Abstract Background Despite substantial improvements in institutional delivery rates, significant socioeconomic and regional disparities persist in Bangladesh. Addressing these inequalities remains crucial to ensuring equitable maternal healthcare and achieving the Sustainable Development Goals (SDGs). Methods This study used nationally representative data from the 2022 Bangladesh Demographic and Health Survey (BDHS), comprising 4,433 women aged 15–49 years. Multilevel binary logistic regression models were estimated within a Bayesian framework via the brms package in R. We specified five hierarchical models—null, individual, household, community, and full—to identify factors associated with institutional delivery. Adjusted odds ratios (AORs) with 95% credible intervals (CrIs) are reported. Model adequacy was evaluated via the widely applicable information criterion (WAIC) and leave-one-out information criterion (LOOIC). Weakly informative priors were applied, and sensitivity analyses using alternative prior specifications were conducted to evaluate the robustness of posterior estimates. Results The full model showed a proportional change in variance (PCV) of approximately 59.9%, indicating a substantial reduction in between-cluster variance after adjustment for socioeconomic and demographic characteristics. The overall prevalence of institutional delivery was 63.5%. Antenatal care (ANC) visits and household wealth were the strongest predictors. Women who attended 4 + ANC visits (AOR = 7.83; 95% CrI: 5.51–11.26) and those in the richest wealth quintile (AOR = 2.76; 95% CrI: 1.94–3.89) had higher odds of delivering in a health facility. Higher maternal education (AOR = 2.87) and lower birth order (AOR = 0.57) were significant predictors. Conversely, women in paid employment had 17% lower odds of institutional delivery (AOR = 0.83). Pronounced divisional (e.g., Khulna vs. Sylhet) and significant religious disparities were also observed. Conclusions Institutional delivery in Bangladesh is associated with a complex interplay of individual-, household-, and community-level factors, with antenatal care (ANC) visits and household wealth demonstrating the strongest associations. Persistent socioeconomic and geographic disparities, particularly in Barishal, Sylhet, and Mymensingh, highlight the need for targeted, multilevel interventions. MOR = 2.09 and PCV = 59.9% indicate the need for policies targeting cluster-level inequalities, household wealth, and education through combined efforts in poverty reduction and health promotion.
Hasan et al. (Thu,) studied this question.