The impact of maternal employment on child nutritional diversity in Bangladesh: A causal forest analysis with clustered data (Journal of Statistical Research, 2025)
Understanding the impact of women’s employment on children’s nutrition is crucial for informing effective public health policies. This study examines the relationship between mothers’ employment status and the dietary diversity of their children, aged 6 months to 5 years, in Bangladesh. The Nutritional Variety Score (NVS) is used as a measure of dietary diversity, capturing the consumption of various food groups, including eggs, meat, bread, potatoes, vegetables, fruits, fish, beans, and dairy products. To explore this relationship, advanced statistical methods were employed, including causal forest models with cluster identifiers and mixed-effects multilevel logistic regression for propensity scores. The analysis utilized data from the 2022 Bangladesh Demographic and Health Survey (BDHS), a comprehensive dataset encompassing information on women’s employment, household characteristics, and children’s dietary intake. The models controlled for several confounding variables, including the number of children, partner’s education and employment status, type of residence, wealth index, and mother’s education level. The results reveal that children of employed mothers have a higher NVS than those of non-employed mothers, with an estimated average treatment effect (ATE) of 0.532 (95% CI: 0.365-0.699). This finding suggests that working mothers may have better access to resources or opportunities to provide a more diverse diet for their children. The statistically significant ATE confirms a positive causal relationship between women’s employment and children’s nutritional variety. This study contributes to the literature by offering robust evidence on how maternal employment affects child nutrition in Bangladesh.Journal of Statistical Research 2024, Vol. 58, No. 2, pp. 317-333