Determinants of Fertility in Bangladesh: Evidence From the 2014 Demographic and Health Survey

Abstract

This study uses the cumulative fertility approach to examine a wide variety of factors affecting fertility among all ever-married women of childbearing ages in Bangladesh. Data are taken from the 2014 Bangladesh Demographic and Health Survey. The mean number of children ever born for all women is 2.45 and for women aged 40 to 49 years is 3.89. The one-way analysis of variance is performed to observe differences in the mean number of children ever born across the levels of covariates. The generalized linear model with Poisson link function is carried out to examine the effect of covariates on fertility. The incidence rate ratio is greater than one, that is, fertility is higher among women who are Muslims, illiterates, or primary school graduates; have no access to mass media; give the first birth at the age of 15 years or earlier; ever use any contraceptive; and desired three or more babies as the ideal number of children. Type of place of residence, administrative divisions, husband’s education, respondent’s working status, husband’s occupation, age at first marriage, and the spousal age difference are also significant to some extent, especially for assessing the fertility of all women.

A Decomposition Analysis of Fertility: Evidence from DKI Jakarta and East Nusa Tenggara

“…Changes in TFR of DKI Jakarta during 2000-2010 are dominated by the decrease in fertility rate. The decreased fertility rate that occurs at young age groups (15)(16)(17)(18)(19)(20)(21)(22)(23)(24), and 25-29 years old) means that more women delay childbearing, regardless the birth order. However, the proportion of married women in the young age groups increases as well.…”

“…There may be some reasons for increased marriages at young ages in DKI Jakarta. They may be women of low economic status unable to continue to higher education (Nahar & Zahangir 2019;Wang & Chi 2017). Since the percentage and number of women in these two age groups decrease, they may be women with no ability to move out from DKI Jakarta, such as for working and studying.…”

Assessing Risk Factors for Short Birth Interval Hot Spots using Geographically Weighted Regression: Findings from a Nationally Representative Survey Data

“…Literature suggests that the prevalence of adverse pregnancy outcomes, including child mortality, is relatively high in the Sylhet division and low in the Rajshahi and Khulna divisions 46,47 and are aligned with the SBI hot spots and cold spots, respectively. There seems to be a two-way relationship between adverse pregnancy outcomes and SBI; adverse outcomes occur due to a relatively high number of births in shorter intervals and vice versa.…”

Determinants of Burundi fertility differentials: Evidence from the 2016-17 Burundi Demographic and Health Survey.

“…Two approaches such as the current and cumulative approaches are used to measure fertility. The current fertility approach is based on the number of living children in a given population in a calendar year [28]. The TFR and general fertility rate (GFR) can be used to measure the current fertility [29].…”

“…On the other hand, the cumulative fertility approach considers past fertility history of CEB to each cohort of women by age. In this study we used CEB as our dependent variable because the CEB for women belonging to the cohort of 15 to 49 years (lifetime fertility) re ects both current and past fertility behavior [28]. In addition, because this study applied a Poisson regression model that deals with count outcomes such as the number of children, we found CEB to be a more suitable outcome.…”