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Estimating seasonality effects on child mortality in Matlab, Bangladesh
1World Health Organization, Geneva, Switzerland. muhurip@who.ch
Insights
Childhood mortality in Matlab peaks in April and November, especially during hungry months for children of uneducated mothers. Interventions offered greater protection during these vulnerable periods.
Area of Science:
- Public Health
- Demography
- Environmental Epidemiology
Background:
- Seasonality significantly influences child mortality rates globally.
- Understanding seasonal patterns is crucial for targeted public health interventions in Matlab.
- Socioeconomic factors, like maternal education, can modify seasonal risks.
Purpose of the Study:
- To estimate the net effect of seasonality on child mortality in Matlab.
- To identify specific months with elevated or reduced child mortality risk.
- To investigate the role of maternal education and health interventions in mitigating seasonal mortality, particularly from diarrheal diseases.
Main Methods:
- Analysis of historical child mortality data from Matlab.
- Statistical estimation of monthly variations in mortality rates.
- Stratification of risk by month, season, maternal education, and intervention status.
Main Results:
- Childhood mortality peaked in April (hot, dry) and November (aman crop harvest).
- Mortality was lowest in February, March (postharvest), and August.
- Increased mortality risk from diarrheal diseases during hungry months (September-October) was linked to lack of maternal schooling; this risk was reduced for children of educated mothers.
- Matlab interventions showed enhanced protective effects against diarrheal disease mortality during hungry months.
Conclusions:
- Seasonality demonstrably impacts child mortality in Matlab, with specific high-risk and low-risk periods.
- Maternal education and existing health interventions play a critical role in reducing seasonal mortality, especially during food-insecure periods.
- Targeted strategies during vulnerable months, considering socioeconomic factors, are essential for improving child survival.
Abstract:
This paper estimates the net effect of seasonality on child morality in Matlab. Results suggest that childhood mortality was well above average monthly level in the hot, dry month of April and in November, the first harvest month of the aman crop. It was found to be remarkably low in the postharvest months of February and March, and also in August. During the hungry months of September and October, children were at a considerably increased risk of mortality, particularly from diarrheal diseases, if mothers had no schooling, but this was not the case if mothers had schooling. The protective effect of the Matlab interventions on childhood death from diarrheal diseases was also greater during the hungry months than during other months of the year.