Assessment of heat stress contributing factors in the indoor environment among vulnerable populations in Klang Valley using principal component analysis (PCA)
Rising global temperatures can lead to heat waves, which in turn can pose health risks to the community. However, a notable gap remains in highlighting the primary contributing factors that amplify heat-health risk among vulnerable populations. This study aims to evaluate the precedence of heat stre...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Research
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/112006/1/45.%20Scientific%20Report.pdf http://psasir.upm.edu.my/id/eprint/112006/ https://www.nature.com/articles/s41598-024-67110-w |
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| Summary: | Rising global temperatures can lead to heat waves, which in turn can pose health risks to the community. However, a notable gap remains in highlighting the primary contributing factors that amplify heat-health risk among vulnerable populations. This study aims to evaluate the precedence of heat stress contributing factors in urban and rural vulnerable populations living in hot and humid tropical regions. A comparative cross-sectional study was conducted, involving 108 respondents from urban and rural areas in Klang Valley, Malaysia, using a face-to-face interview and a validated questionnaire. Data was analyzed using the principal component analysis, categorizing factors into
exposure, sensitivity, and adaptive capacity indicators. In urban areas, five principal components (PCs) explained 64.3% of variability, with primary factors being sensitivity (health morbidity, medicine intake, increased age), adaptive capacity (outdoor occupation type, lack of ceiling, longer residency
duration), and exposure (lower ceiling height, increased building age). In rural, five PCs explained 71.5% of variability, with primary factors being exposure (lack of ceiling, high thermal conductivity roof material, increased building age, shorter residency duration), sensitivity (health morbidity, medicine intake, increased age), and adaptive capacity (female, non-smoking, higher BMI). The order of heat-health vulnerability indicators was sensitivity > adaptive capacity > exposure for urban areas, and exposure > sensitivity > adaptive capacity for rural areas. This study demonstrated a different pattern of leading contributors to heat stress between urban and rural vulnerable populations. |
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