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Rev Diabet Stud, 2017, 14(2-3):279-294 DOI 10.1900/RDS.2017.14.279

Association Between Socioeconomic Determinants and the Metabolic Syndrome in the German Health Interview and Examination Survey for Adults (DEGS1) – A Mediation Analysis

Diego Montano

Department of Psychosomatic Medicine and Psychotherapy, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany

Manuscript submitted March 28, 2017; resubmitted June 23, 2017; accepted August 1, 2017.

Keywords: metabolic syndrome, social epidemiology, diabetes, hypertension, obesity, multivariate regression


BACKGROUND: Metabolic syndrome and different socioeconomic characteristics including education and occupational status have been found to be associated in previous research. Nonetheless, theoretical models defining core variables and causal processes accounting for these associations are lacking. OBJECTIVES: The main objectives of the present investigation are (1) to present a theoretical model integrating physiological, biochemical, and psychosocial factors determining metabolic syndrome prevalence and (2) to corroborate the hypothesis that socioeconomic determinants are (partially) mediated by health-related behaviors, health risks, and dietary habits. METHODS: The research hypothesis is tested with cross-sectional data from the German Health Interview and Examination Survey for Adults (DEGS1) conducted from 2008 to 2011 (n = 7,987) by means of multivariate regression models which appropriately take into account the stochastic dependence of metabolic syndrome components. RESULTS: The results suggest that the metabolic syndrome is less frequent among individuals with a higher educational level and those who have a partner. These associations may point to protective effects of social support, self-efficacy, and other socio-psychological constructs in relation to metabolic syndrome incidence. Furthermore, frequent consumption of wine, muesli, fruits, and raw vegetables are associated with lower prevalence rates of metabolic syndrome components. The associations of occupational status, income, and employment are partially mediated by health-related behavior, physiological and psychosocial factors, and dietary habits. Sensitivity analyses have suggested that even small changes in the distribution of potential risk and protective factors may reduce the prevalence of metabolic syndrome components. CONCLUSIONS: Healthrelated behavior (smoking, physical activity) and physiological and psychosocial factors mediate the association between socioeconomic characteristics and metabolic syndrome prevalence. However, metabolic syndrome components were much less frequent among individuals with a higher educational level, higher income and occupational status, and those having a life partner.

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