March 2009 - Volume 3, Issue 2

Covariates of Early Childbearing in Bangladeshi Mothers: An Analysis of Teenage Women

	Md. Roshidul Islam1, Md. Nurul Islam1, Samad Abedin2 and Golam Hossain1 Institutions: 1Department of Statistics, University of Rajshahi, Rajshahi-6205, Bangladesh. 2 Department of Business Administration, International Islamic University Chittagong, Dhaka Campas, Bangladesh.
	Md. Roshidul Islam PhD Fellow Department of Statistics, University of Rajshahi, Rajshahi-6205, Bangladesh. E-mail: roshidul_stat77@yahoo.com

ABSTRACT Early pregnancy is a critical issue in safe motherhood. Childbearing in Bangladesh is characterized by early start of motherhood, quick progress till the peak age of reproduction and slow progress till the end of the childbearing period. This article presents the results of logistic regression analysis of early childbearing concerns. Out of 11 variables, 8 variables influencing early childbearing are: education of women, place of residence, religion, age at first marriage, father's education, marital duration, women's work status and contraceptive use. The study will utilize data from the 2004 Bangladesh Demographic and Health Survey (BDHS) and we have employed a nationally representative, two-stage sample that was selected from the master sample maintained by the Bangladesh Bureau of Statistics (BBS) for the implementation of surveys. Key Words: Covariate. Early Childbearing. Teenage Women. Bangladesh. Logistic Regression

INTRODUCTION

Fertility in Bangladesh is high even by the standards of developing countries. Recent evidence suggests that fertility has started to decline in Bangladesh (Amin and others, 1993). The total fertility rate has declined from nearly seven births per woman in 1975 to 3.4 births per woman in 1996 (BFS, 1975; BDHS, 1993-1994). A number of demographers have argued that the mechanism of this steep fertility decline was achieved primarily due to successful family planning (Aminet al, 1990; Cleland et al., 1994: Cleland, 1993; Islam et al., 1998), that succeeded in raising the contraceptive prevalence rate (CPR) from a low level of 8 percent in 1975 to as high as 53 percent in 2004. However, from 1993-1994 the level of fertility appears to be unchanged at a level of 3.3, as indicated by the last three surveys (BDHSs) in Bangladesh in 1996-1997, 1999-2000 and 2004. About half of the population of Bangladesh is female and most live in rural areas with low status in the family, as well as in society. Fertility in Bangladesh is high even by the standards of developing countries. Early childbearing may have a risk of a poor or tragic outcome among those who have already had many births (Haaga). High parity is associated with increased risk of maternal mortality where mothers may be less able to meet the physiological demands of repeated pregnancy (Koenig and others, 1987). In many developing countries about 50 percent of pregnancy terminations occur among the high-risk mothers (Rinehart and Kols, 1984) and the wide choice of family planning methods now available allow health programmes to offer an appropriate technique to avoid each type of early pregnancy. Every early pregnant womany faces risk - high or low, during her childbearing period. In the following section an effort is made to identify the factors that have an influence on early childbearing according to teenage women. A women's teenage fertility is considered as a dependent variable. The aim should be in identifying the variables, which have a significant influence on the dependent variables. Logistic regression analysis identifies the variables, which influence early childbearing. The analysis of teenage is of interest in this context since it can provide further insights into the mechanisms underlying fertility change (Njogu and Martin, 1991). Early childbearing in the human population is a complex phenomenon. Analysis of early childbearing is even more complex since a number of biological, behavioral and cultural factors are associated with it. In the context of Bangladesh, only a few studies, not all of them nationally representative, have been carried out to examine the effects of various factors on childbearing performance (Islam et al., 1995; Islam, 1999). Therefore, the purpose of the present paper is to identify the factors influencing early childbearing in the context of teenage years of Bangladeshi women, employing the technique of logistic regression analysis.

MATERIALS AND METHOD

In this study, early childbearing had the demographic characteristics such as teenage. The study will utilize data from the 2004 Bangladesh Demographic and Health Survey (BDHS) which employed a nationally representative, two-stage sample that was selected from the master sample maintained by the Bangladesh Bureau of Statistics (BBS) for the implementation of surveys. A total of 10,811 households were selected for the sample; 10,523 were occupied of which 10,500 were successfully interviewed. The shortfall is primarily due to dwellings that were vacant or destroyed or in which the inhabitants had left for an extended period at the time the interviewing teams visited them. Of the households occupied, 99.8% were successfully interviewed. In these households, 11,601 women were identified as eligible for the individual interview (i.e. ever-married and age 10-49) and interviews were completed for 11,440 or 98.6% of them. The multivariate logistic regression analysis provides a powerful statistical technique for identifying early childbearing with respect to several socio-economic and demographic variables, simultaneously.
The explanatory variables considered in this model are discussed in the following table:

Adolescent Fertility

Adolescent fertility is a major social and health concern. Teenage mothers are more likely to suffer from severe complications during delivery, which result in higher morbidity and mortality for both themselves and their children. In addition, young mothers may not be sufficiently emotionally mature to bear the burden of childbearing and rearing. Every entry into reproduction denies them the opportunity to pursue academic goals. This is detrimental to their prospects for good careers, which often lowers their status in society.

Table 2 shows that one-third of adolescents age 15-19 have begun childbearing. Twenty-eight percent of these teenagers in Bangladesh have given birth, and another five percent are pregnant with their first child. As expected, the proportion of women age 15-19 who have begun childbearing rises rapidly with age. Early childbearing among teenagers is more prominent in rural areas, compared with urban areas, and in Rajshahi and Khulna divisions, compared with other divisions. Childbearing begins later in Sylhet, compared with the rest of the divisions, mainly because of relatively late marriage in Sylhet. Delayed childbearing is strongly related to education among women age 15-19. Only 16 percent of the teenagers who had completed secondary education had begun childbearing, compared with almost half of those with primary incomplete or no education.

Source: BDHS- 2004.

Logistic Regression Model

The logit of the multiple logistic regression models is given by the equation
g(x) = ₀+ ₁ x₁+ ₂ x₂ + …………… _p x_p ------------------- (i)
In which case
P_i = ------------------- (ii)
And 1 - P_i = Pr (Y = 0 / x_i1, x_i2, x_i3 ……...x_ip) = -------------------(iii)
Equations (ii) and (iii) look complicated, however, the logarithm of the ratio of P_i and 1 - P_i is a simple linear function of x_ij

Let _i= log_i = ' x ------------------- (iv)

Which express the log odds of occurrence on an event (i.e. independent variable) as a linear function of the independent variables. The logit is thus the logarithm of the odds of success, that is, the logarithm of the ratio of the probability of success to the probability of failure. It is also called the logit transformation of P_i and equation (iv) is linear logistic model. It has several nice properties; P_i is bounded only between 0 and 1. If (Y) < 0.5, logit P_i is negative; while if P_i > 0.5, logit P_i is positive.

RESULTS OF LOGISTIC REGRESSION ANALYSIS

IThe result of logistic regression analysis is shown in Table 3. The regression coefficients in the model are also shown in the table. The variables are education of women (x₅), religion (x₈) and age at first marriage (x₂) are 1% level of significance, the variables place of residence (x₉), marital duration (x₃) and contraceptive use (x₁₀) are 5% level of significance and the variables father's education (x₆) and women's work status (x₇) are 10% level of significance. The sixth column of the Table 1.3 shows the odds ratios. For example, the odds ratio of mother's education (x₅) is 1.116 indicates that early childbearing will be 1.116 times higher for those mothers who have no education than those mothers who have education. Also, the odds ratio of place of residence (x₉) is 1.355 which indicates that early childbearing will be 1.355 times higher for those mothers who live in rural areas than those mothers who live in urban areas. The odds ratio of religion (x₈) is 1.934 and indicates that early childbearing will be 1.934 times higher for those mothers who are Muslim than those mothers who are non-Muslim. The odds ratio of age at first marriage (x₂) is 1.235 indicates that early childbearing will be 1.235 times higher i.e. for those mothers whose age at first marriage is less than 16 years than those mothers whose age at first marriage is 16 or more years. Similarly the variables on fathers education (x₆) is 0.769 times higher, women work status (x₇) is 2.964 times higher, marital duration (x₃) is 0.241 times higher and the variable contraceptive use (x₁₀) is 0.711 times higher for their categories. Therefore, the most important significant variables that influence early childbearing mothers are place of residence, religion, age at first marriage, women's work status, mother's education, father's education, contraceptive use and marital duration. The most significant variable is education and the next significant variable is place of residence and so on.

The logistic regression equations for early childbearing becomes
Z0 = 2.077 + 0.132x₂ + 6.552x₃ + 0.110x₅ + 0.214x₆ + 0.483X7 + 0.660x₈ + 0.340x₉ -0.342 x₁₀

The present study is a modest attempt to categorize the variables into two ways and to analyze the early childbearing pattern in context of prevailing socio-economic conditions. There is no doubt about the contributions of early childbearing patterns in regulating population growth of the country. Reasonably and hopefully it is believed that in the light of findings of the study, policy makers and planners will show a congenial and judicious path for the development of Bangladesh.

Higher socio-economic status of women will contribute to change the pattern of early childbearing. Education of women and employment opportunities, particularly in rural areas will contribute to depress the level of early childbearing performance.

Education may provide better employment opportunities outside home and providing education to females, especially at the secondary and higher levels can increase age at marriage and age at first birth. Delaying the start of childbearing at young ages would save many women's lives.

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