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Type Journal Article - International Journal of Research in Economics and Social Sciences
Title Prevalence of socioeconomic correlates of unplanned pregnancy in Bangladesh
Author(s)
Volume 5
Issue 6
Publication (Day/Month/Year) 2015
Page numbers 183-195
URL http://www.indianjournals.com/ijor.aspx?target=ijor:ijress&volume=5&issue=6&article=019
Abstract
Unplanned pregnancy is considered as a reproductive health indicator among women in Bangladesh. Such pregnancy creates at a greater risk of complicated pregnancy outcomes. This study determines the prevalence of unplanned pregnancy and correlated socioeconomic factors associated with such pregnancy among women in Bangladesh. The study has been used data extracted from the Bangladesh Demographic and Health Survey (BDHS) 2011. This study considers sub-sample of 7,972 women whose most recent pregnancy occurred five years preceding the date of interview or who were currently pregnant at the survey time. Bivariate and multivariate techniques have been used to analyze the data. The chi-square test is used to detect the significant correlated factors of unplanned pregnancy. For multivariate analysis, multinomial logistic regression has been employed to identify the important socio-demographic predictors on unplanned pregnancy. The result shows that approximately one-third of the recent pregnancies were unplanned in Bangladesh. In bivariate analysis, it is exhibited that women’s age, education, age at marriage, religion, social status, mass media exposure and use of family planning are significantly associated with pregnancy intention status among ever married women. However, the multinomial logistic regression presents that the risk factors such as women’s age, education, religion, parity, place of residence, social status, region and use of family planning methods independently increase the likelihood of an unplanned pregnancy. Policymakers and program planners need to design programs and services carefully to reduce unplanned pregnancy in Bangladesh, especially, service should focus on helping those groups of women who have been identified in the analysis as being at increased risk of unplanned pregnancy such as older women, illiterate, high parity, early age at marriage and rural poor susceptible women.

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