Impact of lipid measurements in youth in addition to conventional clinic-based risk factors on predicting preclinical atherosclerosis in adulthood international childhood cardiovascular cohort consortium

Background: Data suggest that the prediction of adult cardiovascular disease using a model comprised entirely of adult nonlaboratory-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 nonlaboratory risk factors in adolescence versus a lipid model based on nonlaboratory risk factors plus lipids for predicting high-risk carotid intima-media thickness (cIMT) in adulthood. Methode: The study comprised 2893 participants 12 to 18 years of age from 4 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 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 (relative risk [95% confidence interval]), male sex (2.7 [2.0-2.6]), prehypertension (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 low-density lipoprotein cholesterol (1.6 [1.2-2.2]), high low-density lipoprotein cholesterol (1.6 [1.1-2.1]), and borderline low high-density lipoprotein cholesterol (1.4 [1.0-1.8]) remained significant predictors of high cIMT (P<0.05). The addition of lipids into the nonlaboratory risk model slightly but significantly improved discrimination in predicting high cIMT compared with nonlaboratory-based risk factors only (C statistics for laboratory-based model 0.717 [95% confidence interval, 0.685-0.748] and for nonlaboratory 0.698 [95% confidence interval, 0.667-0.731]; P=0.02). Concluision: Nonlaboratory-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.