TY - JOUR
T1 - How urban characteristics affect vulnerability to heat and cold
T2 - A multi-country analysis
AU - Sera, Francesco
AU - Armstrong, Ben
AU - Tobias, Aurelio
AU - Vicedo-Cabrera, Ana Maria
AU - Åström, Christofer
AU - Bell, Michelle L.
AU - Chen, Bing Yu
AU - De Sousa Zanotti Stagliorio Coelho, Micheline
AU - Correa, Patricia Matus
AU - Cruz, Julio Cesar
AU - Dang, Tran Ngoc
AU - Hurtado-Diaz, Magali
AU - Do Van, Dung
AU - Forsberg, Bertil
AU - Guo, Yue Leon
AU - Guo, Yuming
AU - Hashizume, Masahiro
AU - Honda, Yasushi
AU - Iñiguez, Carmen
AU - Jaakkola, Jouni J.K.
AU - Kan, Haidong
AU - Kim, Ho
AU - Lavigne, Eric
AU - Michelozzi, Paola
AU - Ortega, Nicolas Valdes
AU - Osorio, Samuel
AU - Pascal, Mathilde
AU - Ragettli, Martina S.
AU - Ryti, Niilo R.I.
AU - Saldiva, Paulo Hilario Nascimento
AU - Schwartz, Joel
AU - Scortichini, Matteo
AU - Seposo, Xerxes
AU - Tong, Shilu
AU - Zanobetti, Antonella
AU - Gasparrini, Antonio
N1 - Funding Information:
This work was primarily supported by the Medical Research Council—UK (MR/M022625/1). The following individual grants also supported this work: Y.G. was supported by the Career Development Fellowship of Australian National Health and Medical Research Council (APP1107107); A.T. was supported by the Ministry of Education of Spain (PRX17/00705); J.J.K.J. and N.R.I.R. were supported by the Research Council for Health, Academy of Finland (266314); Y.L.G. was supported by the National Health Research Institutes of Taiwan (NHRI-EM-106-SP03); M.L.B. was supported by a US Environmental Protection Agency Assistance Agreement awarded to Yale University (83587101).
Publisher Copyright:
© 2019 The Author(s).
PY - 2019/8/1
Y1 - 2019/8/1
N2 - 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.
AB - 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.
KW - Temperature
KW - cities
KW - climate
KW - epidemiology
KW - heat
KW - mortality
KW - cities
KW - climate
KW - epidemiology
KW - heat
KW - mortality
KW - Temperature
UR - http://www.scopus.com/inward/record.url?scp=85067299967&partnerID=8YFLogxK
U2 - 10.1093/ije/dyz008
DO - 10.1093/ije/dyz008
M3 - Article
C2 - 30815699
AN - SCOPUS:85067299967
SN - 0300-5771
VL - 48
SP - 1101
EP - 1112
JO - International Journal of Epidemiology
JF - International Journal of Epidemiology
IS - 4
M1 - dyz008
ER -