Back

Determinants of malnutrition among Bangladeshi married women: A cross-sectional analysis of Bangladesh Demographic and Health Survey 2022

Shafrin, S. F.; Taki, M. A. T.

2025-08-27 nutrition
10.1101/2025.08.24.25334328 medRxiv
Show abstract

BackgroundMalnutrition, encompassing both overnutrition and undernutrition, remains a global concern. In 2022, an estimated 2.5 billion adults worldwide were overweight and 390 million were underweight. In Bangladesh, women face a growing dual burden of malnutrition, with persistent undernutrition alongside rising overweight and obesity. MethodsWe conducted a cross-sectional analysis of data from 7,893 ever-married, non-pregnant women aged 15-49 years from the 2022 Bangladesh Demographic and Health Survey (BDHS). BMI was categorized as underweight (<18.5), normal (18.5-22.9), and overweight or obese ([&ge;]23) using WHO Asian guidelines. Survey-weighted multinomial logistic regression identified socio-demographic, reproductive, behavioral, and mental health factors associated with underweight and overweight or obesity, with normal weight as the reference. ResultsThe weighted prevalence of normal weight, underweight and overweight or obesity was 33.7%, 9.5%, and 56.9%, respectively. Underweight was more common among adolescents, women from poorer and larger households, those experiencing depression, and those currently breastfeeding. Overweight or obesity was associated with older age, higher education, smaller and wealthier households, and sedentary behaviors such as frequent TV viewing and internet use. Later age at first birth and breastfeeding were protective against overweight or obesity. Depressed women were more likely to be underweight and less likely to be overweight or obese, while women with greater autonomy had higher odds of being overweight or obese. ConclusionBangladeshi women face a pronounced dual burden of malnutrition, with overweight and obesity far exceeding underweight. Socio-demographic, behavioral, reproductive, and mental health factors play distinct roles, underscoring the need for multifaceted public health responses.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.