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

February 18, 2023 updated by: Christopher Gardner, Stanford University

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.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

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 Type

Interventional

Enrollment (Actual)

609

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • United States
    • California
      • Stanford, California, United States, 94305
        • Stanford University School of Medicine

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 50 years (Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Treatment
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Double

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Experimental: Low-Carbohydrate Diet
Healthy, Low-Carbohydrate Diet
Behavioral: Low-Carbohydrate Diet
Counseling/instruction on how to follow a low-carbohydrate diet.
Behavioral: Mobile App
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.
Experimental: Experimental: Low-Fat Diet
Healthy, Low-Fat Diet
Behavioral: Mobile App
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.
Behavioral: Low-Fat Diet
Counseling/instruction on how to follow a low-fat diet.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
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).
Baseline and 12 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Change from baseline in LDL cholesterol at 12 months
Time Frame: Baseline and 12 months
LDL-cholesterol change was calculated as the 12 month value minus the baseline value.
Baseline and 12 months
Change from baseline in HDL cholesterol at 12 months
Time Frame: Baseline and 12 months
HDL-cholesterol change was calculated as the 12 month value minus the baseline value.
Baseline and 12 months
Change from baseline in triglycerides at 12 months
Time Frame: Baseline and 12 months
Triglycerides change was calculated as the 12 month value minus the baseline value.
Baseline and 12 months
Change from baseline in fasting insulin at 12 months
Time Frame: Baseline and 12 months
Fasting insulin change was calculated as the 12 month value minus the baseline value.
Baseline and 12 months
Change from baseline in fasting glucose at 12 months
Time Frame: Baseline and 12 months
Fasting glucose change was calculated as the 12 month value minus the baseline value.
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
Post-OGTT insulin change was calculated as the 12 month value minus the baseline value.
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
Post-OGTT glucose change was calculated as the 12 month value minus the baseline value.
Baseline and 12 months
Change from baseline in body fat percentage at 12 months.
Time Frame: Baseline and 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.
Baseline and 12 months
Change from baseline in body mass index (BMI) at 12 months.
Time Frame: Baseline and 12 months
BMI change was calculated as the 12 month value minus the baseline value.
Baseline and 12 months
Change from baseline in resting energy expenditure (REE) at 12 months.
Time Frame: Baseline and 12 months
REE was assessed by indirect calorimetry and the change was calculated as the 12 month value minus the baseline value.
Baseline and 12 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Stanford University

Collaborators

National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
National Heart, Lung, and Blood Institute (NHLBI)
National Center for Advancing Translational Sciences (NCATS)
Nutrition Science Initiative

Investigators

  • Principal Investigator: Christopher D Gardner, PhD, Stanford University

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Helpful Links

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2013

Primary Completion (Actual)

May 1, 2016

Study Completion (Actual)

May 1, 2016

Study Registration Dates

First Submitted

March 27, 2013

First Submitted That Met QC Criteria

April 3, 2013

First Posted (Estimate)

April 8, 2013

Study Record Updates

Last Update Posted (Estimate)

February 21, 2023

Last Update Submitted That Met QC Criteria

February 18, 2023

Last Verified

February 1, 2023

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 22305 (Other Identifier: City of Hope Comprehensive Cancer Center)
  • 1R01DK091831 (U.S. NIH Grant/Contract)
  • T32HL007034 (U.S. NIH Grant/Contract)
  • UL1TR001085 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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