Literature DB >> 30850877

Prediction of maximal oxygen consumption using the Young Men's Christian Association-step test in Korean adults.

On Lee1, Sukho Lee2, Minsoo Kang3, Junbae Mun4, Jinwook Chung5.   

Abstract

PURPOSE: To develop accurate and practical prediction models of maximal oxygen consumption (VO2max) using the Young Men's Christian Association (YMCA)-step test in South Korean adults.
METHODS: In total, 568 adults (20-66 years) were included in this study. To develop and cross-validate prediction models of VO2max, the total sample was divided into 80% training and 20% testing using a simple random sampling method. VO2max was measured using the maximal-graded exercise treadmill test. Sex, age, 1-min recovery heart rate, body weight, and height were measured as potential predictors. Each test was conducted within a 2- to 3-day interval, ensuring sufficient rest. Preliminary prediction models were developed from training datasets, which were cross-validated using regression analyses and/or repeated-measures analysis of variance. The accuracy of prediction models was evaluated using R2, standard error of estimate (SEE), and mean difference (MD) against a criterion-measured VO2max.
RESULTS: The average age and VO2max were 43.5 ± 12.9 years and 39.1 ± 7.5 ml/kg/min, respectively. For model development, three practical models with acceptable accuracy were developed (R2 = 0.56-0.61; SEE = 4.74-5.01). For model cross-validation, significant relationships between the criterion-measured and predicted VO2max were observed in all three models (R2 = 0.56-0.61; SEE = 4.62-4.88). The difference between criterion-measured and predicted VO2max was not significant in the models (MD =- 0.03 to - 0.14).
CONCLUSIONS: The prediction models included 3-5 variables as significant predictors of VO2max and had acceptable accuracy in a large sample of South Korean adults. The selected models provide a simple and practical method to estimate VO2max using the YMCA-step test for South Korean adults.

Entities:  

Keywords:  Cross-validation; Prediction model; Submaximal exercise tests; VO2max

Mesh:

Year:  2019        PMID: 30850877     DOI: 10.1007/s00421-019-04115-8

Source DB:  PubMed          Journal:  Eur J Appl Physiol        ISSN: 1439-6319            Impact factor:   3.078


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