title: Cardiovascular mortality risk attributable to ambient temperature in China.
abstract: OBJECTIVE
  To examine cardiovascular disease (CVD) mortality burden attributable to ambient temperature; to estimate effect modification of this burden by gender, age and education level.
  
  
  METHODS
  We obtained daily data on temperature and CVD mortality from 15 Chinese megacities during 2007-2013, including 1,936,116 CVD deaths. A quasi-Poisson regression combined with a distributed lag non-linear model was used to estimate the temperature-mortality association for each city. Then, a multivariate meta-analysis was used to derive the overall effect estimates of temperature at the national level. Attributable fraction of deaths were calculated for cold and heat (ie, temperature below and above minimum-mortality temperatures, MMTs), respectively. The MMT was defined as the specific temperature associated to the lowest mortality risk.
  
  
  RESULTS
  The MMT varied from the 70th percentile to the 99th percentile of temperature in 15 cities, centring at 78 at the national level. In total, 17.1% (95% empirical CI 14.4% to 19.1%) of CVD mortality (330,352 deaths) was attributable to ambient temperature, with substantial differences among cities, from 10.1% in Shanghai to 23.7% in Guangzhou. Most of the attributable deaths were due to cold, with a fraction of 15.8% (13.1% to 17.9%) corresponding to 305,902 deaths, compared with 1.3% (1.0% to 1.6%) and 24,450 deaths for heat.
  
  
  CONCLUSIONS
  This study emphasises how cold weather is responsible for most part of the temperature-related CVD death burden. Our results may have important implications for the development of policies to reduce CVD mortality from extreme temperatures.
authors.affiliation: State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
authors.forename: Jun
authors.initials: J
authors.lastname: Yang
authors.affiliation: The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Yin
authors.affiliation: The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, China.
authors.forename: Maigeng
authors.initials: M
authors.lastname: Zhou
authors.affiliation: State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, China.
authors.forename: Chun-Quan
authors.initials: CQ
authors.lastname: Ou
authors.affiliation: Division of Epidemiology and Biostatistics, School of Public Health, University of Queensland, Brisbane, Queensland, Australia.
authors.forename: Yuming
authors.initials: Y
authors.lastname: Guo
authors.affiliation: Department of Social and Environmental Health Research, London School of Hygiene & Tropical Medicine, London, UK.
authors.forename: Antonio
authors.identifier: http://orcid.org/0000-0002-2271-3568
authors.initials: A
authors.lastname: Gasparrini
authors.affiliation: The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, China.
authors.forename: Yunning
authors.initials: Y
authors.lastname: Liu
authors.affiliation: State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
authors.forename: Yujuan
authors.initials: Y
authors.lastname: Yue
authors.affiliation: State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
authors.forename: Shaohua
authors.initials: S
authors.lastname: Gu
authors.affiliation: State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
authors.forename: Shaowei
authors.initials: S
authors.lastname: Sang
authors.affiliation: The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, China.
authors.forename: Guijie
authors.initials: G
authors.lastname: Luan
authors.affiliation: Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Ohio, USA.
authors.forename: Qinghua
authors.initials: Q
authors.lastname: Sun
authors.affiliation: State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
authors.forename: Qiyong
authors.initials: Q
authors.lastname: Liu
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000401:mortality*; D002648:Child; D002675:Child, Preschool; D002681:China / Q000453:epidemiology; D003080:Cold Temperature; D004522:Educational Status; D005260:Female; D006358:Hot Temperature; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D017711:Nonlinear Dynamics; D018570:Risk Assessment; D012307:Risk Factors; D012737:Sex Factors; D013997:Time Factors; D014504:Urban Health; D055815:Young Adult