Repeated exposure to heat waves over the years can accelerate aging, particularly among manual workers, rural residents, and people in communities with fewer air conditioning units, according to a study published in Nature Climate Change.
Heat waves are increasing in frequency as a consequence of climate change and may have significant impacts on public health. Although earlier studies have demonstrated the negative effects of heat waves on age-related health conditions, especially among older people, they have primarily focused on short-term exposure to prolonged heat.
Understanding how prolonged heat exposure over several years can help explain the potential long-term impact of heat waves on human aging.
Cui Guo and colleagues analyzed data from 24,922 adults, with an average biological age of 46.3 years, in Taiwan, to assess how heat waves might influence aging. The authors define age acceleration as the difference between biological age and chronological age, and they evaluated its associations with exposure to heat waves.
After analyzing physical exam data between 2008 and 2022, the authors found that, with each increase in the interquartile range of cumulative exposure to heat waves—the difference between the third and first quartile levels—there was an associated increase in age acceleration of 0.023 to 0.031 years.
Additionally, the study found that although participants seemed to adapt to heat wave conditions over the 15-year period, the harmful health effects did not disappear. Guo and colleagues also identified that manual workers, rural residents, and people in communities with fewer air conditioning units were more susceptible to the impacts of heat waves on aging.
The conclusions underscore the need for policies that reduce environmental inequalities and improve resilience to heat waves, especially among vulnerable groups, guiding targeted protections and efficient allocation of health resources.
The authors note that additional analyses are needed in more diverse groups and that this analysis does not include potentially relevant variables, such as time spent outdoors, the home environment, or patterns of air conditioner use.
