Peer-reviewed article
Higher Pre- and Post-Monsoon Temperatures and Their Impact on Child Undernutrition in Bangladesh.
Hossain SS, Aranya SG, Gulshan J, Rashid MB ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This study examines how unusual seasonal temperatures in Bangladesh affect child malnutrition between 2007 and 2018. Using temperature data and survey information from 2012 and 2019, researchers found that higher-than-normal temperatures during pre- and post-monsoon seasons increase stunting in children, while cooler-than-normal monsoon temperatures increase both stunting and wasting. The findings suggest that climate variations affect child nutrition and indicate a need for climate-aware nutrition policies and early warning systems.
Key points
- Higher-than-usual pre- and post-monsoon temperatures significantly increase child stunting
- Lower-than-usual monsoon temperatures increase both stunting and wasting in children
- Deviations from historical climate norms negatively affect child nutritional outcomes
- District-level climate data from 2007-2018 were linked with child health surveys from 2012 and 2019
- Study recommends strengthening climate-sensitive nutrition policies and early warning systems
Limitations
The study cannot establish direct causal mechanisms explaining how temperature anomalies affect child nutrition, nor can it account for all confounding factors that influence malnutrition beyond climate variables. The cross-sectional nature of the child survey data limits inference about temporal sequences and individual-level changes over time.
Abstract
Child malnutrition remains a critical public health concern in Bangladesh, with emerging evidence linking climatic variability to nutritional outcomes. This study examines the impact of unusual seasonal temperature deviations, particularly in the pre- and post-monsoon periods, on child malnutrition. District-level time series climatic data from 2007 to 2018 were analyzed alongside the pooled cross-sectional children's data, the Multiple Indicator Cluster Survey (MICS) of 2012 and 2019, to assess these effects. Factor analysis and multilevel logistic regression model were used for analyzing the data where factor analysis identified the pre- and post-monsoon seasons as a dominant weather factor, and multilevel logistic regression evaluated its association with malnutrition after adjustment for other individual-level, household-level, and maternal characteristics. Results indicate that higher-than-usual temperatures in pre- and post-monsoon seasons significantly increase stunting, while lower-than-usual monsoon temperatures do the same to both stunting and wasting. These findings suggest that deviations from historical climatic norms may negatively affect child nutrition. Strengthening climate-sensitive nutrition policies and early warning systems is essential in mitigating the impact of unseasonal temperature anomalies on child health in Bangladesh.