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Quantifying Vulnerability to Extreme Heat in Time Series Analyses: A Novel Approach Applied to Neighborhood Social Disparities under Climate Change

Author

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  • Tarik Benmarhnia

    (Université de Montréal, DSEST, Montréal, QC H3T 1A8, Canada
    EHESP School of Public Health, Rennes, Sorbonne-Paris Cité 35043, France
    Institute for Health and Social Policy, McGill University, Montreal QC H3A 1A3, Canada)

  • Patrick Grenier

    (Consortium Ouranos, Montréal, Département Scénarios et Services Climatiques, Montréal, QC H3A 1B9, Canada)

  • Allan Brand

    (Institut National de Santé Publique du Québec, Montréal, QC H3A 1B9, Canada)

  • Michel Fournier

    (Direction de santé publique de l’Agence de la santé et des services sociaux de Montréal, QC H2P 1E2, Canada)

  • Séverine Deguen

    (EHESP School of Public Health, Rennes, Sorbonne-Paris Cité 35043, France
    INSERM U1085 (IRSET), Rennes 35042, France)

  • Audrey Smargiassi

    (Université de Montréal, DSEST, Montréal, QC H3T 1A8, Canada
    Institut National de Santé Publique du Québec, Montréal, QC H3A 1B9, Canada)

Abstract

Objectives : We propose a novel approach to examine vulnerability in the relationship between heat and years of life lost and apply to neighborhood social disparities in Montreal and Paris. Methods : We used historical data from the summers of 1990 through 2007 for Montreal and from 2004 through 2009 for Paris to estimate daily years of life lost social disparities (DYLLD), summarizing social inequalities across groups. We used Generalized Linear Models to separately estimate relative risks (RR) for DYLLD in association with daily mean temperatures in both cities. We used 30 climate scenarios of daily mean temperature to estimate future temperature distributions (2021–2050). We performed random effect meta-analyses to assess the impact of climate change by climate scenario for each city and compared the impact of climate change for the two cities using a meta-regression analysis. Results : We show that an increase in ambient temperature leads to an increase in social disparities in daily years of life lost. The impact of climate change on DYLLD attributable to temperature was of 2.06 (95% CI: 1.90, 2.25) in Montreal and 1.77 (95% CI: 1.61, 1.94) in Paris. The city explained a difference of 0.31 (95% CI: 0.14, 0.49) on the impact of climate change. Conclusion : We propose a new analytical approach for estimating vulnerability in the relationship between heat and health. Our results suggest that in Paris and Montreal, health disparities related to heat impacts exist today and will increase in the future.

Suggested Citation

  • Tarik Benmarhnia & Patrick Grenier & Allan Brand & Michel Fournier & Séverine Deguen & Audrey Smargiassi, 2015. "Quantifying Vulnerability to Extreme Heat in Time Series Analyses: A Novel Approach Applied to Neighborhood Social Disparities under Climate Change," IJERPH, MDPI, vol. 12(9), pages 1-11, September.
  • Handle: RePEc:gam:jijerp:v:12:y:2015:i:9:p:11869-11879:d:56213
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    References listed on IDEAS

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    1. Mengmeng Li & Shaohua Gu & Peng Bi & Jun Yang & Qiyong Liu, 2015. "Heat Waves and Morbidity: Current Knowledge and Further Direction-A Comprehensive Literature Review," IJERPH, MDPI, vol. 12(5), pages 1-28, May.
    2. Elisabeth Tovar & Lise Bourdeau-Lepage, 2013. "Well-being Disparities within the Paris Region: A Capabilist Spatialised Outlook," Urban Studies, Urban Studies Journal Limited, vol. 50(8), pages 1575-1591, June.
    3. Gelman, Andrew & Stern, Hal, 2006. "The Difference Between," The American Statistician, American Statistical Association, vol. 60, pages 328-331, November.
    4. Elisabeth Tovar & Lise Bourdeau-Lepage, 2013. "Well-being Disparities within the Paris Region: A Capabilist Spatialised Outlook," Urban Studies, Urban Studies Journal Limited, vol. 50(8), pages 1575-1591, June.
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    Cited by:

    1. Zhaoqi Yin & Weipeng Li & Zhongsheng Chen & Li Zhu & Panheng Shui, 2024. "Urban Vulnerability under the Extreme High Temperatures in the Chengdu-Chongqing Area, Western China," Sustainability, MDPI, vol. 16(11), pages 1-17, June.

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