Qi Zhao1, Yuming Guo2, Tingting Ye3, Antonio Gasparrini4, Shilu Tong5, Ala Overcenco6, Aleš Urban7, Alexandra Schneider8, Alireza Entezari9, Ana Maria Vicedo-Cabrera10, Antonella Zanobetti11, Antonis Analitis12, Ariana Zeka13, Aurelio Tobias14, Baltazar Nunes15, Barrak Alahmad11, Ben Armstrong16, Bertil Forsberg17, Shih-Chun Pan18, Carmen Íñiguez19, Caroline Ameling20, César De la Cruz Valencia21, Christofer Åström17, Danny Houthuijs20, Do Van Dung22, Dominic Royé23, Ene Indermitte24, Eric Lavigne25, Fatemeh Mayvaneh9, Fiorella Acquaotta26, Francesca de'Donato27, Francesco Di Ruscio28, Francesco Sera29, Gabriel Carrasco-Escobar30, Haidong Kan31, Hans Orru24, Ho Kim32, Iulian-Horia Holobaca33, Jan Kyselý7, Joana Madureira34, Joel Schwartz11, Jouni J K Jaakkola35, Klea Katsouyanni36, Magali Hurtado Diaz21, Martina S Ragettli37, Masahiro Hashizume38, Mathilde Pascal39, Micheline de Sousa Zanotti Stagliorio Coélho40, Nicolás Valdés Ortega41, Niilo Ryti42, Noah Scovronick43, Paola Michelozzi27, Patricia Matus Correa41, Patrick Goodman44, Paulo Hilario Nascimento Saldiva40, Rosana Abrutzky45, Samuel Osorio46, Shilpa Rao28, Simona Fratianni26, Tran Ngoc Dang22, Valentina Colistro47, Veronika Huber48, Whanhee Lee49, Xerxes Seposo50, Yasushi Honda51, Yue Leon Guo52, Michelle L Bell49, Shanshan Li53. 1. Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia. 2. Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia. Electronic address: yuming.guo@monash.edu. 3. Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia. 4. Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, UK; Centre for Statistical Methodology, London School of Hygiene and Tropical Medicine, London, UK; Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, UK. 5. Shanghai Children's Medical Centre, Shanghai Jiao Tong University, Shanghai, China; School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China; Center for Global Health, Nanjing Medical University, Nanjing, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD, Australia. 6. Laboratory of Management in Science and Public Health, National Agency for Public Health of the Ministry of Health, Chisinau, Moldova. 7. Institute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic; Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic. 8. Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany. 9. Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran. 10. Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Oeschger Center for Climate Change Research, University of Bern, Bern, Switzerland. 11. Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA. 12. Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, Athens, Greece. 13. Institute of Environment, Health and Societies, Brunel University London, London, UK. 14. Institute of Environmental Assessment and Water Research, Spanish Council for Scientific Research, Barcelona, Spain; School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan. 15. Department of Epidemiology, Instituto Nacional de Saúde Dr Ricardo Jorge, Porto, Portugal; Centro de Investigação em Saúde Pública, Escola Nacional de Saúde Pública, Universidade NOVA de Lisboa, Lisbon, Portugal. 16. Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, UK. 17. Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden. 18. National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan. 19. Department of Statistics and Computational Research, Universitat de València, València, Spain; CIBER of Epidemiology and Public Health, Madrid, Spain. 20. Centre for Sustainability and Environmental Health, National Institute for Public Health and the Environment, Bilthoven, Netherlands. 21. Department of Environmental Health, National Institute of Public Health, Cuernavaca Morelos, Mexico. 22. Department of Environmental Health, Faculty of Public Health, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam. 23. CIBER of Epidemiology and Public Health, Madrid, Spain; Department of Geography, University of Santiago de Compostela, Santiago de Compostela, Spain. 24. Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia. 25. School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada; Air Health Science Division, Health Canada, Ottawa, ON, Canada. 26. Department of Earth Sciences, University of Turin, Turin, Italy. 27. Department of Epidemiology, Lazio Regional Health Service, Rome, Italy. 28. Norwegian institute of Public Health, Oslo, Norway. 29. Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, UK; Department of Statistics, Computer Science and Applications G. Parenti, University of Florence, Florence, Italy. 30. Health Innovation Lab, Institute of Tropical Medicine Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru; Division of Infectious Diseases, Department of Medicine, University of California, San Diego, CA, USA. 31. Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China. 32. Graduate School of Public Health, Seoul National University, Seoul, South Korea. 33. Faculty of Geography, Babeş-Bolyai University, Cluj-Napoca, Romania. 34. Department of Environmental Health, Instituto Nacional de Saúde Dr Ricardo Jorge, Porto, Portugal; EPIUnit, Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal. 35. Center for Environmental and Respiratory Health Research and Biocenter Oulu, University of Oulu, Oulu, Finland; Finnish Meteorological Institute, Helsinki, Finland. 36. Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, Athens, Greece; School of Population Health and Environmental Sciences, King's College London, London, UK. 37. Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland. 38. Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. 39. Department of Environmental and Occupational Health, Santé Publique France, French National Public Health Agency, Saint Maurice, France. 40. Department of Pathology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil. 41. Department of Public Health, Universidad de los Andes, Santiago, Chile. 42. Center for Environmental and Respiratory Health Research and Biocenter Oulu, University of Oulu, Oulu, Finland. 43. Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA. 44. School of Physics, Technological University Dublin, Dublin, Ireland. 45. Instituto de Investigaciones Gino Germani, Facultad de Ciencias Sociales, Universidad de Buenos Aires, Buenos Aires, Argentina. 46. Department of Environmental Health, University of São Paulo, São Paulo, Brazil. 47. Department of Quantitative Methods, School of Medicine, University of the Republic, Montevideo, Uruguay. 48. Potsdam Institute for Climate Impact Research, Potsdam, Germany; Department of Physical, Chemical and Natural Systems, Universidad Pablo de Olavide, Sevilla, Spain. 49. School of the Environment, Yale University, New Haven, CT, USA. 50. School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan. 51. Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan. 52. National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan; Environmental and Occupational Medicine, NTU College of Medicine and NTU Hospital, National Taiwan University, Taipei, Taiwan; Institute of Environmental and Occupational Health Sciences, NTU College of Public Health, National Taiwan University, Taipei, Taiwan. 53. Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia; Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia. Electronic address: shanshan.li@monash.edu.
Abstract
BACKGROUND: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. METHODS: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature-mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature-mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. FINDINGS: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967-5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58-11·07) of all deaths (8·52% [6·19-10·47] were cold-related and 0·91% [0·56-1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60-87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000-03 to 2016-19, the global cold-related excess death ratio changed by -0·51 percentage points (95% eCI -0·61 to -0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13-0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe. INTERPRETATION: Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios. FUNDING: Australian Research Council and the Australian National Health and Medical Research Council.
BACKGROUND: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. METHODS: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature-mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature-mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. FINDINGS: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967-5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58-11·07) of all deaths (8·52% [6·19-10·47] were cold-related and 0·91% [0·56-1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60-87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000-03 to 2016-19, the global cold-related excess death ratio changed by -0·51 percentage points (95% eCI -0·61 to -0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13-0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe. INTERPRETATION: Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios. FUNDING: Australian Research Council and the Australian National Health and Medical Research Council.
Authors: Yao Wu; Shanshan Li; Qi Zhao; Bo Wen; Antonio Gasparrini; Shilu Tong; Ala Overcenco; Aleš Urban; Alexandra Schneider; Alireza Entezari; Ana Maria Vicedo-Cabrera; Antonella Zanobetti; Antonis Analitis; Ariana Zeka; Aurelio Tobias; Baltazar Nunes; Barrak Alahmad; Ben Armstrong; Bertil Forsberg; Shih-Chun Pan; Carmen Íñiguez; Caroline Ameling; César De la Cruz Valencia; Christofer Åström; Danny Houthuijs; Do Van Dung; Dominic Royé; Ene Indermitte; Eric Lavigne; Fatemeh Mayvaneh; Fiorella Acquaotta; Francesca de'Donato; Shilpa Rao; Francesco Sera; Gabriel Carrasco-Escobar; Haidong Kan; Hans Orru; Ho Kim; Iulian-Horia Holobaca; Jan Kyselý; Joana Madureira; Joel Schwartz; Jouni J K Jaakkola; Klea Katsouyanni; Magali Hurtado Diaz; Martina S Ragettli; Masahiro Hashizume; Mathilde Pascal; Micheline de Sousa Zanotti Stagliorio Coélho; Nicolás Valdés Ortega; Niilo Ryti; Noah Scovronick; Paola Michelozzi; Patricia Matus Correa; Patrick Goodman; Paulo Hilario Nascimento Saldiva; Rosana Abrutzky; Samuel Osorio; Tran Ngoc Dang; Valentina Colistro; Veronika Huber; Whanhee Lee; Xerxes Seposo; Yasushi Honda; Yue Leon Guo; Michelle L Bell; Yuming Guo Journal: Lancet Planet Health Date: 2022-05
Authors: Evan de Schrijver; Marvin Bundo; Martina S Ragettli; Francesco Sera; Antonio Gasparrini; Oscar H Franco; Ana M Vicedo-Cabrera Journal: Environ Health Perspect Date: 2022-03-09 Impact factor: 11.035
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