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...
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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 |
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