Format

Send to

Choose Destination
Int J Epidemiol. 2019 Feb 27. pii: dyz008. doi: 10.1093/ije/dyz008. [Epub ahead of print]

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

Author information

1
Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK.
2
Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC), Barcelona, Spain.
3
Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
4
School of Forestry and Environmental Studies, Yale University, New Haven, CT, USA.
5
National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan.
6
Institute of Advanced Studies, University of São Paulo, São Paulo, Brazil.
7
Department of Public Health, Universidad de los Andes, Santiago, Chile.
8
Department of Environmental Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico.
9
Department of Environmental Health, Faculty of Public Health, University of Medicine and Pharmacy of Ho Chi Minh City, Ho Chi Minh City, Vietnam.
10
Institute of Research and Development, Duy Tan University, Da Nang, Vietnam.
11
Environmental and Occupational Medicine, National Taiwan University (NTU) and NTU Hospital, Taipei, Taiwan.
12
Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
13
Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
14
Department of Pediatric Infectious Diseases, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan.
15
Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan.
16
Department of Statistics and Computational Research, Environmental Health Research Joint Reseaech Unit FISABIO-UV-UJI CIBERESP, University of València, València, Spain.
17
Medical Research Center Oulu (MRC Oulu), Oulu University Hospital and University of Oulu, Oulu, Finland.
18
Center for Environmental and Respiratory Health Research (CERH), University of Oulu, Oulu, Finland.
19
Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China.
20
Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea.
21
School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Canada.
22
Air Health Science Division, Health Canada, Ottawa, Canada.
23
Department of Epidemiology, Lazio Regional Health Service, Rome, Italy.
24
Department of Environmental Health, University of São Paulo, São Paulo, Brazil.
25
Santé Publique France, Department of Environmental Health, French National Public Health Agency, Saint Maurice, France.
26
Swiss Tropical and Public Health Institute, Basel, Switzerland.
27
University of Basel, Basel, Switzerland.
28
Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
29
Department of Environmental Engineering, Graduate School of Engineering, Kyoto University, Kyoto, Japan.
30
Shanghai Children's Medical Centre, Shanghai Jiao-Tong University, Shanghai, China.
31
School of Public Health and Institute of Environment and Human Health, Anhui Medical University, Hefei, China.
32
School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia.

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.

KEYWORDS:

Temperature; cities; climate; epidemiology; heat; mortality

PMID:
30815699
DOI:
10.1093/ije/dyz008

Supplemental Content

Full text links

Icon for Silverchair Information Systems
Loading ...
Support Center