예측과정을 이용한 연령별 시차 분포 모형

Abstract

Interest in mental disease is increasing. Recently a positive association between elevated temperature and mental disease has been reported. However, there was a limitation in that detailed interaction with age could not be confirmed. In this study, to overcome such limitations, the association between emergency room visits due to mental disease and mean temperature was explored by using the age-specific distributed lag model. The age-specific distributed lag model is a model in which a coefficient of age and lagged temperature are integrated into the existing distributed lag model. Accordingly the dimension of the parameter space was reduced by expressing the increased parameters as a linear combination of prediction process basis functions and the accuracy of parameter estimation was increased using information on the total age. The degree of borrowing information over age was estimated through variogram modeling. From 2014 to 2020, 906,958 patients visited the emergency room due to mental disease in Seoul. The age groups with a positive cumulative association over the lag period of 0-3 days between mean temperature and emergency room visits due to mental disease were 15 to 24, 40 to 59 and 80 to 84. As the effects of climate change become a reality, understanding detailed vulnerabilities will become very important for public health planning and intervention.