Author:
Wen Bo,Wu Yao,Guo Yuming,Li Shanshan
Abstract
Abstract
Background
Temperature variability (TV) is associated with increased mortality risks. However, the independent impacts of interday and intraday are still unknown.
Methods
We proposed a new method to decompose TV into interday TV and intraday TV through algebra derivation. Intraday TV was defined as the weighted average standard deviation (SD) of minimum temperature and maximum temperature on each day. Interday TV was defined as the weighted SD of daily mean temperatures during the exposure period. We then performed an illustrative analysis using data on daily mortality and temperature in France in 2019–2021.
Results
The novel interday and intraday TV indices were good proxies for existing indicators, inlcluding diurnal temperature range (DTR) and temperature change between neighbouring days (TCN). In the illustrative analyses, interday and intraday TVs showed differentiated mortality risks. Mortality burden related to TV was mainly explained by the intraday component, accounting for an attributable fraction (AF) of 1.81% (95% CI: 0.64%, 2.97%) of total mortality, more than twice the AF of interday TV (0.86%, 95% CI: 0.47%, 1.24%).
Conclusions
This study proposed a novel method for identifying and isolating the different components of temperature variability and offered a comprehensive way to investigate their health impacts.
Funder
China Scholarship Council
National Health and Medical Research Council
Publisher
Springer Science and Business Media LLC
Subject
Health Informatics,Epidemiology
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