Higher Cardiorespiratory Fitness Cuts Cardiometabolic Multimorbidity Risk by 40%
A pooled study of 12,944 adults across China, England, and the US links estimated fitness to dramatically lower odds of developing multiple cardiometabolic diseases.
Riepilogo
Researchers analyzed data from three nationally representative cohorts totaling 12,944 older adults to examine whether estimated cardiorespiratory fitness (eCRF) predicts cardiometabolic multimorbidity (CMM)—defined as having two or more of hypertension, diabetes, heart disease, or stroke. eCRF was calculated using a validated non-exercise equation requiring no physical testing. Over follow-up, 3,029 participants developed CMM. Each one standard deviation increase in eCRF was associated with a 39% lower risk of CMM. Adults in the highest fitness category faced 60% lower risk compared to those in the lowest category. The association was consistent across all three cohorts and held after sensitivity analyses including competing risk for death and multiple imputation. Adding eCRF to standard predictors modestly improved risk discrimination, suggesting it may be a practical cardiometabolic screening tool.
Riepilogo Dettagliato
Cardiometabolic multimorbidity—the simultaneous presence of two or more conditions such as hypertension, diabetes, heart disease, and stroke—is a growing burden in aging populations worldwide. While cardiorespiratory fitness (CRF) is a well-established predictor of individual cardiometabolic outcomes, its role in predicting CMM across diverse populations has been underexplored. This study addresses that gap using three large, nationally representative longitudinal cohorts spanning different cultural and healthcare contexts.
The study pooled data from the China Health and Retirement Longitudinal Study (CHARLS), the English Longitudinal Study of Ageing (ELSA), and the US Health and Retirement Study (HRS), encompassing 12,944 adults free of CMM at baseline. Estimated CRF was derived from a validated sex-specific non-exercise prediction equation—meaning no treadmill or VO₂ max test was required. CMM was defined as the onset of two or more of the following: hypertension, diabetes, heart disease, or stroke. Cox proportional hazards models assessed associations both continuously (per 1-SD increment) and categorically (low, moderate, high fitness).
Over the follow-up period, 3,029 participants (23.4%) developed incident CMM. In the pooled analysis, each 1-SD increment in eCRF was associated with a hazard ratio of 0.61 (95% CI: 0.58–0.64), indicating a 39% lower risk. Adults classified in the high-fitness category faced a 60% lower risk compared to the low-fitness group (HR 0.40, 95% CI: 0.35–0.45), with a significant dose-response trend (P for trend <0.001). These associations remained directionally consistent across all three cohorts and were robust to competing risks from all-cause mortality, multiple imputation for missing data, and various sensitivity analyses.
Adding eCRF to a model containing sociodemographic and behavioral predictors produced modest but meaningful improvements in discrimination performance, suggesting that this easily obtainable fitness estimate captures cardiometabolic risk information beyond traditional risk factors. As eCRF can be derived from routine clinical data without exercise testing, it could feasibly be integrated into population-level screening programs for aging adults.
Important caveats temper the conclusions. The study is observational, precluding causal inference. Between-cohort heterogeneity was noted across the three populations, reflecting differences in disease prevalence, lifestyle, and healthcare access. The eCRF equation was validated in Western populations and may perform differently in Chinese participants. Additionally, self-reported disease ascertainment introduces potential misclassification. Despite these limitations, the consistency of findings across three geographically and culturally distinct cohorts strengthens the overall signal.
Risultati Principali
- Each 1-SD increase in estimated CRF linked to 39% lower CMM risk (HR 0.61, 95% CI 0.58–0.64).
- High fitness vs. low fitness associated with 60% lower CMM risk (HR 0.40, 95% CI 0.35–0.45).
- 3,029 of 12,944 participants developed CMM over follow-up across three cohorts.
- Adding eCRF to standard predictors modestly improved cardiometabolic risk discrimination.
- Results were consistent across China, England, and US cohorts and multiple sensitivity analyses.
Metodologia
Cox proportional hazards models were applied to pooled data from CHARLS, ELSA, and HRS (n=12,944). Estimated CRF was derived from a validated non-exercise sex-specific equation; CMM was defined as ≥2 of hypertension, diabetes, heart disease, or stroke. Supplementary analyses included competing risks for death, multiple imputation, proportional hazards testing, and random-effects meta-analysis across cohorts.
Limitazioni dello Studio
The observational design prevents causal conclusions, and unmeasured confounding cannot be excluded. Between-cohort heterogeneity and potential non-transferability of the eCRF equation to non-Western populations (e.g., Chinese participants) limit generalizability. Self-reported disease ascertainment may introduce misclassification bias.
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