Dietary Polyphenol Intake Is Associated with Biological Aging, a Novel Predictor of Cardiovascular Disease: Cross-Sectional Findings from the Moli-Sani Study

Nutrients. 2021 May 17;13(5):1701. doi: 10.3390/nu13051701.

Abstract

Biological aging, or the discrepancy between biological and chronological age of a subject (Δage), has been associated with a polyphenol-rich Mediterranean diet and represents a new, robust indicator of cardiovascular disease risk. We aimed to disentangle the relationship of dietary polyphenols and total antioxidant capacity with Δage in a cohort of Italians. A cross-sectional analysis was performed on a sub-cohort of 4592 subjects (aged ≥ 35 y; 51.8% women) from the Moli-sani Study (2005-2010). Food intake was recorded by a 188-item food-frequency questionnaire. The polyphenol antioxidant content (PAC)-score was constructed to assess the total dietary content of polyphenols. Total antioxidant capacity was measured in foods by these assays: trolox equivalent antioxidant capacity (TEAC), total radical-trapping antioxidant parameter (TRAP) and ferric reducing-antioxidant power (FRAP). A deep neural network, based on 36 circulating biomarkers, was used to compute biological age and the resulting Δage, which was tested as outcome in multivariable-adjusted linear regressions. Δage was inversely associated with the PAC-score (β = -0.31; 95%CI -0.39, -0.24) but not with total antioxidant capacity of the diet. A diet rich in polyphenols, by positively contributing to deceleration of the biological aging process, may exert beneficial effects on the long-term risk of cardiovascular disease and possibly of bone health.

Keywords: biological aging; bone health; cardiovascular disease; dietary polyphenols.

MeSH terms

  • Adult
  • Aging / blood
  • Aging / physiology*
  • Antioxidants / analysis*
  • Biomarkers / blood
  • Cardiovascular Diseases / etiology*
  • Chronobiology Phenomena
  • Cohort Studies
  • Cross-Sectional Studies
  • Diet / adverse effects
  • Diet Surveys
  • Diet, Mediterranean / statistics & numerical data
  • Eating / physiology*
  • Female
  • Heart Disease Risk Factors
  • Humans
  • Italy
  • Linear Models
  • Male
  • Neural Networks, Computer
  • Polyphenols / analysis*
  • Risk Assessment

Substances

  • Antioxidants
  • Biomarkers
  • Polyphenols