Modelling personal temperature exposure using household and outdoor temperature and questionnaire data: Implications
Xi Xia1, Ka Hung Chan2, Yue Niu3
1Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China; Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi'an, China; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; School of Public Health, Shaanxi University of Chinese Medicine, Xi'an, China; The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
Environment International
|October 14, 2024
Summary
Personal temperature exposure, crucial for health, differs significantly from outdoor readings, especially in winter. Accurate personal temperature prediction models are essential to avoid misclassification in epidemiological studies.
Area of Science:
- Environmental Health
- Epidemiology
- Biometeorology
Background:
- Non-optimal temperature is a major global disease risk factor.
- Epidemiological studies often rely on outdoor temperature, leading to potential personal exposure misclassification.
- Understanding personal temperature exposure is vital for accurate health risk assessment.
Purpose of the Study:
- To measure personal, household, and outdoor temperatures across different microenvironments.
- To develop and validate models for predicting personal temperature exposure.
- To examine the relationship between personal and outdoor temperatures and heart rate.
Main Methods:
- The CKB-Air study involved 477 participants in China, collecting data over two seasons.
- Multivariable linear regression (MLR) and random forest (RF) models were used to identify predictors of personal temperature.
- Generalized additive mixed effect models analyzed associations between temperature exposure and heart rate.
Main Results:
- Personal and outdoor temperatures showed seasonal variations, with greater differences in winter.
- Household temperatures were strong predictors of personal temperature in winter, unlike outdoor temperatures.
- Developed MLR and RF models demonstrated satisfactory prediction accuracy for personal exposure (R² summer: 0.92; R² winter: 0.68-0.70).
- U-shaped associations were observed between personal temperature exposure and heart rate.
Conclusions:
- Personal temperature exposure differs significantly from outdoor measurements, particularly in winter.
- Prediction models incorporating household and outdoor temperatures, along with questionnaire data, offer accurate personal exposure estimates.
- Relying solely on outdoor temperature in epidemiological studies may lead to exposure misclassification and flawed findings.
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