Seasonality of mortality under climate change: a multicountry projection study.


Journal

The Lancet. Planetary health
ISSN: 2542-5196
Titre abrégé: Lancet Planet Health
Pays: Netherlands
ID NLM: 101704339

Informations de publication

Date de publication:
Feb 2024
Historique:
received: 14 06 2023
revised: 28 11 2023
accepted: 08 12 2023
medline: 9 2 2024
pubmed: 9 2 2024
entrez: 8 2 2024
Statut: ppublish

Résumé

Climate change can directly impact temperature-related excess deaths and might subsequently change the seasonal variation in mortality. In this study, we aimed to provide a systematic and comprehensive assessment of potential future changes in the seasonal variation, or seasonality, of mortality across different climate zones. In this modelling study, we collected daily time series of mean temperature and mortality (all causes or non-external causes only) via the Multi-Country Multi-City Collaborative (MCC) Research Network. These data were collected during overlapping periods, spanning from Jan 1, 1969 to Dec 31, 2020. We projected daily mortality from Jan 1, 2000 to Dec 31, 2099, under four climate change scenarios corresponding to increasing emissions (Shared Socioeconomic Pathways [SSP] scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We compared the seasonality in projected mortality between decades by its shape, timings (the day-of-year) of minimum (trough) and maximum (peak) mortality, and sizes (peak-to-trough ratio and attributable fraction). Attributable fraction was used to measure the burden of seasonality of mortality. The results were summarised by climate zones. The MCC dataset included 126 809 537 deaths from 707 locations within 43 countries or areas. After excluding the only two polar locations (both high-altitude locations in Peru) from climatic zone assessments, we analysed 126 766 164 deaths in 705 locations aggregated in four climate zones (tropical, arid, temperate, and continental). From the 2000s to the 2090s, our projections showed an increase in mortality during the warm seasons and a decrease in mortality during the cold seasons, albeit with mortality remaining high during the cold seasons, under all four SSP scenarios in the arid, temperate, and continental zones. The magnitude of this changing pattern was more pronounced under the high-emission scenarios (SSP3-7.0 and SSP5-8.5), substantially altering the shape of seasonality of mortality and, under the highest emission scenario (SSP5-8.5), shifting the mortality peak from cold seasons to warm seasons in arid, temperate, and continental zones, and increasing the size of seasonality in all zones except the arid zone by the end of the century. In the 2090s compared with the 2000s, the change in peak-to-trough ratio (relative scale) ranged from 0·96 to 1·11, and the change in attributable fraction ranged from 0·002% to 0·06% under the SSP5-8.5 (highest emission) scenario. A warming climate can substantially change the seasonality of mortality in the future. Our projections suggest that health-care systems should consider preparing for a potentially increased demand during warm seasons and sustained high demand during cold seasons, particularly in regions characterised by arid, temperate, and continental climates. The Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, provided by the Ministry of the Environment of Japan.

Sections du résumé

BACKGROUND BACKGROUND
Climate change can directly impact temperature-related excess deaths and might subsequently change the seasonal variation in mortality. In this study, we aimed to provide a systematic and comprehensive assessment of potential future changes in the seasonal variation, or seasonality, of mortality across different climate zones.
METHODS METHODS
In this modelling study, we collected daily time series of mean temperature and mortality (all causes or non-external causes only) via the Multi-Country Multi-City Collaborative (MCC) Research Network. These data were collected during overlapping periods, spanning from Jan 1, 1969 to Dec 31, 2020. We projected daily mortality from Jan 1, 2000 to Dec 31, 2099, under four climate change scenarios corresponding to increasing emissions (Shared Socioeconomic Pathways [SSP] scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We compared the seasonality in projected mortality between decades by its shape, timings (the day-of-year) of minimum (trough) and maximum (peak) mortality, and sizes (peak-to-trough ratio and attributable fraction). Attributable fraction was used to measure the burden of seasonality of mortality. The results were summarised by climate zones.
FINDINGS RESULTS
The MCC dataset included 126 809 537 deaths from 707 locations within 43 countries or areas. After excluding the only two polar locations (both high-altitude locations in Peru) from climatic zone assessments, we analysed 126 766 164 deaths in 705 locations aggregated in four climate zones (tropical, arid, temperate, and continental). From the 2000s to the 2090s, our projections showed an increase in mortality during the warm seasons and a decrease in mortality during the cold seasons, albeit with mortality remaining high during the cold seasons, under all four SSP scenarios in the arid, temperate, and continental zones. The magnitude of this changing pattern was more pronounced under the high-emission scenarios (SSP3-7.0 and SSP5-8.5), substantially altering the shape of seasonality of mortality and, under the highest emission scenario (SSP5-8.5), shifting the mortality peak from cold seasons to warm seasons in arid, temperate, and continental zones, and increasing the size of seasonality in all zones except the arid zone by the end of the century. In the 2090s compared with the 2000s, the change in peak-to-trough ratio (relative scale) ranged from 0·96 to 1·11, and the change in attributable fraction ranged from 0·002% to 0·06% under the SSP5-8.5 (highest emission) scenario.
INTERPRETATION CONCLUSIONS
A warming climate can substantially change the seasonality of mortality in the future. Our projections suggest that health-care systems should consider preparing for a potentially increased demand during warm seasons and sustained high demand during cold seasons, particularly in regions characterised by arid, temperate, and continental climates.
FUNDING BACKGROUND
The Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, provided by the Ministry of the Environment of Japan.

Identifiants

pubmed: 38331534
pii: S2542-5196(23)00269-3
doi: 10.1016/S2542-5196(23)00269-3
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e86-e94

Investigateurs

Rosana Abrutzky (R)
Fiorella Acquaotta (F)
Barrak Alahmad (B)
Antonis Analitis (A)
Hanne Krage Carlsen (HK)
Gabriel Carrasco-Escobar (G)
Micheline de Sousa Zanotti Stagliorio Coelho (M)
Valentina Colistro (V)
Patricia Matus Correa (P)
Tran Ngoc Dang (TN)
Francesca de'Donato (F)
Magali Hurtado Diaz (M)
Do Van Dung (DV)
Alireza Entezari (A)
Bertil Forsberg (B)
Patrick Goodman (P)
Yue Leon Guo (YL)
Yuming Guo (Y)
Iulian-Horia Holobaca (IH)
Danny Houthuijs (D)
Veronika Huber (V)
Ene Indermitte (E)
Haidong Kan (H)
Klea Katsouyanni (K)
Yoonhee Kim (Y)
Ho Kim (H)
Whanhee Lee (W)
Shanshan Li (S)
Fatemeh Mayvaneh (F)
Paola Michelozzi (P)
Hans Orru (H)
Nicolás Valdés Ortega (N)
Samuel Osorio (S)
Ala Overcenco (A)
Shih-Chun Pan (SC)
Mathilde Pascal (M)
Martina S Ragettli (MS)
Shilpa Rao (S)
Raanan Raz (R)
Paulo Hilario Nascimento Saldiva (PHN)
Alexandra Schneider (A)
Joel Schwartz (J)
Noah Scovronick (N)
Xerxes Seposo (X)
César De la Cruz Valencia (C)
Antonella Zanobetti (A)
Ariana Zeka (A)

Informations de copyright

Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests We declare no competing interests.

Auteurs

Lina Madaniyazi (L)

School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan. Electronic address: lina.madaniyazi@nagasaki-u.ac.jp.

Ben Armstrong (B)

Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK.

Aurelio Tobias (A)

Institute of Environmental Assessment and Water Research, Spanish Council for Scientific Research, Barcelona, Spain.

Malcolm N Mistry (MN)

Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK; Department of Economics, Ca' Foscari University of Venice, Venice, Italy.

Michelle L Bell (ML)

School of the Environment, Yale University, New Haven, CT, USA.

Aleš Urban (A)

Institute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic; Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic.

Jan Kyselý (J)

Institute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic; Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic.

Niilo Ryti (N)

Center for Environmental and Respiratory Health Research, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland; Department of Public Health, University of Helsinki, Helsinki, Finland.

Ivana Cvijanovic (I)

Barcelona Institute for Global Health, Barcelona, Spain.

Chris Fook Sheng Ng (CFS)

Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Dominic Roye (D)

Climate Research Foundation, Madrid, Spain; Spanish Consortium for Research and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain.

Ana Maria Vicedo-Cabrera (AM)

Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Oeschger Center for Climate Change Research, University of Bern, Bern, Switzerland.

Shilu Tong (S)

National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD, Australia.

Eric Lavigne (E)

School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada; Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada.

Carmen Íñiguez (C)

Spanish Consortium for Research and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain; Department of Statistics and Computational Research, Universitat de València, València, Spain.

Susana das Neves Pereira da Silva (SDNP)

Department of Epidemiology, Instituto Nacional de Saúde Dr Ricardo Jorge, Lisbon, Portugal.

Joana Madureira (J)

Environmental Health Department, National Institute of Health, Porto, Portugal; EPIUnit, Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal; Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional, Porto, Portugal.

Jouni J K Jaakkola (JJK)

Center for Environmental and Respiratory Health Research, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland; Finnish Meteorological Institute, Helsinki, Finland.

Francesco Sera (F)

Department of Statistics, Computer Science and Applications "G Parenti", University of Florence, Florence, Italy.

Yasushi Honda (Y)

Center for Climate Change Adaptation, National Institute for Environmental Studies, Tsukuba, Japan.

Antonio Gasparrini (A)

Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK.

Masahiro Hashizume (M)

School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan; Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Classifications MeSH