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DIETFITS Study (Diet Intervention Examining the Factors Interacting With Treatment Success (DIETFITS)

Primary Purpose

Obesity, Insulin Resistance

Status
Completed
Phase
Not Applicable
Locations
United States
Study Type
Interventional
Intervention
Low-Carbohydrate Diet
Low-Fat Diet
Mobile App
Sponsored by
Stanford University
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional treatment trial for Obesity

Eligibility Criteria

18 Years - 50 Years (Adult)All SexesAccepts Healthy Volunteers

Inclusion Criteria:

  • 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
  • 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

Exclusion Criteria:

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
  • 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

Sites / Locations

  • Stanford University School of Medicine

Arms of the Study

Arm 1

Arm 2

Arm Type

Experimental

Experimental

Arm Label

Experimental: Low-Carbohydrate Diet

Experimental: Low-Fat Diet

Arm Description

Healthy, Low-Carbohydrate Diet

Healthy, Low-Fat Diet

Outcomes

Primary Outcome Measures

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).

Secondary Outcome Measures

Change from baseline in LDL cholesterol at 12 months
LDL-cholesterol change was calculated as the 12 month value minus the baseline value.
Change from baseline in HDL cholesterol at 12 months
HDL-cholesterol change was calculated as the 12 month value minus the baseline value.
Change from baseline in triglycerides at 12 months
Triglycerides change was calculated as the 12 month value minus the baseline value.
Change from baseline in fasting insulin at 12 months
Fasting insulin change was calculated as the 12 month value minus the baseline value.
Change from baseline in fasting glucose at 12 months
Fasting glucose change was calculated as the 12 month value minus the baseline value.
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.
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.
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.
Change from baseline in body mass index (BMI) at 12 months.
BMI change was calculated as the 12 month value minus the baseline value.
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.

Full Information

First Posted
March 27, 2013
Last Updated
February 18, 2023
Sponsor
Stanford University
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)
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1. Study Identification

Unique Protocol Identification Number
NCT01826591
Brief Title
DIETFITS Study (Diet Intervention Examining the Factors Interacting With Treatment Success
Acronym
DIETFITS
Official Title
Do Insulin Secretion or Genotype Pattern Predict Low Fat vs Low Carb Weight Loss Success?
Study Type
Interventional

2. Study Status

Record Verification Date
February 2023
Overall Recruitment Status
Completed
Study Start Date
January 2013 (Actual)
Primary Completion Date
May 2016 (Actual)
Study Completion Date
May 2016 (Actual)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
Stanford University
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)

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No

5. Study Description

Brief 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. 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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Obesity, Insulin Resistance

7. Study Design

Primary Purpose
Treatment
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Masking
InvestigatorOutcomes Assessor
Allocation
Randomized
Enrollment
609 (Actual)

8. Arms, Groups, and Interventions

Arm Title
Experimental: Low-Carbohydrate Diet
Arm Type
Experimental
Arm Description
Healthy, Low-Carbohydrate Diet
Arm Title
Experimental: Low-Fat Diet
Arm Type
Experimental
Arm Description
Healthy, Low-Fat Diet
Intervention Type
Behavioral
Intervention Name(s)
Low-Carbohydrate Diet
Intervention Description
Counseling/instruction on how to follow a low-carbohydrate diet.
Intervention Type
Behavioral
Intervention Name(s)
Low-Fat Diet
Intervention Description
Counseling/instruction on how to follow a low-fat diet.
Intervention Type
Behavioral
Intervention Name(s)
Mobile App
Intervention Description
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.
Primary Outcome Measure Information:
Title
Change from baseline in weight at 12 months
Description
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).
Time Frame
Baseline and 12 months
Secondary Outcome Measure Information:
Title
Change from baseline in LDL cholesterol at 12 months
Description
LDL-cholesterol change was calculated as the 12 month value minus the baseline value.
Time Frame
Baseline and 12 months
Title
Change from baseline in HDL cholesterol at 12 months
Description
HDL-cholesterol change was calculated as the 12 month value minus the baseline value.
Time Frame
Baseline and 12 months
Title
Change from baseline in triglycerides at 12 months
Description
Triglycerides change was calculated as the 12 month value minus the baseline value.
Time Frame
Baseline and 12 months
Title
Change from baseline in fasting insulin at 12 months
Description
Fasting insulin change was calculated as the 12 month value minus the baseline value.
Time Frame
Baseline and 12 months
Title
Change from baseline in fasting glucose at 12 months
Description
Fasting glucose change was calculated as the 12 month value minus the baseline value.
Time Frame
Baseline and 12 months
Title
Change from baseline in insulin after an oral-glucose tolerance test (OGTT) at 12 months
Description
Post-OGTT insulin change was calculated as the 12 month value minus the baseline value.
Time Frame
Baseline and 12 months
Title
Change from baseline in glucose after an oral-glucose tolerance test (OGTT) at 12 months
Description
Post-OGTT glucose change was calculated as the 12 month value minus the baseline value.
Time Frame
Baseline and 12 months
Title
Change from baseline in body fat percentage at 12 months.
Description
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.
Time Frame
Baseline and 12 months
Title
Change from baseline in body mass index (BMI) at 12 months.
Description
BMI change was calculated as the 12 month value minus the baseline value.
Time Frame
Baseline and 12 months
Title
Change from baseline in resting energy expenditure (REE) at 12 months.
Description
REE was assessed by indirect calorimetry and the change was calculated as the 12 month value minus the baseline value.
Time Frame
Baseline and 12 months

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Maximum Age & Unit of Time
50 Years
Accepts Healthy Volunteers
Accepts Healthy Volunteers
Eligibility Criteria
Inclusion Criteria: 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 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 Exclusion Criteria: 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 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
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Christopher D Gardner, PhD
Organizational Affiliation
Stanford University
Official's Role
Principal Investigator
Facility Information:
Facility Name
Stanford University School of Medicine
City
Stanford
State/Province
California
ZIP/Postal Code
94305
Country
United States

12. IPD Sharing Statement

Plan to Share IPD
No
Citations:
PubMed Identifier
27986647
Citation
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.
Results Reference
background
PubMed Identifier
27193036
Citation
Mummah 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.
Results Reference
background
PubMed Identifier
27501724
Citation
Mummah 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.
Results Reference
background
PubMed Identifier
28027950
Citation
Stanton 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.
Results Reference
background
PubMed Identifier
29466592
Citation
Gardner 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. Erratum In: JAMA. 2018 Apr 3;319(13):1386. JAMA. 2018 Apr 24;319(16):1728.
Results Reference
background
PubMed Identifier
30649213
Citation
Shih 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. Erratum In: Am J Clin Nutr. 2020 Feb 1;111(2):490.
Results Reference
background
PubMed Identifier
31633313
Citation
Fielding-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.
Results Reference
background
PubMed Identifier
31996717
Citation
Grembi 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. Erratum In: Sci Rep. 2020 Jul 1;10(1):11095.
Results Reference
background
PubMed Identifier
32404980
Citation
Figarska 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.
Results Reference
background
PubMed Identifier
34375388
Citation
Cauwenberghs N, Prunicki M, Sabovcik F, Perelman D, Contrepois K, Li X, Snyder MP, Nadeau KC, Kuznetsova T, Haddad F, Gardner CD. Temporal changes in soluble angiotensin-converting enzyme 2 associated with metabolic health, body composition, and proteome dynamics during a weight loss diet intervention: a randomized trial with implications for the COVID-19 pandemic. Am J Clin Nutr. 2021 Nov 8;114(5):1655-1665. doi: 10.1093/ajcn/nqab243.
Results Reference
derived
PubMed Identifier
32186326
Citation
Fragiadakis GK, Wastyk HC, Robinson JL, Sonnenburg ED, Sonnenburg JL, Gardner CD. Long-term dietary intervention reveals resilience of the gut microbiota despite changes in diet and weight. Am J Clin Nutr. 2020 Jun 1;111(6):1127-1136. doi: 10.1093/ajcn/nqaa046.
Results Reference
derived
PubMed Identifier
30964436
Citation
Oppezzo MA, Stanton MV, Garcia A, Rigdon J, Berman JR, Gardner CD. To Text or Not to Text: Electronic Message Intervention to Improve Treatment Adherence Versus Matched Historical Controls. JMIR Mhealth Uhealth. 2019 Apr 9;7(4):e11720. doi: 10.2196/11720.
Results Reference
derived
PubMed Identifier
30672127
Citation
Guo J, Robinson JL, Gardner CD, Hall KD. Objective versus Self-Reported Energy Intake Changes During Low-Carbohydrate and Low-Fat Diets. Obesity (Silver Spring). 2019 Mar;27(3):420-426. doi: 10.1002/oby.22389. Epub 2019 Jan 22.
Results Reference
derived
PubMed Identifier
28915825
Citation
Mummah S, Robinson TN, Mathur M, Farzinkhou S, Sutton S, Gardner CD. Effect of a mobile app intervention on vegetable consumption in overweight adults: a randomized controlled trial. Int J Behav Nutr Phys Act. 2017 Sep 15;14(1):125. doi: 10.1186/s12966-017-0563-2.
Results Reference
derived
Links:
URL
https://med.stanford.edu/nutrition/research/completed-studies/diet-study.html
Description
Study description and results summary

Learn more about this trial

DIETFITS Study (Diet Intervention Examining the Factors Interacting With Treatment Success

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