Li Bai1, Alistair Woodward2, Bin Chen3, Qiyong Liu4. 1. State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing 102206, PR China. Electronic address: baili_ChinaCDC@163.com. 2. School of Population Health, University of Auckland, Private Bag 92019, Auckland 1142, New Zealand. Electronic address: a.woodward@auckland.ac.nz. 3. State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing 102206, PR China. Electronic address: drchenbin@126.com. 4. State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing 102206, PR China; Shandong University Climate Change and Health Center, 44 Wenhua Road, Jinan, Shangdong 250012, PR China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou 310003, PR China. Electronic address: liuqiyong@icdc.cn.
Abstract
BACKGROUND: Tibet of China, with an average altitude of over 4000 m, has experienced noticeable changes in its climate over the last 50 years. The association between temperature and morbidity (most commonly represented by hospital admissions) has been documented mainly in developed countries. Little is known about patterns in China; nor have the health effects of temperature variations been closely studied in highland areas, worldwide. OBJECTIVE: We investigated the temperature-morbidity association in Lhasa, the capital city of Tibet, using sex- and age-specific hospitalizations, excluding those due to external causes. METHODS: A distributed lag non-linear model (DLNM) was applied to assess the nonlinear and delayed effects of temperature on morbidity (including total emergency room visits, total and cause-specific hospital admissions, sex- and age-specific non-external admissions). RESULTS: High temperatures are associated with increases in morbidity, to a greater extent than low temperatures. Lag effects of high and low temperatures were cause-specific. The relative risks (RR) of high temperature for total emergency room visits and non-external hospitalizations were 1.162 (95% CI: 1.002-1.349) and 1.161 (95% CI: 1.007-1.339) respectively, for lag 0-14 days. The strongest cumulative effect of heat for lag 0-27 days was on admissions for infectious diseases (RR: 2.067, 95% CI: 1.026-4.027). Acute heat effects at lag 0 were related with increases of renal (RR: 1.478, 95% CI: 1.005-2.174) and respiratory diseases (RR: 1.119, 95% CI: 1.010-1.240), whereas immediate cold effects increased admission for digestive diseases (RR: 1.132, 95% CI: 1.002-1.282). Those ≥65 years of age and males were more vulnerable to high temperatures. CONCLUSION: We provide a first look at the temperature-morbidity relationship in Tibet. Exposure to both hot and cold temperatures resulted in increased admissions to hospital, but the immediate causes varied. We suggest that initiatives should be taken to reduce the adverse effects of temperature extremes in Tibet.
BACKGROUND: Tibet of China, with an average altitude of over 4000 m, has experienced noticeable changes in its climate over the last 50 years. The association between temperature and morbidity (most commonly represented by hospital admissions) has been documented mainly in developed countries. Little is known about patterns in China; nor have the health effects of temperature variations been closely studied in highland areas, worldwide. OBJECTIVE: We investigated the temperature-morbidity association in Lhasa, the capital city of Tibet, using sex- and age-specific hospitalizations, excluding those due to external causes. METHODS: A distributed lag non-linear model (DLNM) was applied to assess the nonlinear and delayed effects of temperature on morbidity (including total emergency room visits, total and cause-specific hospital admissions, sex- and age-specific non-external admissions). RESULTS: High temperatures are associated with increases in morbidity, to a greater extent than low temperatures. Lag effects of high and low temperatures were cause-specific. The relative risks (RR) of high temperature for total emergency room visits and non-external hospitalizations were 1.162 (95% CI: 1.002-1.349) and 1.161 (95% CI: 1.007-1.339) respectively, for lag 0-14 days. The strongest cumulative effect of heat for lag 0-27 days was on admissions for infectious diseases (RR: 2.067, 95% CI: 1.026-4.027). Acute heat effects at lag 0 were related with increases of renal (RR: 1.478, 95% CI: 1.005-2.174) and respiratory diseases (RR: 1.119, 95% CI: 1.010-1.240), whereas immediate cold effects increased admission for digestive diseases (RR: 1.132, 95% CI: 1.002-1.282). Those ≥65 years of age and males were more vulnerable to high temperatures. CONCLUSION: We provide a first look at the temperature-morbidity relationship in Tibet. Exposure to both hot and cold temperatures resulted in increased admissions to hospital, but the immediate causes varied. We suggest that initiatives should be taken to reduce the adverse effects of temperature extremes in Tibet.
Authors: Yunquan Zhang; Mingquan He; Simin Wu; Yaohui Zhu; Suqing Wang; Masayuki Shima; Kenji Tamura; Lu Ma Journal: Int J Environ Res Public Health Date: 2015-07-10 Impact factor: 3.390
Authors: Joris Adriaan Frank van Loenhout; Tefera Darge Delbiso; Anna Kiriliouk; Jose Manuel Rodriguez-Llanes; Johan Segers; Debarati Guha-Sapir Journal: BMC Public Health Date: 2018-01-05 Impact factor: 3.295