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This study examines the factors influencing contraceptive method choice among ever-married women of reproductive age in Bangladesh, using a multinomial framework to distinguish among no method, traditional methods, and modern methods. This study utilized nationally representative data from the Bangladesh Demographic and Health Survey (BDHS) 2022. A total of 18,904 ever-married women aged 15–49 years (survey-weighted 18,977) were included in the analysis. Descriptive statistics and chi-square tests were used to explore distributions and associations. Multicollinearity was assessed using the generalized variance inflation factor (GVIF). A survey-weighted multinomial logistic regression model was applied to estimate adjusted relative risk ratios (RRRs) and 95% confidence intervals (CIs), accounting for the complex sampling design. A survey-weighted multinomial logistic regression model was used to compare traditional and modern method use, each relative to non-use (the reference category). Overall, 54.8% of women used modern contraceptive methods, 9.3% used traditional methods, and 35.9% reported no contraceptive use. Women aged 25–34 years were more likely to use modern methods (aRRR = 1.16, 95% CI: 1.05–1.29), whereas those aged 35–49 years were more likely to use traditional methods (aRRR = 2.20, 95% CI: 1.74–2.79). Modern method use was more common among women with primary (aRRR = 1.38, 95% CI: 1.20–1.58) and secondary education (aRRR = 1.30, 95% CI: 1.12–1.49), and among those whose husbands had higher education (aRRR = 1.17, 95% CI: 1.00–1.36). Women with one birth in the past five years were more likely to use modern methods (aRRR = 2.66, 95% CI: 2.42–2.92). Women who desired more children were significantly less likely to use both modern (aRRR = 0.35, 95% CI: 0.31–0.39) and traditional methods (aRRR = 0.45, 95% CI: 0.38–0.53). Rural residence and regional disparities were also significantly associated with contraceptive method choice. Contraceptive method choice in Bangladesh is shaped by a range of socioeconomic and demographic factors. The application of multinomial analysis provides nuanced insights into these patterns, underscoring the need for targeted interventions to promote informed decision-making and ensure equitable access to contraceptive services.
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Akib et al. (2026) studied this question.
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