Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ASCO Annual Meeting 2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

2024 ASCO Annual Meeting

Keep up to date with all the top stories and latest evidence with our hub page, including official congress videos and expert takeaways.
ADVANCED SEARCH
Log in
Top
Trials
Published in: Trials 1/2022

Open Access 01-12-2022 | Obesity | Study protocol

Comparison of weight loss induced by daily caloric restriction versus intermittent fasting (DRIFT) in individuals with obesity: study protocol for a 52-week randomized clinical trial

Authors: Danielle M. Ostendorf, Ann E. Caldwell, Adnin Zaman, Zhaoxing Pan, Kristen Bing, Liza T. Wayland, Seth A. Creasy, Daniel H. Bessesen, Paul MacLean, Edward L. Melanson, Victoria A. Catenacci

Published in: Trials | Issue 1/2022

Login to get access

Abstract

Background

The standard of care for treating overweight and obesity is daily caloric restriction (DCR). While this approach produces modest weight loss, adherence to DCR declines over time and weight regain is common. Intermittent fasting (IMF) is an alternative dietary strategy for reducing energy intake (EI) that involves >60% energy restriction on 2–3 days per week, or on alternate days, with habitual intake on fed days. While numerous studies have evaluated IMF as a weight loss strategy, there are several limitations including lack of a standard-of-care DCR control, failure to provide guideline-based behavioral support, and failure to rigorously evaluate dietary and PA adherence using objective measures. To date, only three longer-term (52-week) trials have evaluated IMF as a weight loss strategy. None of these longer-duration studies reported significant differences between IMF and DCR in changes in weight. However, each of these studies has limitations that prohibit drawing generalizable conclusions about the relative long-term efficacy of IMF vs. DCR for obesity treatment.

Methods

The Daily Caloric Restriction vs. Intermittent Fasting Trial (DRIFT) is a two-arm, 52-week block randomized (1:1) clinical weight loss trial. The two intervention arms (DCR and IMF) are designed to prescribe an equivalent average weekly energy deficit from baseline weight maintenance energy requirements. Both DCR and IMF will be provided guideline-based behavioral support and a PA prescription. The primary outcome is change in body weight at 52 weeks. Secondary outcomes include changes in body composition (dual-energy x-ray absorptiometry (DXA)), metabolic parameters, total daily energy expenditure (TDEE, doubly labeled water (DLW)), EI (DLW intake-balance method, 7-day diet diaries), and patterns of physical activity (PA, activPAL device).

Discussion

Although DCR leads to modest weight loss success in the short-term, there is wide inter-individual variability in weight loss and poor long-term weight loss maintenance. Evidence-based dietary approaches to energy restriction that are effective long-term are needed to provide a range of evidence-based options to individuals seeking weight loss. The DRIFT study will evaluate the long-term effectiveness of IMF vs. DCR on changes in objectively measured weight, EI, and PA, when these approaches are delivered using guideline-based behavioral support and PA prescriptions.
Appendix
Available only for authorised users
Literature
1.
Julia C, Peneau S, Andreeva VA, Mejean C, Fezeu L, Galan P, et al. Weight-loss strategies used by the general population: how are they perceived? PLoS One. 2014;9(5):e97834.PubMedPubMedCentralCrossRef
2.
Dansinger ML, Gleason JA, Griffith JL, Selker HP, Schaefer EJ. Comparison of the Atkins, Ornish, weight watchers, and zone diets for weight loss and heart disease risk reduction: a randomized trial. Jama. 2005;293(1):43–53.PubMedCrossRef
3.
Anderson JW, Konz EC, Frederich RC, Wood CL. Long-term weight-loss maintenance: a meta-analysis of US studies. Am J Clin Nutr. 2001;74(5):579–84.PubMedCrossRef
4.
Franz MJ, VanWormer JJ, Crain AL, Boucher JL, Histon T, Caplan W, et al. Weight-loss outcomes: a systematic review and meta-analysis of weight-loss clinical trials with a minimum 1-year follow-up. J Am Diet Assoc. 2007;107(10):1755–67.PubMedCrossRef
5.
MacLean PS, Wing RR, Davidson T, Epstein L, Goodpaster B, Hall KD, et al. NIH working group report: innovative research to improve maintenance of weight loss. Obesity (Silver Spring, Md). 2015;23(1):7–15.CrossRef
6.
Johnston BC, Kanters S, Bandayrel K, Wu P, Naji F, Siemieniuk RA, et al. Comparison of weight loss among named diet programs in overweight and obese adults: a meta-analysis. JAMA. 2014;312(9):923–33.PubMedCrossRef
7.
8.
9.
Johnstone A. Fasting for weight loss: an effective strategy or latest dieting trend? Int J Obes. 2015;39(5):727–33.CrossRef
10.
Patterson RE, Laughlin GA, LaCroix AZ, Hartman SJ, Natarajan L, Senger CM, et al. Intermittent fasting and human metabolic health. J Acad Nutr Diet. 2015;115(8):1203–12.PubMedPubMedCentralCrossRef
11.
12.
Mattson MP, Allison DB, Fontana L, Harvie M, Longo VD, Malaisse WJ, et al. Meal frequency and timing in health and disease. Proc Natl Acad Sci U S A. 2014;111(47):16647–53.PubMedPubMedCentralCrossRef
13.
Mattson MP, Longo VD, Harvie M. Impact of intermittent fasting on health and disease processes. Ageing Res Rev. 2017;39:46–58.PubMedCrossRef
14.
Rynders CA, Thomas EA, Zaman A, Pan Z, Catenacci VA, Melanson EL. Effectiveness of intermittent fasting and time-restricted feeding compared to continuous energy restriction for weight loss. Nutrients. 2019;11(10).
15.
Catenacci VA, Pan Z, Ostendorf D, Brannon S, Gozansky WS, Mattson MP, et al. A randomized pilot study comparing zero-calorie alternate-day fasting to daily caloric restriction in adults with obesity. Obesity. 2016;24(9):1874–83.PubMedCrossRef
16.
Welton S, Minty R, O'Driscoll T, Willms H, Poirier D, Madden S, et al. Intermittent fasting and weight loss: systematic review. Can Fam Physician. 2020;66(2):117–25.PubMedPubMedCentral
17.
Jensen MD, Ryan DH, Apovian CM, Ard JD, Comuzzie AG, Donato KA, et al. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association task force on practice guidelines and the Obesity Society. Circulation. 2014;129(25 Suppl 2):S102–38.PubMed
18.
19.
20.
Headland ML, Clifton PM, Keogh JB. Effect of intermittent compared to continuous energy restriction on weight loss and weight maintenance after 12 months in healthy overweight or obese adults. Int J Obes. 2019;43(10):2028–36.CrossRef
21.
Carter S, Clifton PM, Keogh JB. Effect of intermittent compared with continuous energy restricted diet on glycemic control in patients with type 2 diabetes: a randomized noninferiority trial. JAMA Netw Open. 2018;1(3):e180756.PubMedPubMedCentralCrossRef
22.
Carter S, Clifton PM, Keogh JB. The effect of intermittent compared with continuous energy restriction on glycaemic control in patients with type 2 diabetes: 24-month follow-up of a randomised noninferiority trial. Diabetes Res Clin Pract. 2019;151:11–9.PubMedCrossRef
23.
Franz MJ, Boucher JL, Rutten-Ramos S, VanWormer JJ. Lifestyle weight-loss intervention outcomes in overweight and obese adults with type 2 diabetes: a systematic review and meta-analysis of randomized clinical trials. J Acad Nutr Diet. 2015;115(9):1447–63.PubMedCrossRef
24.
Lytle LA, Nicastro HL, Roberts SB, Evans M, Jakicic JM, Laposky AD, et al. Accumulating data to optimally predict obesity treatment (ADOPT) core measures: behavioral domain. Obesity. 2018;26(Suppl 2):S16–24.PubMedCrossRef
25.
MacLean PS, Rothman AJ, Nicastro HL, Czajkowski SM, Agurs-Collins T, Rice EL, et al. The accumulating data to optimally predict obesity treatment (ADOPT) core measures project: rationale and approach. Obesity. 2018;26(Suppl 2):S6–S15.PubMedCrossRef
26.
Rosenbaum M, Agurs-Collins T, Bray MS, Hall KD, Hopkins M, Laughlin M, et al. Accumulating data to optimally predict obesity treatment (ADOPT): recommendations from the biological domain. Obesity. 2018;26(Suppl 2):S25–34.PubMedCrossRef
27.
Saelens BE, Arteaga SS, Berrigan D, Ballard RM, Gorin AA, Powell-Wiley TM, et al. Accumulating data to optimally predict obesity treatment (ADOPT) core measures: environmental domain. Obesity. 2018;26(Suppl 2):S35–44.PubMedCrossRef
28.
Sutin AR, Boutelle K, Czajkowski SM, Epel ES, Green PA, Hunter CM, et al. Accumulating data to optimally predict obesity treatment (ADOPT) core measures: psychosocial domain. Obesity. 2018;26(Suppl 2):S45–54.PubMedCrossRef
29.
Thomas S, Reading J, Shephard RJ. Revision of the physical activity readiness questionnaire (PAR-Q). Can J Sport Sci. 1992;17(4):338–45.PubMed
30.
Beck AT, Steer RA, Garbin GM. Psychometric properties of the Beck depression inventory: twenty-five years of evaluation. Clin Psychol Rev. 1988;8:77–100.CrossRef
31.
Garner DM, Olmsted MP, Bohr Y, Garfinkel PE. The eating attitudes test: psychometric features and clinical correlates. Psychol Med. 1982;12(4):871–8.PubMedCrossRef
32.
Spitzer RL, Devlin M, Walsh BT, Hasin D, Wing R, Marcus M, et al. Binge eating disorder: a multi-site field trial of the diagnostic criteria. Int J Eat Disord. 1992;11:191–203.CrossRef
33.
Spitzer RL, Yanovski S, Wadden T, Wing R, Marcus MD, Stunkard A, et al. Binge eating disorder: its further validation in a multisite study. Int J Eat Disord. 1993;13(2):137–53.PubMedCrossRef
34.
U.S. Department of Health and Human Services. Physical activity Guidelines for Americans. In: U.S. Department of Health and Human Services, editor. 2nd. Washington, DC: 2018.
35.
Human energy requirements: report of a joint FAO/WHO/UNU expert consultation. Food Nutr Bull. 2005;26(1):166.
36.
Hoddy KK, Kroeger CM, Trepanowski JF, Barnosky A, Bhutani S, Varady KA. Meal timing during alternate day fasting: impact on body weight and cardiovascular disease risk in obese adults. Obesity. 2014;22(12):2524–31.PubMedCrossRef
37.
Heilbronn LK, Smith SR, Martin CK, Anton SD, Ravussin E. Alternate-day fasting in nonobese subjects: effects on body weight, body composition, and energy metabolism. Am J Clin Nutr. 2005;81(1):69–73.PubMedCrossRef
38.
Klempel MC, Bhutani S, Fitzgibbon M, Freels S, Varady KA. Dietary and physical activity adaptations to alternate day modified fasting: implications for optimal weight loss. Nutr J. 2010;9:35.PubMedPubMedCentralCrossRef
39.
Bhutani S, Klempel MC, Kroeger CM, Aggour E, Calvo Y, Trepanowski JF, et al. Effect of exercising while fasting on eating behaviors and food intake. J Int Soc Sports Nutr. 2013;10(1):50.PubMedPubMedCentralCrossRef
40.
Hoddy KK, Gibbons C, Kroeger CM, Trepanowski JF, Barnosky A, Bhutani S, et al. Changes in hunger and fullness in relation to gut peptides before and after 8 weeks of alternate day fasting. Clin Nutr. 2016;35(6):1380–5.PubMedCrossRef
41.
Johnson JB, Summer W, Cutler RG, Martin B, Hyun DH, Dixit VD, et al. Alternate day calorie restriction improves clinical findings and reduces markers of oxidative stress and inflammation in overweight adults with moderate asthma. Free Radic Biol Med. 2007;42(5):665–74.PubMedCrossRef
42.
Antoni R, Johnston KL, Collins AL, Robertson MD. Investigation into the acute effects of total and partial energy restriction on postprandial metabolism among overweight/obese participants. Br J Nutr. 2016;115(6):951–9.PubMedCrossRef
43.
Donnelly JE, Blair SN, Jakicic JM, Manore MM, Rankin JW, Smith BK. American College of Sports Medicine position stand. Appropriate physical activity intervention strategies for weight loss and prevention of weight regain for adults. Med Sci Sports Exerc. 2009;41(2):459–71.PubMedCrossRef
44.
Peters JC, Wyatt HR, Foster GD, Pan Z, Wojtanowski AC, Vander Veur SS, et al. The effects of water and non-nutritive sweetened beverages on weight loss during a 12-week weight loss treatment program. Obesity. 2014;22(6):1415–21.PubMedCrossRef
45.
Wyatt HR, Jortberg BT, Babbel C, Garner S, Dong F, Grunwald GK, et al. Weight loss in a community initiative that promotes decreased energy intake and increased physical activity and dairy consumption: calcium weighs-in. J Phys Act Health. 2008;5(1):28–44.PubMedCrossRef
46.
47.
Berman ES, Fortson SL, Snaith SP, Gupta M, Baer DS, Chery I, et al. Direct analysis of delta2H and delta18O in natural and enriched human urine using laser-based, off-axis integrated cavity output spectroscopy. Anal Chem. 2012;84(22):9768–73.PubMedPubMedCentralCrossRef
48.
Speakman JR, Yamada Y, Sagayama H, Berman ESF, Ainslie PN, Andersen LF, et al. A standard calculation methodology for human doubly labeled water studies. Cell Rep Med. 2021;2(2):100203.PubMedPubMedCentralCrossRef
49.
Racette SB, Das SK, Bhapkar M, Hadley EC, Roberts SB, Ravussin E, et al. Approaches for quantifying energy intake and %calorie restriction during calorie restriction interventions in humans: the multicenter CALERIE study. Am J Physiol Endocrinol Metab. 2012;302(4):E441–8.PubMedCrossRef
50.
Schoeller DA. The energy balance equation: looking back and looking forward are two very different views. Nutr Rev. 2009;67(5):249–54.PubMedCrossRef
51.
Godfrey A, Culhane KM, Lyons GM. Comparison of the performance of the activPAL professional physical activity logger to a discrete accelerometer-based activity monitor. Med Eng Phys. 2007;29(8):930–4.PubMedCrossRef
52.
Grant PM, Ryan CG, Tigbe WW, Granat MH. The validation of a novel activity monitor in the measurement of posture and motion during everyday activities. Br J Sports Med. 2006;40(12):992–7.PubMedPubMedCentralCrossRef
53.
Kozey-Keadle S, Libertine A, Lyden K, Staudenmayer J, Freedson PS. Validation of wearable monitors for assessing sedentary behavior. Med Sci Sports Exerc. 2011;43(8):1561–7.PubMedCrossRef
54.
Ryan CG, Grant PM, Tigbe WW, Granat MH. The validity and reliability of a novel activity monitor as a measure of walking. Br J Sports Med. 2006;40(9):779–84.PubMedPubMedCentralCrossRef
55.
Lyden K, Keadle SK, Staudenmayer J, Freedson PS. The activPAL TM accurately classifies activity intensity categories in healthy adults. Med Sci Sports Exerc. 2017;49(5):1022–8.PubMedPubMedCentralCrossRef
56.
Mano H, Oliver RL. Assessing the dimensionality and structure of the consumption experience - evaluation, feeling, and satisfaction. J Consum Res. 1993;20(3):451–66.CrossRef
57.
Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J Pers Soc Psychol. 1988;54(6):1063–70.PubMedCrossRef
58.
Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385–96.PubMedCrossRef
59.
Jarvela-Reijonen E, Karhunen L, Sairanen E, Rantala S, Laitinen J, Puttonen S, et al. High perceived stress is associated with unfavorable eating behavior in overweight and obese Finns of working age. Appetite. 2016;103:249–58.PubMedCrossRef
60.
Lee EH. Review of the psychometric evidence of the perceived stress scale. Asian Nurs Res (Korean Soc Nurs Sci). 2012;6(4):121–7.
61.
Boggiano MM, Wenger LE, Turan B, Tatum MM, Sylvester MD, Morgan PR, et al. Real-time sampling of reasons for hedonic food consumption: further validation of the palatable eating motives scale. Front Psychol. 2015;6:744.PubMedPubMedCentralCrossRef
62.
Burgess EE, Turan B, Lokken KL, Morse A, Boggiano MM. Profiling motives behind hedonic eating. Preliminary validation of the palatable eating motives scale. Appetite. 2014;72:66–72.PubMedCrossRef
63.
Duarte C, Pinto-Gouveia J, Ferreira C. Expanding binge eating assessment: validity and screening value of the binge eating scale in women from the general population. Eat Behav. 2015;18:41–7.PubMedCrossRef
64.
Mason AE, Vainik U, Acree M, Tomiyama AJ, Dagher A, Epel ES, et al. Improving assessment of the spectrum of reward-related eating: the RED-13. Front Psychol. 2017;8:795.PubMedPubMedCentralCrossRef
65.
Cappelleri JC, Bushmakin AG, Gerber RA, Leidy NK, Sexton CC, Lowe MR, et al. Psychometric analysis of the three-factor eating questionnaire-R21: results from a large diverse sample of obese and non-obese participants. Int J Obes. 2009;33(6):611–20.CrossRef
66.
Markland D, Tobin V. A modification of the behavioral regulation in exercise questionnaire to include an assessment of amotivation. J Sport Exercise Psy. 2004;26:191–6.CrossRef
67.
Wilson PM, Rodgers WM, Loitz CC, Scime G. “It’s who I am … really!” The importance of integrated regulation in exercise contexts1. J Appl Biobehav Res. 2006;11(2):79–104.CrossRef
68.
Duckworth AL, Quinn PD. Development and validation of the short grit scale (grit-s). J Pers Assess. 2009;91(2):166–74.PubMedCrossRef
69.
Levesque CS, Williams GC, Elliot D, Pickering MA, Bodenhamer B, Finley PJ. Validating the theoretical structure of the treatment self-regulation questionnaire (TSRQ) across three different health behaviors. Health Educ Res. 2007;22(5):691–702.PubMedCrossRef
70.
Donnellan MB, Oswald FL, Baird BM, Lucas RE. The mini-IPIP scales: tiny-yet-effective measures of the big five factors of personality. Psychol Assess. 2006;18(2):192–203.PubMedCrossRef
71.
McAuley E. The role of efficacy cognitions in the prediction of exercise behavior in middle-aged adults. J Behav Med. 1992;15(1):65–88.PubMedCrossRef
72.
Ames GE, Heckman MG, Grothe KB, Clark MM. Eating self-efficacy: development of a short-form WEL. Eat Behav. 2012;13(4):375–8.PubMedCrossRef
73.
Grove JR, Prapavessis H. Preliminary evidence for the reliability and validity of an abbreviated profile of mood states. Int J Sport Psychol. 1992;23(2):93–109.
74.
Hays RD, Morales LS. The RAND-36 measure of health-related quality of life. Ann Med. 2001;33(5):350–7.PubMedCrossRef
75.
Hays RD, Sherbourne CD, Mazel RM. The RAND 36-item health survey 1.0. Health Econ. 1993;2(3):217–27.PubMedCrossRef
76.
Norbeck JS. Modification of life event questionnaires for use with female respondents. Res Nurs Health. 1984;7(1):61–71.PubMedCrossRef
77.
Sarason IG, Johnson JH, Siegel JM. Assessing impact of life changes - development of life experiences survey. J Consult Clin Psychol. 1978;46(5):932–46.PubMedCrossRef
78.
Bruijn G-J, Bvd P. Exercise promotion: an integration of exercise self-identity, beliefs, intention, and behaviour. Eur J Sport Sci. 2012;12:354–66.CrossRef
79.
Brook AT, Garcia J, Fleming MA. The effects of multiple identities on psychological well-being. Personal Soc Psychol Bull. 2008;34(12):1588–600.CrossRef
80.
Gross JJ, John OP. Individual differences in two emotion regulation processes: implications for affect, relationships, and well-being. J Pers Soc Psychol. 2003;85(2):348–62.PubMedCrossRef
81.
Ryff CD, Keyes CL. The structure of psychological well-being revisited. J Pers Soc Psychol. 1995;69(4):719–27.PubMedCrossRef
82.
Peterson C, Semmel A, von Baeyer C, Abramson LY, Metalsky GI, Seligman MEP. The attributional style questionnaire. Cognitive Ther Res. 1982;6(3):287–99.CrossRef
83.
Burnette JL, Finkel EJ. Buffering against weight gain following dieting setbacks: an implicit theory intervention. J Exp Soc Psychol. 2012;48(3):721–5.CrossRef
84.
Cyders MA, Smith GT, Spillane NS, Fischer S, Annus AM, Peterson C. Integration of impulsivity and positive mood to predict risky behavior: development and validation of a measure of positive urgency. Psychol Assess. 2007;19(1):107–18.PubMedCrossRef
85.
Nelson MC, Lytle LA. Development and evaluation of a brief screener to estimate fast-food and beverage consumption among adolescents. J Am Diet Assoc. 2009;109(4):730–4.PubMedPubMedCentralCrossRef
86.
Centers for Disease Control and Prevention (CDC). Behavioral risk factor surveillance system survey questionnaire. Atlanta, Georgia U.S. Department of Health and Human Services: Centers for Disease Control and Prevention; 2016. p. 26–7.
87.
Chu AH, Ng SH, Koh D, Muller-Riemenschneider F. Reliability and validity of the self- and interviewer-administered versions of the global physical activity questionnaire (GPAQ). PLoS One. 2015;10(9):e0136944.PubMedPubMedCentralCrossRef
88.
Cleland CL, Hunter RF, Kee F, Cupples ME, Sallis JF, Tully MA. Validity of the global physical activity questionnaire (GPAQ) in assessing levels and change in moderate-vigorous physical activity and sedentary behaviour. BMC Public Health. 2014;14:1255.PubMedPubMedCentralCrossRef
89.
Roenneberg T, Wirz-Justice A, Merrow M. Life between clocks: daily temporal patterns of human chronotypes. J Biol Rhythm. 2003;18(1):80–90.CrossRef
90.
Cuttler C, Spradlin A. Measuring cannabis consumption: psychometric properties of the daily sessions, frequency, age of onset, and quantity of cannabis use inventory (DFAQ-CU). PLoS One. 2017;12(5):e0178194.PubMedPubMedCentralCrossRef
91.
Centers for Disease Control and Prevention (CDC). Behavioral risk factor surveillance system survey questionnaire. Atlanta, Georgia U.S. Department of Health and Human Services: Centers for Disease Control and Prevention; 2016. p. 51.
92.
Cerin E, Conway TL, Saelens BE, Frank LD, Sallis JF. Cross-validation of the factorial structure of the neighborhood environment walkability scale (NEWS) and its abbreviated form (NEWS-A). Int J Behav Nutr Phys Act. 2009;6:32.PubMedPubMedCentralCrossRef
93.
Cerin E, Saelens BE, Sallis JF, Frank LD. Neighborhood environment walkability scale: validity and development of a short form. Med Sci Sports Exerc. 2006;38(9):1682–91.PubMedCrossRef
94.
Kiernan M, Moore SD, Schoffman DE, Lee K, King AC, Taylor CB, et al. Social support for healthy behaviors: scale psychometrics and prediction of weight loss among women in a behavioral program. Obesity. 2012;20(4):756–64.PubMedCrossRef
95.
Koffarnus MN, Bickel WK. A 5-trial adjusting delay discounting task: accurate discount rates in less than one minute. Exp Clin Psychopharmacol. 2014;22(3):222–8.PubMedPubMedCentralCrossRef
96.
Peters JC, Beck J, Cardel M, Wyatt HR, Foster GD, Pan Z, et al. The effects of water and non-nutritive sweetened beverages on weight loss and weight maintenance: a randomized clinical trial. Obesity. 2016;24(2):297–304.PubMedCrossRef
Metadata
Title
Comparison of weight loss induced by daily caloric restriction versus intermittent fasting (DRIFT) in individuals with obesity: study protocol for a 52-week randomized clinical trial
Authors
Danielle M. Ostendorf
Ann E. Caldwell
Adnin Zaman
Zhaoxing Pan
Kristen Bing
Liza T. Wayland
Seth A. Creasy
Daniel H. Bessesen
Paul MacLean
Edward L. Melanson
Victoria A. Catenacci
Publication date
01-12-2022
Publisher
BioMed Central
Keywords
Obesity
Obesity
Published in
Trials / Issue 1/2022
Electronic ISSN: 1745-6215
DOI
https://doi.org/10.1186/s13063-022-06523-2

Other articles of this Issue 1/2022

Trials 1/2022 Go to the issue

Study protocol

Efficacy of contralaterally controlled functional electrical stimulation compared to cyclic neuromuscular electrical stimulation and task-oriented training for recovery of hand function after stroke: study protocol for a multi-site randomized controlled trial

Study protocol

Improving the management of chronic pain, opioid use, and opioid use disorder in older adults: study protocol for I-COPE study

Study protocol

Effect of vitamin D supplementation on brain waves, behavioral performance, nitric oxide, malondialdehyde, and high-sensitivity C-reactive protein in children with attention deficit/hyperactivity disorder: study protocol for a randomized clinical trial

Study protocol

EVITA Dengue: a cluster-randomized controlled trial to EValuate the efficacy of Wolbachia-InfecTed Aedes aegypti mosquitoes in reducing the incidence of Arboviral infection in Brazil

Update

Family-based cognitive behavioural therapy versus family-based relaxation therapy for obsessive-compulsive disorder in children and adolescents (the TECTO trial): a statistical analysis plan for the randomised clinical trial

Study protocol

NeuroSAFE PROOF: study protocol for a single-blinded, IDEAL stage 3, multi-centre, randomised controlled trial of NeuroSAFE robotic-assisted radical prostatectomy versus standard robotic-assisted radical prostatectomy in men with localized prostate cancer