Determinants of maternal morbidity during pregnancy in urban Bangladesh: Negative binomial regression approach

Aim To investigate the prevalence of maternal morbidity during pregnancy and its determinants among the women from urban areas of Bangladesh. Methods The secondary data were used and extracted from the latest Bangladesh Urban Health Survey (BUHS) 2013. Several statistical models: Poisson, negative binomial (NB) and mixed Poisson were adapted and compared to explore the best model for investigating potential determinants of maternal morbidity. Pearson chi-square statistic was used for the detection of overdispersion in the data. Results Overall 13.5% of the urban women in Bangladesh suffered from at least two pregnancy complications. The study detected the overdispersion existing in the maternal morbidity count data and found the NB regression as the best choice for analyzing the data because of its smallest Akaike information criterion. Administrative division (Rangpur: p =0.003, IRR=1.34, 95% CI: 1.11 to 1.63; Sylhet: p =0.006, IRR=1.42, 95% CI: 1.11 to 1.82), wanted pregnancy (p<0.001, IRR=0.80, 95% CI: 0.71 to 0.90), place of delivery ( p <0.001, IRR=0.60, 95% CI: 0.54 to 0.66) and wealth index (Rich: p <0.001, IRR=0.74, 95% CI: 0.66 to 0.84) were found to be statistically significant determinants for maternal morbidity during pregnancy among the urban women in Bangladesh. Conclusions The urban women in Bangladesh with unwanted pregnancy, from poor/middle income group; and living in Rangpur and Sylhet divisional cities have higher risk of maternal morbidity during pregnancy. The women already suffering from major pregnancy related complications visit health centre to give birth. Study findings may help the government and relevant authorities to take necessary steps for reducing maternal morbidity and mortality due to pregnancy related complications. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was partially funded by the University of Dhaka and University of Grants Commission, Bangladesh. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Not Applicable The details of the IRB/oversight body that provided approval or exemption for the research described are given below: None I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Not Applicable I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Not Applicable I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Not Applicable The Bangladesh Urban Health Survey (BUHS) 2013