The health effect of built environment alterations across 2,806 countries in whole China

Population mobility has become more popular with urbanization. Based on social adaptation and adaptive evolution theories, the alteration of the built environment (BE) caused by mobility can have a significant health impact on public. Here, based on the social adaptation theory, we established a series of hierarchical linear models (HLMs) to investigate how the BE affects self-reported health (SRH) among mobile population across 2806 counties in China, through the mediating effects of BE alteration, social integration, and health care services. Group heterogeneity, which referred to variations in these mediating effects across different demographic groups, was further studied. Overall, we find that the people who out-flowed from counties with lower residential greenery and industrial land proportion are more susceptible to SRH due to BE alteration, accounting for a partial mediation of 17.36% and a completed mediation effect, respectively. An increase in residential greenery would impede the ability of the mobile population to access health care services, thereby reducing SRH, with a partial mediating effect accounting for 6.67%. Additionally, a typical suppression effect of health care services is observed in the mechanism by which road network density affected the SRH of mobile population. Furthermore, different demographic groups exhibit heterogeneity in the adaptation process, with females and low-income group showing stronger mediating dependencies rather than direct environmental exposure. These findings revealed improvements in the BE do not always yield health benefits and enhance our understanding the efficacy of the BE alterations on SRH and provide empirical evidence for proposing targeted planning policies aimed at improving the well-being of public given the increasing of people mobility across China and globally. • Built environment affects self-reported health in mobile populations across 2,826 Chinese counties. • Uses hierarchical linear models to analyze mediators: environment alteration, social integration, and health care services. • Built environment alterations significantly mediate health effects. • Females and low-income groups are more vulnerable to negative health effects from environmental alterations.