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Contribution of Body Mass Index Stratification for the Prediction of Maximal Oxygen Uptake

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) a...

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Autores principales: Li, Fang, Yang, Cheng-Pang, Wu, Cheng-You, Ho, Chia-An, Yeh, Hung-Chih, Chan, Yuan-Shuo, ChangChien, Wen-Sheng, Ho, Chin-Shan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9682509/
https://www.ncbi.nlm.nih.gov/pubmed/36438918
http://dx.doi.org/10.7150/ijms.77818
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author Li, Fang
Yang, Cheng-Pang
Wu, Cheng-You
Ho, Chia-An
Yeh, Hung-Chih
Chan, Yuan-Shuo
ChangChien, Wen-Sheng
Ho, Chin-Shan
author_facet Li, Fang
Yang, Cheng-Pang
Wu, Cheng-You
Ho, Chia-An
Yeh, Hung-Chih
Chan, Yuan-Shuo
ChangChien, Wen-Sheng
Ho, Chin-Shan
author_sort Li, Fang
collection PubMed
description 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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spelling pubmed-96825092022-11-25 Contribution of Body Mass Index Stratification for the Prediction of Maximal Oxygen Uptake Li, Fang Yang, Cheng-Pang Wu, Cheng-You Ho, Chia-An Yeh, Hung-Chih Chan, Yuan-Shuo ChangChien, Wen-Sheng Ho, Chin-Shan Int J Med Sci Research Paper 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). Ivyspring International Publisher 2022-10-31 /pmc/articles/PMC9682509/ /pubmed/36438918 http://dx.doi.org/10.7150/ijms.77818 Text en © The author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Research Paper
Li, Fang
Yang, Cheng-Pang
Wu, Cheng-You
Ho, Chia-An
Yeh, Hung-Chih
Chan, Yuan-Shuo
ChangChien, Wen-Sheng
Ho, Chin-Shan
Contribution of Body Mass Index Stratification for the Prediction of Maximal Oxygen Uptake
title Contribution of Body Mass Index Stratification for the Prediction of Maximal Oxygen Uptake
title_full Contribution of Body Mass Index Stratification for the Prediction of Maximal Oxygen Uptake
title_fullStr Contribution of Body Mass Index Stratification for the Prediction of Maximal Oxygen Uptake
title_full_unstemmed Contribution of Body Mass Index Stratification for the Prediction of Maximal Oxygen Uptake
title_short Contribution of Body Mass Index Stratification for the Prediction of Maximal Oxygen Uptake
title_sort contribution of body mass index stratification for the prediction of maximal oxygen uptake
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9682509/
https://www.ncbi.nlm.nih.gov/pubmed/36438918
http://dx.doi.org/10.7150/ijms.77818
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