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Ketogenic diets, physical activity and body composition: a review
Abstract
Obesity remains a serious relevant public health concern throughout the world despite related countermeasures being well understood (i.e. mainly physical activity and an adjusted diet). Among different nutritional approaches, there is a growing interest in ketogenic diets (KD) to manipulate body mass (BM) and to enhance fat mass loss. KD reduce the daily amount of carbohydrate intake drastically. This results in increased fatty acid utilisation, leading to an increase in blood ketone bodies (acetoacetate, 3- β -hydroxybutyrate and acetone) and therefore metabolic ketosis. For many years, nutritional intervention studies have focused on reducing dietary fat with little or conflicting positive results over the long term. Moreover, current nutritional guidelines for athletes propose carbohydrate-based diets to augment muscular adaptations. This review discusses the physiological basis of KD and their effects on BM reduction and body composition improvements in sedentary individuals combined with different types of exercise (resistance training or endurance training) in individuals with obesity and athletes. Ultimately, we discuss the strengths and the weaknesses of these nutritional interventions together with precautionary measures that should be observed in both individuals with obesity and athletic populations. A literature search from 1921 to April 2021 using Medline, Google Scholar, PubMed, Web of Science, Scopus and Sportdiscus Databases was used to identify relevant studies. In summary, based on the current evidence, KD are an efficient method to reduce BM and body fat in both individuals with obesity and athletes. However, these positive impacts are mainly because of the appetite suppressive effects of KD, which can decrease daily energy intake. Therefore, KD do not have any superior benefits to non-KD in BM and body fat loss in individuals with obesity and athletic populations in an isoenergetic situation. In sedentary individuals with obesity, it seems that fat-free mass (FFM) changes appear to be as great, if not greater, than decreases following a low-fat diet. In terms of lean mass, it seems that following a KD can cause FFM loss in resistance-trained individuals. In contrast, the FFM-preserving effects of KD are more efficient in endurance-trained compared with resistance-trained individuals.
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“These findings serve to strengthen the larger body of evidence that KDs excel in fat mass reduction, but are suboptimal for lean mass preservation [166].”
From International Society of Sports Nutrition position stand: diets for body weight reduction (2026) · cites this paper as [166]
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Cited by
Patikorn, C., Saidoung, P., Pham, T., Phisalprapa, P., Lee, Y. Y., Varady, K. A., Veettil, S. K., & Chaiyakunapruk, N. (2023) · BMC Medicine · doi:10.1186/s12916-023-02874-y · Cited by 101
Volek, J. S., Kackley, M. L., & Buga, A. (2024) · Current Nutrition Reports · doi:10.1007/s13668-024-00548-6 · Cited by 48
Schiavo, L., Santella, B., Mingo, M., Rossetti, G., Orio, M., Cobellis, L., Maurano, A., Iannelli, A., & Pilone, V. (2025) · Nutrients · doi:10.3390/nu17071216 · Cited by 22
International Society of Sports Nutrition position stand: diets for body weight reduction
Aragon, A. A., Campbell, B. I., Schoenfeld, B. J., Stout, J. R., Kalman, D., Arciero, P. J., Arent, S. M., Kreider, R. B., Taylor, L. W., Bannock, L., et al. (2026) · Journal of the International Society of Sports Nutrition · doi:10.1080/15502783.2026.2740266
Metadata
- Authors
- Ashtary-Larky, D., Bagheri, R., Bavi, H., Baker, J. S., Moro, T., Mancin, L., & Paoli, A.
- ORCID
- Moro, Tatiana
- Venue
- British Journal of Nutrition
- Publisher
- Cambridge University Press (CUP)
- Published
- 2021-07-12
- Volume
- 127
- Issue
- 12
- Pages
- 1898-1920
- ISSN
- 0007-1145
- 1475-2662
- PMC
- PMC9244428
- Cited by
- 100
- References
- 111
- Language
- en
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.