Dynamic Bayesian network analysis of the social determinants of mental health.

ABSTRACT: Mental disorders contribute substantially to the global burden of disease, accounting for up to 16.5% of all years of healthy life lost due to disability and premature mortality. Epidemiological evidence indicates that mental health problems are associated with a diverse range of demographic, social, and economic factors, referred to collectively as social determinants; however, the causal mechanisms underlying these associations are widely recognized to be complex and are only incompletely understood. Here, we use recently developed structure learning methods for Bayesian networks and high-quality panel data from Australia to construct a provisional dynamic network model of the causal dependencies connecting a broad selection of social determinants and mental health. This provisional caus

SUBMITTER: Skinner A 

PROVIDER: S-EPMC12281507 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature