Integrating linear and nonlinear models to assess the built environment’s impact on older adults’ behaviors in China

Abstract

China is experiencing rapid population aging. The one contributing factor affecting senior citizens’ lives is the disconnect between the built environment in urban and rural areas and the behavioral preferences of older adults. However, research on the relation between the built environment and the behavior of older individuals has been limited. Thus, this paper uses the most recent health tracking data on factors influencing aging in China released in 2020 (China Senior Health Survey Tracking Survey). Applying traditional regression, least absolute shrinkage and selection operator regression, and two decision tree optimization models from machine learning, a comprehensive comparative study is carried out to investigate the correlation between the built environment and the physical activity, dietary habits, and social interactions of older age groups. The findings reveal that built environment variables most significantly impact physical activity, accounting for 52.525%, followed by social interaction behaviors at 50.202% and dietary intake at 47.991%. Furthermore, the authors identify population density and greenness rate as the built environment factors having considerable effects on the behavior of older adults. Thus, this study establishes a theoretical foundation for developing age-friendly community environments for older adults.