Estimating Risks of Heat Strain by Age and Sex: A Population-Level Simulation Model

Individuals living in hot climates face health risks from hyperthermia due to excessive heat. Heat strain is influenced by weather exposure and by individual characteristics such as age, sex, body size, and occupation. To explore the population-level drivers of heat strain, we developed a simulation...

Full description

Bibliographic Details
Main Authors: Kathryn Glass, Peter W. Tait, Elizabeth G. Hanna, Keith Dear
Format: Article
Language:English
Published: MDPI AG 2015-05-01
Series:International Journal of Environmental Research and Public Health
Subjects:
Online Access:http://www.mdpi.com/1660-4601/12/5/5241
id doaj-f0a50b4190c54795a7fb45eebb44aaf8
record_format Article
spelling doaj-f0a50b4190c54795a7fb45eebb44aaf82020-11-25T00:03:24ZengMDPI AGInternational Journal of Environmental Research and Public Health1660-46012015-05-011255241525510.3390/ijerph120505241ijerph120505241Estimating Risks of Heat Strain by Age and Sex: A Population-Level Simulation ModelKathryn Glass0Peter W. Tait1Elizabeth G. Hanna2Keith Dear3National Centre for Epidemiology and Population Health, Australian National University, Canberra 2601, AustraliaNational Centre for Epidemiology and Population Health, Australian National University, Canberra 2601, AustraliaNational Centre for Epidemiology and Population Health, Australian National University, Canberra 2601, AustraliaDuke Global Health Institute, Duke Kunshan University, Kunshan 215316, ChinaIndividuals living in hot climates face health risks from hyperthermia due to excessive heat. Heat strain is influenced by weather exposure and by individual characteristics such as age, sex, body size, and occupation. To explore the population-level drivers of heat strain, we developed a simulation model that scales up individual risks of heat storage (estimated using Myrup and Morgan’s man model “MANMO”) to a large population. Using Australian weather data, we identify high-risk weather conditions together with individual characteristics that increase the risk of heat stress under these conditions. The model identifies elevated risks in children and the elderly, with females aged 75 and older those most likely to experience heat strain. Risk of heat strain in males does not increase as rapidly with age, but is greatest on hot days with high solar radiation. Although cloudy days are less dangerous for the wider population, older women still have an elevated risk of heat strain on hot cloudy days or when indoors during high temperatures. Simulation models provide a valuable method for exploring population level risks of heat strain, and a tool for evaluating public health and other government policy interventions.http://www.mdpi.com/1660-4601/12/5/5241heat storagesimulation modelpopulation-levelMANMOheat strain
collection DOAJ
language English
format Article
sources DOAJ
author Kathryn Glass
Peter W. Tait
Elizabeth G. Hanna
Keith Dear
spellingShingle Kathryn Glass
Peter W. Tait
Elizabeth G. Hanna
Keith Dear
Estimating Risks of Heat Strain by Age and Sex: A Population-Level Simulation Model
International Journal of Environmental Research and Public Health
heat storage
simulation model
population-level
MANMO
heat strain
author_facet Kathryn Glass
Peter W. Tait
Elizabeth G. Hanna
Keith Dear
author_sort Kathryn Glass
title Estimating Risks of Heat Strain by Age and Sex: A Population-Level Simulation Model
title_short Estimating Risks of Heat Strain by Age and Sex: A Population-Level Simulation Model
title_full Estimating Risks of Heat Strain by Age and Sex: A Population-Level Simulation Model
title_fullStr Estimating Risks of Heat Strain by Age and Sex: A Population-Level Simulation Model
title_full_unstemmed Estimating Risks of Heat Strain by Age and Sex: A Population-Level Simulation Model
title_sort estimating risks of heat strain by age and sex: a population-level simulation model
publisher MDPI AG
series International Journal of Environmental Research and Public Health
issn 1660-4601
publishDate 2015-05-01
description Individuals living in hot climates face health risks from hyperthermia due to excessive heat. Heat strain is influenced by weather exposure and by individual characteristics such as age, sex, body size, and occupation. To explore the population-level drivers of heat strain, we developed a simulation model that scales up individual risks of heat storage (estimated using Myrup and Morgan’s man model “MANMO”) to a large population. Using Australian weather data, we identify high-risk weather conditions together with individual characteristics that increase the risk of heat stress under these conditions. The model identifies elevated risks in children and the elderly, with females aged 75 and older those most likely to experience heat strain. Risk of heat strain in males does not increase as rapidly with age, but is greatest on hot days with high solar radiation. Although cloudy days are less dangerous for the wider population, older women still have an elevated risk of heat strain on hot cloudy days or when indoors during high temperatures. Simulation models provide a valuable method for exploring population level risks of heat strain, and a tool for evaluating public health and other government policy interventions.
topic heat storage
simulation model
population-level
MANMO
heat strain
url http://www.mdpi.com/1660-4601/12/5/5241
work_keys_str_mv AT kathrynglass estimatingrisksofheatstrainbyageandsexapopulationlevelsimulationmodel
AT peterwtait estimatingrisksofheatstrainbyageandsexapopulationlevelsimulationmodel
AT elizabethghanna estimatingrisksofheatstrainbyageandsexapopulationlevelsimulationmodel
AT keithdear estimatingrisksofheatstrainbyageandsexapopulationlevelsimulationmodel
_version_ 1725434161281368064