ArticleThe journal of nutrition, health & aging2026
Long-term variability in physiological measures and risk of frailty: evidence from two cohort studies.
Article in The journal of nutrition, health & aging, 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
backgroundWhile blood pressure, pulse rate, and body weight are linked to frailty, the influence of long-term variability in these physiological measures on frailty has not been fully elucidated. Our study aims to investigate the overall effect of long-term variability in physiological measures on frailty risk among middle-aged and older adults.
methodsThis prospective cohort study used data from the US Health and Retirement Study (HRS) (2006-2018) and China Health and Retirement Longitudinal Study (CHARLS) (2011-2018). The composite score of physical variability was composed of blood pressure variability (BPV), pulse rate variability (PRV), and body weight variability (BWV). Logistic regression and linear regression models were used to assess the association between the composite score and frailty.
resultsAmong 7716 adults included in the analysis, 3191 participants were from the HRS, and 4525 were from the CHARLS. A total of 473 (14.82%) and 668 (14.76%) participants developed frailty, respectively. A higher composite score of variability was associated with higher frailty risk in both cohorts (pooled odds ratio [OR] per one-point increment, 1.23; 95% confidence interval [CI], 1.14-1.33; P-heterogeneity = 0.607). Each one-point increment in the composite score of variability was associated with a faster increase in frailty index in both the HRS cohort (β = 0.09 SD; 95% CI, 0.06-0.13 SD; P < 0.001) and the CHARLS cohort (β = 0.08 SD; 95% CI, 0.04-0.11 SD; P < 0.001). Each SD increment in BPV and BWV was related to 14% (95% CI: 1.03-1.26) and 19% (1.09-1.31) higher odds of frailty in HRS, while each SD increment in BWV was related to 10% (1.01, 1.20) increase in CHARLS. This association remained consistent when using a principal component analysis (PCA)-weighted continuous composite score, and BPV contributed the highest weight to this metric.
conclusionsHigher long-term variability in physiological measures was associated with an increased frailty risk. Monitoring noninvasive physiological measures could have clinical utility in identifying the risk of frailty progression.
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