Why the study?
Because maximal oxygen uptake testing is resource intensive, non-exercise-based prediction equations need validation, recalibration, and evaluation for predicting all-cause mortality.
Do non-exercise-based VO2max prediction equations accurately estimate measured VO2max and predict all-cause mortality in older adults?
Do non-exercise-based VO2max prediction equations accurately estimate measured VO2max and predict all-cause mortality in older adults?
While recalibrated non-exercise VO2max prediction equations can estimate measured VO2max with reasonable accuracy, their ability to predict mortality is confounded by the demographic variables used in their calculation.
Answers are grounded in this paper and cite their sources.
Non-exercise VO2max predictions estimate measured values adequately yet lack independent mortality association after adjustment; leaves open their added prognostic value beyond demographics in older adults.
PURPOSE: Maximal oxygen uptake ( ) is the criterion measure of cardiorespiratory fitness. Lower cardiorespiratory fitness is a strong predictor of poor health outcomes, including all-cause mortality. Because testing is resource intensive, several non-exercise-based V˙O 2max prediction equations have been published. We assess these equations' ability to predict measured V˙O 2max , recalibrate these equations, and quantify the association of measured and predicted V˙O 2max with all-cause mortality. METHODS: Baltimore Longitudinal Study of Aging participants with valid V˙O 2max tests were included ( n = 1080). Using published V˙O 2max prediction equations, we calculated predicted V˙O 2max and present performance metrics before and after recalibration (deriving new regression estimates by regressing measured V˙O 2max on Baltimore Longitudinal Study of Aging covariates). Cox proportional hazards models were fit to quantify associations of measured, predicted, and recalibration-predicted values of V˙O 2max with mortality. RESULTS: Mean age and V˙O 2max were 69.0 ± 10.4 yr and 21.6 ± 5.9 mL·kg -1 ·min -1 , respectively. The prediction equations yielded root mean square error values ranging from 4.2 to 20.4 mL·kg -1 ·min -1 . After recalibration, these values decreased to 3.9-4.2 mL·kg -1 ·min -1 . Adjusting for all covariates, all-cause mortality risk was 66% lower for the highest quartile of measured V˙O 2max relative to the lowest. Predicted V˙O 2max variables yielded similar estimates in unadjusted models but were not robust to adjustment. CONCLUSIONS: Measured V˙O 2max is an extremely strong predictor of all-cause mortality. Several published V˙O 2max prediction equations yielded the following: 1) reasonable performance metrics relative to measured V˙O 2max especially when recalibrated, and 2) all-cause mortality hazard ratios similar to those of measured V˙O 2max , especially when recalibrated, yet 3) were not robust to adjustment for basic demographic covariates likely because these were used in the equation for predicted V˙O 2max .
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Schumacher et al. (2022) studied this question.
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