Please use this identifier to cite or link to this item:http://hdl.handle.net/20.500.12105/8386
Dietary Patterns and Cardiovascular Risk Factors in Spanish Adolescents: A Cross-Sectional Analysis of the SI! Program for Health Promotion in Secondary Schools
Bodega, Patricia CNIC | Fernandez-Alvira, Juan Miguel CNIC | Santos-Beneit, Gloria CNIC | de Cos-Gandoy, Amaya CNIC | Fernandez-Jimenez, Rodrigo CNIC | Moreno, Luis Alberto | de Miguel, Mercedes CNIC | Carral, Vanesa | Orrit, Xavier CNIC | Carvajal, Isabel | Storniolo, Carolina E | Tresserra-Rimbau, Anna | Doménech, Mónica | Estruch, Ramón | Lamuela-Raventós, Rosa María | Fuster, Valentin CNIC
Nutrients. 2019; 11(10):E2297
Previous studies on the association between dietary habits and cardiovascular risk factors (CVRF) in adolescents have generated conflicting results. The aim of this study was to describe dietary patterns (DP) in a large sample of Spanish adolescents and to assess their cross-sectional relationship with CVRF. In total, 1324 adolescents aged 12.5 ± 0.4 years (51.6% boys) from 24 secondary schools completed a self-reported food frequency questionnaire. DPs were derived by cluster analysis and principal component analysis (PCA). Anthropometric measurements, blood pressure, lipid profile, and glucose levels were assessed. Linear mixed models were applied to estimate the association between DPs and CVRF. Three DP-related clusters were obtained: Processed (29.2%); Traditional (39.1%); and Healthy (31.7%). Analogous patterns were obtained in the PCA. No overall differences in CVRF were observed between clusters except for z-BMI values, total cholesterol, and non-HDL cholesterol, with the Processed cluster showing the lowest mean values. However, differences were small. In conclusion, the overall association between DPs, as assessed by two different methods, and most analyzed CVRF was weak and not clinically relevant in a large sample of adolescents. Prospective analysis may help to disentangle the direction of these associations.
Adolescents | Cardiovascular health | Cluster analysis | Dietary patterns | Principal components analysis
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