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Differences on the effect of heat waves on mortality by sociodemographic and urban landscape characteristics
  1. Yihan Xu1,2,
  2. Payam Dadvand1,3,
  3. Jose Barrera-Gómez1,3,
  4. Claudio Sartini4,
  5. Marc Marí-Dell'Olmo3,5,
  6. Carme Borrell2,3,5,
  7. Mercè Medina-Ramón1,3,
  8. Jordi Sunyer1,2,3,6,
  9. Xavier Basagaña1,3
  1. 1Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Catalonia, Spain
  2. 2Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
  3. 3CIBER Epidemiologia y Salud Publica (CIBERESP), Barcelona, Catalonia, Spain
  4. 4Department of Primary Care and Population Health, UCL Medical School, London, UK
  5. 5Agència de Salut Pública de Barcelona, Barcelona, Catalonia, Spain
  6. 6IMIM (Hospital del Mar Research Institute), Barcelona, Catalonia, Spain
  1. Correspondence to Dr Xavier Basagaña, Centre for Research in Environmental Epidemiology (CREAL), Doctor Aiguader 88, Barcelona, Catalonia 08003, Spain; xbasagana{at}creal.cat

Abstract

Background Mortality increases during heat waves have been reported worldwide. The magnitude of these increases can vary within regions according to sociodemographic and urban landscape characteristics. The objectives of this study were to explore this variation and its determinants, and to identify the most heat-vulnerable areas by mapping heat vulnerability.

Methods We conducted a time-stratified case-crossover analysis using daily mortality in the Barcelona metropolitan area during the warm seasons of 1999–2006. Temperature data on the date of death were assigned to each individual, which were assigned to their census tract of residence. Eight census tract-level variables on socioeconomic or built environment characteristics were obtained from the census. Residence surrounding greenness was obtained from satellite data. The relative risk (RR) of mortality after three consecutive hot days (defined as those exceeding the 95th percentile of maximum temperature) was calculated via conditional logistic regression. Effect modification was examined by including interaction terms.

Results Analyses were based on 52 806 deaths. The effect of three consecutive hot days was a 30% increase in all-cause mortality (RR=1.30, 95% CI 1.24 to 1.38). Heterogeneity of this effect was observed across census tracts. The effect of heat on mortality was higher in the census tracts with a large percentage of old buildings (RR=1.21, 95% CI 1.00 to 1.46), manual workers (RR=1.25, 95% CI 0.96 to 1.64) and residents perceiving little surrounding greenness (RR=1.29, 95% CI 1.01 to 1.65). After three consecutive hot days, mortality doubled in the most heat-vulnerable census tracts.

Conclusions Sociodemographic and urban landscape characteristics are associated to mortality risk during heat waves and are useful to build heat vulnerability maps.

  • Temperature
  • Mortality
  • Climate Change
  • Socio-Economic
  • Inequalities

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