Determinants of Unhealthy BMI Among Reproductive-Aged Women in Bangladesh: A Multinomial Logistic Regression Analysis

Background: In Bangladesh, both underweight and overweight conditions remain critical public health issues among women of reproductive age. The coexistence of factors contributing to excessive body weight and persistent undernutrition highlights the urgent need to investigate Body Mass Index (BMI) determinants. BMI, a measure of body size based on height and weight, provides insights into nutritional health. This study aims to identify influential factors affecting BMI among reproductive-aged women in Bangladesh.

Materials and Methods: Data were sourced from the 2022 Bangladesh Demographic and Health Survey (BDHS), comprising 22,638 reproductive-aged women. The analysis categorized BMI into underweight, normal weight, overweight, and obese groups. Chi-square and gamma tests were employed to assess associations between BMI and key variables. Multinomial logistic regression was used to identify significant predictors and assess the model's fit for explaining variations in BMI outcomes.

Results: The study revealed that 55.7% of women had normal weight, 32.4% were overweight, and 11.9% were underweight. Age, educational level, wealth index, media access, and place of residence were significantly associated with BMI. Women aged 29–35 and 36–42 exhibited higher BMI levels. BMI was significantly lower in Barisal compared to Sylhet [OR: 0.493; 95% CI: 0.405, 0.600; P ≤ 0.001]. Media access was associated with increased BMI [OR: 1.139; 95% CI: 1.018, 1.274; P = 0.023], while pregnant individuals were 0.587 times more likely to influence BMI compared to non-pregnant women [OR: 0.587; 95% CI: 0.511, 0.674; P ≤ 0.001]. The AIC value indicated that multinomial logistic regression was the best-fitting model.

Conclusion: The analysis underscores that socio-economic and lifestyle factors such as educational attainment, wealth index, media access, and working status significantly influence BMI among reproductive-aged women. These findings provide actionable insights for public health policymakers to design targeted interventions that address malnutrition and promote informed health choices in a rapidly evolving environment.

Keywords: BMI, Underweight, Overweight, Reproductive age, public health, Socio-economic factors.

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