• Biopsychosocial Model of Metabolic Syndrome among U.S. Adults

      Saylor, Jennifer; Friedmann, Erika (2011)
      Background: The Metabolic Syndrome (MetS) is a cluster of medical disorders (obesity, hypertension, dyslipidemia, and insulin/resistance/glucose intolerance) that characteristically occur together in individuals. The prevalence of MetS continues to increase in the U.S. and increases the risk of type 2 diabetes, cardiovascular disease (CVD), and mortality. Little research uses a theoretical model to identify direct or indirect contributions to MetS and predictors to MetS. Identifying the factors that influence MetS in a national sample is necessary to understand targets for intervention to prevent the MetS and its sequelae. Purpose: This study tested a hypothesized conceptual model of the biopsychosocial factors associated with MetS in adults using a representative sample. Methods: A secondary data analysis was conducted using the National Health and Nutrition Examination Survey (NHANES) 2007-2008 data from non-pregnant participants who were 20-80 years old and completed the questionnaire and medical examination with fasting laboratory data. The sample of 2,583 adults represented 212 million non-institutionalized civilian Americans living in the U.S. Path analysis was conducted to test the biopsychosocial model of MetS. Complex samples logistic regression models (CSLR) were utilized to examine the direct and indirect contributions of biomedical (age), biosocial (gender, race, education, income, and marital status), and psychosocial factors (depressive symptoms, diet, physical activity, smoking status, and sleep) to MetS. Results: Of the study population, 29% met the criteria for MetS and 95% had at least one component of MetS. The hypothesized model fit the nationally representative data. The parsimonious model with age, gender, race, education, income, depressive symptoms, physical activity, smoking, and the interaction between age and physical activity explained 25.2% of the variance in the presence of MetS. Mediating effects among the biosocial and psychosocial factors help explain their relationship with MetS. Conclusion: The study supported the hypothesized model and the contributions of biopsychosocial factors to MetS. The study indicated that certain demographic groups were vulnerable to MetS. More studies are needed to examine factors associated with MetS than were from the hypothesized model. Prospective studies are needed to improve psychosocial status and to prevent/reverse MetS.