Research Article Advance Publication
Variability in Temperature-Related Mortality Projections under Climate Change
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Citation: Benmarhnia T, Sottile MF, Plante C, Brand A, Casati B, Fournier M, Smargiassi A. Variability in Temperature-Related Mortality Projections under Climate Change. Environ Health Perspect; http://dx.doi.org/10.1289/ehp.1306954.
Received: 15 April 2013
Accepted: 16 July 2014
Advance Publication: 18 July 2014
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 non-accidental mortality in association with three different daily temperature metrics (mean, minimum, and maximum temperature) during June–August. To estimate future numbers of deaths attributable to ambient temperatures and its uncertainty, we used 32 different simulations of daily temperatures for June-August 2020-2037 derived from 3 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% confidence interval of the attributable number of deaths), We then used an analysis of covariance (ANCOVA) to evaluate the influence of the simulation, the projected year, and the sets of RRs used to derive the attributable numbers of death (ANs).
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.
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