An exploration of temperature metrics for further developing the heat-health weather warning system in Hong Kong

Abstract

Background. The current weather warning system aims to reduce mortality from heat and cold stress but still has room to be improved in terms of incorporating other temperature metrics. The aim of this study is to determine how extreme temperature affects mortality in Hong Kong. Methods. An ecological study was used; daily weather data were subdivided into seven temperature metrics. Daily detrended mortality data were stratified by disease groups and analysed using seven different metrics for temperature. The temperature metrics were then compared. Results. A diurnal temperature range (DTR) of ≥8°C leading to an increase in median mortality of up to 16% and a mean temperature change between neighbouring days of ≥4°C leading to an increase in median mortality of up to 6% were the critical thresholds for excess mortality in Hong Kong. Conclusions. This study reveals that mean net effective temperature, DTR, and temperature change between neighbouring days are effective to predict excess mortality in Hong Kong.

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