Application of Binary Logistic Regression Model for Assessing the Caesarean Risk Factors in Bangladesh: A Case Study of Khulna and Gopalganj District

Biplab Biswas, Md. Murad Hossain, Mohammad Kamal Hossain


The main focus of this study is to investigate the caesarean risk factors in a particular area of Bangladesh. The caesarean delivery rate is increasing day by day in most developing countries like Bangladesh and number of caesarean births has almost doubled in the last eight years in Bangladesh largely due to maternal, socio-economic and demographic factors. Instead of many disadvantages, caesarean deliveries are most common among women but it is not clinically justified. For improving the maternal health status, it is essential to determine the risk factors of caesarean delivery. For this study some hospitals have selected from Khulna and Gopalganj district. Our population is the total number of pregnant women admitted for delivery in the hospitals and 600 respondents were taken as sample. After collecting data, information were arranged in tables and analyzed. For the analysis, chi-square test and fisher’s exact test were performed to identify the significant association between delivery type (caesarean/non-caesarean) and maternal, socio-demographic and socio-economic factor’s respectively. A stepwise binary logistic regression analysis was carried out to identify the most impact factors on caesarean delivery. We found that 14 risk factors were statistically associated with delivery type out of 21 risk factors. From this study, it is clear to us that above influential factors may affects the mother’s health status in Bangladesh as well as Khulna and Gopalganj district.


Caesarean delivery; Fisher’s exact test; Chi-square test; Stepwise binary logistic regression.

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