Dataset Information

Improved VO_2max Estimation by Combining a Multiple Regression Model and Linear Extrapolation Method.

ABSTRACT: Maximal oxygen consumption (VO_2max) is an important health indicator that is often estimated using a multiple regression model (MRM) or linear extrapolation method (LEM) with the heart rate (HR) during a step test. Nonetheless, both methods have inherent problems. This study investigated a VO_2max estimation method that mitigates the weaknesses of these two methods. A total of 128 adults completed anthropometric measurements, a physical activity questionnaire, a step test with HR measurements, and a VO_2max treadmill test. The MRM included step-test HR, age, sex, body mass index, and questionnaire scores, whereas the LEM included step-test HR, predetermined constant VO₂ values, and age-predicted maximal HR. Systematic differences between estimated and measured VO_2max values were detected using Bland-Altman plots. The standard errors of the estimates of the MRM and LEM were 4.15 and 5.08 mL·kg^-1·min^-1, respectively. The range of 95% limits of agreement for the LEM was wider than that for the MRM. Fixed biases were not significant for both methods, and a significant proportional bias was observed only in the MRM. MRM bias was eliminated using the LEM application when the MRM-estimated VO_2max was ≥45 mL·kg^-1·min^-1. In conclusion, substantial proportional bias in the MRM may be mitigated using the LEM within a limited range.

SUBMITTER: Matsuo T

PROVIDER: S-EPMC9865627 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Improved VO2max Estimation by Combining a Multiple Regression Model and Linear Extrapolation Method.

Matsuo Tomoaki T So Rina R Murai Fumiko F

Journal of cardiovascular development and disease 20221227 1

Maximal oxygen consumption (VO2max) is an important health indicator that is often estimated using a multiple regression model (MRM) or linear extrapolation method (LEM) with the heart rate (HR) during a step test. Nonetheless, both methods have inherent problems. This study investigated a VO2max estimation method that mitigates the weaknesses of these two methods. A total of 128 adults completed anthropometric measurements, a physical activity questionnaire, a step test wi ...[more]

PMID: 36661904

Similar Datasets

Project description:BackgroundCardiorespiratory fitness (VO2max) is an excellent predictor of chronic disease morbidity and mortality risk. Guidelines recommend individuals undertake exercise training to improve VO2max for chronic disease reduction. However, there are large inter-individual differences between exercise training responses. This systematic review is aimed at identifying genetic variants that are associated with VO2max trainability.MethodsPeer-reviewed research papers published up until October 2016 from four databases were examined. Articles were included if they examined genetic variants, incorporated a supervised aerobic exercise intervention; and measured VO2max/VO2peak pre and post-intervention.ResultsThirty-five articles describing 15 cohorts met the criteria for inclusion. The majority of studies used a cross-sectional retrospective design. Thirty-two studies researched candidate genes, two used Genome-Wide Association Studies (GWAS), and one examined mRNA gene expression data, in addition to a GWAS. Across these studies, 97 genes to predict VO2max trainability were identified. Studies found phenotype to be dependent on several of these genotypes/variants, with higher responders to exercise training having more positive response alleles than lower responders (greater gene predictor score). Only 13 genetic variants were reproduced by more than two authors. Several other limitations were noted throughout these studies, including the robustness of significance for identified variants, small sample sizes, limited cohorts focused primarily on Caucasian populations, and minimal baseline data. These factors, along with differences in exercise training programs, diet and other environmental gene expression mediators, likely influence the ideal traits for VO2max trainability.ConclusionNinety-seven genes have been identified as possible predictors of VO2max trainability. To verify the strength of these findings and to identify if there are more genetic variants and/or mediators, further tightly-controlled studies that measure a range of biomarkers across ethnicities are required.

Dataset Information

Improved VO_2max Estimation by Combining a Multiple Regression Model and Linear Extrapolation Method.

Publications

Improved VO<sub>2max</sub> Estimation by Combining a Multiple Regression Model and Linear Extrapolation Method.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets