title: Global variation in the effects of ambient temperature on mortality: a systematic evaluation.
abstract: BACKGROUND
  Studies have examined the effects of temperature on mortality in a single city, country, or region. However, less evidence is available on the variation in the associations between temperature and mortality in multiple countries, analyzed simultaneously.
  
  
  METHODS
  We obtained daily data on temperature and mortality in 306 communities from 12 countries/regions (Australia, Brazil, Thailand, China, Taiwan, Korea, Japan, Italy, Spain, United Kingdom, United States, and Canada). Two-stage analyses were used to assess the nonlinear and delayed relation between temperature and mortality. In the first stage, a Poisson regression allowing overdispersion with distributed lag nonlinear model was used to estimate the community-specific temperature-mortality relation. In the second stage, a multivariate meta-analysis was used to pool the nonlinear and delayed effects of ambient temperature at the national level, in each country.
  
  
  RESULTS
  The temperatures associated with the lowest mortality were around the 75th percentile of temperature in all the countries/regions, ranging from 66th (Taiwan) to 80th (UK) percentiles. The estimated effects of cold and hot temperatures on mortality varied by community and country. Meta-analysis results show that both cold and hot temperatures increased the risk of mortality in all the countries/regions. Cold effects were delayed and lasted for many days, whereas heat effects appeared quickly and did not last long.
  
  
  CONCLUSIONS
  People have some ability to adapt to their local climate type, but both cold and hot temperatures are still associated with increased risk of mortality. Public health strategies to alleviate the impact of ambient temperatures are important, in particular in the context of climate change.
authors.affiliation: From the aDepartment of Epidemiology and Biostatistics, School of Population Health, The University of Queensland, Brisbane, Australia; bDepartment of Medical Statistics, London School of Hygiene & Tropical Medicine, London, United Kingdom; cDepartment of Social and Environmental Health Research, London School of Hygiene & Tropical Medicine, London, United Kingdom; dHealth Impact Assessment Division, Department of Heath, Ministry of Public Heath, Thailand; eInstitute of Environmental Assessment and Water Research, Spanish Council for Scientific Research, Barcelona, Spain; fEnvironmental Issues Division, Public Health Agency of Canada, Ottawa, Canada; gInterdisciplinary School of Health Sciences, University of Ottawa, Ottawa, Canada; hLaboratory of Experimental Air Pollution, Department of Pathology, School of Medicine, University of São Paulo, São Paulo, Brazil; iDepartment of Epidemiology of the Lazio Regional Health Service, Rome, Italy; jDepartment of Occupational and Environmental Health, School of Public Health, Peking University, Beijing, China; kSchool of Public Health and Social Work and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia; lThe Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China; mGraduate School of Public Health & Institute of Health and Environment, Seoul National University, Seoul, Republic of Korea; nDepartment of Pediatric Infectious Diseases, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan; oFaculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan; pDepartment of Environmental and Occupational Medicine, National Taiwan University, Taipei, Taiwan; and qDepartment of Public Health, National Taiwan University, Taipei, Taiwan.
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mesh_terms: D000222:Adaptation, Physiological; D002980:Climate; D014943:Global Health; D006801:Humans; D009026:Mortality / Q000639:trends*; D012621:Seasons; D013696:Temperature