Literature DB >> 30815699

How urban characteristics affect vulnerability to heat and cold: a multi-country analysis.

Francesco Sera1, Ben Armstrong1, Aurelio Tobias2, Ana Maria Vicedo-Cabrera1, Christofer Åström3, Michelle L Bell4, Bing-Yu Chen5, Micheline de Sousa Zanotti Stagliorio Coelho6, Patricia Matus Correa7, Julio Cesar Cruz8, Tran Ngoc Dang9,10, Magali Hurtado-Diaz8, Dung Do Van9, Bertil Forsberg3, Yue Leon Guo5,11, Yuming Guo12,13, Masahiro Hashizume14, Yasushi Honda15, Carmen Iñiguez16, Jouni J K Jaakkola17,18, Haidong Kan19, Ho Kim20, Eric Lavigne21,22, Paola Michelozzi23, Nicolas Valdes Ortega7, Samuel Osorio24, Mathilde Pascal25, Martina S Ragettli26,27, Niilo R I Ryti17,18, Paulo Hilario Nascimento Saldiva6, Joel Schwartz28, Matteo Scortichini23, Xerxes Seposo29, Shilu Tong30,31,32, Antonella Zanobetti28, Antonio Gasparrini1.   

Abstract

BACKGROUND: The health burden associated with temperature is expected to increase due to a warming climate. Populations living in cities are likely to be particularly at risk, but the role of urban characteristics in modifying the direct effects of temperature on health is still unclear. In this contribution, we used a multi-country dataset to study effect modification of temperature-mortality relationships by a range of city-specific indicators.
METHODS: We collected ambient temperature and mortality daily time-series data for 340 cities in 22 countries, in periods between 1985 and 2014. Standardized measures of demographic, socio-economic, infrastructural and environmental indicators were derived from the Organisation for Economic Co-operation and Development (OECD) Regional and Metropolitan Database. We used distributed lag non-linear and multivariate meta-regression models to estimate fractions of mortality attributable to heat and cold (AF%) in each city, and to evaluate the effect modification of each indicator across cities.
RESULTS: Heat- and cold-related deaths amounted to 0.54% (95% confidence interval: 0.49 to 0.58%) and 6.05% (5.59 to 6.36%) of total deaths, respectively. Several city indicators modify the effect of heat, with a higher mortality impact associated with increases in population density, fine particles (PM2.5), gross domestic product (GDP) and Gini index (a measure of income inequality), whereas higher levels of green spaces were linked with a decreased effect of heat.
CONCLUSIONS: This represents the largest study to date assessing the effect modification of temperature-mortality relationships. Evidence from this study can inform public-health interventions and urban planning under various climate-change and urban-development scenarios.
© The Author(s) 2019; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Keywords:  Temperature; cities; climate; epidemiology; heat; mortality

Mesh:

Year:  2019        PMID: 30815699     DOI: 10.1093/ije/dyz008

Source DB:  PubMed          Journal:  Int J Epidemiol        ISSN: 0300-5771            Impact factor:   7.196


  18 in total

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6.  Seasonality of suicide: a multi-country multi-community observational study.

Authors:  J Yu; D Yang; Y Kim; M Hashizume; A Gasparrini; B Armstrong; Y Honda; A Tobias; F Sera; A M Vicedo-Cabrera; H Kim; C Íñiguez; E Lavigne; M S Ragettli; N Scovronick; F Acquaotta; B Chen; Y L Guo; M de Sousa Zanotti Stagliori Coelho; P Saldiva; A Zanobetti; J Schwartz; M L Bell; M Diaz; C De la Cruz Valencia; I Holobâcă; S Fratianni; Y Chung
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7.  Role of temperature, influenza and other local characteristics in seasonality of mortality: a population-based time-series study in Japan.

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10.  The role of cities in reducing the cardiovascular impacts of environmental pollution in low- and middle-income countries.

Authors:  Jill Baumgartner; Michael Brauer; Majid Ezzati
Journal:  BMC Med       Date:  2020-02-24       Impact factor: 8.775

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