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Ketogenic diets, physical activity and body composition: a review

Ashtary-Larky, Damoon, Bagheri, Reza, Bavi, Hoda, Baker, Julien S., Moro, Tatiana, Mancin, Laura, Paoli, Antonio·2022·British Journal of Nutrition
DOI 10.1017/s0007114521002609PMC PMC9244428
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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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200 of 270 shown

Cited by

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
DOI
10.1017/s0007114521002609
PMC
PMC9244428
Cited by
100
References
111
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (unspecified)

About these checks

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.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.