The DOI matches its Crossref record; 44 of the 46 references it cites were found in a registry or an index.
Ten-Hour Time-Restricted Eating Reduces Weight, Blood Pressure, and Atherogenic Lipids in Patients with Metabolic Syndrome
Open accessAbstract
In animal models, time-restricted feeding (TRF) can prevent and reverse aspects of metabolic diseases. Time-restricted eating (TRE) in human pilot studies reduces the risks of metabolic diseases in otherwise healthy individuals. However, patients with diagnosed metabolic syndrome often undergo pharmacotherapy, and it has never been tested whether TRE can act synergistically with pharmacotherapy in animal models or humans. In a single-arm, paired-sample trial, 19 participants with metabolic syndrome and a baseline mean daily eating window of ≥14 h, the majority of whom were on a statin and/or antihypertensive therapy, underwent 10 h of TRE (all dietary intake within a consistent self-selected 10 h window) for 12 weeks. We found this TRE intervention improves cardiometabolic health for patients with metabolic syndrome receiving standard medical care including high rates of statin and anti-hypertensive use. TRE is a potentially powerful lifestyle intervention that can be added to standard medical practice to treat metabolic syndrome. VIDEO ABSTRACT.
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?
The cited source says what the claim attributes to it.
In the citing paper
“Recent human trials on TRE have highlighted numerous beneficial metabolic effects of TRE, e.g., improved mean daily glucose levels (107, 108), fasting glucose levels (108–110), insulin resistance (108, 110, 111) or insulin sensitivity (112, 113), triglyceride levels (107, 109, 114, 115), total cholesterol (115, 116), and LDL cholesterol levels (116).”
From Meal timing and its role in obesity and associated diseases (2024) · cites this paper as [116]
The cited source says what the claim attributes to it.
In the citing paper
“The presence of MetS increases the risk of developing cardiovascular diseases (CVDs) twofold, and the risk of all-cause mortality by a factor of 1.5 [2, 3].”
From Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome (2025) · cites this paper as [3]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“The presence of MetS increases the risk of developing cardiovascular diseases (CVDs) twofold, and the risk of all-cause mortality by a factor of 1.5 [2, 3].”
From Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome (2025) · cites this paper as [3]
Experimental — accuracy not yet measured
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
1 retracted
Yuan, X., Zhu, C., Wang, M., Mo, F., Du, W., & Ma, X. (2018) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-17-0221 · Cited by 83
RetractedThe Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research
Buysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R., & Kupfer, D. J. (1989) · Psychiatry Research · doi:10.1016/0165-1781(89)90047-4 · Cited by 35,234
Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin
(2002) · New England Journal of Medicine · doi:10.1056/nejmoa012512 · Cited by 19,011
Alberti, K. G. M. M., Eckel, R. H., Grundy, S. M., Zimmet, P. Z., Cleeman, J. I., Donato, K. A., Fruchart, J.-C., James, W. P. T., Loria, C. M., & Smith, S. C. (2009) · Circulation · doi:10.1161/circulationaha.109.192644 · Cited by 14,860
Lloyd-Jones, D. M., Hong, Y., Labarthe, D., Mozaffarian, D., Appel, L. J., Van Horn, L., Greenlund, K., Daniels, S., Nichol, G., Tomaselli, G. F., et al. (2010) · Circulation · doi:10.1161/circulationaha.109.192703 · Cited by 4,750
National Sleep Foundation’s updated sleep duration recommendations: final report
Hirshkowitz, M., Whiton, K., Albert, S. M., Alessi, C., Bruni, O., DonCarlos, L., Hazen, N., Herman, J., Adams Hillard, P. J., Katz, E. S., et al. (2015) · Sleep Health · doi:10.1016/j.sleh.2015.10.004 · Cited by 2,348
Triglycerides and Cardiovascular Disease: A Scientific Statement From the American Heart Association
Miller, M., Stone, N. J., Ballantyne, C., Bittner, V., Criqui, M. H., Ginsberg, H. N., Goldberg, A. C., Howard, W. J., Jacobson, M. S., Kris-Etherton, P. M., et al. (2011) · Circulation · doi:10.1161/cir.0b013e3182160726 · Cited by 1,871
Sutton, E. F., Beyl, R., Early, K. S., Cefalu, W. T., Ravussin, E., & Peterson, C. M. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.04.010 · Cited by 1,531
Circadian physiology of metabolism
Panda, S. (2016) · Science · doi:10.1126/science.aah4967 · Cited by 1,092
Self-citationErvin, R. B. (2009) · PubMed · Cited by 1,000
Chaix, A., Zarrinpar, A., Miu, P., & Panda, S. (2014) · Cell Metabolism · doi:10.1016/j.cmet.2014.11.001 · Cited by 956 · cited 3×
“TRF is effective in reversing aspects of metabolic syndrome in mice in both sexes by reducing body weight, adiposity, glucose intolerance, plasma cholesterol, and plasma triglycerides (Chaix et al., 2014; Chung et al., 2016), and improving heart function in Drosophila (Gill et al.”
BackgroundSelf-citationGill, S., & Panda, S. (2015) · Cell Metabolism · doi:10.1016/j.cmet.2015.09.005 · Cited by 894
Self-citationTime for food: the intimate interplay between nutrition, metabolism, and the circadian clock
Asher, G., & Sassone-Corsi, P. (2015) · Cell · doi:10.1016/j.cell.2015.03.015 · Cited by 844
National Lipid Association Recommendations for Patient-Centered Management of Dyslipidemia: Part 2
Jacobson, T. A., Maki, K. C., Orringer, C. E., Jones, P. H., Kris-Etherton, P., Sikand, G., La Forge, R., Daniels, S. R., Wilson, D. P., Morris, P. B., et al. (2015) · Journal of Clinical Lipidology · doi:10.1016/j.jacl.2015.09.002 · Cited by 784
Moro, T., Tinsley, G., Bianco, A., Marcolin, G., Pacelli, Q. F., Battaglia, G., Palma, A., Gentil, P., Neri, M., & Paoli, A. (2016) · Journal of Translational Medicine · doi:10.1186/s12967-016-1044-0 · Cited by 732
St-Onge, M.-P., Ard, J., Baskin, M. L., Chiuve, S. E., Johnson, H. M., Kris-Etherton, P., & Varady, K. (2017) · Circulation · doi:10.1161/cir.0000000000000476 · Cited by 728
The Performance and Usability of a Factory-Calibrated Flash Glucose Monitoring System
Bailey, T., Bode, B. W., Christiansen, M. P., Klaff, L. J., & Alva, S. (2015) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2014.0378 · Cited by 685
Gabel, K., Hoddy, K. K., Haggerty, N., Song, J., Kroeger, C. M., Trepanowski, J. F., Panda, S., & Varady, K. A. (2018) · Nutrition and Healthy Aging · doi:10.3233/nha-170036 · Cited by 656
Self-citationShift work and cardiovascular disease – pathways from circadian stress to morbidity
Puttonen, S., Härmä, M., & Hublin, C. (2010) · Scandinavian Journal of Work, Environment & Health · doi:10.5271/sjweh.2894 · Cited by 560
Wei, M., Brandhorst, S., Shelehchi, M., Mirzaei, H., Cheng, C. W., Budniak, J., Groshen, S., Mack, W. J., Guen, E., Di Biase, S., et al. (2017) · Science Translational Medicine · doi:10.1126/scitranslmed.aai8700 · Cited by 553
Meal frequency and timing in health and disease
Mattson, M. P., Allison, D. B., Fontana, L., Harvie, M., Longo, V. D., Malaisse, W. J., Mosley, M., Notterpek, L. M., Ravussin, É., Scheer, F. A. J. L., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1413965111 · Cited by 552
Self-citationHutchison, A. T., Regmi, P., Manoogian, E. N. C., Fleischer, J. G., Wittert, G. A., Panda, S., & Heilbronn, L. K. (2019) · Obesity · doi:10.1002/oby.22449 · Cited by 466
Self-citationLunn, R. M., Blask, D. E., Coogan, A. N., Figueiro, M. G., Gorman, M. R., Hall, J. E., Hansen, J., Nelson, R. J., Panda, S., Smolensky, M. H., et al. (2017) · Science of The Total Environment · doi:10.1016/j.scitotenv.2017.07.056 · Cited by 402
Self-citationMedicine in the Fourth Dimension
Cederroth, C. R., Albrecht, U., Bass, J. T., Brown, S. A., Dyhrfjeld‐Johnsen, J., Gachon, F., Green, C. B., Hastings, M. H., Helfrich‐Förster, C., Hogenesch, J. B., et al. (2019) · Cell Metabolism · doi:10.1016/j.cmet.2019.06.019 · Cited by 374
Time‐restricted feeding in young men performing resistance training: A randomized controlled trial †
Tinsley, G. M., Forsse, J. S., Butler, N. K., Paoli, A., Bane, A. A., La Bounty, P. M., Morgan, G. B., & Grandjean, P. W. (2017) · European Journal of Sport Science · doi:10.1080/17461391.2016.1223173 · Cited by 307
The CardioMetabolic Health Alliance
Sperling, L. S., Mechanick, J. I., Neeland, I. J., Herrick, C. J., Després, J.-P., Ndumele, C. E., Vijayaraghavan, K., Handelsman, Y., Puckrein, G. A., Araneta, M. R. G., et al. (2015) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2015.06.1328 · Cited by 294
Sulli, G., Manoogian, E. N. C., Taub, P. R., & Panda, S. (2018) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2018.07.003 · Cited by 293
Self-citationTime-restricted feeding attenuates age-related cardiac decline in Drosophila
Gill, S., Le, H. D., Melkani, G. C., & Panda, S. (2015) · Science · doi:10.1126/science.1256682 · Cited by 272
Self-citationDaily eating patterns and their impact on health and disease
Zarrinpar, A., Chaix, A., & Panda, S. (2016) · Trends in Endocrinology & Metabolism · doi:10.1016/j.tem.2015.11.007 · Cited by 263
Self-citationZomer, E., Gurusamy, K., Leach, R., Trimmer, C., Lobstein, T., Morris, S., James, W. P. T., & Finer, N. (2016) · Obesity Reviews · doi:10.1111/obr.12433 · Cited by 236
Eating Meals Irregularly: A Novel Environmental Risk Factor for the Metabolic Syndrome
Sierra‐Johnson, J., Undén, A., Linestrand, M., Rosell, M., Sjogren, P., Kolak, M., De Faire, U., Fisher, R. M., & Hellénius, M. (2008) · Obesity · doi:10.1038/oby.2008.203 · Cited by 155
Antoni, R., Robertson, T. M., Robertson, M. D., & Johnston, J. D. (2018) · Journal of Nutritional Science · doi:10.1017/jns.2018.13 · Cited by 154
Chung, H., Chou, W., Sears, D. D., Patterson, R. E., Webster, N. J. G., & Ellies, L. G. (2016) · Metabolism · doi:10.1016/j.metabol.2016.09.006 · Cited by 149
Bhopal, R. S., Douglas, A., Wallia, S., Forbes, J. F., Lean, M. E. J., Gill, J. M. R., McKnight, J. A., Sattar, N., Sheikh, A., Wild, S. H., et al. (2014) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(13)70204-3 · Cited by 149
Weinsier, R. L., Wilson, L. J., & Lee, J. (1995) · The American Journal of Medicine · doi:10.1016/s0002-9343(99)80394-5 · Cited by 148
Pot, G. K., Almoosawi, S., & Stephen, A. M. (2016) · Proceedings of the Nutrition Society · doi:10.1017/s0029665116000239 · Cited by 134
The Healthy Living Partnerships to Prevent Diabetes Study
Katula, J. A., Vitolins, M. Z., Morgan, T. M., Lawlor, M. S., Blackwell, C. S., Isom, S. P., Pedley, C. F., & Goff, D. C. (2013) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2012.12.015 · Cited by 127
LeCheminant, J. D., Christenson, E., Bailey, B. W., & Tucker, L. A. (2013) · British Journal Of Nutrition · doi:10.1017/s0007114513001359 · Cited by 119
Gupta, N. J., Kumar, V., & Panda, S. (2017) · PLOS ONE · doi:10.1371/journal.pone.0172852 · Cited by 100
Self-citationSafety of 8-h time restricted feeding in adults with obesity
Gabel, K., Hoddy, K. K., & Varady, K. A. (2018) · Applied Physiology, Nutrition, and Metabolism · doi:10.1139/apnm-2018-0389 · Cited by 92
A Randomized Comparative Effectiveness Trial for Preventing Type 2 Diabetes
Ackermann, R. T., Liss, D. T., Finch, E. A., Schmidt, K., Hays, L. M., Marrero, D. G., & Saha, C. (2015) · American Journal of Public Health · doi:10.2105/ajph.2015.302641 · Cited by 82
Wennberg, M., Gustafsson, P. E., Wennberg, P., & Hammarström, A. (2016) · Public Health Nutrition · doi:10.1017/s1368980015001445 · Cited by 53
Mohebbi, I., Shateri, K., & Seyedmohammadzad, M. (2012) · International Journal of Occupational Medicine and Environmental Health · doi:10.2478/s13382-012-0051-5 · Cited by 50
Sleep Monitoring: A Comparison Between Three Wearable Instruments
van Wouwe, N. C., Valk, P. J. L., & Veenstra, B. (2011) · Military Medicine · doi:10.7205/milmed-d-10-00389 · Cited by 42
Cited by
Sorted by citations
Metabolic Inflammation and Insulin Resistance in Obesity
Wu, H., & Ballantyne, C. M. (2020) · Circulation Research · doi:10.1161/circresaha.119.315896 · Cited by 1,059
Targeting inflammation in atherosclerosis — from experimental insights to the clinic
Soehnlein, O., & Libby, P. (2021) · Nature Reviews Drug Discovery · doi:10.1038/s41573-021-00198-1 · Cited by 1,085
Type 2 diabetes mellitus in adults: pathogenesis, prevention and therapy
Lu, X., Xie, Q., Pan, X., Zhang, R., Zhang, X., Peng, G., Zhang, Y., Shen, S., & Tong, N. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01951-9 · Cited by 895
Mechanisms of Oxidative Stress in Metabolic Syndrome
Masenga, S. K., Kabwe, L. S., Chakulya, M., & Kirabo, A. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24097898 · Cited by 816
Epigenetic regulation of aging: implications for interventions of aging and diseases
Kang, W., Liu, H., Hu, Q., Wang, L., Liu, J., Zheng, Z., Zhang, W., Ren, J., Zhu, F., & Liu, G. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01211-8 · Cited by 732
Metadata
- Authors
- Wilkinson, M. J., Manoogian, E. N. C., Zadourian, A., Lo, H., Fakhouri, S., Shoghi, A., Wang, X., Fleischer, J. G., Navlakha, S., Panda, S., & Taub, P. R.
- Affiliations
- University of California San Diego (US)
- Salk Institute for Biological Studies (US)
- Corresponding author
- Panda, Satchidananda
- Taub, Pam R.
- ORCID
- Venue
- Cell Metabolism
- Publisher
- Elsevier BV
- Published
- 2020-01
- Volume
- 31
- Issue
- 1
- Pages
- 92-104.e5
- ISSN
- 1550-4131 (ISSN-L)
- PMC
- PMC6953486
- OpenAlex
- W2992787906
- Cited by
- 927
- References
- 46
- Citations by year
- 2026: 121 · 2025: 150 · 2024: 143 · 2023: 124 · 2022: 158 · 2021: 125 · 2020: 102
- FWCI
- 66.37
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell Metabolism (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- American Ceramic Circle
- Amgen
- National Institutes of Health (DK115214, DK118278)
- Novo Nordisk
- Merck
- U.S. Department of Defense (W81XWH1810645)
- American College of Cardiology Foundation
- U.S. Department of Homeland Security (EMW-2016-FP-00788)
- Leona M. and Harry B. Helmsley Charitable Trust (2012-PG-MED002)
- University of California, San Diego
- Larry L. Hillblom Foundation
- Robert Wood Johnson Foundation
- Topics
- Health Sciences › Medicine › Physiology (medical) › Dietary Effects on Health
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Health Sciences › Medicine › Physiology (medical) › Diet and metabolism studies
- Keywords
- time-restricted eating, metabolic syndrome, weight loss, blood pressure, atherogenic lipids, statin therapy, antihypertensive therapy, cardiometabolic health, lifestyle intervention
- MeSH terms
- Antihypertensive Agents, Blood Cell Count, Blood Glucose, Blood Pressure, Body Weight, Circadian Rhythm, Diabetes Mellitus, Type 2, Fasting, Female, Follow-Up Studies, Humans, Lipids, Male, Middle Aged, Obesity, Sleep, Exercise, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Metabolic Syndrome, Lipid Metabolism
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