Article Text

Download PDFPDF
Original research
Prediction of cardiovascular health by non-exercise estimated cardiorespiratory fitness
  1. Verónica Cabanas-Sánchez1,
  2. Enrique G Artero2,3,
  3. Carl J Lavie4,
  4. Sara Higueras-Fresnillo5,
  5. Esther García-Esquinas6,7,
  6. Kabir P Sadarangani8,9,
  7. Rosario Ortolá6,7,
  8. Fernando Rodríguez-Artalejo1,6,7,
  9. David Martínez-Gómez1,6,7
  1. 1 Cardiovascular and Nutritional Epidemiology, IMDEA-Food, Madrid, Spain
  2. 2 Department of Education, Faculty of Education Sciences, University of Almería, Almería, Spain
  3. 3 SPORT Research Group (CTS-1024), CERNEP Research Center, University of Almería, Almería, Spain
  4. 4 Department of Cardiovascular Diseases, John Ochsner Heart and Vascular Institute, Ochsner Clinical School-The University of Queensland School of Medicine, New Orleans, Louisiana, USA
  5. 5 Department of Physical Education, Sport and Human Movement, Faculty of Teacher Training and Education, Autonomous University of Madrid, Madrid, Spain
  6. 6 Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Madrid, Spain
  7. 7 CIBER of Epidemiology and Public Health (CIBERESP) & IdiPAZ, Madrid, Spain
  8. 8 Escuela de Kinesiología, Facultad de Salud y Odontología, Universidad Diego Portales, Santiago 8370057, Chile
  9. 9 Universidad Autónoma de Chile, Santiago, Chile
  1. Correspondence to Dr Verónica Cabanas-Sánchez, Cardiovascular and Nutritional Epidemiology, IMDEA-Food, Madrid 28049, Spain; veronica.cabanas84{at}


Objective To estimate the incidence of major biological cardiovascular disease (CVD) risk factors in adults using non-exercise estimated cardiorespiratory fitness (eCRF).

Methods 200 039 healthy people (99 957 women), aged ≥18 years (38.5±12.1 years) from the Taiwan MJ Cohort. eCRF was estimated with validated algorithms. Biological CVD risk factors, including hypertension (HTN), hypercholesterolemia, atherogenic dyslipidaemia, type 2 diabetes mellitus (T2DM) and systemic inflammation, were assessed by standardised physical examinations and laboratory tests.

Results In a basic model, baseline eCRF was inversely associated with the incidence of each CVD risk factor in both men and women (HR per 1 metabolic equivalent (MET) increase in eCRF ranged from 0.53 for T2DM in women to 0.96 for hypercholesterolemia in women). In full adjusted models, the associations were attenuated but remained statistically significant, with the exception of hypercholesterolemia in women. In a subcohort of 116 313 individuals with two repeated exposure measurements, an increase in eCRF was associated in both sexes with a subsequent lower incidence of CVD risk factors (HR per 1-MET increase ranged from 0.58 to 0.91 in models adjusted for age, year of examination and baseline eCRF). Comparisons of predictive performance showed that the addition of eCRF to values of traditional CVD risk factors had relevant improvements in risk discrimination (C-index increased from 0.1% to 3.2%), mainly for HTN and T2DM risk prediction.

Conclusions eCRF and its changes predict the incidence of biological CVD risk factors, especially HTN and T2DM. Routine assessment of eCRF in clinical settings is technically feasible and might be useful for CVD prevention.

  • cardiac risk factors and prevention
  • diabetes
  • hypertension
  • inflammatory markers
  • health services

Statistics from

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.


  • Contributors DM-G and FR-A had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: VC-S, EGA, CL, FR-A and DM-G. Analysis and interpretation of data: all authors. Drafting of the manuscript: VC-S, FR-A and DM-G. Critical revision of the manuscript for important intellectual content: EGA, CL, SH-F, EG-E, KPS, RO, FR-A and DM-G. Statistical analysis: VC-S, CL, SH-F, FR-A and DM-G. Administrative, technical or material support: EGA, CL, SH-F, EG-E, KPS and RO. Study supervision: DM-G. All authors have read and approved the final manuscript.

  • Funding This work was supported by Grant 02/2014 from the Plan Nacional sobre Drogas (Ministry of Health of Spain), FIS grants 12/1166 and 16/609 (State Secretary of R+D+I and FEDER/FSE) and MINECO R+D+I grant (DEP2013-47786-R). VC-S is supported by a ‘Juan de la Cierva’ contract (IJC2018-038008-I). DM-G is supported by a ‘Ramon y Cajal’ contract (RYC-2016–20546). All data used in this research were authorised by and received from MJ Health Research Foundation by MJ Health Research Center (Authorisation Codes: MJHRF2017006A and MJHRF2017007A). The study was approved by the institutional review boards of the MJ Health Management Institution and the National Health Research Institutes, Taiwan. The MJ cohort was supported by the MJ Health Management Institution.

  • Disclaimer The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data may be obtained from a third party and are not publicly available. Not applicable.