Cardiorespiratory Fitness and Population Attributable Risk: The ETHOS Study
BACKGROUND: Low cardiorespiratory fitness (CRF) and traditional cardiovascular risk factors are associated with mortality, but their relative contributions to mortality and the independent association of CRF remain incompletely understood. METHODS: We analyzed a large Veterans Administration cohort undergoing maximal exercise testing (n=580,290; mean age 65.1±9.7 years) and followed them for 10.2±5.1 years. Relative risks (RRs) for mortality were estimated using Poisson regression with robust (HC3) standard errors across nested models adjusting sequentially for age, sex, BMI, diabetes, smoking, and statin therapy. Population attributable risks (PARs) and exposure impact numbers (EINs) were calculated for low CRF and other major risk factors. RESULTS: Individuals in the highest CRF quintile had approximately 74% lower mortality vs. those in the lowest quintile (<5 METs). Hypertension had the greatest population-level impact (PAR 21.8%; 95% CI 15.2-28.0), followed by low CRF (PAR 14.7%; 95% CI 8.1-21.1). In a fully adjusted sensitivity analysis, low CRF demonstrated the strongest independent association with mortality (RR 1.77; 95% CI 1.75-1.79) compared with hypertension (RR 1.33; 95% CI 1.32-1.35). Absolute EIN was lowest for low CRF (2.36), suggesting that for every 100 individuals whose fitness improved over the observed follow-up period, approximately 24 fewer deaths would be expected. CONCLUSIONS: Low CRF and hypertension were the strongest predictors of mortality and accounted for the greatest proportion of population-level risk. These findings support CRF as a modifiable clinical vital sign and highlight the complementary importance of fitness promotion and blood pressure control for reducing mortality.
Authors
- Jonathan Myers (ORCID: https://orcid.org/0000-0003-2592-136X)
- Cristina Cadenas‐Sánchez (ORCID: https://orcid.org/0000-0002-4513-9108)
- Immanuel Babu Henry Samuel (ORCID: https://orcid.org/0000-0001-7658-9454)
- Charles Faselis
- Andreas Pittaras
- Peter Kokkinos
- Khin Chan
Institutions
- Rutgers, The State University of New Jersey (US)
- Henry M. Jackson Foundation (US)
- Universidad de Granada (ES)
- VA Palo Alto Health Care System (US)
- Cardiovascular Institute of the South (US)
- Veterans Health Administration (US)
- Washington DC VA Medical Center (US)
- Artificial Intelligence in Medicine (Canada) (CA)
- Stanford University (US)
Publication Details
- Journal
- European Journal of Preventive Cardiology
- Published
- 2026-09-04
- DOI
- https://doi.org/10.1093/eurjpc/zwag471
- Primary Topic
- Cardiovascular and exercise physiology
- Type
- article
- Field-Weighted Citation Impact
- 0.00