Aijrhass15 754

American International Journal of Research in Humanities, Arts and Social Sciences

Available online at http://www.iasir.net

ISSN (Print): 2328-3734, ISSN (Online): 2328-3696, ISSN (CD-ROM): 2328-3688 AIJRHASS is a refereed, indexed, peer-reviewed, multidisciplinary and open access journal published by International Association of Scientific Innovation and Research (IASIR), USA (An Association Unifying the Sciences, Engineering, and Applied Research)

Trends in child immunization in Empowered Action Group States, India (1990-2006) Dr. Jeetendra Yadav, Subhash Gautam and Kh Jitenkumar Singh National Institute of Medical Statistics (NIMS), Indian Council of Medical Research (ICMR), Deptt. of Health Research, Ministry of Health & Family Welfare, Govt of India, Medical Enclave Ansari Nagar, New Delhi -110029, INDIA. Abstract: Background and Aim: Immunization is a way of protecting the human body against infectious diseases through vaccination. Low use of maternal and child healthcare services is one of the reasons why maternal mortality is still considerably high in India. In India, the eight socioeconomically backward states of Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttarakhand and Uttar Pradesh, referred to as the Empowered Action Group (EAG) states, lag behind in the demographic transition and child immunization were very less. This paper examine the trends in child immunization in Empowered Action Group States, India (1990-2006).

Methodology/Finding: Data from three rounds of the National Family Health Survey of India were analyzed. multivariate-pooled logistic regression model were applied to examine the child immunization trends over time. The results from analysis indicate that the coverage of child immunization has increased from 20 percent to 31 percent during the last one and half decade. Overall, it can be said that, there was an improvement in the level of child immunization over the period of time. There are considerable differentials in child immunization by various individual (education gender, birth order), household (religion, caste, wealth), community (place of residence, state) characteristics.

Conclusion: The study concludes that much of these inequalities are social constructs that can be reduced by prioritizing the needs of the disadvantaged and adopting appropriate policy change options. The vaccination rates are lower among infants with mothers having no or low literacy, and families with insufficient empowerment of women. Paternal literacy and awareness has an inconsistent positive relationship with child vaccination.

Keywords: NFHS, Full ANC, pooled data, MDG, SBA, child immunization, EAG states.

I.

Introduction and reviews of literature

Immunization is a way of protecting the human body against infectious diseases through vaccination.

Immunization prepares human bodies to fight against diseases which can come into contact with them in the future. Immunization is one of the most successful public health interventions of the past century responsible for averting 3 million deaths globally each year and protecting millions more from illness and permanent disability [1]. Globally, vaccine preventable diseases account for nearly 20% of all deaths occurring annually among children under five years of age, and immunization has a vital role to play in achieving the goals specified in the Millennium Declaration [2]. In 2005, WHO and United Nations Children’s Fund (UNICEF) developed the Global Immunization Vision and Strategy (GIVS), with the aim of reducing vaccine-preventable disease related morbidity and mortality by improving national immunization programs [3]. However, according to the Global

AIJRHASS 15-754; Š 2015, AIJRHASS All Rights Reserved

Page 80

Jeetendra Yadav et al., American International Journal of Research in Humanities, Arts and Social Sciences, 12(1), September-November, 2015, pp. 80-89

Routine Vaccination Coverage (GAVI)–2010, about 19.3 million children were not fully vaccinated and remained at risk for diphtheria, tetanus, and pertussis and other vaccine-preventable causes of morbidity and mortality, and about 50% of these children are from India, Nigeria, and Congo [4]. Even though the immunization services in India are being offered free of cost in public health facilities, about 45% of Indian children are deprived of the recommended vaccinations [5]. After independence in 1947, it took three decades for India to articulate its first official policy for childhood vaccination; nevertheless, childhood immunization has been an important part of the Reproductive and Child Health (RCH) services [6-7].

Since population growth in the BIMARU states was much higher than the Indian average in this period, the income disparity between the BIMARU states and India as a whole also increased. The GOI has given a name to these eight states as Empowered Action Groups or EAG states. These states are Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttarakhand and Uttar Pradesh [8]. Among children aged 12-23 months in urban India, 60% are fully immunized (immunization cards and mother’s recall) which presents an average of the better and poorly performing states. Empowered Action Group (EAG) states which constitute more than 40% of the total urban population of India [9] are way behind. Immunization coverage in urban areas of Bihar, Rajasthan and Orissa is 19%, 27% and 49% respectively as compared to 84% and 73% in Tamil Nadu and Kerala [10]. There is little evidence that highlights the the trends in child immunization coverage in EAG states, India.Thus the present study examining the trends and factor associated with the child immunization in Empowered Action Group States, India (1990-2006).

II.

Study Setting, Data, and Method

This study is based on three rounds of the National Family Health Survey (NFHS) data, which were canvassed during 1992– 93 (NFHS-1), 1998–99 (NFHS-2), and 2005–06 (NFHS-3) in India [11–13]. These surveys used a multistage stratified sampling design. The NFHS is a standard large-scale survey in India, which provides nationally representative estimates on issues related to family welfare, maternal and child healthcare, and nutrition. In NFHS-1 (1992–93), information was collected for the last three births to women in the four years preceding the date of survey. Similarly, in NFHS-2 (1998–99), information was collected for the last two births in the three years preceding the date of survey. However, in NFHS-3 (2005–06), information on place of delivery and assistance during delivery was collected for the last three births in the five years preceding the date of survey. Considering these inconsistencies across the three surveys, the sample for this study was limited to the information for the last birth in the three years preceding the date of survey. Required information/data in states of Sikkim was missing in NFHS-1. Therefore, in order to retain consistency, samples for Sikkim was excluded from the final analytic samples. The details of the sampling weights as well as extensive information on survey design, data collection, and management procedures are described in the NFHS reports of the respective rounds [11-13].

III.

Outcome Measurements

According to the guidelines developed by WHO [14], children aged 12–23 months who received one dose each of BCG and measles, and three doses each of DPT and polio vaccine, were defined as being fully immunized.

IV.

Defining Predictor Variables

Important socioeconomic and demographic predictors included in the analysis are based on their theoretical and observed importance applied in the literature. The study considered a number of potential individual factors, included in the analysis were age of women at the time of birth (Younger age 15-24, Middle 25-34 and Older 35-49), women’s education and husband’s education (illiterate, literate but below primary, primary but below middle school, middle but below high school, and high school and above), women’s and husband work status (Not working, Agricultural work, Skilled/Unskilled work, Professional work), birth order and interval (first birth

AIJRHASS 15-754; © 2015, AIJRHASS All Rights Reserved

Page 81

Jeetendra Yadav et al., American International Journal of Research in Humanities, Arts and Social Sciences, 12(1), September-November, 2015, pp. 80-89

order, birth order 2/3 and interval ,<= 24 and birth order 2/3 and interval >24, Birth order-4+ and interval<=24 and Birth order-4+ and interval>24), status of the child ( wanted and unwanted), Mass media exposure (No exposure, Any exposure). Household characteristics included in the analysis were the religion of the mother (Hindu, Muslim, and others), social group (Scheduled Castes), Scheduled Tribes and Other than SC/ST) wealth quintile (poorest, poorer, middle, richer and richest), while the community characteristics included in analysis were place of residence (urban and rural), City-wise residence (Capital, large city, Small city, Town, Countryside). Since a strong state-level difference in the coverage of maternal and child health services, along with variations in health infrastructure and socioeconomic status across states, have been documented in previous studies [14-15]. For this purpose states were also included in the predictors variables (Bihar, Madhya Pradesh, Oddisa, Rajsthan, Uttar Pradesh).

V.

Analytical approach

To identify the trends in child immunization in EAG states, bi-variate and multivariate analyses were performed.

In order to trace the trend in child immunization, we assessed whether the association between the predictor of interest and the outcome variable varied during the last one and half decade. This required the data from all three rounds to be pooled and tested for the trend using linear or nonlinear trend analysis. As the sampling design of the NFHS offers an opportunity to make all the three rounds of data comparable [17], several earlier studies have pooled the different rounds of DHS/NFHS datasets to observe changes over time [18-20]. To take into account the survey design (i.e. sampling weights with clustering and strata) while estimating bivariate and multivariate statistics, the SVY command [21] in STATA [22] was used. Since all the outcome indicators used in this study were measured with binary responses in all three round of surveys, we used pooled multivariate logistic regression models to assess the effect or the strength of selected key individual, household and community characteristics predictors in explaining child immunization.

The study is based on data available in public domain, therefore no ethical issue is involved.

VI.

Results

A. Differentials in Full Immunization To examining the trends in child immunization, we examined the bi-variate differential of the selected background characteristics. Table 3 shows the weighted percentage of children who have received full immunization full immunization in India increased by nearly eleven percentage points from a level of 20.4% during 1990–93 to 31.1% during 2003-06. A considerable growth in the level of full immunization was observed in the children whose mothers belonging to the Scheduled caste (SCs). The prevalence (%) of full immunization among Scheduled caste grew by 110%, compared to an increase of about 49% among Others then Scheduled Caste/ Scheduled Tribes. A considerable increase was observed in the proportion of full immunization by children whose mother and father were uneducated. The prevalence (%) of full immunization among uneducated mother grew by 45%, compared to an increase of about 6% among women who had been completed their high school and above.

Children whose fathers were uneducated grew 87%, compared to an increase of about 45% among children whose fathers had been completed their high school and above. As regards to state, analysis indicated that a considerable increase was observed in the proportion of full immunization by children who born in Bihar as compared to others states.

Table 1.Percentages and trends of children (aged 12–23 months) who had received full immunization background characteristics, in EAG, states, India, 1990–2006.

Socioeconomic characteristics

and

demographic Full Immunization NFHS-1(1990–93)

NFHS-2 (1996–99)

NFHS-3 (2003–06)

R.C (%)

%

%

%

a

95% CI

AIJRHASS 15-754; © 2015, AIJRHASS All Rights Reserved

95% CI

95% CI

Page 82

Jeetendra Yadav et al., American International Journal of Research in Humanities, Arts and Social Sciences, 12(1), September-November, 2015, pp. 80-89

Individual characteristics Mother’s age at time of birth

χ2=17.023***

χ2=3.67

χ2=27.255***

Younger (15-24)

22.1

[20.0-24.4]

26.1

[23.8-28.4]

33.1

[30.4-35.9]

49.8

Middle

19.5

[17.1-22.1]

27.7

[25.0-30.6]

30.9

[27.9-34.0]

58.5

13.1

[9.8-17.3]

22.0

[16.6-28.6]

15.5

[10.6-22.0]

18.3

Older

(25-34) (35-49)

Sex of child

χ2=21.960***

χ2=10.773***

χ2=8.584***

Male

23.0

[20.9-25.3]

28.8

[26.4-31.3]

33.3

[30.6-36.1]

44.8

Female

17.5

[15.6-19.6]

24.0

[21.7-26.5]

28.7

[26.0-31.6]

64.0

Women’s education

χ2=456.584***

χ2=344.789***

χ2=417.563***

Illiterate

14.0

[12.6-15.6]

18.4

[16.7-20.3]

20.4

[18.3-22.7]

45.7

Literate but below primary

32.9

[27.5-38.7]

29.4

[23.6-36.0]

30.5

[23.5-38.5]

-07.3

Primary but below middle

28.2

[17.6-41.9]

37.2

[30.8-44.1]

39.6

[33.0-46.6]

40.4

Middle but below high school

44.1

[38.7-49.7]

39.6

[34.1-45.5]

53.4

[48.9-57.8]

21.1

High school and above

66.1

[56.2-74.8]

60.8

[54.8-66.5]

70.3

[62.8-76.9]

06.4

Husband’s education

χ2=262.897***

χ2=221.470***

χ2=221.990***

Illiterate

10.6

[8.9-12.6]

14.8

[12.8-17.2]

19.8

[17.1-22.9]

86.8

Literate but below primary

14.8

[10.7-20.1]

22.5

[17.6-28.3]

27.2

[20.3-35.4]

83.8

Primary but below middle

20.1

[16.6-24.2]

22.5

[19.0-26.4]

30.8

[25.8-36.2]

53.2

Middle but below high school

25.2

[21.6-29.2]

29.3

[25.5-33.5]

28.1

[24.2-32.3]

11.5

High school and above

33.9

[30.7-37.3]

41.3

[37.8-44.8]

49.1

[45.3-53.0]

44.8

Women’s occupation

χ2=42.364***

χ2=49.592***

χ2=36.363***

Not working

21.8

[20.0-23.8]

28.9

[26.6-31.4]

34.3

[31.6-37.2]

57.3

Agricultural work

12.4

[9.7-15.7]

18.8

[16.2-21.8]

26.2

[22.9-29.8]

111.3

Skilled/Unskilled work

17.8

[13.3-23.4]

23.5

[16.4-32.4]

21.5

[16.4-27.7]

20.8

Professional work

35.8

[23.5-50.2]

45.1

[32.9-57.9]

42.2

[32.0-53.2]

17.9

Husband’s occupation

χ2=124.69***

χ2=76.112***

χ2=55.658***

Not working

32.2

[22.7-43.4]

33.2

[24.9-42.7]

32.0

[18.5-49.4]

-00.6

Agricultural work

16.2

[14.2-18.5]

21.7

[19.5-24.0]

25.8

[22.5-29.4]

59.3

Skilled/Unskilled work

17.2

[15.1-19.7]

24.8

[22.0-27.7]

29.6

[26.8-32.7]

72.1

Professional work

31.9

[28.5-35.6]

38.2

[34.1-42.5]

41.3

[37.1-45.7]

29.5

Birth order and interval

χ2=65.060***

χ2=43.878***

χ2=133.786***

Birth order 1

26.5

[23.4-29.8]

30.2

[27.0-33.6]

42.2

[38.2-46.3]

59.2

Birth order-2/3 and interval<=24

25.3

[21.2-29.9]

31.4

[26.5-36.7]

36.5

[31.6-41.6]

44.3

Birth order-2/3 and interval>24

20.6

[18.1-23.4]

29.3

[26.3-32.5]

33.0

[29.3-36.8]

60.2

Birth order-4+ and interval<=24

16.8

[12.2-22.7]

18.1

[13.7-23.5]

16.6

[12.5-21.8]

-01.2

Birth order-4+ and interval>24

14.5

[12.4-16.8]

20.7

[17.8-23.9]

20.6

[17.6-24.0]

42.1

Status of the child

χ2=0.089***

χ2=0.544***

χ2=148.147***

Wanted

20.5

[18.7-22.3]

26.8

[24.6-29.0]

33.0

[30.7-35.5]

61.0

Unwanted

20.0

[16.9-23.5]

25.5

[22.3-28.9]

25.3

[21.8-29.1]

26.5

Mass media exposure

χ2=215.338***

χ2=230.912***

χ2=169.923***

No exposure

14.5

[12.9-16.3]

17.6

[15.8-19.7]

19.5

[17.0-22.3]

34.5

Any exposure

33.2

[30.3-36.2]

40.1

[37.2-43.2]

39.0

[36.2-41.9]

17.5

Household characteristics Religion

χ2=25.672***

AIJRHASS 15-754; © 2015, AIJRHASS All Rights Reserved

χ2=36.362***

χ2=45.065***

Page 83

Jeetendra Yadav et al., American International Journal of Research in Humanities, Arts and Social Sciences, 12(1), September-November, 2015, pp. 80-89

Hindu

20.9

[19.2-22.7]

27.3

[25.4-29.3]

33.0

[30.6-35.4]

57.9

Muslim

15.1

[11.3-20.0]

18.1

[13.9-23.2]

19.7

[15.7-24.5]

30.5

Others

40.0

[27.7-53.7]

52.3

[38.5-65.7]

47.3

[34.1-60.9]

18.3

Social group

χ2=49.788***

χ2=36.813***

χ2=27.881***

Scheduled caste (SCs)

11.9

[9.3-15.2]

24.0

[20.9-27.4]

25.0

[21.0-29.5]

110.1

Scheduled tribe (STs)

15.6

[12.1-20.1]

15.1

[11.5-19.6]

25.0

[19.9-31.0]

60.3

Other than SC/ST

22.8

[20.8-24.8]

29.0

[26.7-31.4]

34.0

[31.4-36.7]

49.1

Wealth quintile

χ2=368.691***

χ2=328.679***

χ2=287.888***

Poorest

11.5

[9.6-13.8]

15.3

[13.1-17.8]

19.3

[16.6-22.3]

67.8

Poorer

14.4

[12.3-16.8]

22.9

[20.2-25.8]

26.8

[23.2-30.8]

86.1

Middle

25.0

[21.7-28.6]

29.6

[25.9-33.7]

33.9

[29.3-38.8]

35.6

Richer

31.6

[27.1-36.5]

39.4

[34.3-44.6]

44.7

[39.1-50.5]

41.5

Richest

51.7

[44.8-58.6]

64.2

[57.4-70.5]

62.9

[57.1-68.4]

21.7

Community characteristics Type of residence

χ2=119.135***

χ2=58.498***

χ2=78.280***

Urban

35.2

[31.0-39.7]

43.8

[38.4-49.4]

46.0

[41.0-51.1]

30.7

Rural

17.6

[15.9-19.4]

23.2

[21.5-25.1]

27.9

[25.6-30.4]

58.5

City-wise residence

χ2=126.144***

χ2=114.586***

χ2=84.024***

Capital, large city

39.0

[24.2-56.1]

55.2

[35.8-73.2]

50.8

[42.0-59.4]

30.3

Small city

38.8

[32.6-45.5]

46.6

[36.5-57.1]

49.6

[40.3-59.0]

27.8

Town

31.0

[25.6-37.0]

40.1

[34.0-46.6]

41.2

[34.1-48.7]

32.9

Countryside

17.6

[15.9-19.4]

23.2

[21.5-25.1]

27.9

[25.6-30.4]

58.5

State

χ2=140.612***

χ2=183.920***

χ2=117.376***

Bihar

10.8

[8.1-14.2]

13.4

[11.1-16.1]

32.9

[28.1-38.1]

204.6

Madhya Pradesh

28.1

[24.1-32.5]

30.4

[26.3-34.8]

41.6

[36.8-46.5]

48.0

Oddisa

36.5

[30.5-43.0]

49.3

[43.2-55.5]

52.2

[45.2-59.1]

43.0

Rajsthan

20.7

[16.9-25.1]

21.7

[17.9-26.1]

25.9

[20.6-32.1]

25.1

Uttar Pradesh

19.9

[17.4-22.7]

30.6

[27.1-34.4]

23.6

[20.7-26.8]

18.6

Total

20.4

[18.7-22.1]

26.5

[24.6-28.4]

31.2

[29.0-33.4]

52.9

Determinants of Full Immunization (pooled data) Table 3 presents the results of the logistic regression models examine the effect of individuals, household and community characteristics on receiving full immunization among children aged 12–23 months during 1990-2006. Along with the adjusted odds ratios, the table provides observed (or unadjusted) odds ratios for each correlate, which permit direct comparison of observed and adjusted effects. The study estimated the baseline effect of each variable on receiving full immunization in the unadjusted model, and then controlled for other variables in the adjusted one. The result from the both model unadjusted and adjusted shows that the time period, sex of child, mother’s education, father’s education, birth order and birth interval of child, status of child, mass media exposure, religion, social group, wealth status and states emerged as significant factors affecting the utilization of full immunization. The result from the unadjusted model shows that children born during 1996-99 were 41% and children born during 2003-06 were 77% more likely, to receive full immunization compared with children born during 1990-93. When all other potential individual, household and community variables were controlled in the adjusted model, the direction remained the same. The likelihood of full immunization were 23% and 54% more among children born during 1996-99 and 2003-06 respectively, as compared to children born during 1990-93. Mother’s education shows a significantly positive association with children

AIJRHASS 15-754; © 2015, AIJRHASS All Rights Reserved

Page 84

Jeetendra Yadav et al., American International Journal of Research in Humanities, Arts and Social Sciences, 12(1), September-November, 2015, pp. 80-89

receiving full immunization. The odds of receiving full immunization among children of mothers who were literate, but below the primary educational level (AOR=1.36, 95% CI=1.12–1.65), Primary but below middle (AOR=1.54, 95% CI=1.23–1.92), Middle but below high school (AOR=1.88, 95% CI=1.59–2.22), and with High school and above (AOR=2.57; 95% CI=1.98–3.33) were more likely to receive full immunization compared with children of uneducated mothers. The likelihood of full immunization was higher among those children whose mother had any exposure to mass media (AOR=1.27; 95% CI=1.11–1.45) compared with children whose mother had no mass media exposure. The results from this anlysis indicated that the status of children as a significant determinant for receiving full immunization. The odds of receiving full immunization were found to be less among unwanted children compared with wanted children (AOR=0.82, CI=0.71–0.91).

The likelihood of receiving full immunization was lower among children belonging to the STs social group (AOR=0.80; 95% CI= 0.71–0.94) than children belongs to SCs social group. However, the odds of receiving full immunization was were higher among children belongs to other than SCs and SCs social group than children belongs to SCs social group. Similarly, children belonging to the Muslim religion were less likely to receiving full immunization (AOR=0.62; 95% CI=0.51–0.77) than Hindu children. However, the odds of receiving full immunization was were higher among children belongs to other than Hindu and Muslim than children belongs to Hindu. The odds of receiving full immunization increased significantly with increasing household economic status. The likelihood of receiving full immunization was found to be 2.6 times (CI=1.99–3.50) higher among children from the richest wealth quintile than from those of the poorest wealth quintile. As regards to EAG States, results shows that compared with children of Bihar, children of Madhya Pradesh were 2 times (95% CI=1.66–2.44) and children of Oddisa were 3.6 times more likely to receive full immunization.

Table 2 Binary logistic regression model showing odds ratio (OR) and confidence intervals (95% CI) for receiving full immunization among children age 12-23 month in EAG, states, India, 1990–2006. (pulled data) Socio- demographic characteristics

Full Immunization Unadjusted Odds ratio

Adjusted 95% CI

Odds ratio

95% CI

Period 1990–93 (ref)

1.00

1.00

1996–99

1.41***

[1.23-1.62]

1.23***

[1.07-1.43]

2003–06

1.77***

[1.53-2.05]

1.54***

[1.32-1.80]

Individual characteristics Mother’s age at time of birth Younger (15-24) (ref)

1.00

Middle

0.93

[0.84-1.02]

1.21***

[1.05-1.39]

0.51***

[0.41-0.64]

1.05

[0.80-1.37]

Older

(25-34) (35-49)

1.00

Sex of child Male (ref)

1.00

Female

0.76***

1.00 [0.70-0.84]

0.81***

[0.73-0.90]

Women’s education Illiterate (ref)

1.00

Literate but below primary

2.19***

[1.85-2.60]

1.36***

[1.12-1.65]

Primary but below middle

2.91***

[2.39-3.56]

1.54***

[1.23-1.92]

Middle but below high school

4.35***

[3.79-4.99]

1.88***

[1.59-2.22]

AIJRHASS 15-754; © 2015, AIJRHASS All Rights Reserved

1.00

Page 85

Jeetendra Yadav et al., American International Journal of Research in Humanities, Arts and Social Sciences, 12(1), September-November, 2015, pp. 80-89

High school and above

9.05***

[7.49-10.92]

2.57***

[1.98-3.33]

Husband’s education Illiterate (ref)

1.00

1.00

Literate but below primary

1.53***

[1.22-1.92]

1.04

[0.82-1.33]

Primary but below middle

1.85***

[1.58-2.17]

1.21**

[1.02-1.44]

Middle but below high school

2.18***

[1.87-2.55]

1.22**

[1.02-1.46]

High school and above

4.04***

[3.55-4.61]

1.52***

[1.28-1.82]

Women’s occupation Not working (ref)

1.00

1.00

Agricultural work

0.69***

[0.61-0.79]

1.12

[0.97-1.30]

Skilled/Unskilled work

0.67***

[0.53-0.83]

0.84

[0.66-1.07]

Professional work

1.84***

[1.37-2.48]

1.14

[0.80-1.63]

Husband’s occupation Not working (ref)

1.00

1.00

Agricultural work

0.54***

[0.40-0.73]

0.76

[0.53-1.09]

Skilled/Unskilled work

0.67***

[0.49-0.90]

0.91

[0.63-1.31]

Professional work

1.22

[0.90-1.66]

0.83

[0.58-1.20]

Birth order and interval Birth order 1 (ref)

1.00

1.00

Birth order-2/3 and interval<=24

0.89*

[0.78-1.02]

0.98

[0.82-1.17]

Birth order-2/3 and interval>24

0.78***

[0.70-0.87]

0.87**

[0.75-1.01]

Birth order-4+ and interval<=24

0.39***

[0.32-0.46]

0.64***

[0.49-0.83]

Birth order-4+ and interval>24

0.42***

[0.38-0.48]

0.74***

[0.60-0.91]

Status of the child Wanted (ref)

1.00

Unwanted

0.85***

1.00 [0.76-0.96]

0.82***

[0.71-0.94]

Mass media exposure No exposure (ref)

1.00

Any exposure

3.03***

1.00 [2.73-3.36]

1.27***

[1.11-1.45]

Household characteristics Religion Hindu (ref)

1.00

1.00

Muslim

0.59***

[0.49-0.71]

0.62***

[0.51-0.77]

Others

2.35***

[1.68-3.28]

1.99***

[1.32-2.99]

Social group Scheduled caste (SCs) (ref)

1.00

1.00

Scheduled tribe (STs)

0.87

[0.70-1.08]

0.80***

[0.63-1.01]

Other than SC/ST

1.49***

[1.29-1.72]

1.17***

[1.00-1.37]

Wealth quintile Poorest (ref)

1.00

Poorer

1.44***

[1.25-1.66]

1.24***

[1.06-1.44]

Middle

2.26***

[1.94-2.63]

1.61***

[1.34-1.93]

Richer

3.42***

[2.88-4.07]

1.79***

[1.43-2.25]

Richest

8.01***

[6.61-9.70]

2.64***

[1.99-3.50]

AIJRHASS 15-754; © 2015, AIJRHASS All Rights Reserved

1.00

Page 86

Jeetendra Yadav et al., American International Journal of Research in Humanities, Arts and Social Sciences, 12(1), September-November, 2015, pp. 80-89

Community characteristics Type of residence Urban (ref)

1.00

Rural

0.41***

1.00 [0.36-0.47]

0.91

[0.77-1.07]

State Bihar (ref)

1.00

1.00

Madhya Pradesh

2.00***

[1.66-2.42]

2.03***

[1.66-2.47]

Oddisa

3.38***

[2.74-4.17]

3.57***

[2.83-4.49]

Rajsthan

1.20*

[0.96-1.50]

1.02

[0.80-1.29]

Uttar Pradesh

1.25***

[1.05-1.50]

1.13

[0.94-1.37]

Levels of significance: *p<0.10; **p<0.05; ***p<0.01; OR= Odds ratio City wise residence was excluded from the multivariate analysis after examining high collinearity between type of residence and city wise residence.

VII. Discussion The present study examines the utilization of maternal and child health care services among women who had their last childbirth during their adolescence in the five years. The results from both bivariate and multivariate analyses confirmed the importance of mother’s education for the utilization of child health care services which indicated in several other studies in developing countries [23-28] . Wealth quintile of the household was found to be another significant factor affecting the full immunization in EAG states in India. Children belonging to the richest households were two times more likely to receive full immunization than the children from the poorest quintile. Previous studies also indicated that the poor–rich gap in the utilization of maternal and child health care services [29-30]. Most of the studies indicated that women are significantly more likely to use maternal health care services for their first child [31-34]. The findings of this study also highlighted that the child immunization were less for the second and higher births order children compared with the first birth order children which evident from several others studies that higher birth order suggests a greater family size and hence lower resources (both time and money) available to seek formal health care [35-37]. The variations in the receiving of full immunization by children in different states of the EAG states may be partly linked with the diversity and availability of resources and the state of socioeconomic and demographic progress.

VIII. Conclusion This study concludes that the full immunization receiving by children in EAG states over the last one and a half decades, increases but it is far from satisfactory. Moreover, the adverse effect of the low coverage of child immunization could lead to high child morbidity and mortality. It is well documented in previous study and this study also that education is most important factor influencing of child immunization. The information, education and communication should be improve specially for poor and uneducated women and awareness about the adverse effects of child immunization. Since EAG states are demographically lagging behind, eradication about child immunization in the next few years will provide opportunities to introduce newer vaccines in the programme specially for poor community. Higher birth order children have lower child immunization the precise reasons for this have not been elucidated.

Funding: No funding was received to conduct this study.

Competing interests:The authors declare that they have no competing interests.

Author’s contribution: JY, SG and JKS contributed in the concept of the analysis of NFHS dataset. JY and JKS performed all statistical analysis. JY wrote manuscript with significant contribution from SG and JKS. All authors have read and approved the final manuscript.

AIJRHASS 15-754; © 2015, AIJRHASS All Rights Reserved

Page 87

Jeetendra Yadav et al., American International Journal of Research in Humanities, Arts and Social Sciences, 12(1), September-November, 2015, pp. 80-89

References [01]

Kane M and Lasher H. 2002, ‘The Case for Childhood Immunization’, Children’s Vaccine Program at path. Occasional Paper # 5, March 2002.

[02]

World Health Organization (2012) Millennium development goals: Immunization’s contribution to reaching the Millennium Development Goal on child survival. World Health Organization, Geneva.

[03]

World Health Organization, United Nations Children’s Fund (2005) Global immunization vision and strategy

2006–2015.

Geneva, Switzerland: World Health Organization; 2005.

[04]

Centre for Disease Control and Prevention (2011) Global Routine Vaccination Coverage, 2010. Morbidity and Mortality Weekly Report 60: 1520–1522.

[05]

International Institute for Population Sciences (2010) District Level Household and Facility Survey (DLHS-3), 2007–08: India.

Mumbai: IIPS.

[06]

Pande RP, Yazbeck AS (2003) What’s in a country average? Wealth, gender, and regional inequalities in immunization in India.

Social Science and Medicine 57: 2075–88.

[07]

Madhavi Y (2005) Vaccine Policy in India. PLoS Med 2: e127.

[08]

Singh RK., Lifestyle behavior affecting the prevalence of anaemia among women in EAG states, India, Journal of Public Health, 21, 279–288 (2012)

[09]

Banthia J. Final Population Totals, Urban Agglomerations and Towns. New Delhi: Census of India, 2001.

[10]

EHP-USAID, 2003. Standard of Living Index based reanalysis of National Family Health Survey (NFHS-2), India and State reports 1998-1999, International Institute for Population Sciences (IIPS) and ORC-Macro (2001), Mumbai.

[11]

International Institute for Population Sciences (1995) National Family Health Survey India, 1992–93 NFHS-1. Mumbai: IIPS.

[12]

International Institute for Population Sciences, ORC Macro (2000) National Family Health Survey India, 1998–99 NFHS-2.

Mumbai: IIPS.

[13]

International Institute for Population Sciences, ORC Macro (2007) National Family Health Survey India, 2005–06 NFHS-3.

Mumbai: IIPS.

[14]

WHO (1998) Postpartum Care of the Mother and Newborn: A Practical Guide.Maternal and Newborn Health/Safe Motherhood Unit, Division of Reproductive Health (Technical Support), Geneva, Switzerland.

[15]

Kumar, C., Singh, P. K. & Rai, R. K. (2012) Under-five mortality in high focus states in India: a district level

geospatial

analysis. PLoS ONE 7(5), e37515.

[16]

Kumar, C., Singh, P. K. & Rai, R. K. (2013) Coverage gap in maternal and child health services in India: assessing trends and regional deprivation during 1992–2006. Journal of Public Health doi: 10.1093/pubmed/fds108.

[17]

Mishra V, Roy TK, Retherford RD (2004) Sex differentials in childhood feeding, health care, and nutritional

status in India.

Population and Development Review 30: 269–295.

[18]

Subramanyam MA, Kawachi I, Berkman LF, Subramanian SV (2010) Socioeconomic Inequalities in Childhood Undernutrition in India: Analyzing Trends between 1992 and 2005. PLoS ONE 5: e11392.

[9]

Corsi D, Finlay JE, Subramanian SV (2012) Weight of communities: A multilevel analysis of body mass index in 32,814 neighborhoods in 57 low- to middle-income countries (LMICs). Social Science and Medicine 75:

[20]

311–322.

Kumar C, Singh PK, Rai RK, Singh L (2013) Early neonatal mortality in India: 1990–2006. Journal of Community Health 38: 120–130.

[21]

Korn EL, Graubard BI (1990) Simultaneous testing of regression coefficients with complex survey data: Use of Bonferroni statistics. American Statistician 44: 270–276.

[22]

Statacorp (2007) Stata statistical software: Release 10. College Station: Statacorp LP.

[23]

Jafarey, S., Kamal, I., Qureshi, A. F. & Fikree, F. (2008) Safe motherhood in Pakistan. International Journal of Gynecology and Obstetrics 102(2), 179–185.

[24]

Ahmed, S., Creanga, A. A., Gillespie, D. G. & Tsui, A. O. (2010) Economic status, education and empowerment: implications

AIJRHASS 15-754; © 2015, AIJRHASS All Rights Reserved

Page 88

Jeetendra Yadav et al., American International Journal of Research in Humanities, Arts and Social Sciences, 12(1), September-November, 2015, pp. 80-89

for maternal health service utilization in developing countries. PLoS ONE 5(6), e11190.

[25]

Amin, R., Shah, N. M. & Becker, S. (2010) Socioeconomic factors differentiating maternal and child health-seeking behavior in rural Bangladesh: a cross-sectional analysis. International Journal for Equity in Health 9(1), 9.

[26]

Bhutta, Z. A., Chopra, M., Axelson, H., Berman, P., Boerma, T., Bryce, J. et al. (2010) Countdown to 2015 decade report (2000–10): taking stock of maternal, newborn, and child survival. Lancet 375(9730), 2032–2044.

[27]

Hussein, J., Newlands, D., D’Ambruoso, L., Thaver, I., Talukder, R. & Besana, G. (2010) Identifying practices and ideas to improve

the implementation of maternal Utilization of maternal and child health care in India 23 mortality

programmes: findings [28]

Ronsmans, C., Chowdhury, M. E., Koblinsky, M. & Ahmed, A. (2010) Care seeking at time of childbirth, and maternal and perinatal

[29]

reduction

from five south Asian countries. BJOG 117(3), 304–313.

mortality in Matlab, Bangladesh. Bulletin of the World Health Organization 88(4), 289–296.

Mohanty, S. K. & Pathak, P. K. (2009) Rich–poor gap in utilization of reproductive and child health services in India, 1992–2005. Journal of Biosocial Science 41(3), 381–398.

[30]

Pathak, P. K. & Mohanty, S. K. (2010) Does the safe-motherhood programme reach the poor in Uttar Pradesh, India? Asian Population Studies 6(2), 173–191.

[31]

Adekunle, C., Filippi, V., Graham, W., On yemunwa, P. & Udjo, E. (1990) Patterns of maternity care among women in On do States,

Nigeria. In Hill, A. G. (eds) Determinants of Health and Mortality in Africa. Issue 10. Demographic and Health

Survey Further [32]

Analysis Series. Population Council, New York, pp. 1–45.

Stewart, K. & Sommerfelt, A. E. (1991) Utilization of maternity care services: a comparative study using DHS data. In Demographic and Health Surveys World Conference, Washington, DC, 5–7th August 1991. Proceedings: Institute for Resource Development/Macro International, Demographic and Health Surveys (DHS), Columbia, MD, Vol. 3, pp. 1645–1667.

[33]

Akin, A. & Munevver, B. (1996) Contraception, Abortion and Maternal Health Services in Turkey: Results of Further Analysis of

the 1993 Turkish Demographic and Health Survey. Ministry of Health [Turkey] and Macro International Inc, Calverton,

MD. [34]

Celik, Y. & Hotchkiss, D. R. (2000) The socioeconomic determinants of maternal health care utilization in Turkey. Social Science &

[35]

Medicine 50(12), 1797–1806.

Wong, E. L., Popkin, B. M., Guilkey, D. K. & Akin, J. S. (1987) Accessibility, quality of care and prenatal use in the Philippines. Social Science & Medicine 24(11), 927–944.

[36]

Elo, I. T. (1992) Utilization of maternal health care services in Peru: the role of women’s education. Health Transition Review 2(1), 49–69.

[37]

Bhatia, J. C. & Cleland, J. (1995) Determinants of maternal care in a region of South India. Health Transition Review 5(2), 127–142.

AIJRHASS 15-754; © 2015, AIJRHASS All Rights Reserved

Page 89