Abstract

Objectives

Climate change has intensified heatwaves, posing significant health risks to older adults; yet, their impact on health-related quality of life (HRQoL) in China’s aging population remains underexplored. This study investigates the impact of heatwaves on HRQoL among older adults using the EuroQol 5-Dimension 5-Level (EQ-5D-5L).

Methods

A cohort of community-dwelling Chinese adults aged ≥60 years were followed up from spring to fall in 2023. Univariate regression and restricted cubic spline models analyzed linear and nonlinear relationships between meteorological/demographic factors and EQ-5D-5L outcomes (utility values and EuroQol Visual Analog Scale [EQ VAS] scores). Machine learning models identified key predictors of heatwave-related HRQoL changes.

Results

Among the 627 participants, both EQ-5D-5L utility values and EQ VAS scores followed a rise-and-fall pattern, initially increasing during the early heatwave period (T1) but subsequently declining significantly during the peak heatwave period (T2) (P .05). The Support Vector Machine model outperformed the other machine learning models, identifying body mass index as the most influential variable in predicting the EQ-5D-5L utility values, followed by age, preretirement occupation, education level, and daily average relative humidity.

Conclusions

Heatwaves dynamically affect HRQoL in older adults in China, with an initial increase followed by a significant decline. Older, underweight, and less-educated adults are more vulnerable to the adverse impacts of heatwaves on HRQoL.