Literature DB >> 28712114

Comparative evaluation of human heat stress indices on selected hospital admissions in Sydney, Australia.

James Goldie1,2, Lisa Alexander1,2, Sophie C Lewis2,3, Steven Sherwood1,2.   

Abstract

OBJECTIVE: To find appropriate regression model specifications for counts of the daily hospital admissions of a Sydney cohort and determine which human heat stress indices best improve the models' fit.
METHODS: We built parent models of eight daily counts of admission records using weather station observations, census population estimates and public holiday data. We added heat stress indices; models with lower Akaike Information Criterion scores were judged a better fit.
RESULTS: Five of the eight parent models demonstrated adequate fit. Daily maximum Simplified Wet Bulb Globe Temperature (sWBGT) consistently improved fit more than most other indices; temperature and heatwave indices also modelled some health outcomes well. Humidity and heat-humidity indices better fit counts of patients who died following admission.
CONCLUSIONS: Maximum sWBGT is an ideal measure of heat stress for these types of Sydney hospital admissions. Simple temperature indices are a good fallback where a narrower range of conditions is investigated. Implications for public health: This study confirms the importance of selecting appropriate heat stress indices for modelling. Epidemiologists projecting Sydney hospital admissions should use maximum sWBGT as a common measure of heat stress. Health organisations interested in short-range forecasting may prefer simple temperature indices.
© 2017 The Authors.

Entities:  

Keywords:  New South Wales; heatwave; humidity; morbidity; temperature

Mesh:

Year:  2017        PMID: 28712114     DOI: 10.1111/1753-6405.12692

Source DB:  PubMed          Journal:  Aust N Z J Public Health        ISSN: 1326-0200            Impact factor:   2.939


  2 in total

1.  Changes in relative fit of human heat stress indices to cardiovascular, respiratory, and renal hospitalizations across five Australian urban populations.

Authors:  James Goldie; Lisa Alexander; Sophie C Lewis; Steven C Sherwood; Hilary Bambrick
Journal:  Int J Biometeorol       Date:  2017-09-30       Impact factor: 3.787

2.  Using the excess heat factor to indicate heatwave-related urinary disease: a case study in Adelaide, South Australia.

Authors:  Matthew Borg; Monika Nitschke; Susan Williams; Stephen McDonald; John Nairn; Peng Bi
Journal:  Int J Biometeorol       Date:  2019-01-28       Impact factor: 3.787

  2 in total

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