Abstract
What is already known on this topic?Different socioecological factors were associated with childhood pneumonia in Bangladesh. However, previous studies did not assess spatial patterns, and socioecological factors and spatial variation have the potential to improve the accuracy and predictive ability of existing models.What is added by this report?The spatial random effects were present at the district level and were heterogeneous. Average temperature, temperature variation, and population density may influence the spatial pattern of childhood pneumonia in Bangladesh.What are the implications for public health practice?The study results will help policymakers and health managers to identify the vulnerable districts, plan further investigations, help to improve proper resource allocation, and improve health interventions.
Highlights
This study aimed to identify the association between weather, social factors and childhood pneumonia and identify the spatial variation of the disease
A Bayesian spatial Poisson regression model with a conditional autoregressive prior structure was developed to quantify the association between childhood pneumonia and socioecological factors and identify the spatial variation
The study results suggested that a 1 °C increase in monthly temperature and monthly temperature variation may increase the monthly associated log relative risk (RR) of childhood pneumonia by 1.161 [95% credible interval (CrI): 1.013−1.429] and 1.463 (95% CrI: 1.170−1.839), respectively
Summary
This study aimed to identify the association between weather, social factors and childhood pneumonia and identify the spatial variation of the disease. A Bayesian spatial Poisson regression model with a conditional autoregressive prior structure was developed to quantify the association between childhood pneumonia and socioecological factors and identify the spatial variation.
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