Frailty index is positively associated with stroke risk in nationally representative cohorts from the united States and China.

Sci Rep

Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Shangtang road NO.158, Hangzhou, 310014, Zhejiang, Chin

Published: August 2025


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Frailty has been linked to adverse health outcomes, but its relationship with stroke remains insufficiently understood in general populations. In this study, we examined the association between frailty and stroke using two nationally representative cohorts: the U.S. National Health and Nutrition Examination Survey (NHANES) and the China Health and Retirement Longitudinal Study (CHARLS). Frailty was assessed using a multidimensional frailty index, analyzed both continuously and by category. Weighted logistic regression and restricted cubic spline models were applied. We found that higher frailty index scores were associated with greater odds of stroke in both populations, independent of demographic and clinical risk factors. The association appeared remained consistent in multiple sensitivity and subgroup analyses. Each 0.1-unit increase in the frailty index was associated with a 2.90-fold and 1.78-fold higher odds of stroke in NHANES and CHARLS, respectively. While CHARLS provides prospective evidence supporting the temporal relationship between frailty and stroke, the cross-sectional nature of NHANES limits causal inference. Overall, these findings suggest that frailty may be a useful marker for identifying individuals at higher risk of stroke. Further research is needed to validate its predictive utility and to explore whether modifying frailty can help reduce stroke incidence, particularly in aging populations.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12322301PMC
http://dx.doi.org/10.1038/s41598-025-14116-7DOI Listing

Publication Analysis

Top Keywords

frailty
10
stroke
8
nationally representative
8
representative cohorts
8
frailty stroke
8
odds stroke
8
frailty positively
4
positively associated
4
associated stroke
4
stroke risk
4

Similar Publications

Background: Frailty is defined as a biological syndrome characterized by a decreased reserve and resistance to stressors. Frailty is closely related to lifestyle, and improving lifestyle can effectively reduce the incidence of frailty and related adverse events. Multi-component interventions were an effective mean of improving lifestyle, which has been validated in studies of other populations.

View Article and Find Full Text PDF

Predicting the future risk and outcomes of severe heart failure and coronary artery disease with machine learning in the UK Biobank Cohort.

PLoS One

September 2025

Department of Medicine, The Red Rogers Centre for Heart Research, Peter Munk Cardiac Centre, University Health Network, University of Toronto, Toronto, Ontario, Canada.

Background: In order to seriously impact the global burden of heart failure (HF) and coronary artery disease (CAD), identifying at-risk individuals as early as possible is vital. Risk calculator tools in wide clinical use today are informed by traditional statistical methods that have historically yielded only modest prediction accuracy.

Methods: This study uses machine learning algorithms to generate predictions models for the development and progression of severe HF and CAD.

View Article and Find Full Text PDF

Introduction: Cognitive frailty (CF), which typically precedes dementia and functional decline, serves as a more robust predictor of adverse health outcomes compared to physical frailty alone, representing a critical challenge in promoting healthy aging among older people living with HIV (PLWH) aged ≥ 50 years. This study aimed to investigate the prevalence of cognitive frailty and identify its associated factors among PLWH aged ≥ 50 years.

Methods: A convenience sample of 344 PLWH ≥ 50 years was recruited from a tertiary Grade A hospital in Zunyi, China.

View Article and Find Full Text PDF