Pular para o conteúdo principal

ETHNOS_APP

Início • Busca • Periódicos • Lista 0

Temperature-attributable mortality projections under scenarios of climate change for Oslo, Norway

Dados Bibliográficos

ID15366261
AutoresLiliana Vázquez Fernández (0000-0003-3778-9415, Norwegian Institute of Public Health, autor correspondente), Alfonso Diz-Lois Palomares (0000-0001-5381-9421, Norwegian Institute of Public Health), S L N Rao (Norwegian Institute of Public Health), Shilpa Rao (0000-0003-4012-9063), Ana Maria Vicedo-Cabrera (University of Bern)
Ano2026
Volume26
Fascículo1
Páginas511-511
Data de publicação2026-01-12
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoBMC Public Health (JOURNAL)
Identificadores do periódicoISSN: 1471-2458 • E-ISSN: 1471-2458
EditoraBioMed Central (PUBLISHER • GB)
DOI10.1186/s12889-025-25980-3
PMID41526859
OpenAlexW7122735866
IdiomaEN
Referências citadas33

Climate change and evolving of population dynamics, including ageing and changes in population size, are reshaping temperature-attributable mortality patterns. However, there is limited evidence on the prospective trajectory of heat- and cold-attributable mortality in Oslo, particularly under combined scenarios of global warming and population development. This study aims to project heat- and cold-attributable mortality in Oslo and assess the distinct contributions of each of these drivers, utilising high-resolution data. We conducted a two-step approach with time series analysis with distributed lag non-linear models to estimate heat- and cold-attributable mortality relationship based on mean daily ambient temperature. Then, we performed a health impact assessment to compute the attributable mortality to heat and cold in the baseline period (2010–2019) and by the end of the century using regional population projections, mortality rates and projected daily temperature under two climate scenarios: RCP4.5 and RCP8.5. For the RCP4.5/Medium Road scenario, the attributable mortality fractions for heat and cold are projected to increase over time, with values ranging from 9.05% (95%CI: 1.55–15.90) in 2010–2019 to 9.78% (95% CI: 2.96–15.86) in 2090–2099. Cold mortality consistently dominates the total, while heat mortality remains relatively low, starting at 1.80% (95%CI: 0.10–3.68) at baseline and increasing slightly to 3.12% (95%CI: 0.34–5.94) by the end of the century. In contrast, the RCP8.5/Strong Ageing scenario shows a more pronounced rise, with temperature-attributable mortality increasing from 9.07% (95%CI: 1.53–15.89) in 2010–2019 to 11.86% (95%CI: 4.29–18.53) in 2090–2099. In this scenario, heat mortality contributes significantly more, rising from 1.83% (95%CI: 0.12–3.85) in 2010–2019 to 5.99% (95%CI: 1.23–10.35) by 2090–2099, reflecting the greater climate and population impact under RCP8.5 and the Strong Ageing pathway. Our findings highlight the need for climate and population dynamics to be considered in public health policies. Tailored interventions are crucial to mitigate heat and cold-attributable mortality, particularly for vulnerable populations. Future research should integrate socio-economic factors and explore adaptation strategies to refine mortality projections and inform policy

Baseline (sea · Biostatistics · Climate change · Distributed lag · Mean radiant temperature · Mortality rate · Poison control · Population · Public health · Air Quality and Health Impacts · Climate Change and Health Impacts · Thermal Regulation in Medicine

  • Mortality risk attributable to high and low ambient temperature

    Open Access•Antonio Gasparrini, Yuming Guo et al.•The Lancet•2015

  • The next generation of scenarios for climate change research and assessment

    Open Access•Richard H Moss, Jae Edmonds et al.•Nature•2010

  • Projections of temperature-related excess mortality under climate change scenarios

    Open Access•Antonio Gasparrini, Yuming Guo et al.•The Lancet Planetary Health•2017

  • Reducing and meta-analysing estimates from distributed lag non-linear models

    Open Access•Antonio Gasparrini, Ben Armstrong•BMC Medical Research Methodology•2013

  • The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

    Open Access•Brian C O''Neill, Claudia Tebaldi et al.•Geoscientific Model Development•2016

  • How does the CMIP6 ensemble change the picture for European climate projections

    Open Access•Tamzin Palmer, Ben Booth et al.•Environmental Research Letters•2021

  • Climate Change Effects on Heat- and Cold-Related Mortality in the Netherlands

    Open Access•Maud Huynen, Pim Martens•International Journal of…•2015

  • Heat, Heatwaves and Cardiorespiratory Hospital Admissions in Helsinki, Finland

    Open Access•Hasan Sohail, Virpi Kollanus et al.•International Journal of…•2020

  • Cold Weather and Cardiac Arrest in 4 Seasons

    Niilo R I Ryti, Jouni Nurmi et al.•American Journal of Public Health•2022

Velocidade de citaçãohistorical
Altamente citadoNão
Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae