Impact of lipid measurements in youth in addition to conventional clinic-based risk factors on predicting preclinical atherosclerosis in adulthood: The International Childhood Cardiovascular Cohort (i3C) Consortium

Background: Data suggest that the prediction of adult cardiovascular disease using a model comprised entirely of adult non-laboratory based risk factors is equivalent to an approach that additionally incorporates adult lipid measures. We assessed and compared the utility of a risk model based solely on non-laboratory risk factors in adolescence vs. a lipid model based on non-laboratory risk factors + lipids for predicting high-risk carotid intima-media thickness (cIMT) in adulthood.

Methods: The study comprised 2,893 participants aged 12-18 years from four longitudinal cohort studies from the United States (Bogalusa Heart Study and the Insulin Study), Australia (Childhood Determinants of Adult Health Study) and Finland (The Cardiovascular Risk in Young Finns Study) and followed into adulthood when cIMT was measured (mean follow-up 23.4 years). Overweight status was defined according to the Cole classification. Hypertension was defined according to the Fourth Report on High Blood Pressure in Children and Adolescents from the National High Blood Pressure Education Program. High-risk plasma lipid levels were defined according to the National Cholesterol Education Program (NCEP) Expert Panel on Cholesterol Levels in Children. High cIMT was defined as a study-specific value ≥ 90th percentile. Age-and sex were included in each model.

Results: In univariate models all risk factors except for borderline high-and high triglycerides in adolescence were associated with high cIMT in adulthood. In multivariable models (RR [95% CI]), male sex (2.7 [2.0-2.6]), pre-hypertension (1.4 [1.0-1.9]), hypertension (1.9 [1.3-2.9]), overweight (2.0 [1.4-2.9]), obesity (3.7 [2.0-7.0]), borderline high LDL-cholesterol (1.6 [1.2-2.2]), high LDL-cholesterol (1.6 [1.1-2.1]) and borderline low HDL-cholesterol (1.4 [1.0-1.8]) remained significant predictors of high cIMT (P always < 0.05). The addition of lipids into the non-laboratory risk model slightly, but significantly, improved discrimination in predicting high cIMT compared with non-laboratory-based risk factors only (c-statistics for laboratory-based model 0.717 [95%CI 0.685-0.748] and for non-laboratory 0.698 [95%CI 0.667-0.731], P = 0.02).

Conclusions: Non-laboratory-based risk factors and lipids measured in adolescence independently predicted preclinical atherosclerosis in young adulthood. The addition of lipid measurements to traditional clinic based risk factor assessment provided a statistically significant but clinically modest improvement on adolescent prediction of high cIMT in adulthood.