Analyzing the Relationship between Health Damage Caused by Heat Wave and Socioeconomic Factors

Kim, Tae Ho; Baek, Jong In; Ban, Yong

doi:10.14251/crisisonomy.2016.12.5.67

Cited by 10 publications

(1 citation statement)

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“…Heatwaves cause heat-related illnesses, such as allergies, asthma, exhaustion, fainting, and dehydration [6]; they also increase the incidence of various diseases by weakening the body's thermoregulatory function [7]. Numerous studies have related heatwave damage to vulnerable populations; for example, in an Australian study, it was reported that a considerable number of elderly persons died as a result of heatwaves compared with other age groups [8].…”

Section: Introductionmentioning

confidence: 99%

Spatial Relationship between Heat Illness Incidence and Heat Vulnerability in Gurye and Sunchang, South Korea, 2018

Kwon

2023

IJERPH

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Heatwaves, along with their affiliated illnesses and mortalities, are increasing in frequency and severity under climate change. Spatial analyses at the level of census output areas can produce detailed maps of heatwave risk factors and potential correlated damages, thus contributing to practical policies to reduce the risk of heatwave illnesses. This study analyzed the 2018 summer heatwave in Gurye and Sunchang counties in South Korea. To compare damages and analyze the detailed causes of heatwave vulnerability, spatial autocorrelation analyses were conducted, incorporating weather, environmental, personal, and disease factors. Gurye and Sunchang, although similar in demographics and region, exhibited large differences in heatwave damage specifically in the number of heat-related illness cases. In addition, exposure data were constructed at the census output area level by calculating the shadow pattern, sky view factor, and mean radiant temperature, revealing a higher risk in Sunchang. Spatial autocorrelation analyses revealed that the factors most highly correlated with heatwave damage were hazard factors, in the case of Gurye, and vulnerability factors, in the case of Sunchang. Accordingly, it was concluded that regional vulnerability factors were better distinguished at the finer scale of the census output area and when detailed and diversified weather factors were incorporated.

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Section: Introductionmentioning

confidence: 99%

Spatial Relationship between Heat Illness Incidence and Heat Vulnerability in Gurye and Sunchang, South Korea, 2018

Kwon

2023

IJERPH

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Deep Learning-Based analytic framework using comprehensive urbanization index for heat vulnerability assessment in urban areas

Kim

2024

Expert Systems with Applications

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An analytical framework for assessing heat vulnerability in urban thermal environmental planning

Kim,

Kim

2024

Urban Climate

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Analyzing the Relationship between Health Damage Caused by Heat Wave and Socioeconomic Factors

Cited by 10 publications

References 0 publications

Spatial Relationship between Heat Illness Incidence and Heat Vulnerability in Gurye and Sunchang, South Korea, 2018

Spatial Relationship between Heat Illness Incidence and Heat Vulnerability in Gurye and Sunchang, South Korea, 2018

Deep Learning-Based analytic framework using comprehensive urbanization index for heat vulnerability assessment in urban areas

An analytical framework for assessing heat vulnerability in urban thermal environmental planning

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