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Sci Total Environ. 2019 Feb 15;651(Pt 2):2558-2565. doi: 10.1016/j.scitotenv.2018.10.186. Epub 2018 Oct 15.

Impacts of heat, cold, and temperature variability on mortality in Australia, 2000-2009.

Author information

1
School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia.
2
Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Anhui, China.
3
School of Public Health and Social Work, Queensland University of Technology, Queensland, Australia; School of Public Health, Institute of Environment and Human Health, Anhui Medical University, Anhui, China; Shanghai Children's Medical Centre, Shanghai Jiao-Tong University, Shanghai, China.
4
School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia. Electronic address: w2.hu@qut.edu.au.

Abstract

OBJECTIVES:

Evidence is limited on the relative contribution of different temperature exposures (i.e., heat, cold and significant temperature variability) to mortality. This study aims to examine mortality risk and associated mortality burden from heat, cold, and temperature variability in Australia.

METHODS:

We collected daily time-series data on all-cause deaths and weather variables for the five most populous Australian cities (Sydney, Melbourne, Brisbane, Adelaide, and Perth), from 2000 to 2009. Temperature variability was calculated from the standard deviation of hourly temperatures between two adjacent days. Three-stage analysis was used. We firstly used quasi-Poisson regression models to model the associations of mortality with heat (mean temperature) during the warm season, with cold (mean temperature) during the cold season, and with temperature variability all year round, while controlling for long-term trend and seasonality, day of week, and population change over time. We then estimated the effects of different non-optimum temperatures using the simplified log-linear regression model. Finally, we computed and compared the fraction (%) of deaths attributable to different non-optimum temperatures.

RESULTS:

The greatest percentage increase in mortality was for cold (2.0%, 95% confidence interval (CI): 1.4%, 2.6%), followed by heat (1.2%, 95% CI: 0.7%, 1.7%), and temperature variability (0.5%, 95% CI: 0.3%, 0.7%). There was no clear temporal pattern in mortality risk associated with any temperature exposure in Australia. Heat, cold and temperature variability together resulted in 42,414 deaths during the study period, accounting for about 6.0% of all deaths. Most of attributable deaths were due to cold (61.4%), and noticeably, contribution from temperature variability (28.0%) was greater than that from heat (10.6%).

CONCLUSIONS:

Exposure to either cold or heat or a large variation in temperature was associated with increased mortality risk in Australia, but population adaptation appeared to have not occurred in most cities studied. Most of the temperature-induced deaths were attributable to cold, and contributions from temperature variability were greater than that from heat. Our findings highlight that, in addition to heat and cold, temperature variability needs to be considered in assessing and projecting the health impacts of climate change.

KEYWORDS:

Climate; Disease burden; Health; Relative risk; Temperature change

PMID:
30340191
DOI:
10.1016/j.scitotenv.2018.10.186
[Indexed for MEDLINE]

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