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Background:  Social isolation has been identified as a substantial health concern in aging populations, associated with adverse chronic disease outcomes and health inequalities; however, little is known about the interconnections between social capital, diabetes management, and hospital burdens. This study aimed to assess the role of community belonging with the risk of potentially avoidable hospitalization among aging adults living with diabetes in Canada.   Methods:  The study leveraged a novel resource available through Statistics Canada's Social Data Linkage Environment: the Canadian Community Health Survey linked to administrative health records from the hospital Discharge Abstract Database. A population-representative sample of 13,580 community-dwelling adults aged 45 and over with diabetes was identified. Multiple logistic regression was used to assess the association of individuals' sense of community belonging with the risk of diabetes-related hospitalization over the period 2006–2012.   Results:  Most (69.9%) adults with diabetes reported a strong sense of belonging to their local community. Those who reported weak community belonging were significantly more likely to have been hospitalized for diabetes (χ 2  = 13.82;  p  < 0.05). The association between weak community attachment and increased risk of diabetes hospitalization remained significant [adjusted OR: 1.80 (95%CI: 1.12–2.90)] after controlling for age, education, and other sociodemographic and behavioral factors.   Conclusion:  The COVID-19 pandemic has resurfaced attention to the need to better address social capital and diabetes care in public health strategies. While the causal pathways are unclear, this national study highlighted that deficits in social attachments may place adults with diabetes at greater risk of acute complications leading to hospitalization.

frontiers in public health

Reduced Risk of Hospitalization With Stronger Community Belonging Among Aging Canadians Living With Diabetes: Findings From Linked Survey and Administrative Data