Cause-specific mortality attributable to cold and hot ambient temperatures in Hong Kong: a time-series study, 2006–2016. (June 2020)

• Record Type: Journal Article
• Authors: Liu, Jingwen; Hansen, Alana; Varghese, Blesson; Liu, Zhidong; Tong, Michael; Qiu, Hong; Tian, Linwei; Lau, Kevin Ka-Lun; Ng, Edward; Ren, Chao; Bi, Peng
• Is Part Of: Sustainable cities and society. Volume 57(2020)
• Publication Date: 2020-06
• Subjects: AN attributable number -- AF attributable fraction -- CI confidence interval -- CLRD chronic lower respiratory diseases -- DOW day of the week -- DM diabetes mellitus -- DLNM distributed lag non-linear model -- ICD international classification of diseases -- NO2 nitrogen dioxide -- MBD mental and behavioural disorders -- MMT minimum mortality temperature -- O3 ozone -- OT optimal temperature -- SO2 sulphur dioxide -- PM2.5 fine particulate matters -- RD renal diseases -- RH relative humidity -- RR relative risk; Temperature -- Cause-specific Mortality -- Attributable Risk -- Time-series -- Hong Kong; Sustainable urban development -- Periodicals; Sustainable buildings -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.76
• DOI: 10.1016/j.scs.2020.102131
• Languages: English
• ISSNs: 2210-6707

Abstract

Highlights: There is lack of evidence regarding attributable burden on cause-specific mortality in Hong Kong. Non-optimal ambient temperatures accounted for almost 5% of total mortality. Exposure to extreme temperatures are associated with a greater risk of mortality, but moderate temperature resulted in the greatest burden of deaths. Cold temperatures generally contributed to higher attributable risks of mortality than hot temperatures. Findings are important for local decision making to reduce public health burden due to the varies MMTs and AF of temperature by groups. Abstract: Background: This study aimed to quantify the mortality burden attributable to non-optimal cold and hot conditions from moderate and extreme temperatures in Hong Kong during 2006-2016. Methods: The association between mortality and daily mean temperature was assessed using a distributed lag non-linear model (DLNM) integrated with a quasi-Poisson model. The cumulated effects of cold and hot temperature were firstly quantified. The attributable risks of non-optimal ambient temperature on deaths by cause-specific mortality and age groups were then estimated. Results: A reversed J-shaped relationship was found between temperature and total mortality. The highest increase in risk was at extreme cold, with the highest relative risk (RR) for injuries of 2.18 (95%CI: 1.03-4.62), followed by the respiratory and circulatory system diseases for lag 0-21 days. Cold temperature was associated with a greater burden of death than hot temperature, with attributable fractions (AF) of 4.72% and 0.16%, respectively. Moderate temperatures played a major role in all-cause mortality with AF of 4.25%, and 0.63% for extreme temperature. Conclusions: Most of the temperature-related mortality burden was attributed to moderate weather, suggesting relevant temperature-related preventive strategies and measurements should be implemented to minimize the negative impact of temperatures on population health, particularly for vulnerable sub-populations.