medwireNews: US researchers have identified five social risk profiles, incorporating economic, neighborhood, psychological, and behavioral risks, that are associated with clinical outcomes in people with type 2 diabetes and could be used to tailor interventions to specific groups.
“Social determinants of health are conditions in which people are born, grow, live, work, and age and that shape their health over the life course,” explain Leonard Egede (University at Buffalo, New York) and co-authors in JAMA Network Open. “These factors have been noted to account for between 30% to 55% of health outcomes, and are shaped by upstream factors, as well as adverse social conditions, commonly referred to as social risk.”
Egede et al say that although targeting social risk factors can improve health outcomes, it is unclear how best to group social risks in a way that can inform the most effective interventions.
To investigate, they used latent profile analysis, a method that identifies subgroups with common characteristics that could benefit from a similar intervention.
In all, 615 people with type 2 diabetes (mean age 61 years, 62% men) completed validated questionnaires that collected information on 19 social risk factors from five domains of social determinants of health: socioeconomic, neighborhood and built environment, education, food security, and social factors (isolation and discrimination).
Participants also answered questions that measured five psychological risk factors, including diabetes distress, and two behavioral risk factors, namely smoking and substance use.
The researchers report that their method identified five unique clusters of social risk factors.
Group 1 (36% of the sample) had the lowest social risk overall; group 2 (34%) had low economic risk, but high neighborhood risk; group 3 (6%) had high economic and neighborhood risk; group 4 (14%) had high psychological and behavioral risk; and group 5 (8%) had the highest overall risk, with high risk in the economic, neighborhood, psychological, and behavioral risk categories.
Using group 2 as a reference category, Egede and team found that individuals in groups 4 and 5 had significantly higher glycated hemoglobin levels and significantly worse mental health-related quality of life.
“This finding supports the important role psychological health plays in outcomes for adults with diabetes but highlights that a compounded burden of economic and neighborhood risks in addition to psychological and behavioral risk may require a different approach to improve health outcomes,” the researchers remark.
In addition, individuals in group 3 had significantly higher blood pressure than those in group 2, while people in group 1 had significantly higher mental health-related quality of life than group 2 individuals. There were no statistically significant differences in physical health-related quality of life among any of the groups.
Egede and co-authors conclude: “An important implication of this work is the use of social risk profiles to identify interventions that will be most effective in improving health outcomes for specific subgroups of adults with type 2 diabetes.”
They add: “Rather than approaching individuals with a one-size-fits-all approach, these findings suggest interventions that target different domains of risk may need to be assessed with populations that identify these areas of risk as particularly problematic for them.”
In an accompanying comment, Brita Roy, from NYU Grossman School of Medicine in New York, USA, says that the identification of the five social risk profiles is “an important first step in defining additional, clinically relevant information on diabetes and cardiometabolic risk that can be used at the individual and population levels.”
She writes: “For example, these social risk clusters could be used to inform point-of-care clinical risk scores, as well as more holistic population health program development or community health improvements on the right combination of factors. The latter is advantageous, because intervening on a single social risk factor alone is likely to be insufficient to effectively lower the risk of poor diabetes outcomes.”
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JAMA Netw Open 2024; 7: e2425996
JAMA Netw Open 2024; 7: e2425957
