Multidimensional social exposure clusters and incident multimorbidity in a population-based cohort

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Abstract
Multimorbidity follows a strong social gradient, yet how the co-occurrence of social determinants shapes risk remains poorly understood. Most research examines individual determinants in isolation, potentially obscuring socially patterned subgroups relevant to multimorbidity risk. This study examines the association between multidimensional social exposure profiles (derived from individual- and area-level determinants) and multimorbidity risk. Profiles were derived through unsupervised clustering applied to population-based cohort of Ontario respondents to the Canadian Community Health Survey (2001-2011) and linked area-level Census measures. Chronic disease and subsequent multimorbidity status were identified through linkage to administrative health data until 2022. Sex-stratified Weibull models were used to estimate hazard ratios for the association between multidimensional social exposure and incident multimorbidity. Unsupervised clustering identified six distinct social exposure profiles, with multimorbidity onset differing across profiles and elevated risk observed across multiple patterns of social disadvantage, rather than following a simple graded gradient. In sex-stratified analyses, disadvantage social exposure profiles were associated with an earlier multimorbidity onset among females (adjusted HR: 1.70, 95%CI, 1.18-2.53) and males (adjusted HR: 1.59, 95%CI, 1.20-2.05). These multidimensional social exposure profiles capture population-level social patterning associated with differential multimorbidity risk. These findings have implications for upstream policy aimed at reducing inequities in multimorbidity.
Funding Information
  • CIHR Frederick Banting and Charles Best Canada Graduate Scholarship Doctoral Award (72064776)
  • Canada Research Chair in Population Health Analytics (72074328)
  • the MLTC
  • the Ontario MOH

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