Key result
Developing separate prediction models within body mass index stratifications effectively improved the prediction accuracy of maximal oxygen uptake compared to a single model developed regardless of BMI.
Why the study?
To investigate whether modeling within separate BMI stratifications improves the accuracy of VO2max prediction compared to a model developed regardless of adults' BMIs.
Does modeling within separate BMI stratifications improve the accuracy of VO2max prediction compared to a general model in healthy adults?
Cross-Sectional (n=250)
Does modeling within separate BMI stratifications improve the accuracy of VO2max prediction compared to a general model in healthy adults?
Developing VO2max prediction models based on specific BMI stratifications significantly improves the accuracy and reliability of estimating cardiorespiratory fitness from a 3-minute step test compared to a generalized model.
BMI-stratified models may enhance VO2max prediction accuracy; hypothesis-generating and requires validation before clinical use.
The purpose of this study was to investigate whether modeling within separate body mass index (BMI) stratifications improves the accuracy of maximal oxygen uptake (VO 2max ) prediction compared to a model developed regardless of adults' BMIs. A total of 250 Taiwanese adults (total group, TOG) aged 22-64 years participated in this study, and were stratified into a normal group (NOG: 135), an overweight group (OVG: 69), and an obesity group (OBG: 46), according to the BMI classification recommended by the Taiwan Ministry of Health and Welfare. VO 2max was directly measured on an electromagnetic bicycle ergometer. Using the participant's heart rate in the 3-min incremental step-in-place test and demographic parameters, VO 2max prediction models established for four groups were TOG model, NOG model, OVG model, and OBG model, respectively. Compared with the TOG model, the OVG and OBG models had higher coefficients of determination and lower standard error of estimates (SEEs), or %SEEs. The validities of the NOG (r = 0.780), OVG (r = 0.776), and OBG (r = 0.791) models for BMI subgroups increased by 1.79%, 4.64%, and 8.22% respectively, and the reliabilities (NOG model: ICC = 0.755; OVG model: ICC = 0.765; OBG model: ICC = 0.779) increased by 3.18%, 3.27%, and 9.63%, respectively. These results suggested using separate models established in BMI stratifications can effectively improve the prediction of VO 2max .
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Li et al. (2022) conducted a cross-sectional in Healthy adults (n=250). BMI-stratified VO2max prediction models vs. Total group (TOG) model developed regardless of BMI was evaluated on Accuracy of VO2max prediction (R2, SEE, %SEE, validity, and reliability). Developing separate prediction models within body mass index stratifications effectively improved the prediction accuracy of maximal oxygen uptake compared to a single model developed regardless of BMI.
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