16*

Age Education Income▪ Weight▪ CSS

BSI

-.13

Education

.08

-.08

Income Sufficiency▪

.02

-.01

Weight▪

.27*** .11

Below the diagonal: Parents Born in Israel (PBI) (n=103). DEB = Disordered Eating Behaviors, CSS = Critical Self Scale, BSI = Brief Symptom Inventory ◊ p< 0.10, *p < 0.05, **p < 0.01, ***p < 0.001 ▪ Spearman›s RHO (ordinal data)

Distress (BSI)

.15◊

.02

.31***

.19*

.10

-.46**

.01

.04

-.06

.08

-.30***

-.08

-.15

-.31***

.08

.10

.18*

.05

.09

-.16* -.11

.09

-.02

.25***

.13

-.04 -.08

.24***

.11

Self Criticism .23** .02 (CSS) .50***

.17*

◊

.46***

◊

.38***

Above the diagonal: PBA/S (n=162). Below the diagonal: PBA/A (n=183) DEB = Disordered Eating Behaviors, CSS = Critical Self Scale, BSI = Brief Symptom Inventory ◊ p< 0.10, *p < 0.05, **p < 0.01, ***p < 0.001 ▪ Spearman›s RHO (ordinal data)

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Disordered Eating and Cultural Distinctions: Exploring Prevalence and Predictors among Women in Israel

Table 3. Hierarchical Regressions: Variables Influencing DEB by Cultural Origin Group Variables influencing DEB

Change statistics R F change change p

Overall

PBI Jews (N=103) Age (yrs)

.055

5.879

.017

.055

101

5.879 .017

Marital Status (MS)

.038

2.092

n.s

.093

3.397

.021

Education (yrs)

0.000

.003

n.s

.093

2.523

.046

Weight

.045

.023

2.529

n.s

.139

2.577

Self Criticism .108 (CSS)

13.586

.000 .246

4.440 .000

Distress (BSI) 0.000

.020

n.s

3.847 .001

MS x CSS

8.617

.000 .366

.119

.247

10, 92

5.300 0.000

Adjusted R2 for total model = .297 PBA/S Sephardic Jews (N=162) Age (yrs)

.016

2.644

n.s

.016

160 2.644 n.s

Marital Status (MS)

.002

.174

n.s

.018

158

0.988 n.s

Education (yrs)

.014

2.242

n.s

.032

157

1.308

n.s

Weight

.102

9.164

.000 .135

155

4.017

.001

Self Criticism .039 (CSS)

7.242

.008 .173

154

4.616

.000

Distress (BSI) .004

.822

n.s

.178

153

4.137

.000

MS x CSS

1.089

n.s

.190

10, 151

3.532

.000

.012

Adjusted R2 for total model = .136 PBA/A Ashkenazi Jews (N=183) Age (yrs)

.025

4.649

.032

.025

181

4.649 .032

Marital Status (MS)

.029

2.719

n.s

.054

179

3.392 .019

Education (yrs)

.004

.710

n.s

.058

178

2.717

.031

Weight

.057

5.660

.004 .115

176

3.793

.001

Self Criticism .037 (CSS)

7.620

.006 .151

175

4.462 .000

174

3.940 .000

Distress (BSI) .002

.393

n.s

.153

MS x CSS

.529

n.s

.159

10, 172

.005

3.241

.001

Adjusted R for total model = .110 PBI - Parents Born in Israel PBA - Parents Born Abroad DEB = Disordered Eating Behaviors, CSS = Critical Self Scale, BSI = Brief Symptom Inventory 2

compared to 13.6% and 11% for Sephardic and Ashkenazi respondents respectively. In brief, these findings document a complex reality regarding cultural aspects of disordered eating. Along with substantial differences between first and 150

second generation groups, there also are strong similarities for first generation respondents from distinctly different cultural backgrounds. Discussion In general, there is a dearth of data concerning serious eating problems among adult women from diverse cultural origins. While socio-cultural factors have been considered central to their development, our understanding of the relationship remains “relatively rudimentary” (33). The current study highlights cultural considerations by comparing prevalence and clinical predictors for three culturally distinct groups of Israeli Jews. Beginning with the prevalence of disordered eating in this study, it is estimated at 15%. This is based on a 14.5% rate among those who completed screening questionnaires (n=1194) and a slightly higher rate of 15.9% for telephone interviewees (n=567). It is important to note that the overall rate of 15% is comparable to other studies of eating problems among adult women. These include a 13% rate with “probable” binge eating (1), and a 14% rate with regular binge eating (2), 12% meeting diagnostic criteria for binge eating disorder, binge eating, or eating disorder not otherwise in a U.S. population study (34) and 17% with disordered eating among primary care users in Israel (35). The prevalence rate varies considerably by cultural origin with lower and similar rates for Sephardic and Ashkenazi Jews (11.4%, 13.9%; ns) compared to a higher rate of 19.4% for PBI respondents (p<.05). Indeed, the PBI rate is substantially higher than for adult women in community studies from the U.S. At first glance, one explanation points to a greater exposure to Israel’s westernized norms. There are, however, several caveats. First, assuming that societal norms influence the development of eating disturbances, it is unclear which specific norms are involved, particularly for adult women whose disturbed eating patterns largely reflect binge eating. Second, if westernized norms are major contributors, equally high rates should be found among Ashkenazi women (PBA/A) with cultural roots in highly westernized countries (Europe, Americas). Third, without specifically assessing respondents’ level of awareness and internalization of specific norms (36), the attribution of eating problems to cultural norms remains purely speculative. Fourth, all three cultural origin groups have similar levels of exposure to Israeli norms and, thus, would be expected to have similar rates of disordered eating. Indeed, the concept of “biculturality,” which “… assumes the possibility of vitality, effectiveness and fulfillment in the

Marjorie C. Feinson and Adi Meir

process of experiencing two cultures,” may be particularly relevant to lower rates for first generation respondents. Having been born in Israel, albeit to immigrant parents, may produce identification with two cultures, rather than a conflict in having to choose one or the other. In this regard, “biculturality” may turn out to be an important protective factor rather than a risk factor (37). In addition, the lowest rate of disordered eating found among Sephardic respondents might reflect stabilizing aspects of Sephardic culture, as recently described by Feinson and Meir (38). Regarding the substantial influence of weight found in many studies (25, 35, 39-41), the contribution of weight is not consistent for Israelis. Obesity is the strongest predictor of DEB severity for Sephardic and Ashkenazi women, but not at all significant for second generation Israelis. This finding is similar to variations for adult Black, White, and Hispanic women in a U.S. study (42). Self-criticism is a significant predictor of DEB severity and particularly influential for second generation Israelis (PBI). The consistent and significant role of critical selfjudgments, together with an insignificant contribution of psychological distress, is noteworthy, and may warrant a shift not only in assessment and treatment interventions, but perhaps in prevention strategies as well (43). These findings also support several other studies that recognize a critical view of the self as an important risk factor vis-à-vis eating disturbances in adulthood (e.g., 44, 45). A forthcoming analysis will shed further light on the relationship between self-criticism and DEB. Another striking group difference is that the regression model explains more than twice as much variance for second generation respondents compared to their first generation counterparts: 29.7 % vs. 13.6%, 11% (respectively). Apparently, the same correlates are not similarly meaningful for culturally distinct groups. Clearly, additional variables not currently included are needed in order to better understand disordered eating severity among Sephardic and Ashkenazi Jews. Meanwhile, these different predictor patterns reveal the limitations of a single explanatory model that “… a given risk factor applies to all cases” while highlighting the need for a “… more complicated explanatory model than ‘one size fits all’…” (46). Indeed, some researchers have observed the need to investigate a broad range of common risk factors, together with factors unique to specific groups (47). Some risk factors that have begun to be explored include specific events or experiences such as family dysfunction and childhood abuse (48), physical abuse and bullying by peers (26) and sexual assault (49). Experiences of emotional abuse in

childhood were explicitly linked to the development of eating problems in a recent qualitative study of Israeli women (50). The analysis of 25 personal narratives by Feinson and Ben Dror (50) uncovered a broad range of emotionally abusive experiences including emotional neglect and abandonment, death or illness in the family without the presence of nurturing adults, geographic dislocation, and the aftermath of the Holocaust. Most interviewees directly attributed their eating problems to these experiences because, as children, food helped to ease the pain and suffering when there was nothing else. A forthcoming analysis of the Israeli quantitative study will provide a detailed exploration of abuse issues in childhood and the connection to DEB in adulthood. Conclusion Several methodological caveats are relevant to the findings. First, categorizing diverse groups into a single origin group obscures unique cultural characteristics which may influence the findings. Also, a full understanding of cultural influences necessitates measuring the degree of identification with beliefs and traditions of particular cultural groups (36), including attitudes toward eating, the meaning of food, and family behaviors vis-à-vis eating rituals and meals. Finally, eating disturbances develop over time and cross-sectional studies do not capture developmental processes nor do they permit causal inferences. They are, however, extremely useful in identifying meaningful correlates, which, as this analysis reveals, differ significantly among Israeli Jews from diverse cultural origins. These limitations notwithstanding, the study contains important methodological advantages. Respondents come from a part of the world and cultural groups not previously studied. Moreover, this community-based study focuses on adult women from a broad age range, in contrast to the majority of studies that utilize convenience samples of high school and college students. While several North American studies show higher rates of eating problems among Jews (51, 52), the present analysis reveals considerable heterogeneity within a Jewish sample. Also, the complex relationship between disordered eating and cultural origin is explored with multivariate analyses that reveal strikingly different patterns of predictors. Moreover, the important contribution of critical self-judgment, rather than psychological distress, provides an intriguing insight, with treatment and prevention implications. Another methodological advantage is a clinically meaningful instrument for assessing disordered 151

Disordered Eating and Cultural Distinctions: Exploring Prevalence and Predictors among Women in Israel

eating with a multicultural population. The absence of adequately standardized instruments with documented utility for use with older individuals (1), makes the assessment of eating problems challenging (8, 53, 54), especially for respondents whose primary language is not English. Therefore, our culturally-sensitive screening questionnaire was developed from widely used instruments measuring eating pathology. Although not subject to rigorous psychometric evaluation, the findings indicate acceptable internal consistency as a measure of disordered eating with a multicultural community sample (54), where symptom patterns rather than diagnoses are the focus. In summary, the complexity of serious eating problems among adult women from diverse cultural backgrounds requires additional exploration. Expanding the research agenda to include a broad spectrum of socio-cultural risk factors has significant implications for prevention policies and treatment strategies. Undoubtedly, the heterogeneity of adult women with eating problems warrants the development of more illuminating explanatory models than “one size fits all.” Acknowledgements A great debt of gratitude to women in Israel without whose participation there would be no study. This includes more than 1,500 who completed DEB screening questionnaires in the clinics and more than 800 who graciously participated in long telephone interviews. Outstanding Field Supervisors, Lisa (Gold) Margolin and Tamar (Levy) Ben Dror, were responsible for the first and second waves of data collection and a joy to work with. Generous funding from The Hadassah Foundation, New York and Geula Charitable Trust, New York made this work possible. Thank you all.

References 1. Marcus M, Bromberger J, Wei H-L, Brown C, Kravitz H. Prevalence and selected correlates of eating disorder symptoms among a multiethnic community sample of midlife women. Ann Behav Med 2007;33:269-277. 2. Reagan P, Hersch J. Influence of race, gender and socioeconomic status on binge eating frequency in a population-based sample. Int J Eat Disord 2005;38:252-256. 3. Striegel-Moore RH, Wilfley DE, Pike KM, Dohm FA, Fairburn CG. Recurrent binge eating in Black American women. Arch Fam Med 2000;9:83-87. 4. Smith ED, Marcus MD, Lewis CE, Fitzgibbon ML, Schreiner P. Prevalence of binge eating disorder, obesity, and depression in a biracial cohort of young adults. Ann Behav Med 1998;20:227-232. 5. Wilfley DE, Schreiber GB, Pike KM, Striegel-Moore RH, Wright DJ, Rodin J. Eating disturbance and body image: A comparison of a community sample of adult Black and White women. Int J Eat Disord 1996;20:377-387. 6. Striegel-Moore RH, Fairburn CG, Wilfley DE, Pike KM, Dohm FA, Kraemer HC. Toward an understanding of risk factors for binge-eating disorder in black and white women: A community-based case-control study. Psychol Med 2005;35:907-917. 7. Pike KM, Dohm FA, Striegel-Moore RH, Wilfley DE, Fairburn CG. A comparison of Black and White women with binge eating disorder. Am J Psychiatry 2001;158:1455-1460.

152

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Marjorie C. Feinson and Adi Meir

31. Ritsner M, Ponizovsky A, Kurs R, Modai I. Somatization in an immigrant population in Israel: A community survey of prevalence, risk factors, and help-seeking behavior. Am J Psychiatry 2000;157:385-392. 32. Central Bureau of Statistics. Statistical Abstract of Israel. No 54. Jerusalem, Israel, 2003. 33. Cummins LH, Simmons AM, Zane NWS. Eating disorders in Asian populations: A critique of current approaches to the study of culture, ethnicity, and eating disorders. Am J Orthopsychiatry 2005;75:553-574. 34. Bruce B, Agras WS. Binge eating in females: A population-based investigation. Int J Eat Disord 1991;12:365-373. 35. Darby A, Hay P, Mond J, Quirk F, Buttner P, Kennedy L. The rising prevalence of comorbid obesity and eating disorder behaviors from 1995 to 2005. Int J Eat Disord 2009;42:104-108. 36. Warren CS, Gleaves DH, Cepeda-Benito A, Fernandez MC, RodriguezRuiz S. Ethnicity as a protective factor against internalization of a thin ideal and body dissatisfaction. Int J Eat Disord 2005;37:241-249. 37. Mezzich J, Ruiperez MA, Yoon G, Liu J, Zapata-Vega MI. Measuring cultural identity: Validation of a modified Cortes, Rogler and Malgady bicultural scale in three ethnic groups in New York. Cult Med Psychiatry 2009;33:451-472. 38. Feinson MC, Meir A. Disordered eating and complexities of cultural origin: A focus on Jews from Muslim countries Eat Behav 2012;13:135138. 39. Pike KM, Dohm FA, Striegel-Moore RH, Wilfley DE, Fairburn CG. A comparison of black and white women with binge eating disorder. Am J Psychiatry 2001;158:1455-1460. 40. Alegria M, Woo M, Cao Z, Torres M, Meng XL, Striegel-Moore R. Prevalence and correlates of eating disorders in Latinos in the United States. Int J Eat Disord 2007;40:S15-S21. 41. Cachelin FM, Veisel C, Barzegarnazari E, Striegel-Moore RH. Disordered eating, acculturation and treatment-seeking in a community sample of Hispanic, Asian, Black, and White women. Psychol Women Q 2000;24:244-253. 42. Fitzgibbon ML, Spring B, Avellone ME, Blackman LR, Pingitore R, Stolley MR. Correlates of binge eating in Hispanic, Black, and White

women. Int J Eat Disord 1998;24:43-52. 43. Fennig S, Hadas A, Itzhaky L, Roe D, Apter A, Shahar G. Self-criticism is a key predictor of eating disorder dimensions among inpatient adolescent females. Int J Eat Disord [Brief report] 2008;41:762-765. 44. Dunkley DM, Masheb RM, Grilo CM. Childhood maltreatment, depressive symptoms, and body dissatisfaction in patients with binge eating disorder: The mediating role of self-criticism. Int J Eat Disord 2010;43:274-281. 45. Dunkley DM, Grilo CM. Self-criticism, low self-esteem, depressive symptoms, and over-evaluation of shape and weight in binge eating disorder patients. Behav Res Ther 2007;45:139-149. 46. Striegel-Moore RH, Dohm FA, Kraemer HC, Schreiber GB, Taylor CB, Daniels SR. Risk factors for binge-eating disorders: An exploratory study. Int J Eat Disord 2007;40:481-487. 47. Harrington EF, Crowther JH, Henrickson HC, Mickelson KD. The relationships among trauma, stress, ethnicity, and binge eating. Cultur Divers Ethnic Minor Psychol 2006;12:212-229. 48. Mazzeo SE, Mitchell KS, Williams LJ. Anxiety, alexithymia, and depression as mediators of the association between childhood abuse and eating disordered behavior in African American and European American women. Psychol Women Q 2008;32:267-280. 49. La Flair LN, Franko DL, Herzog DB. Sexual assualt and disordered eating in Asian women. Harv Rev Psychiatry 2008;16:248-257. 50. Feinson MC, Ben Dror T. Soul food: Emotional abuse in childhood and the complex role of food. Adv Gender Res 2010;14:35-63. 51. Pinhas L, Heinmaa M, Bryden P, Bradley S, Toner B. Disordered eating in Jewish adolescent girls. Can J Psychiatry 2008;53:601-608. 52. Rayworth BB, Wise LA, Harlow BL. Childhood abuse and risk of eating disorders in women. Epidemiology 2004;15:271-278. 53. Striegel-Moore RH, Bulik CM. Risk factors for eating disorders. Am Psychol 2007;62:181-198. 54. Franko DL, Becker AE, Thomas JJ, Herzog DB. Cross-ethnic differences in eating disorder symptoms and related distress. Int J Eat Disord 2007;40:156-164.

153

‫ההיריון והלידה ועל החוויה הסובייקטיבית שלה‪ ,‬על מנת‬ ‫לצפות סימפטומים של חרדה לאחר לידה‪ ,‬אפילו על ידי שאלון‬ ‫סקירה קצר‪ .‬הממצא שלפיו תסמונת פוסט–טראומטית קשורה‬ ‫לחומרת החרדה לאחר לידה יכול לשמש בעתיד כסמן לתסמונת‬ ‫פוסט–טראומטית בקרב נשים שערכי החרדה אצלן גבוהים‪.‬‬ ‫אריפיפרזול בשילוב עם תכשירים פסיכוטרופיים‬ ‫אחרים בהיריון‪ :‬שני תיאורי מקרה‬

‫ו‪ .‬פירק‪ ,‬א‪ .‬מהטה וס‪ .‬שוש‪ ,‬שיקאגו‪ ,‬ארה"ב‬

‫חשיפה של האם לתכשירים אנטי–פסיכוטיים מהדור השני‬ ‫במשך ההיריון נקשרת לכמה תופעות שליליות אצל האמהות‬ ‫והתינוקות‪ .‬אריפיפרזול נכנס לשימוש רחב יותר‪ ,‬אולם נתונים‬ ‫לגבי השימוש בו בהיריון מועטים‪ .‬כמו כן‪ ,‬יש מידע מועט על‬ ‫ההשפעה של שילובי תרופות על תוצאות ההיריון‪.‬‬ ‫בהתחשב במעט המידע הקיים בהקשר לשימוש‬ ‫באריפיפרזול בהיריון‪ ,‬קשה לייעץ לנשים (הרות) לגבי‬ ‫הסיכונים הפוטנציאליים ולגבי תופעות הלוואי של התרופה‪.‬‬ ‫אנו מציגים שני מקרים שמתארים שימוש באריפיפרזול כחלק‬ ‫מתכנית טיפול המשלבת תרופות לאישה בהיריון‪ ,‬ומתארים‬ ‫את תוצאות ההיריון‪ ,‬כדי לסייע לרופאים הניצבים בפני‬ ‫החלטות טיפול מורכבות בנשים הרות‪.‬‬ ‫מגדר ואכילה מופרעת בקרב מתבגרים בישראל‬

‫ב‪ .‬כץ‪ ,‬עכו‬

‫רקע‪ :‬מחקרים מהעשורים האחרונים מצביעים על עלייה‬ ‫בחוסר שביעות הרצון מהמשקל ובשכיחות של אכילה מופרעת‬ ‫בגיל מוקדם כביטויים של אידיאל הרזון‪.‬‬ ‫מטרה‪ :‬מחקר זה אומד את השכיחות של אכילה מופרעת‬ ‫(מעל לציון סף ‪ 30‬לפי שאלון ‪ )EAT-40‬בקרב תלמידים בישראל‪.‬‬ ‫שיטות‪ :‬מדגם המחקר כלל ‪ 326‬בני נוער ישראלים (יהודים)‬ ‫מכיתות ז' עד יב' מארבעה בתי ספר‪ 323 .‬מהם (‪ 181‬בנות‬ ‫ו–‪ 142‬בנים) השיבו על שאלון דיווח עצמי (‪ )EAT-40‬שבחן את‬ ‫עמדותיהם כלפי אכילה‪ ,‬ועל שאלון נוסף שהתייחס למאפיינים‬ ‫אישיים ומידע אחר‪.‬‬ ‫תוצאות‪ 41.5% :‬מהמתבגרים אינם מרוצים מהמשקל שלהם‬ ‫ו–‪ 45.3%‬הביעו רצון להפחית ממשקלם‪ .‬שליש מהמדגם עסוק‬ ‫בדיאטה לעתים קרובות‪ .‬ל–‪ 6.1%‬מבני הנוער יש ציוני אכילה‬ ‫מופרעת‪ .‬שיעור הבנות עם ציונים אלה גבוה פי ‪ 3‬משיעור‬ ‫הבנים‪ .‬נמצא כי ל–‪ 8.2%‬מהבנות ול–‪ 2.8%‬מהבנים יש ציוני‬ ‫אכילה מופרעת (‪ .)Ø=0.115, p<0.05‬מספר המתבגרים שקיבלו‬ ‫ציוני אכילה מופרעת בקרב מתבגרים שאינם מרוצים ממשקלם‬

‫גבוה פי ‪ 7.6‬ממספר המתבגרים שקיבלו ציוני אכילה מופרעת‬ ‫בקבוצת המתבגרים אשר מרוצים ממשקלם (;‪Ø=0.220‬‬ ‫‪ .)p<0.01‬מספר המתבגרים שקיבלו ציוני אכילה מופרעת‬ ‫בקרב אלה שרוצים להפחית ממשקלם גבוה פי ‪ 10.8‬ממספר‬ ‫המתבגרים שקיבלו ציוני אכילה מופרעת בקבוצת המתבגרים‬ ‫שאינם רוצים להפחית ממשקלם‪ .‬לא נמצאו הבדלים מובהקים‬ ‫בציוני אכילה מופרעת בקרב מתבגרים ממוצא שונה או ברמות‬ ‫דתיות שונות‪.‬‬ ‫מסקנות‪ :‬השכיחות של התנהגות אכילה מופרעת בקרב בני‬ ‫נוער גבוהה יותר בישראל מאשר במדינות אחרות בכלל‪ ,‬ובקרב‬ ‫בנים בפרט‪ .‬יש צורך במאמץ מוגבר לאיתור מתבגרים בסיכון‬ ‫לפיתוח הפרעות אכילה בסיוע כלים קליניים‪ .‬נוסף על כך יש‬ ‫להנהיג מדיניות של חינוך למניעת הפרעות אכילה‪.‬‬ ‫הבדלים בין תרבותיים בשכיחות של‬ ‫הפרעות אכילה ובגורמים המנבאים אותן‪:‬‬ ‫מחקר על נשים בישראל‬ ‫מ‪ .‬ס‪ .‬פיינסון וע‪ .‬מאיר‪ ,‬ירושלים‬

‫רקע‪ :‬להבדלים בין תרבותיים בהפרעות אכילה עשויות להיות‬ ‫השלכות ניכרות על אופני המניעה של הפרעות אלה ועל‬ ‫הטיפול בהן‪ ,‬אך למרות זאת הבדלים אלו לא נחקרו בהרחבה‬ ‫עד כה‪ .‬זהו המחקר הראשון שבוחן הבדלים אלה בקרב נשים‬ ‫בוגרות בחברה הרב־תרבותית של ישראל‪.‬‬ ‫שיטה‪ :‬קיומה של הפרעת אכילה (‪ )DEB‬הוערך על פי ‪14‬‬ ‫סימפטומים הלקוחים מה–‪( DSM‬כולל בולמוס אכילה)‪ ,‬בקרב‬ ‫מדגם של ‪ 485‬נשים‪ .‬במחקר נבחנו שכיחות התופעה והגורמים‬ ‫המנבאים אותה בשלוש קבוצות של נשים יהודיות‪ ,‬המובחנות‬ ‫מבחינה תרבותית‪.‬‬ ‫תוצאות‪ :‬בשלוש קבוצות הנשים‪ ,‬דור שני של ילידות ישראל‪,‬‬ ‫דור ראשון בישראל ממוצא ספרדי ודור ראשון בישראל ממוצא‬ ‫אשכנזי‪ ,‬נמצאה שכיחות שונה של הפרעות אכילה (‪,19.4%‬‬ ‫‪ 11.4%‬ו–‪ ,13.9%‬בהתאמה‪ .)p<.05 .‬מבין המנבאים הקליניים‬ ‫להפרעת אכילה‪ ,‬המנבא החזק ביותר בקרב ילידות הארץ מדור‬ ‫שני הוא ביקורת עצמית‪ ,‬בעוד המנבא החזק ביותר עבור שתי‬ ‫הקבוצות האחרות הוא המשקל‪.‬‬ ‫מסקנות‪ :‬מקובל לחשוב שהפרעות אכילה קשורות לנורמות‬ ‫הרזון הנהוגות בחברה‪ ,‬אולם ההבדלים בין ישראליות מרקעים‬ ‫תרבותיים שונים‪ ,‬שלהן רמת חשיפה דומה לנורמות המערביות‪,‬‬ ‫קוראים תיגר על התפישה המקובלת הזו‪ .‬נדרש מחקר נוסף‬ ‫ופיתוח של מודלים שמתחשבים בהבדלים בין תרבותיים‪ ,‬על‬ ‫מנת שהטיפולים יוכלו להיות רגישים לתרבות‪.‬‬

‫‪154‬‬

‫דיכאון בקרב אימהות והתפיסה‬ ‫לגבי סיכון למומים בעובר‬ ‫ג‪ .‬קורן‪ ,‬טורונטו‪ ,‬קנדה‬

‫דיכאון בהיריון מאופיין בתפיסה לא מציאותית מוקצנת לגבי‬ ‫הסיכון למומים אצל היילוד‪ .‬ייעוץ הולם ומתאים‪ ,‬בהקשר‬ ‫לסיכון‪ ,‬יכול להפחית את הדאגה של האם‪ .‬טיפול נאות‬ ‫בדיכאון במהלך ההיריון‪ ,‬ובמקביל מתן ייעוץ (המבוסס על‬ ‫מידע קיים) לגבי השימוש בנוגדי דיכאון במהלך ההיריון‪ ,‬יכול‬ ‫למנוע סיכונים בריאותיים משמעותיים‪.‬‬ ‫ההשפעה של אפקט חיובי ושלילי של האם על‬ ‫הפיזיולוגיה של העובר ועל דפוסים יומיים‬

‫ג' הנלי‪ ,‬ד' רורק‪ ,‬ק' לים‪ ,‬א' בריין‪ ,‬וט' פ' אוברלנדר‪ ,‬וונקובר‪ ,‬קנדה‬

‫רקע‪ :‬בעוד מחקרים הראו שמצב הרוח של האם (דיכאון או‬ ‫חרדה) יכול להשפיע על העובר‪ ,‬מעט ידוע על ההשפעה של‬ ‫אפקט חיובי ואפקט שלילי של האם על העובר‪.‬‬ ‫שיטה‪ :‬שינויים בכלי הדם ובקצב הלב של העובר נבדקו‬ ‫בשבוע ה–‪ 36‬של ההיריון בקרב ‪ 53‬אמהות אוטימיות לפי ציוני‬ ‫סולם אפקט חיובי ושלילי‪.‬‬ ‫תוצאות‪ :‬אצל אמהות שדיווחו על רמות גבוהות של אפקט‬ ‫שלילי נראתה זרימה מופחתת בעורקי הרחם‪ ,‬ירידה בהשתנות‬ ‫קצב הלב של העובר (‪ ,)fHR‬שינויים בדפוס היומי וירידה של‬ ‫עורק הרחם באזור החתך הרוחבי בהשוואה לאמהות שדיווחו‬ ‫על רמות נמוכות של אפקט שלילי‪ .‬לאמהות שנמצא אצלן‬ ‫אפקט חיובי נמוך היה דפוס יומי תלול יותר בתאוצת ‪fHR‬‬ ‫והמהירות הממוצעת של הזרימה בעורק הרחם אצלן הייתה‬ ‫נמוכה יותר בהשוואה לאמהות עם אפקט חיובי גבוה‪.‬‬ ‫מגבלות‪ :‬במחקר תצפיתי זה גודל המדגם היה קטן‪.‬‬ ‫מסקנה‪ :‬גם בהיעדר הפרעת דיכאון חמורה של ציר ‪ ,I‬ואריאציות‬ ‫באפקט של האם נראות קשורות לשינויים בפיזיולוגיה של הרחם‬ ‫ושל העובר‪.‬‬ ‫הבדלי מגדר מבחינת מידת השימוש‬ ‫ומאפייני השימוש בתרופות פסיכוטרופיות‬ ‫בקרב קשישים בישראל‬

‫צ‪ .‬בלומשטיין‪ ,‬י‪ .‬בנימיני‪ ,‬ד‪ .‬שמוטקין ול‪ .‬לרנר־גבע‪ ,‬רמת גן‬

‫רקע‪ :‬מטרת מחקר זה היא להעריך הבדלי מגדר מבחינת מידת‬ ‫השימוש בתרופות פסיכוטרופיות‪ ,‬ולמפות את המאפיינים‬ ‫הסוציו–דמוגרפיים והבריאותיים הקשורים לשימוש זה בקרב‬ ‫ישראלים קשישים‪.‬‬ ‫שיטה‪ :‬המחקר מתבסס על נתוני סקר ארצי של האוכלוסייה‬ ‫היהודית בגילאי ‪ 94-65‬המתגוררת בקהילה בישראל‪ .‬תרופות‬ ‫פסיכוטרופיות אותרו מנתוני התרופות שנוטלים הנבדקים‪,‬‬ ‫כפי שדווחו בעת ריאיון פנים אל פנים‪ .‬המחקר מתמקד בשלוש‬ ‫קטגוריות של תרופות‪ :‬נוגדי חרדה (‪ ,)anxiolytics‬מיישנים‬ ‫(‪ )sedatives/hypnotics‬ונוגדי דיכאון (‪.)antidepressants‬‬ ‫‪155‬‬

‫ממצאים‪ :‬נמצא באופן מובהק כי נשים משתמשות יותר‬ ‫מגברים בנוגדי חרדה‪ ,‬גם לאחר התאמה למצב הבריאות‬ ‫הגופנית והנפשית הירוד יותר של נשים‪ .‬במודל רב משתנים‬ ‫לבדיקת הגורמים הקשורים לשימוש בנוגדי חרדה ומיישנים‬ ‫יחדיו‪ ,‬נמצא כי השימוש בתרופות אלה בקרב גברים היה‬ ‫קשור לעלייה בגיל‪ ,‬למצב משפחתי (לא נשוי)‪ ,‬לבעיות שינה‪,‬‬ ‫ולסימפטומים של דיכאון‪ ,‬ואילו בקרב נשים שימוש בתרופות‬ ‫אלה היה קשור למספר התרופות הלא־פסיכוטרופיות‪ ,‬לאירועי‬ ‫חיים טראומטיים‪ ,‬ולמצב משפחתי (נשואה)‪ .‬השימוש בנוגדי‬ ‫דיכאון היה מועט הן בקרב נשים והן בקרב גברים‪ ,‬ונמצא קשור‬ ‫בעיקר למוגבלות בתפקודי היום יום (‪.)ADL‬‬ ‫מסקנות‪ :‬מחקר זה מצביע על נטייה לרישום יתר של נוגדי‬ ‫חרדה לנשים‪ ,‬על אבחון חסר של דיכאון ועל טיפול לא מספק‬ ‫בו בקרב קשישים בארץ‪.‬‬ ‫חרדה לאחר לידה בקוהורט של נשים באוכלוסייה‬ ‫הכללית‪ :‬גורמי סיכון וקשר לדיכאון במהלך‬ ‫השבוע האחרון של ההיריון‪ ,‬לדיכאון לאחר‬ ‫לידה ולתסמונת פוסט־טראומטית לאחר לידה‬

‫ע' שלומי־פולצ'ק‪ ,‬ל' הולר הררי‪ ,‬מ' באום וי' שטראוס‪ ,‬באר יעקב‬

‫רקע‪ :‬בשונה מדיכאון לאחר לידה‪ ,‬חרדה לאחר לידה זכתה‬ ‫להתייחסות מועטה‪ ,‬בעיקר באוכלוסייה הכללית‪ .‬הכרה‬ ‫בתופעה היא חשובה‪ ,‬מפני שהתופעה עלולה להוביל למצוקה‬ ‫משמעותית ולפגיעה בתפקוד האם‪.‬‬ ‫מטרה‪ :‬לחקור את התופעה בקוהורט של נשים באוכלוסייה‬ ‫הכללית ולבדוק גורמים אפשריים לה‪.‬‬ ‫שיטות‪ :‬בימים הראשונים לאחר הלידה רואיינו נשים‬ ‫במחלקת יולדות במרכז הרפואי ע"ש חיים שיבא‪ .‬שאלוני‬ ‫המחקר כללו משתנים פסיכוסוציאליים‪ ,‬רגשות ופחדים במהלך‬ ‫ההיריון והלידה וכן את ה–‪Edinburgh Postnatal Depression‬‬ ‫‪( )EPDS( Scale‬אשר התייחס לשבוע האחרון לפני הלידה)‪.‬‬ ‫לאחר חודש השלימו הנבדקות את ה–‪ ,EPDS‬ה–‪modified‬‬ ‫‪ Spielberger Anxiety Scale‬וה–‪Diagnostic ScalePost traumatic‬‬ ‫‪ Stress‬בריאיון שנערך בטלפון‪.‬‬ ‫תוצאות‪ :‬בקרב ‪ 40.4%‬מהמשתתפות נמצאו ערכי חרדה‬ ‫גבוהים‪ .‬נמצא קשר משמעותי בין חרדה לאחר לידה‪ ,‬דיכאון‬ ‫בשבוע האחרון של ההיריון‪ ,‬דיכאון לאחר לידה ותסמונת פוסט–‬ ‫טראומטית לאחר לידה‪ .‬ערכי החרדה של הנבדקות שסבלו‬ ‫מתסמונת פוסט–טראומטית לאחר לידה היו גדולים בכמעט‬ ‫‪ 50%‬מאלו של נשים שסבלו מדיכאון לאחר לידה‪ .‬כמו כן נמצא‬ ‫קשר לפחד מהלידה‪ ,‬לפחד ממוות במהלך הלידה (אם או עובר)‪,‬‬ ‫להרגשה של חוסר שליטה במהלך הלידה ולביטחון נמוך יותר‬ ‫בעצמן ובצוות הרפואי‪ 75% .‬מהנשים שסבלו מחרדה לאחר לידה‬ ‫דיווחו על כעס‪ ,‬פחד או ניתוק רגשי במהלך הלידה‪ .‬לא נמצא קשר‬ ‫בין חרדה לאחר לידה לבין לסיבוכים מיילדותיים‪.‬‬ ‫מסקנות‪ :‬עולה כי סימפטומים של חרדה נפוצים לאחר לידה‪,‬‬ ‫ולכן חשוב לשאול את המטופלת על דיכאון‪ ,‬על פחדים במהלך‬

‫כתב עת ישראלי‬ ‫לפסיכיאטריה‬ ‫תקצירים‬ ‫הבדלי מגדר בפסיכופתולוגיה‬ ‫של פסיכוזה שמתפרצת‬

‫א‪ .‬גונזלס־רודריגז‪ ,‬א‪ .‬סטודרס‪ ,‬א‪ .‬שפיץ‪ ,‬ה‪ .‬בוגרה‪ ,‬ג'‪ .‬אסטון‪,‬‬ ‫ס‪ .‬בורגוורט‪ ,‬ס‪ .‬ראפ וא‪ .‬רייכלר־רוסלר‪ ,‬בריסל‪ ,‬בלגיה‬

‫רקע‪ :‬לעתים קרובות נצפו הבדלים בין המגדרים בסימפטומים‬ ‫הפסיכופתולוגיים בקרב אנשים חולי סכיזופרניה כרונית‬ ‫וכן בקרב אנשים הסובלים מאפיזודה ראשונה של פסיכוזה‪.‬‬ ‫למרות זאת‪ ,‬רוב המחקרים בנושא לוקים בבעיות מתודולוגיות‬ ‫ובתוצאות לא עקביות‪ .‬נוסף על כך‪ ,‬מעט מחקרים בדקו את‬ ‫ההבדלים המגדריים בקרב אנשים הנמצאים במצב נפשי שיש‬ ‫בו סיכון לפסיכוזה‪.‬‬ ‫שיטות‪ :‬הערכת הסימפטומים הפסיכופתולוגיים של ‪117‬‬ ‫מטופלים הנמצאים בסיכון למצב פסיכוטי ושל ‪ 87‬מטופלים‬ ‫שחוו אפיזודה ראשונה של פסיכוזה‪ .‬ההערכה נעשתה‬ ‫באמצעות שני סולמות ‪ -‬הגרסה המורחבת של סולם הדירוג‬ ‫הפסיכיאטרי המקוצר (‪ )BPRS‬והמדד להערכה של סימפטומים‬ ‫שליליים (‪ ,)SANS‬ובאמצעות כלי דיווח עצמי ‪ -‬שאלון תלונות‬ ‫פרנקפוטר (‪ .)FCQ‬הבדלי המגדר נבחנו באמצעות ניתוחי‬ ‫שונות של תת–הסולמות של ה–‪ ,BPRS‬ה–‪ SANS‬וה–‪FCQ‬‬ ‫כמשתנים תלויים‪ ,‬וקבוצה ומין נבחנו כגורמים בין נושאים‬ ‫(‪ - )between subject factors‬בשלב שני באמצעות הכללת‬ ‫גיל ושימוש בתכשירים אנטי–פסיכוטיים‪ ,‬בתכשירים אנטי–‬ ‫דכאוניים ובקנביס כמשתנים המוספים לניתוח הסטטיסטי כדי‬ ‫לפקח על השפעתו (‪.)covariates‬‬ ‫תוצאות‪ :‬לא היו הבדלים מגדריים משמעותיים בין קבוצות‬ ‫המטופלים‪ .‬לנשים היו ציונים גבוהים יותר בסימפטומים‬ ‫הפסיכוטיים החיוביים) פסיכוזה והפרעות חשיבה לפי ה–‬ ‫‪ )BPRS‬ולגברים היו ציונים גבוהים יותר בסימפטומים‬ ‫השליליים (סימנים שליליים לפי ה–‪ ,BPRS‬ציון כולל של‬ ‫ה–‪ SANS‬וכן ציון בתת–הסולמות של השטחה אפקטיבית‪,‬‬ ‫אבוליציה–אפאתיה ואסוציאליות ואנהדוניה)‪ .‬עם זאת‪,‬‬ ‫ההבדלים לא נותרו בעינם בתיקון למבחנים מרובים‪ .‬התוצאות‬ ‫לא השתנו כאשר ההבדלים תוקנו עבור משתנים מתערבים‬ ‫פוטנציאליים‪.‬‬

‫‪israel journal of‬‬

‫‪psychiatry‬‬ ‫כרך ‪ ,51‬מס' ‪2014 ,2‬‬

‫מסקנות‪ :‬נראה שאין הבדלים מגדריים בפסיכופתולוגיה‬ ‫בקרב אנשים שלא נמצאים במצב נפשי שיש בו סיכון לפסיכוזה‬ ‫ובקרב אנשים עם אפיזודה ראשונה של פסיכוזה‪ .‬ממצאים אלה‬ ‫תקפים לגבי סימפטומים בדיווח עצמי או כאלה המדווחים על‬ ‫ידי גורם אחר‪ ,‬כאשר נערכים תיקונים עבור בדיקות מרובות‬ ‫ומשתנים מתערבים פוטנציאליים‪.‬‬ ‫שימוש בתרופות נוגדות דיכאון בתקופת ההיריון‪:‬‬ ‫הערכת תופעות שליליות למעט מומים‬

‫ל‪.‬לורנצו וא‪.‬אינרסון‪ ,‬בואנוס איירס‪ ,‬ארגנטינה‬

‫עד כה התפרסמו עבודות ומחקרים רבים בנושא הבטיחות‬ ‫שבשימוש בתרופות נוגדות דיכאון במהלך ההיריון‪ .‬רוב העבודות‬ ‫התמקדו באפשרות שיש קשר בין נטילת תרופות במהלן ההיריון‬ ‫לבין מומים משמעותיים אצל התינוק‪ .‬עבודות בודדות בלבד‬ ‫נעשו כדי לבדוק תוצאות שליליות אחרות אצל התינוקות‪.‬‬ ‫מטרות‪ :‬לבדוק אפשרות של השפעות שליליות של תרופות‬ ‫נוגדות דיכאון על ההיריון‪.‬‬ ‫שיטות‪ :‬שלפנו מאמרים מרכזיים בנושא מהספרות‬ ‫המקצועית ומאתרים מקצועיים כגון ‪MEDLINE , PUBMED,‬‬ ‫‪ .EMBASE, REPROTOX‬בדקנו את תוצאות כל המחקרים‪,‬‬ ‫למעט אלה שכללו מומים גדולים או קטנים‪.‬‬ ‫תוצאות‪ :‬לא מצאנו שהשימוש בתרופות נוגדות דיכאון‬ ‫במהלך ההיריון מעלה את הסיכון ללידת תינוקות במשקל‬ ‫נמוך מהממוצע או בגודל קטן מהממוצע‪ ,‬ביחס למשך ההיריון‪.‬‬ ‫כמו–כן‪ ,‬לא מצאנו שיש קשר סיבתי בין נטילת התרופות לבין‬ ‫כשלים בהתפתחות הנוירולוגית של התינוקות‪.‬‬ ‫יחד עם זאת‪ ,‬מצאנו כי נטילת התרופות יכולה לגרום להגדלת‬ ‫הסיכון להפלות ספונטניות‪ ,‬ללידות מוקדמות וללידות של‬ ‫תינוקות במשקל נמוך מ–‪ 2.500‬ק"ג‪ .‬נוסף על כך‪ ,‬מצאנו כי נטילת‬ ‫התרופות בשלהי ההיריון גורמת להגדלת הסיכון ל–‪ PPHN‬ול–‬ ‫‪ .PNAS‬יש לציין כי הסיכון הנ"ל היה קטן ולא נמצאו רישומים‬ ‫לגבי השלכותיו או תוצאותיו הקליניות בקרב היילודים‪.‬‬ ‫מסקנות‪ :‬במידת הצורך‪ ,‬אין לשלול טיפול בנשים בהיריון‬ ‫באמצעות תרופות נוגדות דיכאון‪ ,‬מכיוון שאי–טיפול (במצב‬ ‫הדיכאון) עלול‪ ,‬גם הוא‪ ,‬להוביל לתוצאות בלתי רצויות עבור‬ ‫היילוד‪ .‬יש לערוך מחקרים נוספים על מנת להעריך אם הסיבה‬ ‫לתוצאות השליליות הללו היא מחלות אחרות של האם‪,‬‬ ‫התרופות שהאם נטלה במהלך ההיריון או שתי הסיבות גם יחד‪.‬‬ ‫‪156‬‬

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‫‪ | medic.co.il‬הרשמו עכשיו באתר וקבלו מנוי שנתי בהנחה מיוחדת‬ ‫יחזאל‪-‬זמיר ‪ | 054-7568656‬דוא"ל ‪sales@medic.co.il‬‬ ‫ֿ‬ ‫מדיק הוצאה לאור בע"מ | טלפון‪ | 09-9581960 :‬לרכישת מנוי‪ :‬רוני‬

‫גברים רבים הסובלים מ‪ ED -‬סובלים גם מתסמינים‬

‫שתי בעיות‪ .‬פתרון אחד‪.‬‬

‫סיאליס יומי ‪ 5‬מ"ג‪.‬‬ ‫סיאליס יומי לטיפול בהפרעה בזקפה וגם‬ ‫בתסמינים של הגדלה שפירה של הערמונית‪.‬‬

‫למידע מלא נא עיין בעלון לרופא כפי שאושר ע"י משרד הבריאות‪.‬‬ ‫‪Cialis 5mg: For the treatment of erectile dysfunction in adult men.‬‬ ‫‪Treatment of the signs and symptoms of benign prostatic hyperplasma (BPH).‬‬ ‫‪Treatment of ED and the signs and symptoms of BPH (ED/BPH).‬‬

‫יצרן‪ :‬אלי לילי בע"מ‪ ,‬בעל רישום‪ :‬אלי לילי ישראל בע"מ‪ ,‬ת‪.‬ד‪ 2160 .‬הרצליה פיתוח ‪ 46120‬טל‪09-9606234 :‬‬ ‫‪CI051225‬‬

‫‪*Reference: 1. Rosen R, et al. Eur Urol 2003;44:637‬‬

‫של ‪*BPH‬‬