Spatial variation of heat-related morbidity: A hierarchical Bayesian analysis in multiple districts of the Mekong Delta Region

This study examined spatial variability of heat-relatedmorbidity in multiple districts of the Mekong Delta Region (MDR), Vietnam. It was conducted in 132 district/cities of the MDR. We used a series of hierarchical Bayesian models to examine the region-wide and district-specific association between temperatures and hospitalizations during the period of 2010-2013. The potential effects of seasonality, long-termtrends, day of the week and holidays were controlled in the models. We also examined influences of socio-demographic factors on the temperature-hospitalization relationship. The results indicate that an increase of 5 degrees C in average temperature was associated with a 6.1% increase (95% CI: 5.9, 6.2) in region-wide hospital admissions. However, the district-level risks ranged from a 55.2% decrease {95% CI: (-54), (-56)} to a 24.4% increase (24.3-24.6) in admissions per 5 degrees C increase in average temperature. This reflects the heterogeneous magnitudes of temperature-hospitalization risk across districts. The results also indicate that temperature-hospitalization risk increased by 1.3% (95% CI: 1.2-1.4), for each increase of 1000 persons/km(2) in population density, 2.1% (95% CI: 2.04-2.11) for each 1% increase in percent of females, and 2.7% (95% CI: 2.6-2.8) for each 1% increase in percent of pre-school students. In contrast, the temperature-related hospitalization risk decreased up to 6.8% {(95% CI: (-6.6)-(-6.9)} for each 1% increase in rural population. Public health intervention measures for both short-termand long-termeffects of heat-related health risk should be developed with consideration of the use of city/district scale for the factors rather than the province scale. The province scale of factors does not accurately represent the variability of health risk due to exposure to high temperatures. (C) 2018 Elsevier B.V. All rights reserved.