ObesityDIETFITSNCT01826591
DIETFITS Study (Diet Intervention Examining the Factors Interacting With Treatment Success
A study testing Low-Carbohydrate Diet, Low-Fat Diet and Mobile App in people with Obesity and Insulin Resistance, run by Stanford University at 1 site in United States.
Trial summary
Genomics research is advancing rapidly, and links between genes and obesity continue to be discovered and better defined. A growing number of single nucleotide polymorphisms (SNPs) in multiple genes have been shown to alter an individual's response to dietary macronutrient composition. Read more about this study
- Who is it for?
- Ages 18 to 50 yearsHealthy volunteers can take part
- Conditions the study is for
- Obesity, Insulin Resistance
- What is being tested?
- Low-Carbohydrate Diet, Low-Fat Diet and Mobile App
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 609 participants
- Where
- 1 siteUnited States
- Study dates
- Jan 2013to May 2016
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 50 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- Age: > 18 years of age
- Women: Pre-menopausal (self-report) and <50 years of age
- Men: <50 years of age
- BMI (body mass index): 27-40 kg/m2 (need to lose >10% body weight to achieve healthy BMI)
- Body weight stable for the last two months, and not actively on a weight loss plan
- No plans to move from the area over the next two years
Show all 12Show fewer
- Available and able to participate in the evaluations and intervention for the study period
- Willing to accept random assignment
- To enhance study generalizability, people on medications not noted below as specific exclusions can
- participate if they have been stable on such medications for at least three months
- Ability and willingness to give written informed
- No known active psychiatric illness
Who cannot join
- Subjects with the following conditions will be excluded (determined by self-report):
- Pregnant, lactating, within 6 months post-partum, or planning to become pregnant in the next 2 years
- Diabetes (type 1 and 2) or history of gestational diabetes or on hypoglycemic medications for any other indication
- Prevalent diseases: Malabsorption, renal or liver disease, active neoplasms, recent myocardial infarction (<6 months)(patient self-report and, if available, review of labs from primary care provider)
- Smokers (because of effect on weight and lipids)
- History of serious arrhythmias, or cerebrovascular disease
Show all 13Show fewer
- Uncontrolled hyper- or hypothyroidism (TSH not within normal limits)
- Medications: Lipid lowering, antihypertensive medications, and those known to affect weight/energy expenditure
- Excessive alcohol intake (self-reported, >3 drinks/day)
- Musculoskeletal disorders precluding regular physical activity
- Unable to follow either of the two study diets for reasons of food allergies or other (e.g., vegan)
- Currently under psychiatric care, or taking psychiatric medications
- Inability to communicate effectively with study personnel
Trial locations and contacts
1 site in 1 country.
United States1 site
Stanford University School of Medicine
Stanford, California, 94305
About this study
Official title: Do Insulin Secretion or Genotype Pattern Predict Low Fat vs Low Carb Weight Loss Success?
Genomics research is advancing rapidly, and links between genes and obesity continue to be discovered and better defined. A growing number of single nucleotide polymorphisms (SNPs) in multiple genes have been shown to alter an individual's response to dietary macronutrient composition. Based on prior genetic studies evaluating the body's physiological responses to dietary carbohydrates or fats, the investigators identified multi-locus genotype patterns with SNPs from three genes (FABP2, PPARG, and ADRB2): a low carbohydrate-responsive genotype (LCG) and a low fat-responsive genotype (LFG). In a preliminary, retrospective study (using the A TO Z weight loss study data), the investigators observed a 3-fold difference in 12-month weight loss for initially overweight women who were determined to have been appropriately matched vs. mismatched to a low carbohydrate (Low Carb) or low fat (Low Fat) diet based on their multi-locus genotype pattern. The primary objective of this study is to confirm and expand on the preliminary results and determine if weight loss success can be increased if the dietary approach (Low Carb vs. Low Fat) is appropriately matched to an individual' s genetic predisposition (Low Carb Genotype vs. Low Fat Genotype) toward those diets.
Read the detailed description
If the intriguing preliminary retrospective results are confirmed in this full scale study, the results will demonstrate that inexpensive DNA testing could help dieters predict whether they will have greater weight loss success on a Low Carb or a Low Fat diet. Commensurate with increasing scientific interest in personalized medicine approaches to intervention development, this would provide an example of the potentially substantial health impacts that could be obtained through understanding specific gene-environment interactions that have been anticipated from the unraveling of the human genome.
Mobile App Sub-Study-For the purpose of augmenting adherence to high vegetable consumption in both diet groups, we will develop a theory-based mobile app to increase vegetable consumption through goal-setting, self-monitoring, and social comparison. Participants from both diet groups with iPhones will be re-randomized to receive the app at either months 4-5 or months 7-8. The first phase during months 4-7 will be used to compare the effect of a mobile app (intervention) vs. no mobile app (waiting-list control). The a priori hypothesis is that vegetable consumption will increase among those who receive the app in both diet arms. The investigator and outcomes assessor will be blinded to group assignment. Intention-to-treat analysis will be used.
- Conditions
- Obesity, Insulin Resistance
- Being tested
- Low-Carbohydrate Diet, Low-Fat Diet, Mobile App
- Medical subject headings
- Obesity, Insulin Resistance
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Low-Carbohydrate DietBehavioural
Counseling/instruction on how to follow a low-carbohydrate diet.
Low-Fat DietBehavioural
Counseling/instruction on how to follow a low-fat diet.
Mobile AppBehavioural
Mobile app to increase vegetable consumption. Participants with iPhones will be re-randomized to receive a mobile app beginning at either months 4-5 or months 7-8. The first phase during months 4-7 will be used to compare the effect of a mobile app (intervention) vs. no mobile app (waiting-list control). The a priori hypothesis is that vegetable consumption will increase among those who receive the app in both diet groups.
| Study group | Role | What they receive |
|---|---|---|
| Experimental: Low-Carbohydrate Diet | Experimental | Healthy, Low-Carbohydrate Diet Receives: Behavioral: Low-Carbohydrate Diet; Behavioral: Mobile App |
| Experimental: Low-Fat Diet | Experimental | Healthy, Low-Fat Diet Receives: Behavioral: Low-Fat Diet; Behavioral: Mobile App |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change from baseline in weight at 12 months
Weight change was calculated as the 12 month value minus the baseline value. The study was designed to determine if either insulin secretion or genotype pattern (low-fat genotype pattern vs .low-carb genotype pattern) were significant effect modifiers of 12-month weight loss for the two diet arms (e.g., 2X2 analyses).
Measured: Baseline and 12 months
Secondary outcomes (10)
Change from baseline in LDL cholesterol at 12 months
LDL-cholesterol change was calculated as the 12 month value minus the baseline value.
Measured: Baseline and 12 months
Change from baseline in HDL cholesterol at 12 months
HDL-cholesterol change was calculated as the 12 month value minus the baseline value.
Measured: Baseline and 12 months
Change from baseline in triglycerides at 12 months
Triglycerides change was calculated as the 12 month value minus the baseline value.
Measured: Baseline and 12 months
Change from baseline in fasting insulin at 12 months
Fasting insulin change was calculated as the 12 month value minus the baseline value.
Measured: Baseline and 12 months
Change from baseline in fasting glucose at 12 months
Fasting glucose change was calculated as the 12 month value minus the baseline value.
Measured: Baseline and 12 months
Change from baseline in insulin after an oral-glucose tolerance test (OGTT) at 12 months
Post-OGTT insulin change was calculated as the 12 month value minus the baseline value.
Measured: Baseline and 12 months
Change from baseline in glucose after an oral-glucose tolerance test (OGTT) at 12 months
Post-OGTT glucose change was calculated as the 12 month value minus the baseline value.
Measured: Baseline and 12 months
Change from baseline in body fat percentage at 12 months.
Body fat percentage was assessed by dual-energy x-ray absorptiometry (DXA) and the change was calculated as the 12 month value minus the baseline value.
Measured: Baseline and 12 months
Change from baseline in body mass index (BMI) at 12 months.
BMI change was calculated as the 12 month value minus the baseline value.
Measured: Baseline and 12 months
Change from baseline in resting energy expenditure (REE) at 12 months.
REE was assessed by indirect calorimetry and the change was calculated as the 12 month value minus the baseline value.
Measured: Baseline and 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Apr 2013 (estimated)
- Study startJan 2013
- Primary completionMay 2016
- Study completionMay 2016
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (21)Papers the sponsor has linked to this study.
- Other trials for ObesityStudies of the same condition, open and under way.
- More trials run by Stanford UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Investigator, Outcomes assessor
- Enrolment
- 609 participants (actual)
Sponsor and investigators
- Lead sponsor
- Stanford University
- Sponsor type
- University, hospital or other
- Collaborators
- Nutrition Science Initiative, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Heart, Lung, and Blood Institute (NHLBI), National Center for Advancing Translational Sciences (NCATS)
- Responsible party
- Principal investigator, Christopher Gardner, Stanford University
- Investigators
- Christopher D Gardner, PhD, Principal investigator, Stanford University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT01826591
- Sponsor's protocol ID
- 22305
- Other IDs
- 1R01DK091831, T32HL007034, UL1TR001085
- Acronym
- DIETFITS
- Status last verified
- Feb 2023
- First submitted
- 27 Mar 2013
- Last updated
- 21 Feb 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Mummah SA, Robinson TN, King AC, Gardner CD, Sutton S. IDEAS (Integrate, Design, Assess, and Share): A Framework and Toolkit of Strategies for the Development of More Effective Digital Interventions to Change Health Behavior. J Med Internet Res. 2016 Dec 16;18(12):e317. doi: 10.2196/jmir.5927.
PubMed 27986647Mummah SA, Mathur M, King AC, Gardner CD, Sutton S. Mobile Technology for Vegetable Consumption: A Randomized Controlled Pilot Study in Overweight Adults. JMIR Mhealth Uhealth. 2016 May 18;4(2):e51. doi: 10.2196/mhealth.5146.
PubMed 27193036Mummah SA, King AC, Gardner CD, Sutton S. Iterative development of Vegethon: a theory-based mobile app intervention to increase vegetable consumption. Int J Behav Nutr Phys Act. 2016 Aug 8;13:90. doi: 10.1186/s12966-016-0400-z.
PubMed 27501724Stanton MV, Robinson JL, Kirkpatrick SM, Farzinkhou S, Avery EC, Rigdon J, Offringa LC, Trepanowski JF, Hauser ME, Hartle JC, Cherin RJ, King AC, Ioannidis JP, Desai M, Gardner CD. DIETFITS study (diet intervention examining the factors interacting with treatment success) - Study design and methods. Contemp Clin Trials. 2017 Feb;53:151-161. doi: 10.1016/j.cct.2016.12.021. Epub 2016 Dec 24.
PubMed 28027950Gardner CD, Trepanowski JF, Del Gobbo LC, Hauser ME, Rigdon J, Ioannidis JPA, Desai M, King AC. Effect of Low-Fat vs Low-Carbohydrate Diet on 12-Month Weight Loss in Overweight Adults and the Association With Genotype Pattern or Insulin Secretion: The DIETFITS Randomized Clinical Trial. JAMA. 2018 Feb 20;319(7):667-679. doi: 10.1001/jama.2018.0245.
PubMed 29466592Shih CW, Hauser ME, Aronica L, Rigdon J, Gardner CD. Changes in blood lipid concentrations associated with changes in intake of dietary saturated fat in the context of a healthy low-carbohydrate weight-loss diet: a secondary analysis of the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) trial. Am J Clin Nutr. 2019 Feb 1;109(2):433-441. doi: 10.1093/ajcn/nqy305.
PubMed 30649213Fielding-Singh P, Patel ML, King AC, Gardner CD. Baseline Psychosocial and Demographic Factors Associated with Study Attrition and 12-Month Weight Gain in the DIETFITS Trial. Obesity (Silver Spring). 2019 Dec;27(12):1997-2004. doi: 10.1002/oby.22650. Epub 2019 Oct 21.
PubMed 31633313Grembi JA, Nguyen LH, Haggerty TD, Gardner CD, Holmes SP, Parsonnet J. Gut microbiota plasticity is correlated with sustained weight loss on a low-carb or low-fat dietary intervention. Sci Rep. 2020 Jan 29;10(1):1405. doi: 10.1038/s41598-020-58000-y.
PubMed 31996717Figarska SM, Rigdon J, Ganna A, Elmstahl S, Lind L, Gardner CD, Ingelsson E. Proteomic profiles before and during weight loss: Results from randomized trial of dietary intervention. Sci Rep. 2020 May 13;10(1):7913. doi: 10.1038/s41598-020-64636-7.
PubMed 32404980Roberts AK, Panyard DJ, Hislop B, Ward CP, Snyder MP, Gardner CD, Haddad F. Diet-based weight-loss intervention is not associated with a meaningful change in lean soft tissue. Am J Clin Nutr. 2026 May;123(5):101251. doi: 10.1016/j.ajcnut.2026.101251. Epub 2026 Feb 23.
PubMed 41740726Follis S, Landry MJ, Cunanan KM, Stefanick ML, Ward CP, Gardner CD. Effect of low-carbohydrate vs low-fat diet intervention on visceral fat estimated from dual energy X-ray absorptiometry in a 12-month randomized controlled trial. Int J Obes (Lond). 2026 Mar;50(3):640-646. doi: 10.1038/s41366-025-01989-x. Epub 2025 Dec 23.
PubMed 41436888Lai CQ, Parnell LD, Das SK, Gardner CD, Ordovas JM. Differential weight-loss responses of APOA2 genotype carriers to low-carbohydrate and low-fat diets: the DIETFITS trial. Obesity (Silver Spring). 2025 Jun;33(6):1048-1057. doi: 10.1002/oby.24288. Epub 2025 May 1.
PubMed 40310284Krauss RM, Fisher LM, King SM, Gardner CD. Changes in soluble LDL receptor and lipoprotein fractions in response to diet in the DIETFITS weight loss study. J Lipid Res. 2024 Mar;65(3):100503. doi: 10.1016/j.jlr.2024.100503. Epub 2024 Jan 19.
PubMed 38246235Hauser ME, Hartle JC, Landry MJ, Fielding-Singh P, Shih CW, Qin F, Rigdon J, Gardner CD. Association of dietary adherence and dietary quality with weight loss success among those following low-carbohydrate and low-fat diets: a secondary analysis of the DIETFITS randomized clinical trial. Am J Clin Nutr. 2024 Jan;119(1):174-184. doi: 10.1016/j.ajcnut.2023.10.028. Epub 2023 Nov 4.
PubMed 37931749Soto-Mota A, Pereira MA, Ebbeling CB, Aronica L, Ludwig DS. Evidence for the carbohydrate-insulin model in a reanalysis of the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) trial. Am J Clin Nutr. 2023 Mar;117(3):599-606. doi: 10.1016/j.ajcnut.2022.12.014. Epub 2023 Jan 6.
PubMed 36811468
Study at a glance
From the registry record, last updated by the sponsor on 21 Feb 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Do Insulin Secretion or Genotype Pattern Predict Low Fat vs Low Carb Weight Loss Success?
- ClinicalTrials.gov ID
- NCT01826591
- Acronym / sponsor ID
- DIETFITS / 22305
- Conditions
- Obesity, Insulin Resistance
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 609 participants (actual)
- Lead sponsor
- Stanford UniversityUniversity, hospital or other
- Collaborators
- Nutrition Science Initiative, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Heart, Lung, and Blood Institute (NHLBI), National Center for Advancing Translational Sciences (NCATS)
- Study start
- Jan 2013 (actual)
- Primary completion
- May 2016 (actual)
- Study completion
- May 2016 (actual)
- First posted
- 8 Apr 2013 (estimated)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Genomics research is advancing rapidly, and links between genes and obesity continue to be discovered and better defined. A growing number of single nucleotide polymorphisms (SNPs) in multiple genes have been shown to alter an individual's response to dietary macronutrient composition. Based on prior genetic studies evaluating the body's physiological responses to dietary carbohydrates or fats, the investigators identified multi-locus genotype patterns with SNPs from three genes (FABP2, PPARG, and ADRB2): a low carbohydrate-responsive genotype (LCG) and a low fat-responsive genotype (LFG). In a preliminary, retrospective study (using the A TO Z weight loss study data), the investigators observed a 3-fold difference in 12-month weight loss for initially overweight women who were determined to have been appropriately matched vs. mismatched to a low carbohydrate (Low Carb) or low fat (Low Fat) diet based on their multi-locus genotype pattern. The primary objective of this study is to confirm and expand on the preliminary results and determine if weight loss success can be increased if the dietary approach (Low Carb vs. Low Fat) is appropriately matched to an individual' s genetic predisposition (Low Carb Genotype vs. Low Fat Genotype) toward those diets.
Detailed description
If the intriguing preliminary retrospective results are confirmed in this full scale study, the results will demonstrate that inexpensive DNA testing could help dieters predict whether they will have greater weight loss success on a Low Carb or a Low Fat diet. Commensurate with increasing scientific interest in personalized medicine approaches to intervention development, this would provide an example of the potentially substantial health impacts that could be obtained through understanding specific gene-environment interactions that have been anticipated from the unraveling of the human genome.
Mobile App Sub-Study-For the purpose of augmenting adherence to high vegetable consumption in both diet groups, we will develop a theory-based mobile app to increase vegetable consumption through goal-setting, self-monitoring, and social comparison. Participants from both diet groups with iPhones will be re-randomized to receive the app at either months 4-5 or months 7-8. The first phase during months 4-7 will be used to compare the effect of a mobile app (intervention) vs. no mobile app (waiting-list control). The a priori hypothesis is that vegetable consumption will increase among those who receive the app in both diet arms. The investigator and outcomes assessor will be blinded to group assignment. Intention-to-treat analysis will be used.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (investigator, outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Experimental: Low-Carbohydrate Diet | Experimental | Behavioral: Low-Carbohydrate Diet, Behavioral: Mobile AppHealthy, Low-Carbohydrate Diet |
| Experimental: Low-Fat Diet | Experimental | Behavioral: Low-Fat Diet, Behavioral: Mobile AppHealthy, Low-Fat Diet |
Who may qualify
- Ages
- 18 to 50 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (12 listed)
- Age: > 18 years of age
- Women: Pre-menopausal (self-report) and <50 years of age
- Men: <50 years of age
- BMI (body mass index): 27-40 kg/m2 (need to lose >10% body weight to achieve healthy BMI)
- Body weight stable for the last two months, and not actively on a weight loss plan
Key exclusion criteria (13 listed)
- Pregnant, lactating, within 6 months post-partum, or planning to become pregnant in the next 2 years
- Diabetes (type 1 and 2) or history of gestational diabetes or on hypoglycemic medications for any other indication
- Prevalent diseases: Malabsorption, renal or liver disease, active neoplasms, recent myocardial infarction (<6 months)(patient self-report and, if available, review of labs from primary care provider)
- Smokers (because of effect on weight and lipids)
- History of serious arrhythmias, or cerebrovascular disease
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Low-Carbohydrate DietCounseling/instruction on how to follow a low-carbohydrate diet. | Behavioural | Experimental: Low-Carbohydrate Diet |
| Low-Fat DietCounseling/instruction on how to follow a low-fat diet. | Behavioural | Experimental: Low-Fat Diet |
| Mobile AppMobile app to increase vegetable consumption. Participants with iPhones will be re-randomized to receive a mobile app beginning at either months 4-5 or months 7-8. The first phase during months 4-7 will be used to compare the effect of a mobile app (intervention) vs. no mobile app (waiting-list control). The a priori hypothesis is that vegetable consumption will increase among those who receive the app in both diet groups. | Behavioural | Experimental: Low-Carbohydrate Diet, Experimental: Low-Fat Diet |
Primary outcome
Change from baseline in weight at 12 months
Time frame: Baseline and 12 months
Weight change was calculated as the 12 month value minus the baseline value. The study was designed to determine if either insulin secretion or genotype pattern (low-fat genotype pattern vs .low-carb genotype pattern) were significant effect modifiers of 12-month weight loss for the two diet arms (e.g., 2X2 analyses).
10 secondary outcomes
Change from baseline in LDL cholesterol at 12 months
Time frame: Baseline and 12 months
Change from baseline in HDL cholesterol at 12 months
Time frame: Baseline and 12 months
Change from baseline in triglycerides at 12 months
Time frame: Baseline and 12 months
Change from baseline in fasting insulin at 12 months
Time frame: Baseline and 12 months
Change from baseline in fasting glucose at 12 months
Time frame: Baseline and 12 months
Change from baseline in insulin after an oral-glucose tolerance test (OGTT) at 12 months
Time frame: Baseline and 12 months
Change from baseline in glucose after an oral-glucose tolerance test (OGTT) at 12 months
Time frame: Baseline and 12 months
Change from baseline in body fat percentage at 12 months.
Time frame: Baseline and 12 months
Change from baseline in body mass index (BMI) at 12 months.
Time frame: Baseline and 12 months
Change from baseline in resting energy expenditure (REE) at 12 months.
Time frame: Baseline and 12 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Feb 2023.
- Background: PubMed 27986647Mummah SA, Robinson TN, King AC, Gardner CD, Sutton S. IDEAS (Integrate, Design, Assess, and Share): A Framework and Toolkit of Strategies for the Development of More Effective Digital Interventions to Change Health Behavior. J Med Internet Res. 2016 Dec 16;18(12):e317. doi: 10.2196/jmir.5927.
- Background: PubMed 27193036Mummah SA, Mathur M, King AC, Gardner CD, Sutton S. Mobile Technology for Vegetable Consumption: A Randomized Controlled Pilot Study in Overweight Adults. JMIR Mhealth Uhealth. 2016 May 18;4(2):e51. doi: 10.2196/mhealth.5146.
- Background: PubMed 27501724Mummah SA, King AC, Gardner CD, Sutton S. Iterative development of Vegethon: a theory-based mobile app intervention to increase vegetable consumption. Int J Behav Nutr Phys Act. 2016 Aug 8;13:90. doi: 10.1186/s12966-016-0400-z.
- Background: PubMed 28027950Stanton MV, Robinson JL, Kirkpatrick SM, Farzinkhou S, Avery EC, Rigdon J, Offringa LC, Trepanowski JF, Hauser ME, Hartle JC, Cherin RJ, King AC, Ioannidis JP, Desai M, Gardner CD. DIETFITS study (diet intervention examining the factors interacting with treatment success) - Study design and methods. Contemp Clin Trials. 2017 Feb;53:151-161. doi: 10.1016/j.cct.2016.12.021. Epub 2016 Dec 24.
- Background: PubMed 29466592Gardner CD, Trepanowski JF, Del Gobbo LC, Hauser ME, Rigdon J, Ioannidis JPA, Desai M, King AC. Effect of Low-Fat vs Low-Carbohydrate Diet on 12-Month Weight Loss in Overweight Adults and the Association With Genotype Pattern or Insulin Secretion: The DIETFITS Randomized Clinical Trial. JAMA. 2018 Feb 20;319(7):667-679. doi: 10.1001/jama.2018.0245.
- Background: PubMed 30649213Shih CW, Hauser ME, Aronica L, Rigdon J, Gardner CD. Changes in blood lipid concentrations associated with changes in intake of dietary saturated fat in the context of a healthy low-carbohydrate weight-loss diet: a secondary analysis of the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) trial. Am J Clin Nutr. 2019 Feb 1;109(2):433-441. doi: 10.1093/ajcn/nqy305.
- Background: PubMed 31633313Fielding-Singh P, Patel ML, King AC, Gardner CD. Baseline Psychosocial and Demographic Factors Associated with Study Attrition and 12-Month Weight Gain in the DIETFITS Trial. Obesity (Silver Spring). 2019 Dec;27(12):1997-2004. doi: 10.1002/oby.22650. Epub 2019 Oct 21.
- Background: PubMed 31996717Grembi JA, Nguyen LH, Haggerty TD, Gardner CD, Holmes SP, Parsonnet J. Gut microbiota plasticity is correlated with sustained weight loss on a low-carb or low-fat dietary intervention. Sci Rep. 2020 Jan 29;10(1):1405. doi: 10.1038/s41598-020-58000-y.
- Background: PubMed 32404980Figarska SM, Rigdon J, Ganna A, Elmstahl S, Lind L, Gardner CD, Ingelsson E. Proteomic profiles before and during weight loss: Results from randomized trial of dietary intervention. Sci Rep. 2020 May 13;10(1):7913. doi: 10.1038/s41598-020-64636-7.
- Derived from this study: PubMed 41740726Roberts AK, Panyard DJ, Hislop B, Ward CP, Snyder MP, Gardner CD, Haddad F. Diet-based weight-loss intervention is not associated with a meaningful change in lean soft tissue. Am J Clin Nutr. 2026 May;123(5):101251. doi: 10.1016/j.ajcnut.2026.101251. Epub 2026 Feb 23.
- Derived from this study: PubMed 41436888Follis S, Landry MJ, Cunanan KM, Stefanick ML, Ward CP, Gardner CD. Effect of low-carbohydrate vs low-fat diet intervention on visceral fat estimated from dual energy X-ray absorptiometry in a 12-month randomized controlled trial. Int J Obes (Lond). 2026 Mar;50(3):640-646. doi: 10.1038/s41366-025-01989-x. Epub 2025 Dec 23.
- Derived from this study: PubMed 40310284Lai CQ, Parnell LD, Das SK, Gardner CD, Ordovas JM. Differential weight-loss responses of APOA2 genotype carriers to low-carbohydrate and low-fat diets: the DIETFITS trial. Obesity (Silver Spring). 2025 Jun;33(6):1048-1057. doi: 10.1002/oby.24288. Epub 2025 May 1.
- Study description and results summaryLink provided by the sponsor.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Christopher D Gardner, PhD principal investigator
Stanford University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Low-Carbohydrate Diet, Low-Fat Diet and Mobile App in people with Obesity and Insulin Resistance, run by Stanford University at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 12 inclusion and 13 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 21 Feb 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change from baseline in weight at 12 months (time frame: Baseline and 12 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT01826591, which also lists 21 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Feb 2023.