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Updated: Feb 3, 2026

A Training Program Using an Agility Ladder for Community-Dwelling Older Adults
Published on: March 7, 2020
Predictors of metabolic syndrome in community-dwelling older adults
Jeanine M Van Ancum1, Nini H Jonkman1, Natasja M van Schoor2
1Department of Human Movement Sciences, @AgeAmsterdam, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, The Netherlands.
Objectives:
The metabolic syndrome has been associated with a variety of individual variables, including demographics, lifestyle, clinical measures and physical performance. We aimed to identify independent predictors of the prevalence and incidence of metabolic syndrome in a large cohort of older adults.
Methods:
The Longitudinal Aging Study Amsterdam is a prospective cohort including community-dwelling adults aged 55-85 years. Metabolic syndrome was defined according to criteria of the National Cholesterol Education Program Adult Treatment Panel III. The incidence of metabolic syndrome was calculated over a period of three years. Stepwise backward logistic regression analyses were used to identify predictors, including variables for demographics, lifestyle, clinical measures and physical performance, both in a cross-sectional cohort (n = 1292) and a longitudinal sub-cohort (n = 218).
Results:
Prevalence and incidence of metabolic syndrome were 37% (n = 479) and 30% (n = 66), respectively. Cross-sectionally, heart disease (OR: 1.91, 95% CI: 1.37-2.65), peripheral artery disease (OR: 2.13, 95% CI: 1.32-3.42), diabetes (OR: 4.74, 95% CI: 2.65-8.48), cerebrovascular accident (OR: 1.92, 95% CI: 1.09-3.37), and a higher Body Mass Index (OR: 1.32, 95% CI: 1.26-1.38) were significant independent predictors of metabolic syndrome. Longitudinally, Body Mass Index (OR: 1.16, 95% CI: 1.05-1.27) was an independent predictor of metabolic syndrome.
Conclusion:
Four age related diseases and a higher Body Mass Index were the only predictors of metabolic syndrome in the cross-sectional cohort, despite the large variety of variables included in the multivariable analysis. In the longitudinal sub-cohort, a higher Body Mass Index was predictive of developing metabolic syndrome.
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