PhenoAge and PhenoAgeAccel in the context of dyslipidemia: association with stroke and potential as a new predictor in the US general population.

Abstract

Background: The challenges posed by an aging society are increasingly recognized, particularly regarding the potential impacts of high-fat diets and the trend toward younger ages of disease onset. The purpose of this study was to clarify the relationships between the prevalence of stroke in the general US population and PhenoAge (PA) and PhenoAgeAccel (PAA).

Methods: Key methods included a correlation heatmap to explore linear relationships between some of the variables and weighted multivariable logistic regression to assess associations between PA, PAA, and stroke. Restricted cubic spline (RCS) analysis was used to investigate nonlinear relationships and dose-response effects. The ability of the PAA to predict stroke risk was assessed by a nomogram model and a receiver operating characteristic curve.

Results: After adjusting for confounding variables, both continuous and categorical PA and PAA were significantly associated with stroke prevalence. RCS analysis revealed a significant nonlinear relationship between PA and stroke prevalence. Further subgroup RCS analysis indicated that maintaining PA below 31.6 could provide greater benefits across all races and genders, specifically for individuals aged 40-80 years and those who are overweight or obese.

Conclusion: This study highlights the importance of stroke prevention in overweight and obese populations. Monitoring intermediary factors such as high-density lipoprotein cholesterol and waist circumference may reduce stroke risk. Additionally, PA and PAA may serve as novel markers for stroke, offering new directions for health management in an aging society.