Qi Zhao1, Yongming Zhang2, Wenyi Zhang3, Shanshan Li1, Gongbo Chen1, Yanbin Wu4, Chen Qiu5, Kejing Ying6, Huaping Tang7, Jian-An Huang8, Gail Williams1, Rachel Huxley9, Yuming Guo10. 1. Division of Epidemiology and Biostatistics, School of Public Health, University of Queensland, 288 Herston Road, Brisbane, 4006, Queensland, Australia. 2. Department of Respiratory and Critical Care Medicine, China-Japan Friendship Hospital, 2 East Yinghua Road, Beijing 100029, China. 3. Institute for Disease Control and Prevention, Academy of Military Medical Science, 20 East Road, Fengtai District, Beijing, 102206, China. 4. First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi, China. 5. Shenzhen People's Hospital, 1017 North Dongmen Road, Shenzhen, 518020, Guangdong, China. 6. Respiratory and Critical Care Department, Sir Run Run Shaw Hospital, Zhejiang University, 3 East Qingchun Road Hangzhou, 310016, Zhejiang, China. 7. Qingdao Municipal Hospital, 1 Jiaozhou Road, Qingdao, 266011, Shandong, China. 8. First Affiliated Hospital of Soochow University, 188 Shizi Street, Suzhou, 215006, Jiangsu, China. 9. School of Public Health, Curtin University, Kent Street, Perth, 6102, Western Australia, Australia. 10. Division of Epidemiology and Biostatistics, School of Public Health, University of Queensland, 288 Herston Road, Brisbane, 4006, Queensland, Australia. Electronic address: y.guo1@uq.edu.au.
Abstract
BACKGROUND: The association between ambient temperature and mortality has been well documented worldwide. However, limited data are available on nonfatal health outcomes, such as emergency department visits (EDVs), particularly from China. OBJECTIVES: To examine the temperature-EDV association in 12 Chinese cities; and to assess the modification effects by region, gender and age. METHODS: Daily meteorological data and non-accidental EDVs were collected during 2011-2014. Poisson regression with distributed lag non-linear model was applied to examine the temperature-lag-EDV association in each city. The effect estimates were pooled using multivariate meta-analysis at the national and regional level. Stratified analyses were performed by gender and age-groups. Sensitivity analyses adjusting for air pollution and relative humidity were conducted. RESULTS: A total of 4,443,127 EDVs were collected from the 12 cities. Both cold and hot temperatures were associated with increased risk of EDVs, with minimum-mortality temperature located at 64th percentile of temperature. The effect of cold temperature appeared on day 2 and persisted until day 30, causing a cumulative relative risk (RR) of 1.80 (1.54, 2.11). The effect of hot temperature appeared immediately and lasted until day 3, with a cumulative RR of 1.15 (1.03, 1.29). The effect of temperature on EDVs was similar in male and female but was attenuated with increasing age. The effect of cold temperature on EDVs was greater in southern areas of the country whereas the hot effect was greater in northern cities. The association was robust to a large range of sensitivity analyses. CONCLUSIONS: In China, there is a U-shaped association between temperature and risk of EDVs that is independent of air pollution and humidity. The temperature-EDV association varies with latitude and age-groups but is not affected by gender. Forecasting models for hospital emergency departments may be improved if temperature is included as an independent predictor.
BACKGROUND: The association between ambient temperature and mortality has been well documented worldwide. However, limited data are available on nonfatal health outcomes, such as emergency department visits (EDVs), particularly from China. OBJECTIVES: To examine the temperature-EDV association in 12 Chinese cities; and to assess the modification effects by region, gender and age. METHODS: Daily meteorological data and non-accidental EDVs were collected during 2011-2014. Poisson regression with distributed lag non-linear model was applied to examine the temperature-lag-EDV association in each city. The effect estimates were pooled using multivariate meta-analysis at the national and regional level. Stratified analyses were performed by gender and age-groups. Sensitivity analyses adjusting for air pollution and relative humidity were conducted. RESULTS: A total of 4,443,127 EDVs were collected from the 12 cities. Both cold and hot temperatures were associated with increased risk of EDVs, with minimum-mortality temperature located at 64th percentile of temperature. The effect of cold temperature appeared on day 2 and persisted until day 30, causing a cumulative relative risk (RR) of 1.80 (1.54, 2.11). The effect of hot temperature appeared immediately and lasted until day 3, with a cumulative RR of 1.15 (1.03, 1.29). The effect of temperature on EDVs was similar in male and female but was attenuated with increasing age. The effect of cold temperature on EDVs was greater in southern areas of the country whereas the hot effect was greater in northern cities. The association was robust to a large range of sensitivity analyses. CONCLUSIONS: In China, there is a U-shaped association between temperature and risk of EDVs that is independent of air pollution and humidity. The temperature-EDV association varies with latitude and age-groups but is not affected by gender. Forecasting models for hospital emergency departments may be improved if temperature is included as an independent predictor.
Authors: Kate R Weinberger; Kipruto Kirwa; Melissa N Eliot; Julia Gold; Helen H Suh; Gregory A Wellenius Journal: Epidemiology Date: 2018-07 Impact factor: 4.822
Authors: Qi Zhao; Shanshan Li; Micheline S Z S Coelho; Paulo H N Saldiva; Kejia Hu; Michael J Abramson; Rachel R Huxley; Yuming Guo Journal: JAMA Netw Open Date: 2019-02-01
Authors: Qi Zhao; Shanshan Li; Micheline S Z S Coelho; Paulo H N Saldiva; Kejia Hu; Rachel R Huxley; Michael J Abramson; Yuming Guo Journal: PLoS Med Date: 2019-02-22 Impact factor: 11.069
Authors: Junyu He; Yong Wang; Di Mu; Zhiwei Xu; Quan Qian; Gongbo Chen; Liang Wen; Wenwu Yin; Shanshan Li; Wenyi Zhang; Yuming Guo Journal: Int J Environ Res Public Health Date: 2019-09-16 Impact factor: 3.390