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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA)
Rachmad Suhanda
Syiah Kuala University
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Materials Science & Nanotechnology Physics

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Standardization of VO₂max Predictive Models Based on Body Composition in Endurance Sports: A Systematic Review Yuni Rahmayanti; Nyak Amir; Zulkarnain; Rachmad Suhanda
Jurnal Penelitian Pendidikan IPA Vol 12 No 3 (2026): In Progress
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i3.13822

Abstract

VO₂max is the main indicator of aerobic capacity that is widely used in endurance sports. However, direct measurement of VO₂max requires special equipment and laboratory conditions that are not always available in the field. This study aims to examine the predictive model of VO₂max based on body composition through a systematic literature review approach. Data were obtained from four scientific databases (Scopus, PubMed, Web of Science, and Google Scholar) with a publication range of 2013–2025. The selection process followed the PRISMA guidelines with inclusion criteria of human population-based quantitative studies and the use of body parameters as predictors of VO₂max. A total of 15 articles met the criteria and were analyzed narratively. The results showed that parameters such as fat-free mass (FFM), body fat percentage (BF%), and body mass index (BMI) were the most commonly used variables. Linear regression and machine learning approaches were the dominant statistical methods. Although these approaches are potential, a universal model has not been found due to variations in population, measurement methods, and training conditions. This study recommends the development of population-specific predictive models and the integration of anthropometric data, biomarkers, and exercise response to improve model accuracy and applicability.
Co-Authors Nyak Amir Yuni Rahmayanti Zulkarnain