Affiliations: [a] Department of Psychology, University of Kansas, Lawrence, KS, USA | [b] Gerontology Center, Lifespan Institute, University of Kansas, Lawrence, KS, USA | [c] Department of Physical Therapy and Rehabilitation Science, University of Kansas Medical Center, Lawrence, KS, USA | [d] Department of Neurology, University of Kansas Medical Center, Lawrence, KS, USA | [e] Alzheimer's Disease Center, University of Kansas, Lawrence, KS, USA
Correspondence:
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Correspondence to: Amber S. Watts, 1415 Jayhawk Blvd, Fraser Hall 417, Lawrence, KS 66045, USA. Tel.: +1 785 864 2604; Fax: +1 785 864 5696; E-mail: amberwatts@ku.edu.
Abstract: Metabolic syndrome (MetS) is a cluster of risk factors (i.e., abdominal obesity, hypertension, dyslipidemia, glucose and insulin dysregulation) that is associated with cardiovascular disease, diabetes, and dementia. Recent studies addressing the association of MetS with cognitive performance and risk for dementia report mixed results. An important step in clarifying these conflicting results is determining whether cognition is influenced by the effects of individual MetS components versus the additive effects of multiple components. We assessed the effect of MetS on cognitive performance and decline over two years in 75 cases of early Alzheimer's disease (AD) and 73 healthy older adult controls in the Brain Aging Project. Using factor analytic techniques, we compared the effect of a combined MetS factor to the effect of individual MetS components on change in attention, verbal memory, and mental status. In healthy controls, a combined MetS factor did not significantly predict cognitive performance, though higher insulin predicted poorer cognitive performance outcomes. In the AD group, higher scores on a combined MetS factor predicted better cognitive outcomes. Our findings suggest that MetS does not have the same association with cognitive decline in healthy older adults and those with early AD. We suggest that individual MetS components should not be evaluated in isolation and that careful methodological approaches are needed to understand the timing and non-linear relationships among these components over time.
