Uncovering heterogeneous cardiometabolic risk profiles in US adults: the role of social and behavioral determinants of health
Authors' conclusion
Self-reported SBDH combined with metabolic factors can be used to classify adults into subgroups with distinct cardiometabolic risk profiles. This approach may help identify individuals who would benefit from screening for diabetes and pre-diabetes and potentially suggest effective prevention strategies.
Study context
- Population
- US adults without prior diabetes diagnosis, National Health and Nutrition Examination Survey (NHANES) 1999–2018
- Participants
- 38,476 adults
- Exposure
- Cardiometabolic risk clusters identified by social and behavioral determinants of health (SBDH) and metabolic factors
- Outcome
- Undiagnosed diabetes and pre-diabetes by cluster
Methodological detailsk-prototypes clustering, logistic regression
- K-prototypes clustering
- Logistic regression
Main finding
As reported in the abstract
Undiagnosed diabetes
Each group vs cluster 2Adjusted odds ratio (95% CI)
Cluster 3
14.9(10.9–20.2)
Cluster 1
3.7(2.8–4.8)
Observational data: associations, not effects.
Further findings
| Outcome | OR (CI) | |
|---|---|---|
| Pre-diabetesCluster 1vs Cluster 2 | 1.8 (1.6–1.9) | |
| Pre-diabetesCluster 3vs Cluster 2 | 2.1 (1.8–2.4) | |
| 0.512Odds ratio (log scale) |
Pre-diabetes
- Race/ethnicity modified the relationship between subgroups and pre-diabetes risk
Original publication
Uncovering heterogeneous cardiometabolic risk profiles in US adults: the role of social and behavioral determinants of health. BMJ Open Diabetes Res Care. Published 12 September 2023. doi:10.
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