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BACKGROUND: Hong Kong, a major city in China, has one of the world's highest income inequalities and one of the world's highest average increases in urban ambient temperatures. Heat-related mortality in urban areas may vary with acclimatisation and population characteristics. This study examines how the effect of temperature on mortality is associated with sociodemographic characteristics at an intracity level in Hong Kong, China, during the warm season. METHODS: Data from the Hong Kong Observatory, Census and Statistics Department, Environmental Protection Department and government general outpatient clinics during 1998-2006 were used to construct generalised additive (Poisson) models to examine the temperature mortality relationship in Hong Kong. Adjusted for seasonality, long-term trends, pollutants and other potential confounders, effect modification of the warm season temperature-mortality association by demographic, socioeconomic factors and urban design were examined. RESULTS: An average 1°C increase in daily mean temperature above 28.2°C was associated with an estimated 1.8% increase in mortality. Heat-related mortality varied with sociodemographic characteristics: women, men less than 75 years old, people living in low socioeconomic districts, those with unknown residence and married people were more vulnerable. Non-cancer-related causes such as cardiovascular and respiratory infection-related deaths were more sensitive to high temperature effects. CONCLUSION: Public health protection strategies that target vulnerable population subgroups during periods of elevated temperature should be considered.

Original publication

DOI

10.1136/jech.2008.085167

Type

Journal article

Journal

J Epidemiol Community Health

Publication Date

04/2012

Volume

66

Pages

322 - 327

Keywords

Adolescent, Adult, Aged, Aged, 80 and over, Air Pollution, Child, Child, Preschool, China, Female, Hong Kong, Hot Temperature, Humans, Infant, Infant, Newborn, Male, Middle Aged, Mortality, Poisson Distribution, Residence Characteristics, Seasons, Sex Distribution, Socioeconomic Factors, Urban Population