Predicting adaptations to resistance training plus overfeeding using bayesian regression: A preliminary investigation

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dc.creatorSmith, Robert W. (TTU)
dc.creatorHarty, Patrick S. (TTU)
dc.creatorStratton, Matthew T. (TTU)
dc.creatorRafi, Zad
dc.creatorRodriguez, Christian (TTU)
dc.creatorDellinger, Jacob R. (TTU)
dc.creatorBenavides, Marqui L. (TTU)
dc.creatorJohnson, Baylor A. (TTU)
dc.creatorWhite, Sarah J. (TTU)
dc.creatorWilliams, Abegale D. (TTU)
dc.creatorTinsley, Grant M. (TTU)
dc.date.accessioned2023-05-11T18:49:03Z
dc.date.available2023-05-11T18:49:03Z
dc.date.issued2021
dc.description© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). cc-by
dc.description.abstractRelatively few investigations have reported purposeful overfeeding in resistance-trained adults. This preliminary study examined potential predictors of resistance training (RT) adaptations during a period of purposeful overfeeding and RT. Resistance-trained males (n = 28; n = 21 completers) were assigned to 6 weeks of supervised RT and daily consumption of a high-calorie protein/carbohydrate supplement with a target body mass (BM) gain of ≥0.45 kg·wk−1 . At baseline and post-intervention, body composition was evaluated via 4-component (4C) model and ultrasonography. Additional assessments of resting metabolism and muscular performance were performed. Accelerometry and automated dietary interviews estimated physical activity levels and nutrient intake before and during the intervention. Bayesian regression methods were employed to examine potential predictors of changes in body composition, muscular performance, and metabolism. A simplified regression model with only rate of BM gain as a predictor was also developed. Increases in 4C whole-body fat-free mass (FFM; (mean ± SD) 4.8 ± 2.6%), muscle thickness (4.5 ± 5.9% for elbow flexors; 7.4 ± 8.4% for knee extensors), and muscular performance were observed in nearly all individuals. However, changes in outcome variables could generally not be predicted with precision. Bayes R2 values for the models ranged from 0.18 to 0.40, and other metrics also indicated relatively poor predictive performance. On average, a BM gain of ~0.55%/week corresponded with a body composition score ((∆FFM/∆BM)*100) of 100, indicative of all BM gained as FFM. However, meaningful variability around this estimate was observed. This study offers insight regarding the complex interactions between the RT stimulus, overfeeding, and putative predictors of RT adaptations.
dc.identifier.citationSmith, R.W., Harty, P.S., Stratton, M.T., Rafi, Z., Rodriguez, C., Dellinger, J.R., Benavides, M.L., Johnson, B.A., White, S.J., Williams, A.D., & Tinsley, G.M.. 2021. Predicting adaptations to resistance training plus overfeeding using bayesian regression: A preliminary investigation. Journal of Functional Morphology and Kinesiology, 6(2). https://doi.org/10.3390/jfmk6020036
dc.identifier.urihttps://doi.org/10.3390/jfmk6020036
dc.identifier.urihttps://hdl.handle.net/2346/93459
dc.language.isoeng
dc.subjectBulking
dc.subjectCalorie surplus
dc.subjectEnergy surplus
dc.subjectHypertrophy
dc.subjectMuscle gain
dc.subjectWeight gain
dc.titlePredicting adaptations to resistance training plus overfeeding using bayesian regression: A preliminary investigation
dc.typeArticle

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