4.8 Article

What individual and neighbourhood-level factors increase the risk of heat-related mortality? A case-crossover study of over 185,000 deaths in London using high-resolution climate datasets

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ENVIRONMENT INTERNATIONAL
卷 134, 期 -, 页码 -

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.envint.2019.105292

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资金

  1. National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Environmental Change and Health at the London School of Hygiene and Tropical Medicine
  2. Public Health England (PHE)
  3. UK Met Office - Wellcome Trust for the 'Complex Urban Systems for Sustainability and Health' (CUSSH) project [205207/Z/16/Z, 209387/Z/17/Z]
  4. Wellcome Trust [205207/Z/16/Z] Funding Source: Wellcome Trust
  5. EPSRC [EP/P022405/1] Funding Source: UKRI
  6. MRC [MR/K019341/1] Funding Source: UKRI

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Objective: Management of the natural and built environments can help reduce the health impacts of climate change. This is particularly relevant in large cities where urban heat island makes cities warmer than the surrounding areas. We investigate how urban vegetation, housing characteristics and socio-economic factors modify the association between heat exposure and mortality in a large urban area. Methods: We linked 185,397 death records from the Greater London area during May-Sept 2007-2016 to a high resolution daily temperature dataset. We then applied conditional logistic regression within a case-crossover design to estimate the odds of death from heat exposure by individual (age, sex) and local area factors: land-use type, natural environment (vegetation index, tree cover, domestic garden), built environment (indoor temperature, housing type, lone occupancy) and socio-economic factors (deprivation, English language, level of employment and prevalence of ill-health). Results: Temperatures were higher in neighbourhoods with lower levels of urban vegetation and with higher levels of income deprivation, social-rented housing, and non-native English speakers. Heat-related mortality increased with temperature increase (Odds Ratio (OR), 95% CI=1.039, 1.036-1.043 per 1 degrees C temperature increase). Vegetation cover showed the greatest modification effect, for example the odds of heat-related mortality in quartiles with the highest and lowest tree cover were OR, 95%CI 1.033, 1.026-1.039 and 1.043, 1.037-1.050 respectively. None of the socio-economic variables were a significant modifier of heat-related mortality. Conclusions: We demonstrate that urban vegetation can modify the mortality risk associated with heat exposure. These findings make an important contribution towards informing city-level climate change adaptation and mitigation policies.

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