Yifan Hu1, Fengfeng Liu2, Xing Zhao1, Yue Ma1, Tianjiao Lan1, Fan Yang1, Zhaorui Chang3, Xiong Xiao4, Zhongjie Li2. 1. Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China. 2. Division of Infectious Disease & Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China. 3. Division of Infectious Disease & Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China. Electronic address: changzr@chinacdc.cn. 4. Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China. Electronic address: xiaoxiong.scu@scu.edu.cn.
Abstract
BACKGROUND: Growing evidence suggests that the diurnal temperature range (DTR) could modify the temperature-disease relationship for those environmentally-related infectious diseases. However, there is a lack of evidence on the hand, foot and mouth disease (HFMD). In this study, we thoroughly examined this hypothesis via a nationwide study. METHOD: We collected the daily time series of HFMD cases and meteorological factors of 143 cities in mainland China from 2009 to 2014. For each city, we calculated the arithmetic average of the meteorological factors as a proxy for the climatic differences. We then performed two-stage time series analyses for four different climatic regions. Specifically, a distributed lag nonlinear model was applied to estimate the temperature-HFMD relationship for each city, and then a multivariate meta-regression was implemented to examine whether the DTR could explain the potential heterogeneity as an effect modifier. In addition, we compared the modification effect of the DTR with those of other climatic factors. RESULT: We found a significant modification effect of DTR on the temperature-HFMD relationship in the moderate-temperature region. Besides, the modification effect was only observed at hot temperatures. Comparing the maximum temperature (32.2 °C) to the median temperature (11.9 °C), the risk ratio was 1.60 (1.33, 1.92) when DTR was in the 10th percentile (6.8 °C) and 0.81 (0.69, 0.96) when the DTR was in the 90th percentile (11.8 °C). By comparing DTR with other climatic variables, we found that the DTR had the best performance in improving the model fit (ΔQAIC= 10.1) and reducing the heterogeneity (ΔI2 = 3.1%) in the multivariate meta-regression. CONCLUSION: Our findings verified that DTR can modify the temperature-HFMD relationship. Besides, our findings also implied that DTR could be used as a proxy variable to comprehensively reflect the modification effects of multiple climatic factors.
BACKGROUND: Growing evidence suggests that the diurnal temperature range (DTR) could modify the temperature-disease relationship for those environmentally-related infectious diseases. However, there is a lack of evidence on the hand, foot and mouth disease (HFMD). In this study, we thoroughly examined this hypothesis via a nationwide study. METHOD: We collected the daily time series of HFMD cases and meteorological factors of 143 cities in mainland China from 2009 to 2014. For each city, we calculated the arithmetic average of the meteorological factors as a proxy for the climatic differences. We then performed two-stage time series analyses for four different climatic regions. Specifically, a distributed lag nonlinear model was applied to estimate the temperature-HFMD relationship for each city, and then a multivariate meta-regression was implemented to examine whether the DTR could explain the potential heterogeneity as an effect modifier. In addition, we compared the modification effect of the DTR with those of other climatic factors. RESULT: We found a significant modification effect of DTR on the temperature-HFMD relationship in the moderate-temperature region. Besides, the modification effect was only observed at hot temperatures. Comparing the maximum temperature (32.2 °C) to the median temperature (11.9 °C), the risk ratio was 1.60 (1.33, 1.92) when DTR was in the 10th percentile (6.8 °C) and 0.81 (0.69, 0.96) when the DTR was in the 90th percentile (11.8 °C). By comparing DTR with other climatic variables, we found that the DTR had the best performance in improving the model fit (ΔQAIC= 10.1) and reducing the heterogeneity (ΔI2 = 3.1%) in the multivariate meta-regression. CONCLUSION: Our findings verified that DTR can modify the temperature-HFMD relationship. Besides, our findings also implied that DTR could be used as a proxy variable to comprehensively reflect the modification effects of multiple climatic factors.