Mapping environmental determinants of aging in place through network analysis

As populations age globally, creating supportive environments for aging in place becomes increasingly critical. However, existing research typically examines environmental dimensions and their associations with aging outcomes independently, overlooking how features interact across levels to collectively shape the lived experiences of older adults. To address this limitation, this study employed network analysis to examine the multilevel contributions of environmental features to aging-in-place experiences. We interviewed 308 long-term older residents in Taipei, assessing 31 environmental experience features across housing, neighborhood, and community levels. Gaussian graphical models and centrality analysis were employed to estimate pairwise partial correlations and identify the most influential and bridging features. The network revealed complex environmental connections, with community-level environmental quality showing the highest centrality. Four factors served as multilevel bridges: community safety, environmental maintenance, community vitality, and historical-cultural atmosphere. Among these, community safety showed the strongest cross-level connectivity. Our findings enhance traditional factor analysis, a dimension-reduction approach, by uncovering feature interconnections and cross-level interactions that advance aging-in-place theory. While the network reveals correlational relationships, highly central features emerge as critical leverage points. These features provide empirical direction for strategic interventions and guide future causal investigations to enhance supportive aging-in-place environments.