Uncovering actionable cardiovascular risk subgroups in type 2 Diabetes: A latent class analysis
Authors' conclusion
Diverse lifestyle and psychosocial CVD risk factor patterns impact CVD outcomes in individuals with type 2 diabetes, emphasizing the necessity of a whole-person CVD prevention tailored to the person's needs.
Study context
- Population
- Individuals with T2D
- Comparison
- Low risk vs Mobility related risk vs Psychosocial risk
- Outcome
- CVD risk factor classes (3-class model superior)
Main finding
As reported in the abstract
| Group | Value | Probability of limitations in mobility | Probability of not meeting exercise norm | Probability of being lonely | Probability of anxiety and depression |
|---|---|---|---|---|---|
| Low risk | 71.2 % | ||||
| Mobility related risk | 19.3 % | 0.90 | 0.89 | ||
| Psychosocial risk | 9.5 % | 0.49 | 0.56 |
Value
Low risk71.2 %
Mobility related risk19.3 %
Psychosocial risk9.5 %
Probability of limitations in mobility
Low risk— not stated in the abstract
Mobility related risk0.90
Psychosocial risk— not stated in the abstract
Probability of not meeting exercise norm
Low risk— not stated in the abstract
Mobility related risk0.89
Psychosocial risk— not stated in the abstract
Probability of being lonely
Low risk— not stated in the abstract
Mobility related risk— not stated in the abstract
Psychosocial risk0.49
Probability of anxiety and depression
Low risk— not stated in the abstract
Mobility related risk— not stated in the abstract
Psychosocial risk0.56
Further findings
Predictors of risk class membership
- Strong predictors (OR ≥ 2.00): female gender, non-western immigrant status, lower education, financial difficulties, unfit for work and/or prior HF
Cardiovascular disease (CVD) incidence (cardiology care and/or stroke diagnosis) · 3 years
- Lower in 'low risk' class vs the risk classes
Original publication
Uncovering actionable cardiovascular risk subgroups in type 2 Diabetes: A latent class analysis. Diabetes Res Clin Pract. Published 19 March 2025. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →