ArticleJournal of the American Heart Association2026
Walking Pace Optimizes Conventional Cardiovascular Disease Risk Prediction Models Among Vulnerable Subpopulations: A Prospective Cohort Study.
Article in Journal of the American Heart Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundGrip strength and walking pace are potential indicators of adverse health outcomes for the general population. However, their role in primary cardiovascular disease (CVD) prevention among various subpopulations remains uncertain.
methodsA total of 206 371 individuals without CVD (aged 40-69 years) from the UK Biobank were included. Four conventional CVD prediction models (Framingham, Reynolds, ASSessing cardiovascular risk using Scottish Intercollegiate Guidelines Network [ASSIGN], and pooled cohort equations [PCEs]) were used to estimate 10-year CVD risk. Model performances were compared across diverse subpopulations defined by age, grip strength, or walking pace using a C index and calibration plot in the UK Biobank. Added predictive value was further validated in ELSA (English Longitudinal Study of Ageing).
resultsDuring the follow-up period 19 664 cases of incident CVD were registered (mean 12.85 years [SD 2.74]). Vulnerable subpopulations were characterized by advanced age, low grip strength, or slow walking pace. The ASSIGN model showed lower C indexes in vulnerable subpopulations: 0.659 (95% CI, 0.646-0.672) for low grip strength versus 0.702 (95% CI, 0.699-0.706) for normal grip strength, 0.646 (95% CI, 0.635-0.657) for slow walking pace versus 0.701 (95% CI, 0.698-0.705) for normal walking pace, and 0.624 (95% CI, 0.614-0.634) for older versus 0.701 (95% CI, 0.689-0.712) for young subpopulation. Adding walking pace to the ASSIGN model improved its discriminative ability in the older subpopulation with low grip strength (C index change, 0.027 [95% CI, 0.009-0.045]). The finding was similar in ELSA.
conclusionsWalking pace, but not grip strength, improved the performance of conventional CVD prediction models among vulnerable subpopulations. This highlights the role of physical function in primary prevention of CVD.
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