The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Effect of Dietary Protein Content on Weight Gain, Energy Expenditure, and Body Composition During Overeating: A Randomized Controlled Trial
Open accessAbstract
CONTEXT: The role of diet composition in response to overeating and energy dissipation in humans is unclear. OBJECTIVE: To evaluate the effects of overconsumption of low, normal, and high protein diets on weight gain, energy expenditure, and body composition. DESIGN, SETTING, AND PARTICIPANTS: A single-blind, randomized controlled trial of 25 US healthy, weight-stable male and female volunteers, aged 18 to 35 years with a body mass index between 19 and 30. The first participant was admitted to the inpatient metabolic unit in June 2005 and the last in October 2007. INTERVENTION: After consuming a weight-stabilizing diet for 13 to 25 days, participants were randomized to diets containing 5% of energy from protein (low protein), 15% (normal protein), or 25% (high protein), which they were overfed during the last 8 weeks of their 10- to 12-week stay in the inpatient metabolic unit. Compared with energy intake during the weight stabilization period, the protein diets provided approximately 40% more energy intake, which corresponds to 954 kcal/d (95% CI, 884-1022 kcal/d). MAIN OUTCOME MEASURES: Body composition was measured by dual-energy x-ray absorptiometry biweekly, resting energy expenditure was measured weekly by ventilated hood, and total energy expenditure by doubly labeled water prior to the overeating and weight stabilization periods and at weeks 7 to 8. RESULTS: Overeating produced significantly less weight gain in the low protein diet group (3.16 kg; 95% CI, 1.88-4.44 kg) compared with the normal protein diet group (6.05 kg; 95% CI, 4.84-7.26 kg) or the high protein diet group (6.51 kg; 95% CI, 5.23-7.79 kg) (P = .002). Body fat increased similarly in all 3 protein diet groups and represented 50% to more than 90% of the excess stored calories. Resting energy expenditure, total energy expenditure, and body protein did not increase during overfeeding with the low protein diet. In contrast, resting energy expenditure (normal protein diet: 160 kcal/d [95% CI, 102-218 kcal/d]; high protein diet: 227 kcal/d [95% CI, 165-289 kcal/d]) and body protein (lean body mass) (normal protein diet: 2.87 kg [95% CI, 2.11-3.62 kg]; high protein diet: 3.18 kg [95% CI, 2.37-3.98 kg]) increased significantly with the normal and high protein diets. CONCLUSIONS: Among persons living in a controlled setting, calories alone account for the increase in fat; protein affected energy expenditure and storage of lean body mass, but not body fat storage. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00565149.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Over 12 weight-stable wk this led to 0.7 kg greater lean mass gain and fat loss compared to isoenergetic controls [33].”
From Dietary protein to maximize resistance training: a review and examination of protein spread and change theories (2012) · cites this paper as [33]
In the citing paper
“Soenen et al. had participants increase habitual protein intake 16%, from 1.13 g/kg/day to 1.31 g/kg/day via substitution of ~500 kcal with a milk protein based supplement containing 52 g protein.”
From Dietary protein to maximize resistance training: a review and examination of protein spread and change theories (2012) · cites this paper as [33]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Prevalence and Trends in Obesity Among US Adults, 1999-2008
Flegal, K. M. (2010) · JAMA · doi:10.1001/jama.2009.2014 · Cited by 7,580
Prevalence of High Body Mass Index in US Children and Adolescents, 2007-2008
Ogden, C. L. (2010) · JAMA · doi:10.1001/jama.2009.2012 · Cited by 3,200
Pocock, S. J., & Simon, R. (1975) · Biometrics · doi:10.2307/2529712 · Cited by 2,350
Long-term persistence of hormonal adaptations to weight loss
Sumithran, P., Prendergast, L. A., Delbridge, E., Purcell, K., Shulkes, A., Kriketos, A., & Proietto, J. (2011) · New England Journal of Medicine · doi:10.1056/nejmoa1105816 · Cited by 1,449
Church, T. S., Thomas, D. M., Tudor-Locke, C., Katzmarzyk, P. T., Earnest, C. P., Rodarte, R. Q., Martin, C. K., Blair, S. N., & Bouchard, C. (2011) · PLoS ONE · doi:10.1371/journal.pone.0019657 · Cited by 1,294
Self-citationRole of Nonexercise Activity Thermogenesis in Resistance to Fat Gain in Humans
Levine, J. A., Eberhardt, N. L., & Jensen, M. D. (1999) · Science · doi:10.1126/science.283.5399.212 · Cited by 997
Minimization: A new method of assigning patients to treatment and control groups
Taves, D. R. (1974) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt1974155443 · Cited by 891
The Effects of High Protein Diets on Thermogenesis, Satiety and Weight Loss: A Critical Review
Halton, T. L., & Hu, F. B. (2004) · Journal of the American College of Nutrition · doi:10.1080/07315724.2004.10719381 · Cited by 822
Relationship of genetics, age, and physical fitness to daily energy expenditure and fuel utilization
Ravussin, É., & Bogardus, C. (1989) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/49.5.968 · Cited by 615
Measurement of Energy Expenditure in Free-Living Humans by Using Doubly Labeled Water
Schoeller, D. A. (1988) · Journal of Nutrition · doi:10.1093/jn/118.11.1278 · Cited by 603
Flagged first, then by citations
Research works printed but not linked: 2
- [13]Goldman R Haisman M Bynum G Horton E Sims E Bray GA Experimental obesity in man: metabolic rate in relation to dietary intake Obesity in Perspective: A Conference 1975 165 186 US Government Printing Office Washington, DC
- [31]Flatt JP Bray GA The biochemistry of energy expenditure Recent Advances in Obesity Research: II. Proceedings of the 2nd International Congress on Obesity 1978 211 228 Newman Publishing London, England
Cited by
Sorted by citations
A New Body Shape Index Predicts Mortality Hazard Independently of Body Mass Index
Krakauer, N. Y., & Krakauer, J. C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0039504 · Cited by 1,357
The science of obesity management: an endocrine society scientific statement
Bray, G. A., Heisel, W. E., Afshin, A., Jensen, M. D., Dietz, W. H., Long, M., Kushner, R. F., Daniels, S. R., Wadden, T. A., Tsai, A. G., et al. (2018) · Endocrine Reviews · doi:10.1210/er.2017-00253 · Cited by 812
Self-citationGlobal Gender Disparities in Obesity: A Review
Kanter, R., & Caballero, B. H. (2012) · Advances in Nutrition · doi:10.3945/an.112.002063 · Cited by 680
“However, a recent randomized, controlled trial in healthy American adults who overate during the experiment showed that increased energy intake as a result of greater protein intake does not affect fat mass, but rather fat-free mass (32).”
FGF21 is an endocrine signal of protein restriction
Laeger, T., Henagan, T. M., Albarado, D. C., Redman, L. M., Bray, G. A., Noland, R. C., Münzberg, H., Hutson, S. M., Gettys, T. W., Schwartz, M. W., et al. (2014) · Journal of Clinical Investigation · doi:10.1172/jci74915 · Cited by 593
Self-citationGDF15 Provides an Endocrine Signal of Nutritional Stress in Mice and Humans
Patel, S., Alvarez-Guaita, A., Melvin, A., Rimmington, D., Dattilo, A., Miedzybrodzka, E. L., Cimino, I., Maurin, A.-C., Roberts, G. P., Meek, C. L., et al. (2019) · Cell Metabolism · doi:10.1016/j.cmet.2018.12.016 · Cited by 509
Self-citation
Metadata
- Authors
- Bray, G. A., Smith, S. R., de Jonge, L., Xie, H., Rood, J., Martin, C. K., Most, M., Brock, C., Mancuso, S., & Redman, L. M.
- Affiliations
- Pennington Biomedical Research Center (US)
- Corresponding author
- Bray, George A.
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2012-01-04
- Volume
- 307
- Issue
- 1
- Pages
- 47
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- PMC
- PMC3777747
- OpenAlex
- W2151035323
- Semantic Scholar
- 35084a4991db22c42be3fd1b5b7641943f3ce15e
- Cited by
- 285
- References
- 32
- Citations by year
- 2026: 17 · 2025: 13 · 2024: 5 · 2023: 6 · 2022: 19 · 2021: 19 · 2020: 27 · 2019: 24 · 2018: 19 · 2017: 20 · 2016: 23 · 2015: 18 · 2014: 26 · 2013: 25 · 2012: 24
- FWCI
- 13.17
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Louisiana State University
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK072476)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R00HD060762)
- Topics
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Regulation of Appetite and Obesity
- Health Sciences › Nursing › Nutrition and Dietetics › Muscle metabolism and nutrition
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diet, Metabolism, and Disease
- Keywords
- dietary protein level, overeating, overfeeding, weight gain, energy expenditure, resting energy expenditure, total energy expenditure, body composition, fat mass, protein intake, energy balance, fat-free mass, lean body mass, fat-free mass index, fat mass index, body mass index, body age
- MeSH terms
- Adipose Tissue, Adolescent, Adult, Body Composition, Dietary Proteins, Energy Metabolism, Female, Humans, Hyperphagia, Male, Weight Gain, Single-Blind Method, Young Adult
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 ›
Are you an author, or do you see a problem with this page? Request a review