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Circulation. 2018 Mar 20;137(12):1246-1255. doi: 10.1161/CIRCULATIONAHA.117.029726. Epub 2017 Nov 23.

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.

Author information

1
Research Center of Applied and Preventive Cardiovascular Medicine (J.K., O.T.R., C.G.M.) jkkosk@utu.fi.
2
Heart Center (J.K.).
3
Department of Medicine (M.J., J.S.A.V.), University of Turku, Finland.
4
Division of Medicine (M.J., J.S.A.V.).
5
George Institute, University of Oxford, United Kingdom (T.D.).
6
Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia (T.D., A.V., C.G.M.).
7
Centre for Research in Mathematics, School of Computing, Engineering and Mathematics, Western Sydney University, Australia (R.T.).
8
Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (L.B., G.S.B.).
9
Murdoch Children's Research Institute, The Royal Children's Hospital and University of Melbourne, Australia (M.A.S.).
10
Department of Epidemiology, College of Public Health, University of Iowa, Iowa City (T.L.B.).
11
Department of Pediatrics, Division of Biostatistics and Epidemiology (J.G.W.).
12
Department of Medicine, University of Cincinnati, OH (J.G.W.).
13
Department of Pediatrics, Division of Cardiology (E.M.U.), Cincinnati Children's Hospital Medical Center and University of Cincinnati, OH.
14
Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC (R.P.).
15
Department of Pediatrics, University of Tampere School of Medicine and Tampere University Hospital, Finland (N.H.-K.).
16
Department of Pediatrics (A.S., J.S.).
17
Division of Epidemiology and Community Health (D.J.), University of Minnesota, Minneapolis.
18
Department of Pediatrics, Children's Hospital Colorado, University of Colorado School of Medicine, Aurora (S.D.).
19
Research Center of Applied and Preventive Cardiovascular Medicine (J.K., O.T.R., C.G.M.).
20
Department of Clinical Physiology (O.T.R.), Turku University Hospital, Finland.

Abstract

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.

METHODS:

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).

CONCLUSIONS:

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.

KEYWORDS:

intima-media thickness; lipids; risk prediction

PMID:
29170152
PMCID:
PMC5860965
[Available on 2019-03-20]
DOI:
10.1161/CIRCULATIONAHA.117.029726

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