Maternal Anemia as a Predictor of Anemia in the Child in Nepal: An Analysis of the Demographic and Health Survey

This study aims to evaluate the extent to which maternal anemia predicts anemia in the child. This secondary data analysis used the Nepal Demographic and Health Survey datasets from 2011, 2016, and 2022. The study included children aged six to 59 months of age and their mothers from households eligible for blood testing. We performed multiple logistic regression analyses to determine adjusted odds ratios (ORs) for the association between maternal anemia and anemia in the child. We used the child's age, gender, birth as a twin, birth order, and body mass index (BMI), as well as maternal age, BMI, education level, wealth index, and place of residence as variables for adjustment covariates. We used eXtreme Gradient Boosting (XGBoost) to develop the prediction model for anemia in the child. We utilized the SHapley Additive exPlanations (SHAP) method to explain the importance of predictors. Children with moderate-to-severe anemia (hemoglobin level <10.0 g/dL) accounted for 21% of the studied population. Maternal anemia demonstrated a positive association with anemia in the child (adjusted OR: 2.26; 95% confidence interval: 1.84-2.76). It demonstrated the second most substantial effect on the prediction model, succeeding the child's age, within the SHAP framework for the XGBoost model. Higher maternal hemoglobin levels (g/dL) were associated with a lower likelihood of anemia in the child, shifting the prediction toward nonanemic status. Maternal anemia is thus a significant predictor of anemia in the child. Determining the presence of anemia in the child may be important in instances where the mother is diagnosed with anemia. Comprehensive interventions targeting mothers and the entire household may be indispensable in ameliorating anemia in children from a public health perspective.