Rainfall events and daily mortality across 645 global locations: two stage time series analysis
Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu časopisecké články
PubMed
39384295
PubMed Central
PMC12036573
DOI
10.1136/bmj-2024-080944
Knihovny.cz E-zdroje
- MeSH
- časové faktory MeSH
- celosvětové zdraví statistika a číselné údaje MeSH
- déšť * MeSH
- kardiovaskulární nemoci * mortalita MeSH
- lidé MeSH
- mortalita trendy MeSH
- nemoci dýchací soustavy * mortalita MeSH
- příčina smrti trendy MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
OBJECTIVE: To examine the associations between characteristics of daily rainfall (intensity, duration, and frequency) and all cause, cardiovascular, and respiratory mortality. DESIGN: Two stage time series analysis. SETTING: 645 locations across 34 countries or regions. POPULATION: Daily mortality data, comprising a total of 109 954 744 all cause, 31 164 161 cardiovascular, and 11 817 278 respiratory deaths from 1980 to 2020. MAIN OUTCOME MEASURE: Association between daily mortality and rainfall events with return periods (the expected average time between occurrences of an extreme event of a certain magnitude) of one year, two years, and five years, with a 14 day lag period. A continuous relative intensity index was used to generate intensity-response curves to estimate mortality risks at a global scale. RESULTS: During the study period, a total of 50 913 rainfall events with a one year return period, 8362 events with a two year return period, and 3301 events with a five year return period were identified. A day of extreme rainfall with a five year return period was significantly associated with increased daily all cause, cardiovascular, and respiratory mortality, with cumulative relative risks across 0-14 lag days of 1.08 (95% confidence interval 1.05 to 1.11), 1.05 (1.02 to 1.08), and 1.29 (1.19 to 1.39), respectively. Rainfall events with a two year return period were associated with respiratory mortality only, whereas no significant associations were found for events with a one year return period. Non-linear analysis revealed protective effects (relative risk <1) with moderate-heavy rainfall events, shifting to adverse effects (relative risk >1) with extreme intensities. Additionally, mortality risks from extreme rainfall events appeared to be modified by climate type, baseline variability in rainfall, and vegetation coverage, whereas the moderating effects of population density and income level were not significant. Locations with lower variability of baseline rainfall or scarce vegetation coverage showed higher risks. CONCLUSION: Daily rainfall intensity is associated with varying health effects, with extreme events linked to an increasing relative risk for all cause, cardiovascular, and respiratory mortality. The observed associations varied with local climate and urban infrastructure.
Center for Climate Change Adaptation National Institute for Environmental Studies Tsukuba Japan
Center for Environmental and Respiratory Health Research University of Oulu Oulu Finland
Climate Research Foundation CIBER of Epidemiology and Public Health Madrid Spain
Department of Earth Sciences University of Turin Turin Italy
Department of Environmental Health Harvard T H Chan School of Public Health Boston MA USA
Department of Environmental Health National Institute of Public Health Cuernavaca Morelos Mexico
Department of Environmental Health School of Public Health Fudan University Shanghai China
Department of Environmental Health Sciences Yale School of Public Health New Haven CT USA
Department of Environmental Health University of Sao Paulo Sao Paulo Brazil
Department of Epidemiology Lazio Regional Health Service ASL ROMA 1 Rome Italy
Department of Family Medicine and Public Health University of Tartu Tartu Estonia
Department of Global Health Policy Graduate School of Medicine University of Tokyo Tokyo Japan
Department of Pathology Faculty of Medicine University of Sao Paulo Sao Paulo Brazil
Department of Public Health and Clinical Medicine Umea University Umea Sweden
Department of Statistics and Computational Research University of Valencia Valencia Spain
Division of Infectious Diseases Department of Medicine University of California San Diego CA USA
Environmental Health Science and Research Bureau Health Canada Ottawa ON Canada
EPIUnit Instituto de Saúde Pública Universidade do Porto Porto Portugal
Faculty of Environmental Sciences Czech University of Life Sciences Prague Czech Republic
Faculty of Geography Babeș Bolyai University Cluj Napoca Romania
Finnish Meteorological Institute Helsinki Finland
Graduate School of Public Health Seoul National University Seoul Republic of Korea
Institute for Global Health University College London UK
Institute of Atmospheric Physics Czech Academy of Sciences Prague Czech Republic
Institute of Research and Development Duy Tan University Da Nang Vietnam
Institute of Social and Preventive Medicine University of Bern Bern Switzerland
Institute of Tropical Medicine Universidad Peruana Cayetano Heredia Lima Peru
Laboratório para a Investigação Integrativa e Translacional em Saúde Pública Porto Portugal
National Institute of Environmental Health Science National Health Research Institutes Zhunan Taiwan
National Institute of Health Dr Ricardo Jorge Portugal
Norwegian institute of Public Health Oslo Norway
Oeschger Center for Climate Change Research University of Bern Bern Switzerland
School of Epidemiology and Public Health Faculty of Medicine University of Ottawa Ottawa ON Canada
School of Public Health and Preventive Medicine Monash University Melbourne VIC Australia
School of Public Health and Social Work Queensland University of Technology Brisbane QLD Australia
School of the Environment Yale University New Haven CT USA
School of Tropical Medicine and Global Health Nagasaki University Nagasaki Japan
Swiss Tropical and Public Health Institute Allschwil Switzerland
Technological University Dublin Dublin Ireland
University of Basel Basel Switzerland
Yale Center on Climate Change and Health Yale School of Public Health New Haven CT USA
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