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Journal of Public Health
Article . 2019 . Peer-reviewed
License: OUP Standard Publication Reuse
Data sources: Crossref
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The impact of extreme heat events on hospital admissions to the Royal Hobart Hospital

Authors: Kyle M. Gardiner; Kaitlyn E. Watson; Judith A. Singleton; Judith A. Singleton;

The impact of extreme heat events on hospital admissions to the Royal Hobart Hospital

Abstract

Abstract Background Extreme heat (EH) events are increasing in frequency and duration and cause more deaths in Australia than any other extreme weather event. Consequently, EH events lead to an increase in the number of patient presentations to hospitals. Methods Climatic observations for Hobart’s region and Royal Hobart Hospital (RHH) emergency department admissions data were collected retrospectively for the study period of 2003–2010. A distributed lag non-linear model (DLNM) was fitted using a generalized linear model with quasi-Poisson family to obtain adjusted estimates for the relationship between temperature and the relative risk of being admitted to the RHH. Results The model demonstrated that relative to the annual mean temperature of 14°C, the relative risk of being admitted to the RHH for the years 2003–2010 was significantly higher for all temperatures above 27°C (P < 0.05 in all cases). The peak effect upon admission was noted on the same day as the EH event, however, the model suggests that a lag effect exists, increasing the likelihood of admission to the RHH for a further 14 days. Conclusions To relieve the added burden on emergency departments during these events, adaptation strategies adopted by public health organizations could include preventative health initiatives.

Country
Australia
Keywords

public health, Environmental and Occupational Health, Australia, 610, Extreme Heat, 2739 Public Health, 333, Hospitals, Hospitalization, climate change, heatwave, tasmania, Humans, extreme heat events, Emergency Service, Hospital, emergency department admissions, Retrospective Studies

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    26
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
26
Top 10%
Top 10%
Top 10%
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