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

作者：Francesco Sera, Ben Armstrong, Aurelio Tobı́as, Ana M. Vicedo‐Cabrera, Christofer Åström, Michelle L. Bell, Bing‐Yu Chen, Micheline de Sousa Zanotti Stagliorio Coêlho, Patricia Matus Correa, César De la Cruz Valencia, Trần Ngọc Đăng, Magali Hurtado‐Díaz, Dung Do Van, Bertil Forsberg, Yue Leon Guo, Yuming Guo, Masahiro Hashizume, Yasushi Honda, Carmen Íñiguez, Jouni J. K. Jaakkola, Haidong Kan, Ho Kim, Éric Lavigne, Paola Michelozzi, Nicolás Valdés Ortega, Samuel Osorio, Mathilde Pascal, Martina S. Ragettli, Niilo Ryti, Paulo Hilário Nascimento Saldiva, Joel Schwartz, Matteo Scortichini, Xerxes Seposo, Shilu Tong, Antonella Zanobetti, Antonio Gasparrini · 发表于：International Journal of Epidemiology · 年份：2019 · DOI：10.1093/ije/dyz008 · 被引用次数：285 · 研究领域：Climate Change and Health Impacts、Urban Heat Island Mitigation、Thermoregulation and physiological responses

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 decreas...