Determinants of Under-Five Mortality in Bangladesh

Abdul Hamid Chowdhury

Department of Business Administration, International Islamic University Chittagong, Chittagong, Bangladesh.

DOI: 10.4236/ojs.2013.33024                

Abstract

This paper examines determinants of under-five mortality in Bangladesh. The study utilizes the data extracted from the 2007 Bangladesh demographic and health survey. Chi-square test for independence and multivariate proportional hazard analysis reflects that father’s education, place of residence, region of residence, number of children under five years of age, previous death of sibling, mother’s age and breastfeeding have significant influence on under-five mortality. The proximate determinants are found to have stronger influence on under-five mortality than the socioeconomic factors considered in the study do.

Keywords

Under-Five Mortality; Proportional Hazard; Significance; Determinant

1. Introduction

Under-five mortality, the probability of dying between birth and age 5 expressed per 1000 live births and a subject of great interest to social scientists and policy makers, are widely used as an indicator of the level of socioeconomic development and quality of life in less developed countries. Data indicate that some eleven million children under the age of five die annually in the world as a whole, of whom over ten million are in the developing world [1]. Bangladesh is a developing country in southeast Asia. Childhood mortality rates obtained for the five years preceding successive DHS surveys conducted in Bangladesh since 1993-1994 confirm a declining pattern. Between the periods 1990-1994 and 2003-2007, underfive mortality declined by 51 percent from 133 deaths per 1000 live births to 65 deaths per 1000. One in fifteen children born in Bangladesh dies before reaching the fifth birthday.

Previous studies reveal that childhood mortality varies due to the variations of associated characteristics of the parents as well as children under five [2,3]. Focusing on 28 developing countries mostly in Asia and Latin America, Hobcraft et al. [4] found that mother’s and husband’s education, their work status and their residence were more or less associated with child survival. Da Vanzo et al. [5] in Malaysia found a higher risk of death to children born to mothers below 18 and above 40 years of age. Short preceding birth interval influences child mortality through three mechanisms. First, closely spaced births cause depletion of the mother [6]. Second mechanism is through sibling competition and the third is transition of infectious diseases between the closely spaced children [7]. The first one is the biological and the other two are behavioral effects of short preceding birth interval [8]. This paper attempts to identify the factors which influence the under-five mortality in Bangladesh.

2. Data and Methods

The analysis presented in this paper uses data collected in the Bangladesh Demographic and Health Survey conducted from March to August 2007. The BDHS, 2007 data comprise a total of 6150 births that occurred 5 years preceding the survey. Multiple births are excluded because they experience a higher risk of death linked with their multiplicity, which could distort the results [9]. Births happening during the month of interview are also excluded because their disclosure to neonatal is censored. Therefore, this analysis is limited to singleton births, born 1 - 59 months before the survey. To include the survival status of the older siblings of the analysis, only women are included who have at least two births.

Table 1 presents the number and percentage of births included in this work for studying differentials and determinants of childhood mortality in Bangladesh. Finally, we have considered 4003 births, which are about 65 percent of sample for analyzing child mortality.

The study develops a framework in which the socioeconomic variables affect the outcome through the four

Table 1. Distribution of births five year preceding the survey, 2007.

proximate determinants namely, demographic factors, environmental factors, nutritional factors and health seeking behavior factors. The variables included in the framework under five broad heads are as follows:

Socioeconomic Variables: Parental education; socioeconomic status; place of residence; region of residence and religion of respondents. Demographic Factors: Age of the mother at the time of birth; birth order; birth interval; sex of the child; previous sibling death and Number of children under five years of age. Environmental Contamination: Source of drinking water; Toilet facilities and Housing construction material. Nutritional Factor: Breast feeding, body mass index. Health-seeking Behavior: Prenatal care; place of birth; tetanus injection before birth and contraceptive use.

The methodologies used to evaluate factors associated with childhood mortality include a variety of generalized linear models. For example, probability or rates models have been proposed by Hobcraft et al. [4], conditional logit models by Da Vanza and Habicht [10]; and proportional hazard models by Martin et al. [11]; and Retherford et al. [12].

Proportional hazard models are most commonly used and also more preferable to other statistical models in demographic studies [13]. For example, life table has been developed to study the probability of dying at various ages according to a specific criterion, such as education, sex, residence and so on. By contrast with logistic models, life tables can be used when the dependent variable is expressed as the elapsed between an initial event, such as birth, and a final event, such as death. Another advantage of life tables is that censored observations can be included in the study. When more than one or two factors are believed to influence the waiting time under study, however, life tables cannot be used effectively. This is so because life table techniques require that a separate set of age-specific mortality rates be calculated for each category. This procedure limits the number of covariates since the sample size becomes smaller and smaller as the number of subgroups increase. In such situations, hazard models are more appropriate technique over logistic regression model and life tables.

Considering its relevance the present study has employed Cox’s proportional hazard model to assess the effects of selected variables on mortality rates. In this study, age in completed months of index children is considered as dependent variable. Age of dead children is calculated by subtracting date of birth of children from the date of death whereas; age of survived children is computed by subtracting date of birth from date of interview. Numbers of children who are surviving at the time of interview are considered as censored cases because their true duration of surviving could not be followed till death as the survey is retrospective.

3. Results and Discussion

Independent variables under different broad heads are tested by chi-square to study the association with neonatal mortality. Except religion of the respondents, sex of child and body mass index of mothers, all other variables have shown significant association with under-five mortality. To examine the effect of explanatory variables on under-five deaths, five models are fitted to the data considering all the explanatory variables found significant in bivariate analysis. The findings are presented in the Table 2. The results of Model-1 show that babies born to mothers with secondary and above education have lower risk of under-five mortality relative to mothers with no education. The hazard of under-five mortality of higher educated mothers is 46 percent lower than those of illiterate mothers. These results are in positive direction with the earlier studies, which show that no educated mothers experience more childhood mortality than educated mothers [14,15]. There are several explanations can be made where maternal education influences child mortality. More educated women adopt simple health knowledge contrary to fatalistic acceptance of health outcomes; they adopt alternatives in child care and recent treatments. Educated women are more capable of handling the possible causes, which can affect child health. Communication with doctors and nurses should be easier for educated women.

Table 2 further shows that in Model-1, children of fathers with primary and secondary and higher education have 4 percent and 42 percent lower risks of under-five deaths respectively compared to children of illiterate fathers. Father’s education with secondary and above education has a strong significant negative effect on underfive deaths. Findings thus suggest that with the increasing level of father’s education, there is a clear significant evidence of decreasing under-five mortality in Bangla-

Conflicts of Interest

The authors declare no conflicts of interest.

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