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Variability in Temperature-Related Mortality Projections under Climate Change
Background: Most studies that have assessed impacts on mortality of future temperature increases have relied on a small number of simulations and have not addressed the variability and sources of uncertainty in their mortality projections. Objectives: We assessed the variability of temperature proje...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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NLM-Export
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4256694/ https://www.ncbi.nlm.nih.gov/pubmed/25036003 http://dx.doi.org/10.1289/ehp.1306954 |
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author | Benmarhnia, Tarik Sottile, Marie-France Plante, Céline Brand, Allan Casati, Barbara Fournier, Michel Smargiassi, Audrey |
author_facet | Benmarhnia, Tarik Sottile, Marie-France Plante, Céline Brand, Allan Casati, Barbara Fournier, Michel Smargiassi, Audrey |
author_sort | Benmarhnia, Tarik |
collection | PubMed |
description | Background: Most studies that have assessed impacts on mortality of future temperature increases have relied on a small number of simulations and have not addressed the variability and sources of uncertainty in their mortality projections. Objectives: We assessed the variability of temperature projections and dependent future mortality distributions, using a large panel of temperature simulations based on different climate models and emission scenarios. Methods: We used historical data from 1990 through 2007 for Montreal, Quebec, Canada, and Poisson regression models to estimate relative risks (RR) for daily nonaccidental mortality in association with three different daily temperature metrics (mean, minimum, and maximum temperature) during June through August. To estimate future numbers of deaths attributable to ambient temperatures and the uncertainty of the estimates, we used 32 different simulations of daily temperatures for June–August 2020–2037 derived from three global climate models (GCMs) and a Canadian regional climate model with three sets of RRs (one based on the observed historical data, and two on bootstrap samples that generated the 95% CI of the attributable number (AN) of deaths). We then used analysis of covariance to evaluate the influence of the simulation, the projected year, and the sets of RRs used to derive the attributable numbers of deaths. Results: We found that < 1% of the variability in the distributions of simulated temperature for June–August of 2020–2037 was explained by differences among the simulations. Estimated ANs for 2020–2037 ranged from 34 to 174 per summer (i.e., June–August). Most of the variability in mortality projections (38%) was related to the temperature–mortality RR used to estimate the ANs. Conclusions: The choice of the RR estimate for the association between temperature and mortality may be important to reduce uncertainty in mortality projections. Citation: Benmarhnia T, Sottile MF, Plante C, Brand A, Casati B, Fournier M, Smargiassi A. 2014. Variability in temperature-related mortality projections under climate change. Environ Health Perspect 122:1293–1298; http://dx.doi.org/10.1289/ehp.1306954 |
format | Online Article Text |
id | pubmed-4256694 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | NLM-Export |
record_format | MEDLINE/PubMed |
spelling | pubmed-42566942014-12-18 Variability in Temperature-Related Mortality Projections under Climate Change Benmarhnia, Tarik Sottile, Marie-France Plante, Céline Brand, Allan Casati, Barbara Fournier, Michel Smargiassi, Audrey Environ Health Perspect Research Background: Most studies that have assessed impacts on mortality of future temperature increases have relied on a small number of simulations and have not addressed the variability and sources of uncertainty in their mortality projections. Objectives: We assessed the variability of temperature projections and dependent future mortality distributions, using a large panel of temperature simulations based on different climate models and emission scenarios. Methods: We used historical data from 1990 through 2007 for Montreal, Quebec, Canada, and Poisson regression models to estimate relative risks (RR) for daily nonaccidental mortality in association with three different daily temperature metrics (mean, minimum, and maximum temperature) during June through August. To estimate future numbers of deaths attributable to ambient temperatures and the uncertainty of the estimates, we used 32 different simulations of daily temperatures for June–August 2020–2037 derived from three global climate models (GCMs) and a Canadian regional climate model with three sets of RRs (one based on the observed historical data, and two on bootstrap samples that generated the 95% CI of the attributable number (AN) of deaths). We then used analysis of covariance to evaluate the influence of the simulation, the projected year, and the sets of RRs used to derive the attributable numbers of deaths. Results: We found that < 1% of the variability in the distributions of simulated temperature for June–August of 2020–2037 was explained by differences among the simulations. Estimated ANs for 2020–2037 ranged from 34 to 174 per summer (i.e., June–August). Most of the variability in mortality projections (38%) was related to the temperature–mortality RR used to estimate the ANs. Conclusions: The choice of the RR estimate for the association between temperature and mortality may be important to reduce uncertainty in mortality projections. Citation: Benmarhnia T, Sottile MF, Plante C, Brand A, Casati B, Fournier M, Smargiassi A. 2014. Variability in temperature-related mortality projections under climate change. Environ Health Perspect 122:1293–1298; http://dx.doi.org/10.1289/ehp.1306954 NLM-Export 2014-07-18 2014-12 /pmc/articles/PMC4256694/ /pubmed/25036003 http://dx.doi.org/10.1289/ehp.1306954 Text en http://creativecommons.org/publicdomain/mark/1.0/ Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, “Reproduced with permission from Environmental Health Perspectives”); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. |
spellingShingle | Research Benmarhnia, Tarik Sottile, Marie-France Plante, Céline Brand, Allan Casati, Barbara Fournier, Michel Smargiassi, Audrey Variability in Temperature-Related Mortality Projections under Climate Change |
title | Variability in Temperature-Related Mortality Projections under Climate Change |
title_full | Variability in Temperature-Related Mortality Projections under Climate Change |
title_fullStr | Variability in Temperature-Related Mortality Projections under Climate Change |
title_full_unstemmed | Variability in Temperature-Related Mortality Projections under Climate Change |
title_short | Variability in Temperature-Related Mortality Projections under Climate Change |
title_sort | variability in temperature-related mortality projections under climate change |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4256694/ https://www.ncbi.nlm.nih.gov/pubmed/25036003 http://dx.doi.org/10.1289/ehp.1306954 |
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