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SEDENTARY BEHAVIOR IMPACTS METABOLIC SYNDROME SEVERITY MORE IN OLDER ADULTS AND IS NOT ATTENUATED BY PHYSICAL ACTIVITY

Abstract

Anthony Campitelli1, Megan Jones1, Ray Urbina1, & Michelle Gray1

1University of Arkansas, Fayetteville, Arkansas

Metabolic syndrome (MetSyn) is a condition that is defined by underlying metabolic dysfunction that manifests as hypertension, dyslipidemia, insulin resistance, and central adiposity. MetSyn is associated with several negative health outcomes including cardiovascular disease, diabetes, proinflammatory state, and reproductive disorders. As a clustering of metabolic conditions, MetSyn cannot be measured directly, and its diagnosis typically requires dysfunction across at least three measures of the related conditions but the severity of MetSyn can only be measured through latent construct modeling. Sedentary behavior (SB) is believed to be one of the root causes of MetSyn and several studies have suggested that physical activity (PA) does not mitigate its negative impact, however, the effects of SB and PA across the lifespan are unknown.

PURPOSE: The purpose of this study was to determine how SB and PA affect MetSyn severity across the lifespan. METHODS: Data were compiled from the National Health and Nutrition Examination Study from 2007-2018. MetSyn was measured using factor analysis with fasting blood glucose (GLU), systolic blood pressure (SBP), plasma triglycerides (TRG), plasma HDL cholesterol (HDL), and waist circumference (WC) as indicators. A unique model was fit for each of three age cohorts: young adults (18-39 years of age, n = 5186), middle-aged adults (40-64 years of age, n = 6019), and older adults (>65 years of age, n = 2454). For each model, a structural model was fit regressing MetSyn severity on SB and PA. RESULTS: All measurement models and structural models were over-identified in accordance with the t-rule. Measurement models and structural models including only SB demonstrated good model fit (CFI > .94, TLI > .90, RMSEA < .057, SRMR < .044). The regressed effect of MetSyn on SB increased with age (β = .033, .102, and .182 for young, middle-aged, and older adults, respectively). MetSyn regressed on PA indicated a very small effect size (β < .001) and models including PA generally had poor data model fit. CONCLUSION: The relationship between SB and MetSyn strengthens with age such that SB in younger adults leads to almost no increase in MetSyn risk but represents a substantial risk in older adults. PA has little impact on MetSyn severity and does not attenuate the relationship between SB and MetSyn.

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