# Exploring the multilevel determinants of low birth weight in Bangladesh: Understanding implications for targeted public health interventions

## TL;DR

This study explores factors contributing to low birth weight in Bangladesh to guide public health interventions.

## Contribution

The study identifies multilevel determinants of low birth weight using recent survey data from Bangladesh.

## Key findings

- The prevalence of low birth weight in Bangladesh is 9.15%.
- Factors like maternal education, household wealth, and antenatal care significantly influence low birth weight.
- Community-level factors also play a role, with reduced variability observed in multilevel models.

## Abstract

Low birth weight (LBW), a key indicator of impaired fetal growth, is strongly associated with infant morbidity, mortality, and long-term health problems, particularly in developing countries such as Bangladesh. LBW reflects complex public health challenges shaped by interlinked factors across health, education, and socioeconomic sectors, where low maternal education, limited household income, poor nutrition, inadequate healthcare access, and insufficient antenatal care contribute to adverse birth outcomes. Understanding these multilevel determinants is essential for designing effective public health interventions. This study examined the prevalence and determinants of LBW in Bangladesh while accounting for both individual- and community-level factors using data from the 2022 Bangladesh Demographic and Health Survey. The analysis included 5,342 newborns with recorded birth weights from births occurring within the five years preceding the survey. Birth weight was classified as LBW, defined as less than 2,500 grams, or normal birth weight of at least 2,500 grams. Binary logistic regression was applied to identify associated risk factors, and adjusted odds ratios with 95% confidence intervals were reported using a significance level of p < 0.05. Multilevel logistic regression models were additionally employed to capture community-level variation and improve model fit and predictive performance. The prevalence of LBW was 9.15%, with significant associations observed for administrative division, place of residence, household wealth index, mode of delivery, number of antenatal care visits, and place of delivery. Random-effects estimates showed reduced cluster-level variability across models, with the intraclass correlation coefficient declining from 10.65% to 6.66% and the median odds ratio decreasing from 1.81 to 1.58, indicating improved explanatory power after adjustment. Overall, LBW in Bangladesh is influenced by maternal characteristics, socioeconomic conditions, healthcare utilization, and contextual factors, underscoring the need for targeted interventions that strengthen maternal healthcare services, expand antenatal care coverage, and address socioeconomic disparities to reduce LBW prevalence and related risks.