Predictors of metabolic syndrome in community-dwelling older adults

PLoS One. 2018 Oct 31;13(10):e0206424. doi: 10.1371/journal.pone.0206424. eCollection 2018.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Cohort Studies
  • Female
  • Humans
  • Independent Living / statistics & numerical data*
  • Longitudinal Studies
  • Male
  • Metabolic Syndrome / diagnosis
  • Metabolic Syndrome / epidemiology*
  • Middle Aged
  • Prognosis
  • Risk Factors

Grants and funding

This work was part of the PreventIT and PANINI research projects, funded by the European Union's Horizon 2020 research and innovation programme [689238, 675003]. The Longitudinal Aging Study Amsterdam was supported by a grant from the Netherlands Ministry of Health Welfare and Sports, Directorate of Long-Term Care. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.