OBJECTIVE: To determine the extent to which depressive symptoms are associated with metabolic risk factors and whether genetic or environmental factors account for this association. METHOD: Twin structural equation modeling was employed to estimate genetic and environmental contributions to the covariation of depressive symptoms, as indexed by the Centers for Epidemiological Studies-Depression Scale, and common variance among blood pressure, body mass index, waist-to-hip ratio, and serum triglycerides and glucose among 87 monozygotic and 86 dizygotic male twin pairs who participated in the NHLBI twin study. RESULTS: Depressive symptoms were associated with individual components of the metabolic syndrome and common variance among the risk factors. Twin structural equation modeling indicated that the associations were attributable to environmental (nongenetic) factors. CONCLUSIONS: These results support the hypothesis that depressive symptoms may increase risk for a pattern of physiological risk consistent with the metabolic syndrome.
OBJECTIVE: To determine the extent to which depressive symptoms are associated with metabolic risk factors and whether genetic or environmental factors account for this association. METHOD: Twin structural equation modeling was employed to estimate genetic and environmental contributions to the covariation of depressive symptoms, as indexed by the Centers for Epidemiological Studies-Depression Scale, and common variance among blood pressure, body mass index, waist-to-hip ratio, and serum triglycerides and glucose among 87 monozygotic and 86 dizygotic male twin pairs who participated in the NHLBI twin study. RESULTS:Depressive symptoms were associated with individual components of the metabolic syndrome and common variance among the risk factors. Twin structural equation modeling indicated that the associations were attributable to environmental (nongenetic) factors. CONCLUSIONS: These results support the hypothesis that depressive symptoms may increase risk for a pattern of physiological risk consistent with the metabolic syndrome.
Authors: Roger S McIntyre; Ka Young Park; Candy W Y Law; Farah Sultan; Amanda Adams; Maria Teresa Lourenco; Aaron K S Lo; Joanna K Soczynska; Hanna Woldeyohannes; Mohammad Alsuwaidan; Jinju Yoon; Sidney H Kennedy Journal: CNS Drugs Date: 2010-09 Impact factor: 5.749
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