The DOI matches its Crossref record; 46 of the 47 references it cites were found in a registry or an index.
Long-term effects of low-fat diets either low or high in protein on cardiovascular and metabolic risk factors: a systematic review and meta-analysis
Open accessAbstract
BACKGROUND: Meta-analyses of short-term studies indicate favorable effects of higher protein vs. lower protein diets on health outcomes like adiposity or cardiovascular risk factors, but their long-term effects are unknown. METHODS: Electronic databases (MEDLINE, EMBASE, Cochrane Trial Register) were searched up to August 2012 with no restriction to language or calendar date. A random effect meta-analysis was performed using the Software package by the Cochrane Collaboration Review Manager 5.1. Sensitivity analysis was performed for RCTs with a Jadad Score ≥ 3, and excluding type 2 diabetic subjects (T2D). RESULTS: 15 RCTs met all objectives and were included in the present meta-analysis. No significant differences were observed for weight, waist circumference, fat mass, blood lipids (i.e. total cholesterol, LDL-cholesterol, HDL-cholesterol, triacylglycerols), C-reactive protein, diastolic and systolic blood pressure, fasting glucose and glycosylated hemoglobin. In contrast, improvements of fasting insulin was significantly more pronounced following high protein diets as compared to the low protein counterparts (weighted mean difference: -0.71 μIU/ml, 95% CI -1.36 to -0.05, p = 0.03). Sensitivity analysis of high quality RCTs confirmed the data of the primary analyses, while exclusion of studies with diabetic subjects resulted in an additional benefit of high-protein diets with respect to a more marked increase in HDL-cholesterol. CONCLUSION: According to the present meta-analysis of long-term RCTs, high-protein diets exerted neither specific beneficial nor detrimental effects on outcome markers of obesity, cardiovascular disease or glycemic control. Thus, it seems premature to recommend high-protein diets in the management of overweight and obesity.
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
Figures




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.
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
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & for the PRISMA Group (2009) · BMJ · doi:10.1136/bmj.b2535 · Cited by 83,823
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The PRISMA Group (2009) · PLoS Medicine · doi:10.1371/journal.pmed.1000097 · Cited by 64,042
Measuring inconsistency in meta-analyses
Higgins, J. P. T., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003) · BMJ · doi:10.1136/bmj.327.7414.557 · Cited by 63,139
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.
(2009) · PubMed Central · Cited by 44,859
The Cochrane Collaboration's tool for assessing risk of bias in randomised trials
Higgins, J. P. T., Altman, D. G., Gotzsche, P. C., Juni, P., Moher, D., Oxman, A. D., Savovic, J., Schulz, K. F., Weeks, L., Sterne, J. A. C., et al. (2011) · BMJ · doi:10.1136/bmj.d5928 · Cited by 33,817
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2009.06.005 · Cited by 19,575
Assessing the quality of reports of randomized clinical trials: Is blinding necessary?
Jadad, A. R., Moore, R. A., Carroll, D., Jenkinson, C., Reynolds, D. J. M., Gavaghan, D. J., & McQuay, H. J. (1996) · Controlled Clinical Trials · doi:10.1016/0197-2456(95)00134-4 · Cited by 17,582
Trumbo, P., Schlicker, S., Yates, A. A., & Poos, M. (2002) · Journal of the American Dietetic Association · doi:10.1016/s0002-8223(02)90346-9 · Cited by 5,993
Comparison of Weight-Loss Diets with Different Compositions of Fat, Protein, and Carbohydrates
Sacks, F. M., Bray, G. A., Carey, V. J., Smith, S. R., Ryan, D. H., Anton, S. D., McManus, K., Champagne, C. M., Bishop, L. M., Laranjo, N., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0804748 · Cited by 1,966 · cited 2×
“A total of 8/15 studies remained for sensitivity analyses [22,24,26,28,32,33,35,36].”
BackgroundDansinger, M. L., Gleason, J. A., Griffith, J. L., Selker, H. P., & Schaefer, E. J. (2005) · JAMA · doi:10.1001/jama.293.1.43 · Cited by 1,726
Research works printed but not linked: 1
- Higgins JP, Green S: Cochrane Handbook of systematic reviews, Version 5.1.0. 2011, updated March http://handbook.cochrane.org/ (accessed August 2012)
Cited by
Sorted by citations
Mozaffarian, D. (2016) · Circulation · doi:10.1161/circulationaha.115.018585 · Cited by 2,216
“In meta-analysis of randomized trials, increased protein consumption has little effect on cardiometabolic risk factors including adiposity, lipids, blood pressure, inflammation, or glucose.(385) Few longitudinal studies have reported on total protein intake and CHD events, with generally null results.”
Kinoshita, M., Yokote, K., Arai, H., Iida, M., Ishigaki, Y., Ishibashi, S., Umemoto, S., Egusa, G., Ohmura, H., Okamura, T., et al. (2018) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.gl2017 · Cited by 813
Franz, M. J., Boucher, J. L., Rutten-Ramos, S., & VanWormer, J. J. (2015) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2015.02.031 · Cited by 672
The role of protein in weight loss and maintenance
Leidy, H. J., Clifton, P. M., Astrup, A., Wycherley, T. P., Westerterp-Plantenga, M. S., Luscombe-Marsh, N. D., Woods, S. C., & Mattes, R. D. (2015) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.114.084038 · Cited by 475
Ge, L., Sadeghirad, B., Ball, G. D. C., da Costa, B. R., Hitchcock, C. L., Svendrovski, A., Kiflen, R., Quadri, K., Kwon, H. Y., Karamouzian, M., et al. (2020) · BMJ · doi:10.1136/bmj.m696 · Cited by 426
Metadata
- Authors
- Schwingshackl, L., & Hoffmann, G.
- Affiliations
- University of Vienna (AT)
- Corresponding author
- Schwingshackl, Lukas
- Venue
- Nutrition Journal
- Published
- 2013-04-15
- Volume
- 12
- Issue
- 1
- Pages
- 48-48
- ISSN
- 1475-2891 (ISSN-L)
- PMC
- PMC3636027
- OpenAlex
- W2160520777
- Cited by
- 184
- References
- 47
- Citations by year
- 2026: 4 · 2025: 11 · 2024: 11 · 2023: 15 · 2022: 8 · 2021: 16 · 2020: 16 · 2019: 11 · 2018: 14 · 2017: 19 · 2016: 18 · 2015: 18 · 2014: 19 · 2013: 2
- FWCI
- 2.09
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nutrition Journal (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Phaidra (Universität Wien) (submittedVersion, cc-by-nc-nd)
- Topics
- Health Sciences › Medicine › Physiology (medical) › Diet and metabolism studies
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Health Sciences › Nursing › Nutrition and Dietetics › Muscle metabolism and nutrition
- Keywords
- high-protein diet, low-fat diet, protein intake, cardiovascular risk factors, metabolic risk factors, fasting insulin, serum lipids, HDL cholesterol, obesity, weight, blood pressure, glycemic control, long-term dietary effects
- MeSH terms
- Blood Glucose, Blood Pressure, C-Reactive Protein, Cardiovascular Diseases, Dietary Proteins, Glycated Hemoglobin, Humans, Cholesterol, HDL, Cholesterol, LDL, Obesity, Risk Factors, Time Factors, Triglycerides, Biomarkers, Weight Loss, Randomized Controlled Trials as Topic, Databases, Factual, Diet, Fat-Restricted, Metabolic Syndrome, Glycemic Index, Waist Circumference
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