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Importance of Assessing Cardiorespiratory Fitness in Clinical Practice: A Case for Fitness as a Clinical Vital Sign: A Scientific Statement From the American Heart Association
Open accessAbstract
Mounting evidence has firmly established that low levels of cardiorespiratory fitness (CRF) are associated with a high risk of cardiovascular disease, all-cause mortality, and mortality rates attributable to various cancers. A growing body of epidemiological and clinical evidence demonstrates not only that CRF is a potentially stronger predictor of mortality than established risk factors such as smoking, hypertension, high cholesterol, and type 2 diabetes mellitus, but that the addition of CRF to traditional risk factors significantly improves the reclassification of risk for adverse outcomes. The purpose of this statement is to review current knowledge related to the association between CRF and health outcomes, increase awareness of the added value of CRF to improve risk prediction, and suggest future directions in research. Although the statement is not intended to be a comprehensive review, critical references that address important advances in the field are highlighted. The underlying premise of this statement is that the addition of CRF for risk classification presents health professionals with unique opportunities to improve patient management and to encourage lifestyle-based strategies designed to reduce cardiovascular risk. These opportunities must be realized to optimize the prevention and treatment of cardiovascular disease and hence meet the American Heart Association’s 2020 goals.
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“Higher levels of PA and/or CRF before hospitalization for acute coronary syndromes and elective or emergent surgical procedures also appear to yield more favorable short-term outcomes [2] .”
From Physical activity, cardiorespiratory fitness, and cardiovascular health: A clinical practice statement of the American Society for Preventive Cardiology Part II: Physical activity, cardiorespiratory fitness, minimum and goal intensities for exercise training, prescriptive methods, and special patient populations (2022) · cites this paper as [2]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Numerous epidemiologic analyses combined with evidence of biologic plausibility support a cause-and-effect relationship between increased PA and/or CRF levels and reduced CVD mortality.”
From Physical activity, cardiorespiratory fitness, and cardiovascular health: A clinical practice statement of the American Society for Preventive Cardiology Part II: Physical activity, cardiorespiratory fitness, minimum and goal intensities for exercise training, prescriptive methods, and special patient populations (2022) · cites this paper as [2]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“at a magnitude that has been associated with a decreased risk of cardiovascular disease and decreased all-cause mortality, 34”
From Healthy Weight Loss Maintenance with Exercise, Liraglutide, or Both Combined (2021) · cites this paper as [34]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Cardiorespiratory fitness (peak or maximal oxygen uptake) is now regarded as a clinical vital sign,47”
From Effect of exercise training for five years on all cause mortality in older adults—the Generation 100 study: randomised controlled trial (2020) · cites this paper as [47]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Consequently, low levels of CRF have now been designated as a clinical vital sign, risk factor for CVD [1] , [2] , [3] , and as a strong prognostic indicator in exercise-based cardiac rehabilitation (CR) [ 4 , 5 ].”
From Physical activity, cardiorespiratory fitness, and cardiovascular health: A clinical practice statement of the American Society for Preventive Cardiology Part II: Physical activity, cardiorespiratory fitness, minimum and goal intensities for exercise training, prescriptive methods, and special patient populations (2022) · cites this paper as [2]
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In the citing paper
“Adding CRF to conventional risk assessment significantly enhances the accuracy of risk stratification for adverse outcomes [44].”
From Global consensus on optimal exercise recommendations for enhancing healthy longevity in older adults (ICFSR) (2025) · cites this paper as [44]
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In the citing paper
“Low cardiorespiratory fitness is a leading risk factor for CVD morbidity and mortality (33), with higher levels of fitness universally considered cardioprotective (34) and an important ' vital sign ' of cardiovascular health (35).”
From Cardiorespiratory Fitness, Workload, and the Blood Pressure Response to Exercise Testing (2022) · cites this paper as [35]
In the citing paper
“cardiorespiratory fitness (CRF) is a stronger predictor of mortality risk than traditional risk factors such as smoking, hypertension, high cholesterol, or T2D”
From Global consensus on optimal exercise recommendations for enhancing healthy longevity in older adults (ICFSR) (2025) · cites this paper as [44]
In the citing paper
“Adding CRF to conventional risk assessment significantly enhances the accuracy of risk stratification for adverse outcomes [44]”
From Global consensus on optimal exercise recommendations for enhancing healthy longevity in older adults (ICFSR) (2025) · cites this paper as [44]
In the citing paper
“the risk reduction per 1 MET increase in measured CRF is associated with a 10–30% reduction in adverse cardiovascular events [37,48,49]”
From Global consensus on optimal exercise recommendations for enhancing healthy longevity in older adults (ICFSR) (2025) · cites this paper as [49]
In the citing paper
“However, epidemiological data increasingly demonstrate that cardiorespiratory fitness (CRF) is a stronger predictor of mortality risk than traditional risk factors such as smoking, hypertension, high cholesterol, or T2D.”
From Global consensus on optimal exercise recommendations for enhancing healthy longevity in older adults (ICFSR) (2025) · cites this paper as [44]
In the citing paper
“Proof-of-concept trials39 have shown that very small doses of exercise-based intermittent VPA can have rapid and measurable effects on cardiorespiratory fitness, a key causal determinant of CVD14.”
From Association of wearable device-measured vigorous intermittent lifestyle physical activity with mortality (2022) · cites this paper as [14]
In the citing paper
“High-intensity interval training40 and studies of intermittent stair climbing39 have shown that VPA bursts lasting 20 s to a few minutes, performed three to five times a day, can result in substantial improvements in cardiorespiratory fitness in previously inactive adults within a few weeks, providing a plausible physiological basis14 for the associations we observed.”
From Association of wearable device-measured vigorous intermittent lifestyle physical activity with mortality (2022) · cites this paper as [14]
In the citing paper
“Beyond its implications in medicine, CRF is frequently used in sports as an indicator of endurance capacity, having strong predictive value for other sport-related performance traits [148].”
From Human-centred artificial intelligence for mobile health sensing: challenges and opportunities (2023) · cites this paper as [148]
In the citing paper
“Clinical evidence shows that CRF is not only potentially a stronger predictor of mortality than well-established risk factors like hypertension, type 2 diabetes, high cholesterol or smoking, but that using CRF to complement these traditional risk factors significantly improves the precision of risk prediction models for adverse CVD health outcomes [148].”
From Human-centred artificial intelligence for mobile health sensing: challenges and opportunities (2023) · cites this paper as [148]
In the citing paper
“using CRF to complement these traditional risk factors significantly improves the precision of risk prediction models for adverse CVD health outcomes [148].”
From Human-centred artificial intelligence for mobile health sensing: challenges and opportunities (2023) · cites this paper as [148]
In the citing paper
“However, many studies have demonstrated numerous strong benefits from PA, especially among those who suffer from a variety of chronic diseases. 25-28”
From Physical inactivity is associated with a higher risk for severe COVID-19 outcomes: a study in 48 440 adult patients (2021) · cites this paper as [26]
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Healthy Vascular Aging Is Associated With Higher Cardiorespiratory Fitness
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Self-citationJakicic, J. M., Behrens, C. E., Deemer, S. E., Forseth, B., Katsanos, C. S., Nickerson, B. S., Prado, W. L., Wang, X., Deru, L. S., & Rogers, R. J. (2026) · Journal of Sport and Health Science · doi:10.1016/j.jshs.2025.101097 · Cited by 13
Swift, D. L., Ross, L. M., Laddu, D. R., Conroy, M. B., German, C. A., Evangelista, L. S., Marvel, F. A., Jerome, G. J., on behalf the American Heart Association Council on Lifestyle and Cardiometabolic Health, Council on Cardiovascular and Stroke Nursing, et al. (2026) · Circulation · doi:10.1161/cir.0000000000001441 · Cited by 13
Liang, W., Liu, C., Yan, X., Hou, Y., Yang, G., Dai, J., & Wang, S. (2024) · PeerJ · doi:10.7717/peerj.17064 · Cited by 12
Economic burden of low cardiorespiratory fitness in Canada
Chaput, J.-P., Janssen, I., Sampasa-Kanyinga, H., Tomkinson, G. R., & Lang, J. J. (2023) · Preventive Medicine · doi:10.1016/j.ypmed.2023.107424 · Cited by 11
Jensen, S. B. K., Fiorenza, M., Juhl, C. R., Sandsdal, R. M., Jensen, E., Seier, S. S., Janus, C., Jørgensen, J. R., Blond, M. B., Holst, J. J., et al. (2026) · Sports Medicine · doi:10.1007/s40279-025-02386-0 · Cited by 9
“…with reduced all-cause and cardiovascular mortality and prevention of age-related declines [2, 33, 34] and were considered realistic to detect [7, 26], and they were therefore chosen as the minimum clinically relevant differences (see the statistical analysis plan in the ESM for details).”
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Metadata
- Authors
- Ross, R., Blair, S. N., Arena, R., Church, T. S., Després, J.-P., Franklin, B. A., Haskell, W. L., Kaminsky, L. A., Levine, B. D., Lavie, C. J., Myers, J., Niebauer, J., Sallis, R., Sawada, S. S., Sui, X., & Wisløff, U.
- ORCID
- Venue
- Circulation
- Published
- 2016-12-13
- Volume
- 134
- Issue
- 24
- Pages
- e653-e699
- ISSN
- 0009-7322 (ISSN-L)
- 1524-4539
- OpenAlex
- W2555189237
- Semantic Scholar
- 88871f3a128b0217f4058ab714e636cae4b88b8f
- Cited by
- 2,486
- References
- 307
- Citations by year
- 2026: 298 · 2025: 294 · 2024: 344 · 2023: 302 · 2022: 289 · 2021: 282 · 2020: 229 · 2019: 202 · 2018: 164 · 2017: 74 · 2016: 4
- FWCI
- 304.38
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- other-oa
- Locations
- Circulation (publishedVersion, other-oa)
- PubMed (publishedVersion)
- Funders
- U.S. Department of Veterans Affairs (I01 RX000344, IK6 RX002477)
- Topics
- Health Sciences › Medicine › Physiology (medical) › Cardiovascular and exercise physiology
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Keywords
- cardiorespiratory fitness, cardiovascular risk prediction, mortality risk, cardiovascular disease prevention, risk reclassification, all-cause mortality, cancer mortality, cardiovascular risk management
- MeSH terms
- Cardiorespiratory Fitness, Cardiovascular Diseases, Humans, Metabolic Diseases, Oxygen Consumption, Risk Factors, Exercise, Metabolic Equivalent
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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