BackgroundHong 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.MethodsData 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.ResultsAn 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.ConclusionPublic health protection strategies that target vulnerable population subgroups during periods of elevated temperature should be considered.
The negative impact of extreme temperatures on health is well-established. Individual help-seeking behavior, however, may mitigate the extent of morbidity and mortality during elevated temperatures. This study examines individual help-seeking behavior during periods of elevated temperatures among a Chinese population. Help-seeking patterns and factors that influence behavior will be identified so that vulnerable subgroups may be targeted for health protection during heat crises. A retrospective time-series Poisson generalized additive model analysis, using meteorological data of Hong Kong Observatory and routine emergency help call data from The Hong Kong Senior Citizen Home Safety Association during warm seasons (June–September) 1998–2007, was conducted. A “U”-shaped association was found between daily emergency calls and daily temperature. About 49% of calls were for explicit health-related reasons including dizziness, shortness of breath, and general pain. The associate with maximum temperature was statistically significant (p = 0.034) with the threshold temperature at which the frequency of health-related calls started to increase being around 30–32°C. Mean daily relative humidity (RH) also had a significant U-shaped association with daily emergency health-related calls with call frequency beginning to increase with RH greater than 70–74% (10–25% of the RH distribution). Call frequency among females appeared to be more sensitive to high temperatures, with a threshold between 28.5°C and 30.5°C while calls among males were more sensitive to cold temperatures (threshold 31.5–33.5°C). Results indicate differences in community help-seeking behavior at elevated temperatures. Potential programs or community outreach services might be developed to protect vulnerable subgroups from the adverse impact of elevated temperatures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.