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BioMed Research International
Volume 2014 (2014), Article ID 389853, 13 pages
http://dx.doi.org/10.1155/2014/389853
Research Article

Social and Behavioral Risk Marker Clustering Associated with Biological Risk Factors for Coronary Heart Disease: NHANES 2001–2004

1Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912, USA
2Center for Statistical Sciences, Brown University School of Public Health, Providence, RI 02912, USA
3Department of Biostatistics, Brown University School of Public Health, Providence, RI 02912, USA
4Diabetes Prevention and Control Program, Rhode Island Department of Health, Providence, RI 02912, USA
5International Health Institute, Brown University School of Public Health, Providence, RI 02912, USA
6Center for Population Health & Clinical Epidemiology, Brown University School of Public Health, Providence, RI 02912, USA

Received 30 April 2013; Revised 20 November 2013; Accepted 24 December 2013; Published 25 February 2014

Academic Editor: Kazuhiko Kotani

Copyright © 2014 Nicholas J. Everage et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background. Social and behavioral risk markers (e.g., physical activity, diet, smoking, and socioeconomic position) cluster; however, little is known whether clustering is associated with coronary heart disease (CHD) risk. Objectives were to determine if sociobehavioral clustering is associated with biological CHD risk factors (total cholesterol, HDL cholesterol, systolic blood pressure, body mass index, waist circumference, and diabetes) and whether associations are independent of individual clustering components. Methods. Participants included 4,305 males and 4,673 females aged ≥20 years from NHANES 2001–2004. Sociobehavioral Risk Marker Index (SRI) included a summary score of physical activity, fruit/vegetable consumption, smoking, and educational attainment. Regression analyses evaluated associations of SRI with aforementioned biological CHD risk factors. Receiver operator curve analyses assessed independent predictive ability of SRI. Results. Healthful clustering (SRI = 0) was associated with improved biological CHD risk factor levels in 5 of 6 risk factors in females and 2 of 6 risk factors in males. Adding SRI to models containing age, race, and individual SRI components did not improve C-statistics. Conclusions. Findings suggest that healthful sociobehavioral risk marker clustering is associated with favorable CHD risk factor levels, particularly in females. These findings should inform social ecological interventions that consider health impacts of addressing social and behavioral risk factors.