Conventional Cardiovascular Risk Factors and Metabolic Syndrome in Predicting Carotid Intima-Media Thickness Progression in Young Adults

Author:

Koskinen Juha1,Kähönen Mika1,Viikari Jorma S.A.1,Taittonen Leena1,Laitinen Tomi1,Rönnemaa Tapani1,Lehtimäki Terho1,Hutri-Kähönen Nina1,Pietikäinen Matti1,Jokinen Eero1,Helenius Hans1,Mattsson Noora1,Raitakari Olli T.1,Juonala Markus1

Affiliation:

1. From the Research Center of Applied and Preventive Cardiovascular Medicine (J.K., N.M., O.T.R., M.J.) and the Departments of Clinical Physiology (O.T.R.), Biostatistics (H.H.), and Medicine (J.S.A.V., T.R., M.J.) University of Turku, Turku; Departments of Clinical Physiology (M.K.), Clinical Chemistry (T. Lehtimäki), and Pediatrics (N.H.-K.), University of Tampere and Tampere University Hospital, Tampere; Department of Pediatrics, University of Oulu, Oulu (L.T.); Vaasa Central Hospital, Vaasa (L.T....

Abstract

Background— Conventional risk factors and metabolic syndrome (MetS) are cross-sectionally associated with subclinical atherosclerosis in young adults. We evaluated the relations of conventional risk factors and MetS to the 6-year progression of carotid intima-media thickness (IMT) in a population of young adults. Results and Methods— The study included 1809 subjects (aged 32±5 years) who had IMT measured in 2001 and 2007. Risk factor measurements included low-density lipoprotein cholesterol, body mass index, C-reactive protein, smoking, and family history of coronary disease in addition to MetS components. We used European Group for the Study of Insulin Resistance, revised National Cholesterol Education Program, and International Diabetes Federation definitions to diagnose MetS in 2001. Waist circumference ( P <0.0001), low-density lipoprotein cholesterol ( P =0.01), and insulin ( P =0.003) were directly associated with IMT progression in a multivariable model adjusted for age, sex, and baseline IMT (model R 2 =24%). When the MetS/European Group for the Study of Insulin Resistance definition was included in the model, it was directly associated with IMT progression ( P =0.03), but its inclusion did not improve the model’s predictive value. IMT increased 79±7 μm (mean±SEM) in subjects with MetS according to the MetS/European Group for the Study of Insulin Resistance definition and 42±2 μm in subjects without MetS ( P <0.0001). In addition, the number of MetS components was linearly associated with IMT progression ( P <0.0001). Similar results were seen with MetS/revised National Cholesterol Education Program and MetS/International Diabetes Federation definitions. Conclusions— Obesity, high low-density lipoprotein cholesterol, and high insulin level predicted IMT progression in young adults. All MetS definitions identified young adults with accelerated IMT progression, but we found no evidence that MetS would predict IMT progression more than expected from the sum of its risk components.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Physiology (medical),Cardiology and Cardiovascular Medicine

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