August 2008 - Volume 2, Issue 4

Factors Affecting Children Ever Born in Slum Areas of Rajshahi City Corporation, Bangladesh

Md. Mosfequr Rahman1, Md. Tanvir Ahmad2, Md. Aminul Hoque3 1. Department of Population Science and Human Resource Development, University of Rajshahi, Rajshahi-6205, Bangladesh. Email: mosfeque@gmail.com 2. Department of Population Science and Human Resource Development, University of Rajshahi, Rajshahi-6205, Bangladesh. 3. Department of Statistics, University of Rajshahi, Rajshahi-6205, Bangladesh. Email: mdaminulh@gmail.com Correspondence to: Md. Mosfequr Rahman Lecturer, Department of Population Science and Human Resource Development, University of Rajshahi, Rajshahi-6205, Bangladesh. Mobile: +880-1712-196574 Fax: +88-721-750064 (off.) Email: mosfeque@gmail.com

ABSTRACT Children ever born is a major counteracting force to population attrition from mortality and therefore, has significant impact as an expansionary force in population dynamics. It is well known that increasing birth rates cause exposure to several social problems like crisis of minimum needs for survival and subsistence which includes scarcity of food and land, poverty, unemployment, illiteracy etc. Information on fertility is relevant to demographic assessment of the population. Keeping this in mind, the present study was conducted among slum areas of Rajshahi City Corporation (RCC). The data for the present study was collected by interviewing ever-married slum women aged 15-49 years from a sample of 250 households. It is found from the study that the mean age at marriage is 15.69 years. Slum women tend to marry early and there is still a fair amount of fertility at very younger ages. Their mean reproductive life span was found to be 33.47 years. Again, ever married slum women in the child bearing years have borne an average of 2.49 children. Education of both spouses, average monthly income and expenditure, ideal number of children, age at marriage, reproductive life span are found to have significant impact on children ever born to slum women in RCC. Key Words: Children ever born, Mean age at marriage, Reproductive life span.

INTRODUCTION

Human fertility is responsible for the biological replacement and maintenance of the human species. In fact, the fertility is a major counteracting force to population attrition from mortality and therefore, has a significant impact as an expansionary force in population dynamics. Fertility may be defined as the actual reproductive performance of a woman or group of women (Thompson and Lewis, 1965). However, the phase of actual reproductive performance is contented in terms of the physiological potential of a woman to conceive and bear children. This phase is termed as the fecund period, which has two extremes, viz., menarche and menopause. In demographic studies, the reproductive span i.e., the child-bearing period of women is usually taken as between 15 to 44 or 15 to 49 years of age. Thus, a fecund woman may or may not be fertile but a fertile woman must be fecund. The main events or phenomenon associated with fertility are age at menarche and age at menopause.

The relationship between age at marriage and fertility is well known (Maudlin and Berelson, 1978; Pandey and Talwar, 1987). As age at cohabitation (i.e., age at consummation of marriage) determines the reproductive life span of a woman and has a direct bearing on fertility, it is one of the important aspects with regards to fertility (Maudlin and Berelson, 1978; Nag, 1982; Chaudhury, 1984). It is found that a later age at marriage reduces fertility (Agarwala, 1967; Durch, 1980; Yadav and Badari, 1997). Educational level, economic status, religious attitudes, women's work participation etc. are other factors, affecting fertility (Basu et al., 1988; Bhasin, V., 1990; Elamin and Bhuyan, 1999; Pandey et al., 2000; Bhasin and Nag, 2002), in addition to, conception control practice and attitudes (Bhuyan and Ahmad, 1984).

The most striking demographic event in the past few decades has been the unprecedented increase in the population, particularly in the developing countries, such as Bangladesh, primarily due to the remarkable fall in mortality. There can be little doubt that the massive investment in health, sanitation, water supply, and other associated sectors have directly contributed to decline in the mortality rates (Preston, 1978; Kshatriya et al., 1997; Verma, 2002). Again over the past four decades the developed and developing nations have been witness to important changes in reproductive behavior among their female populations. Accompanied by higher level of schooling, better health care, increased urbanization, and greater exposure to modern forms of mass communication, fertility has dropped rapidly in many regions. However, wide variations in reproductive behavior persist at national and sub-national levels and across the social groups. While research and analysis have been conducted on the causes and consequences of such differential behavior among women, they have received relatively little attention.

In the present paper an attempt has been made to assess fertility of slum women of Rajshahi city corporation, Bangladesh. It aims to estimate various fertility measures besides evaluating the reproductive profile of slum women.

MATERIALS AND METHOD

The present study was conducted among slums residing in Rajshahi city corporation, Bangladesh. Two slum predominated wards selected at random, were visited during June, 2007. The data was collected from ever-married slum women aged 15-49 years from a sample of 250 households using interview schedule. The interview schedule consisted of questions on household identification, age etc., besides questions related to reproductive profile. The data collected was statistically treated, using descriptive statistics. In some cases age could not be appropriately assessed due to misstatement of age especially by older women who tend to understate their true ages.

A look at the general characteristics of the respondents reflects that the majority (65.6%) of the respondents are illiterate, 26% have primary knowledge of education and only 8.4% have secondary education. Analysis of work status of the respondents reflects that almost three-quarters are not working and are engaged in household activities. All these reflect the present overall status of slum women in Rajshahi city corporation, Bangladesh.

Linear Logistic Regression Analysis

\When we examine each independent variable individually, it can only provide a preliminary idea of how important each variable is by itself. So the relative importance of all the variables has to be examined simultaneously by some multivariate methods. There are varieties of multivariate statistical techniques that can be used to predict a binary dependent variable from a set of independent variables. Multiple regression analysis and discriminant analysis are two related techniques but these techniques are applicable only when the dependent and independent variables are measured in interval scale under the assumption that they are normally distributed with equal variances. However, in most applications, the dependent variable may be a dichotomous one and one or more explanatory variables are qualitative or measured in nominal or ordinal scales and the assumption of normality is violated. To overcome this problem, a very interesting and appropriate technique is the linear logistic regression method developed by Cox (1970), which does not require any distributional assumption. This regression is useful when the dependent variable is dichotomous. Since it does not require any distributional assumptions, unlike many other multivariate techniques (i.e. the variables are normally distributed with equal variances), it can appropriately handle situations in which the independent variables are qualitative or measured in nominal and ordinal scale. The logistic regression model can be used not only to identify risk factors but also to predict the probability of success. This model expresses a qualitative dependent variable as a function of several independent variables, both qualitative and quantitative (Fox, 1984).

Let Yi denote the dependent variable for the ith observation and Yi = 1, if the ith individual is a success and Yi = 0, if the ith individual is a failure. Suppose that for each of the individuals k independent variables Xi1, Xi2, ………………,Xik are measured. These variables can be either qualitative such as residence, religion, education etc. or quantitative such as age, number of living children etc. in logistic regression model, it is assumed that Yi's are normally distributed with mean Pi and variance s², and Pi is defined as the probability of success, that is,

And

Where, Xi0 = 1 and ßj's are unknown coefficients.
Estimation of the parameters of ßj's from equation (1) and (2) seems to be very complicated. However, the logit transformation of Pi turns out to be a linear function of Xij, that is

which expresses the log odds of occurrence of an event (i.e. dependent variable) as a linear function of the independent variables. Thus logarithm of the value of "success" (P) to "failure" (1-P) are relating it to the independent variables, the logistic parameters can easily be interpreted in turns of odds ratios. Relative odds can be estimated for the categories of each independent categorical variable or combination of such variables.

In logistics regression the parameters of the models are estimated using maximum likelihood method. The contribution of individual variables in logistics regression depends on the other independent variables and the interpretation is difficult when they are highly correlated. A statistic that is used to look at the partial correlation between the dependent variable and each of the independent variable is the R statistic.

RESULTS AND DISCUSSION

Age at marriage

There is a popular cultural proverb existing in Bangladesh "a girl at twenty is old", so most of the parents and guardians are motivated by this proverb and they arrange marriage for girls soon after their menarche and sometimes before menstruation in rural areas even nowadays. In the present study of pattern of age at marriage indicates that more than half of the women got married before they reached the age of 15 years and more than one-third got married between age 15-19 years while the proportion marrying after 20 years of age is very low (Table 1).

A shortening of the child-bearing period in a woman's life has become an important determinant of persistent below-replacement fertility. In fact although earlier menarche lengthens the fecund lifespan, postponement of first birth until age 30 and beyond shortens the effectively used childbearing period. Figure 1 illustrates the reproductive life spans typical of developed and developing countries today and that for our study area (Figure 2).

The ages at which women start and stop childbearing are important demographic determinants of fertility. The higher median age at first birth and a lower median age at last birth are indicators of fertility.

Figure 1: Reproductive lifespan of women in developed and under-developed areas

Figure 2: Reproductive lifespan of women in the study area

From the following figure it is obviously clear that reproductive lifespan is one of the important factors that influence fertility. An average child ever born is decreasing with the decrease of reproductive lifespan. If we think of reproductive lifespan as land then we have too much land area to produce population. With a small economy and small land area of our country, it is impossible to drive such a vast population structure. In advanced and semi-advanced countries, the reproductive lifespan is half of the reproductive lifespan of the developing and underdeveloped counties. Figure 3 shows that with the increase of reproductive life span, average children ever born are also increasing significantly.

Figure 3: Average children ever born on reproductive life span

Children ever born
The number of children a woman has ever born is a cohort measure of fertility as compared to period measure of fertility like crude birth rate, age specific fertility rate, etc. as it reflects the experience of groups of women over a number of years rather than a specific calendar year (Weeks, 2002). The interaction of maternal age and parity (i.e. order of birth) is of interest as younger mothers are at risk of pregnancy wastage and babies of older mother are at risk of congenital malformations. Also, the frequency of mortality increases considerably with higher order of birth. From Table 3 we observe that 47.2 percent of the slum women have more than two children and 52.8 percent have less than or equal to two children. Again, ever married slum women in the child bearing years have borne an average of 2.49 children (Table 4).

Children ever born	Frequency	Percent
2	132	52.8
2+	118	47.2
Total	250	100.0

Note: A= Absence

The mean number of children ever born increases steadily with age, reaching a high of over three children per woman for the age group 35 and over. More than two thirds of the women in the age group of below 20 years have ever had a child reflecting the past pattern of relatively early marriage and teenage childbearing.

Factors Affecting Children Ever Born

In this section, we apply logistic regression technique to estimate the effects of selected socio-demographic and programmatic factors on children ever born which will help to identify the key factors for unwanted rapid growth in population and to take decisions and policy implications. The logistic model is fitted by considering children ever born as the dependent variable which we dichotomized by assessing 0 for less than or is equal to two children and 1 for more than two children.

From the results of logistic regression analysis, it appears that the respondent's education has a very strong and negative independent effect on children ever born with the likelihood of children ever born decreasing significantly for the women of primary, and secondary and higher education. From our data we found that, women with a primary level of education were 0.104 times less \likely to bear children as those who had no education and women of secondary education were found to be 0.014 times less likely to bear children than those who are illiterate.

Husband's education also exerts negative significant effect on children ever born. It is observed that the wives of primary educated husbands are 0.254 times as less likely to bear children as those wives of illiterate husbands and the wives of secondary educated husbands are 0.257 times less likely to bear children as those wives of illiterate husbands.

The regression co-efficient of respondent's expenditure is also positively affected on children ever born. From the results we also observe that children ever born is likely to be 8.330 times higher among those women, who have expenses above 4000Tk monthly than women who are expending less than 3000Tk, and children ever born is likely to be 2.149 times higher among those women, who are expending 3000-4000Tk monthly than women who are expending less than 3000Tk.

Independent variables	Coefficient()	S.E ().	Sig.	Exp(B)
Respondent education Illiterate (r.c) Primary Secondary	-2.265 -4.240	.536 1.219	.000 .001	1.000 .104 .014
Husband education Illiterate (r.c) Primary Secondary	-1.369 -1.360	.507 .770	.007 .008	1.000 .254 .257
Income of respondents No earnings (r.c) 500-1000 1000+	3.023 2.073	.755 .973	.000 .033	1.000 20.543 7.948
Monthly average expenditure <3000 (r.c) 3000-4000 4000+	.765 2.120	.467 .666	.003 .001	1.000 2.149 8.330
Ideal number of children 2 (r.c) 2+	.977	.567	.005	1.000 2.657
Age at marriage <15 (r.c) 15-19 20+	-1.469 -1.974	.445 1.171	.001 .007	1.000 .230 .139
Reproductive lifespan 30 (r.c) 30+	.970	.422	.022	1.000 2.637
Constant	-.110	.456	.409	.496

r.c = reference category

Children ever born is 2.657 times higher among those women, who have been identified as having more than two children as the ideal number of children than those who have identified less than or equal to two children as the ideal number of children.

From the above table it is obviously clear that age at marriage has a negative independent effect on children ever born. The women who have married at age group 15-20, are bearing children 0.237 times less than the women who have married at age group <15 and the women who have married at age group 20+, are also bearing children 0.139 times less than the women who have married at age group <15.

Reproductive lifespan is also an effective predictor for children ever born. The women, who have a long reproductive lifespan, are producing more children. The women with thirty and above reproductive lifespan are bearing children 2.637 times higher than the women with less than or equal to a thirty year reproductive lifespan.

CONCLUSION

Some findings of this study deserve consideration from the viewpoint of their policy implications. If has been found that education of the spouses has a significant negative impact on children ever born. Education may provide better employment opportunities outside the home and age at marriage can be raised by providing education to females, especially at the secondary and higher levels. Based on the findings of the study, it may be suggested that attention should be focused on the need for providing educational facilities for the women. Respondents' monthly income and average monthly expenditure of the family also have a significant influence on children ever born. It is also found from the study that female age at marriage has a significant negative impact on children ever born as well as on fertility. In support of this, reproductive life span also shows significant impact on children ever born. The higher the reproductive life span, the higher the number of children ever born to the respondents. Thus, raising the age at marriage by implementing a minimum-age marriage law is likely to lower fertility in the study area as well as on a national scale. Ideal number of children also appears to have a significant impact on children ever born.

ACKNOWLEDGEMENT

The authors are grateful to the families who from the basis of present study without whose co-operation and kind help, this work would not have been so smoothly possible.

REFERENCES

Agarwala, S.N.: Effect of a rise in female age at marriage on birth rate in India, In: Proceedings of the World Population Conference, Belgrade (1967).

Basu, S.K., Kshatriya, G.K and Jindal, A.: Fertility and mortality differentials among the tribal population groups of Bastar district Madhya Pradesh. Human Biology, 60:407-416 (1988).

Bhasin, M.K and Nag, Shampa: A demographic profile of Jammu and Kashmir: Estimates, trends and differential in fertility behaviour. Journal of Human Ecology, 13: 57-112 (2002).

Bhasin, V.: Habitat, Habitation and Health in the Himalayas. Kamla-Raj Enterprises, Delhi (1990).

Bhuyan, K.C. and Ahmed, M.U.: Fertility and family planning practices in rural Bangladesh. The Journal of Family Welfare, 30(3): 57-70 (1984).

Choudhury, R.H.: The influence of female education, labor force participation, and age at marriage on fertility behavior in Bangladesh. Social Biology, 31: 59-73 (1984).

Cox, D.R. (1970): Analysis of Binary Data. Chapman and Hall Ltd. London.

Durch, J.A.: Nuptiality Patterns in Developing Countries -Implications of Fertility. Population Reference Bureau, Washington (1980).

Elamin,M.A. and Bhuyan,K.C.: Differential fertility in north eastern Libya. The Journal of Family Welfare, 45(1): 12-22 (1999).

Fox, J. (1984): Linear Statistical Models and Related Methods. Witey and Sons, New York.

Frank, Bianchi and Campana, 1994 ("The end of fetility: age, fecundity and fecundability in women", Journal of Biosocial Sciences. Vol. 26; pp. 349-368).

Kshatriya, G.K., Singh, P. and Basu, S.K.: Anthropo-demographic features and health care practices among the Jaunsaris of Jaunsar-Bawar, Dehradun, Uttar Pradesh. Journal of Human Ecology, 8: 347-354 (1997).

Maudlin, W.P. and Berelson, B.: Conditions of fertility decline in developing countries, 1965-1975. Studies in Family Planning, 9: 89-145 (1978).

Pandey, G.D. and Talwar, P.P.: Some aspects of marriage and fertility in rural Uttar Pradesh. Demography India, 16:301-310 (1987).

Pandey, P.L., Jain, D.C., Pandey, G.D., Choubey, R. and Tiwary, R.S.: Some aspects of social factors affecting fertility behaviour of Gond Women. Man in India, 80(3 and 4):251-258 (2000).

Preston, H.Samuel: The Effects of Infant and Child Mortality on Fertility. Academic Press, New York (1978).

Thompson, W.S. and Lewis, D.T.: Population Problems. McGraw Hill Publishing Co., New Delhi (1965).

Verma, Arvind: Socio-cultural correlates of infant mortality in a primitive tribe. Journal of Human Ecology, 13: 203-207 (2002).

Weeks, John, R.: Population: An Introduction to Concepts and Issues, 8th Ed. Wadsworth Thomson learning, U.S.A (2002).

Yadav,S.S. and Badari,V.S.: Age at effective marriage and fertility: An analysis of data for North Kanara. The Journal of Family Welfare, 43(3): 61-66 (1997).