An Overview of Non-exercise Estimated Cardiorespiratory Fitness: Estimation Equations, Cross-Validation and Application

Abstract

Purpose: To summarize current non-exercise prediction models to estimate cardiorespiratory fitness (CRF), cross-validate these models, and apply them to predict health outcomes. Methods: PubMed search was up to August 2018 for eligible publications. The current review was comprised of three steps. The first step was to search the literature on non-exercise prediction models. The key words combined non-exercise, CRF and one among prediction, prediction model, equation, prediction equation and measurement. The second step was to search the literature about cross-validation of non-exercise equations. The key words included non-exercise, CRF and one among validation, cross-validation and validity. The last step was to search for application of CRF assessed from non-exercise equations. The key words were non-exercise, CRF, mortality, all-cause mortality, cardiovascular disease (CVD) mortality and cancer mortality. Results: Sixty non-exercise equations were identified. Age, gender, percent body fat, body mass index, weight, height and physical activity status were commonly used in the equations. Several researchers cross-validated non-exercise equations and proved their validity. In addition, non-exercise estimated CRF was significantly associated with all-cause mortality and fatal and nonfatal CVD. Conclusions: Measurement of CRF from non-exercise models is practical and viable when exercise testing is not feasible. Despite the limitations of equations, application of CRF from non-exercise methods showed accuracy and predictive ability.