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As the population ages, the thermal environment indoors for the elderly has garnered extensive attention. However, current research on thermal comfort for the elderly is not comprehensive, particularly for rural elderly individuals who experience unique thermal perceptions and adaptation behaviors due to physical changes. Moreover, metabolic rates, which are often overlooked in thermal comfort studies for the elderly, play a crucial role. A year-long survey of thermal comfort was conducted in the rural areas of Weihai, a coastal city in China's cold region, collecting 203 questionnaires. Three different values of metabolic rates (recommended values, estimated values, and values calculated using Basal Metabolic Rate and Physical Activity Ratio) were analyzed. The results demonstrate that the Basal Metabolic Rate and Physical Activity Ratio method provides predictions of thermal sensation that more closely align with actual thermal sensations. The adaptive coefficient of the aPMV model was found to be −0.38 in colder environments and 0.272 in warmer ones. Additionally, using PMV regression, TSV regression, and Griffiths' method, we calculated the local elderly's comfort temperatures to be 18.9 °C (15.43–22.57 °C), 19.3 °C (15.16–22.75 °C), and 21.63 °C (21.34–23.49 °C) respectively. This study introduces a straightforward method for calculating metabolic rates in elderly individuals, offering new insights for research on thermal comfort in the elderly and expanding the database for thermal comfort studies. It lays a foundation for future design and standardization of housing for rural elderly populations. • A year-long study in rural Weihai defines the comfort temperature for the elderly. • Three different values of metabolic rates were analyzed. • Developed the adaptive thermal comfort models for rural elderly populations. • The adaptive thermal comfort model coefficients are −0.38 (cold) and 0.272 (warm).
Zhang et al. (Wed,) studied this question.