4.2 Article

Modeling Metabolic Syndrome and Its Association with Cognition: The Northern Manhattan Study

期刊

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CAMBRIDGE UNIV PRESS
DOI: 10.1017/S1355617714000861

关键词

Cognition; Dementia; Hypertension; Aging; Metabolic syndrome; Cardiovascular; Vascular markers

资金

  1. NINDS Grant [R37 NS029993]

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Metabolic syndrome (MetS) is a clustering of vascular risk factors and is associated with increased risk of cardiovascular disease. Less is known about the relationship between MetS and cognition. We examined component vascular risk factors of MetS as correlates of different cognitive domains. The Northern Manhattan Study (NOMAS) includes 1290 stroke-free participants from a largely Hispanic multi-ethnic urban community. We used structural equation modeling (SEM) to model latent variables of MetS, assessed at baseline and an average of 10 years later, at which time participants also underwent a full cognitive battery. The two four-factor models, of the metabolic syndrome (blood pressure, lipid levels, obesity, and fasting glucose) and of cognition (language, executive function, psychomotor, and memory), were each well supported (CFI = 0.97 and CFI = 0.95, respectively). When the two models were combined, the correlation between metabolic syndrome and cognition was -.31. Among the metabolic syndrome components, only blood pressure uniquely predicted all four cognitive domains. After adjusting for age, gender, race/ethnicity, education, smoking, alcohol, and risk factor treatment variables, blood pressure remained a significant correlate of all domains except memory. In this stroke-free race/ethnically diverse community-based cohort, MetS was associated with cognitive function suggesting that MetS and its components may be important predictors of cognitive outcomes. After adjusting for sociodemographic and vascular risk factors, blood pressure was the strongest correlate of cognitive performance. Findings suggest MetS, and in particular blood pressure, may represent markers of vascular or neurodegenerative damage in aging populations.

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