Identifying young adults at high risk of cardiometabolic disease using cluster analysis and the Framingham 30-yr risk score.

Background And Aims: Current strategies to reduce cardiovascular disease (CVD) risk in young adults are largely limited to those at extremes of risk. In cohort studies we have shown cluster analysis identified a large sub-group of adolescents with multiple risk factors. This study examined if individuals classified at 'high-risk' by cluster analysis could also be identified by their Framingham risk scores.

Methods And Results: Raine Study data at 17- (n = 1048) and 20-years (n = 1120) identified high- and low-risk groups by cluster analysis using continuous measures of systolic BP, BMI, triglycerides and insulin resistance. We assessed:- CVD risk at 20-years using the Framingham 30 yr-risk-score in the high- and low-risk clusters, and cluster stability from adolescence to adulthood. Cluster analysis at 17- and 20-years identified a high-risk group comprising, 17.9% and 21.3%, respectively of the cohort. In contrast, only 1.2% and 3.4%, respectively, met the metabolic syndrome criteria, all of whom were within the high-risk cluster. Compared with the low-risk cluster, Framingham scores of the high-risk cluster were elevated in males (9.4%; 99%CI 8.3, 10.6 vs 6.0%; 99%CI 5.7, 6.2) and females (4.9%; 99%CI 4.4, 5.4 vs 3.2%; 99%CI 3.0, 3.3) (both P < 0.0001). A score >8 for males and >4 for females identified those at high CVD risk with 99% confidence.

Conclusion: Cluster analysis using multiple risk factors identified ∼20% of young adults at high CVD risk. Application of our Framingham 30 yr-risk cut-offs to individuals allows identification of more young people with multiple risk factors for CVD than conventional metabolic syndrome criteria.