Metabolic Syndrome Predicts Mobility Decline in a Community-Based Sample of Older Adults

• Published in: Journal of the American Geriatrics Society (JAGS) Vol. 54; no. 3; pp. 502 - 506
• Main Authors: Blazer, Dan G., Hybels, Celia F., Fillenbaum, Gerda G.
• Format: Journal Article
• Language: English
• Published: Malden, USA Blackwell Publishing Inc 01.03.2006; Blackwell; Wiley Subscription Services, Inc
• Subjects: Activities of Daily Living; Aged; Biological and medical sciences; Community living; Disease Progression; Female; Follow-Up Studies; functional status; General aspects; Geriatrics; Humans; Male; Medical sciences; Metabolic diseases; Metabolic syndrome; Metabolic Syndrome - epidemiology; Metabolic Syndrome - physiopathology; Miscellaneous; Mobility; Mobility Limitation; older adults; Older people; Other metabolic disorders; Prognosis; Prospective Studies; Regression analysis; Risk Factors; Rural areas; Urban areas; Walking - physiology; North Carolina; Endocrinopathy; Human; Prediction; Mobility; Cardiovascular disease; Metabolic diseases; metabolic syndrome; Gerontology; functional status; X Syndrome; older adults; Predictive factor; Elderly; Community; Geriatrics
• ISSN: 0002-8614; 1532-5415
• DOI: 10.1111/j.1532-5415.2005.00607.x

OBJECTIVES: To determine whether metabolic syndrome is an independent predictor of decline in mobility in an elderly community sample. DESIGN: Biracial community‐based prospective cohort study. SETTING: Urban and rural areas of central North Carolina. PARTICIPANTS: One thousand two hundred twenty‐nine older African Americans and whites, mean age 77.0, who were participants in the Duke Established Populations for Epidemiologic Studies of the Elderly. MEASUREMENTS: Sociodemographic data and data on mobility (a subset of items from the Rosow‐Breslau scale), depression (Center for Epidemiological Studies Depression Scale), self‐report of medical conditions, body mass index, cognitive function (Short Portable Mental Status Questionnaire), blood pressure, height, and waist circumference. High‐density lipoprotein cholesterol, triglycerides, and blood glucose were available from blood samples. Metabolic syndrome was calculated for subjects with complete data. RESULTS: Twenty‐nine percent of the sample met criteria for metabolic syndrome. In bivariate analyses, age, sex, race, education, cognitive impairment, depression, impairment in mobility, history of stroke and heart disease, and metabolic syndrome at baseline were associated with a decline in mobility 4 years later. Regression analysis controlling for the above variables demonstrated that metabolic syndrome persisted as an independent and highly significant predictor of decline in mobility. CONCLUSION: These findings suggest that metabolic syndrome may be a distinct risk factor for mobility decline in community‐dwelling older people.