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

Abstract

Background and aimsCurrent 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 resultsRaine 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. ConclusionCluster 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.