Caesarean delivery and its correlates in Northern Region of Bangladesh: application of logistic regression and cox proportional hazard model

Background: Caesarean delivery (C-section) rates have been increasing dramatically in the past decades around the world. This increase has been attributed to multiple factors such as maternal, socio-demographic and institutional factors and is a burning issue of global aspect like in many developed and developing countries. Therefore, this study examines the relationship between mode of delivery and time to event with provider characteristics (i.e., covariates) respectively.
Methods: The study is based on a total of 1142 delivery cases from four private and four public hospitals maternity wards. Logistic regression and Cox proportional hazard models were the statistical tools of the present study.
Results: The logistic regression of multivariate analysis indicated that the risk of having a previous C-section, prolonged labour, higher educational level, mother age 25 years and above, lower order of birth, length of baby more than 45 cm and irregular intake of balanced diet were significantly predict for C-section. With regard to survival time, using the Cox model, fetal distress, previous C-section, mother’s age, age at marriage and order of birth were also the most independent risk factors for C-section. By the forward stepwise selection, the study reveals that the most common factors were previous C-section, mother’s age and order of birth in both analysis. As shown in the above results, the study suggests that these factors may influence the health-seeking behaviour of women.
Conclusions: Findings suggest that program and policies need to address the increase rate of caesarean delivery in Northern region of Bangladesh. Also, for determinant of risk factors, the result of Akaike Information Criterion (AIC) indicated that logistic model is an efficient model.

Keywords
Caesarean delivery; Risk factors; Logistic regression; Cox model; AIC; Bangladesh