Objectives: In order to evaluate which temperature index is the best predictor for the health impact assessment of heat stress in Korea, several indexes were compared.
Methods: We adopted temperature, perceived temperature (PT), and apparent temperature (AT), as a heat stress index, and changes in the risk of death for Seoul and Daegu were estimated with 1℃ increases in those temperature indexes using generalized additive model (GAM) adjusted for the non-temperature related factors: time trends, seasonality, and air pollution. The estimated excess mortality and Akaike's Information Criterion (AIC) due to the increased temperature indexes for the 75th percentile in the summers from 2001 to 2008 were compared and analyzed to define the best predictor.
Results: For Seoul, all-cause mortality presented the highest percent increase (2.99% [95% CI, 2.43 to 3.54%]) in maximum temperature while AIC showed the lowest value when the all-cause daily death counts were fitted with the maximum PT for the 75(th) percentile of summer. For Daegu, all-cause mortality presented the greatest percent increase (3.52% [95% CI, 2.23 to 4.80%]) in minimum temperature and AIC showed the lowest value in maximum temperature. No lag effect was found in the association between temperature and mortality for Seoul, whereas for Daegu one-day lag effect was noted.
Conclusions: There was no one temperature measure that was superior to the others in summer. To adopt an appropriate temperature index, regional meteorological characteristics and the disease status of population should be considered.
Keywords: Climate change; Generalized additive model (GAM); Heat-related mortality temperature index.