- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06800794
Investigating Metabolic and Psychological Adaptations in a Clinical Trial (IMPACT)
Effect of Meal Timing and Dietary Changes on Metabolic and Behavioral Factors Involved in the Food Insecurity-Obesity Paradox
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Study Type
Enrollment (Estimated)
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
New York
-
Buffalo, New York, United States, 14221
- Farber Hall G56
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Woman between the ages of 18-45.
- Premenopausal.
- Obese (BMI ≥ 30).
- Diagnosed with prediabetes (HbA1c: 5.7%-6.4%).
- Experiencing food insecurity (score of 2-6 on the six-item food insecurity questionnaire).
- Income below 300% of the household federal poverty threshold.
- Lives alone.
Exclusion Criteria:
- Actively planning to become pregnant (e.g., individuals trying to conceive or undergoing fertility treatment, based on self-report).
- Delivered a baby within the past 6 months (self-report).
- Non-ambulatory (e.g., individuals unable to walk independently or requiring a wheelchair for mobility).
- Intellectual impairment that would impact treatment adherence.
Unmanaged mood disorders, substance use disorders, personality disorders, or a history of eating disorders, including:
- Generalized anxiety disorder.
- Depression.
- Alcohol dependence.
- Schizophrenia.
- Anorexia nervosa, bulimia, or binge eating disorder within the past 6 months.
- Recent weight loss exceeding 5% of body weight within the past 6 months (self-report).
- Food allergies to study-related foods, including dairy, soy, nuts, or gluten.
- History of bariatric surgery or GLP-1 agonist use (self-report).
- Inability to read or write in English (self-report).
- Planned relocation out of the study area during the study timeframe (self-report).
- Uncontrolled diabetes (HbA1c > 9%) or hypertension (blood pressure > 160/100 mmHg), based on self-report or screening visit measurements.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: Randomized
- Interventional Model: Sequential Assignment
- Masking: Single
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
No Intervention: Control phase
During this phase, participants are told to maintain typical behaviors and not change any normal patterns of activity/eating.
|
|
|
Experimental: Treatment phase
There are two components to the treatment: Food provisioning: The food provisioning component will consist of bi-weekly home deliveries of three meals a day. The number of calories in the provided meals for each day will be personalized based on each participant's resting metabolic rate. Caloric targets for each participant will be 20% of TDEE as this translates to ~1-2 pounds of weight loss per week. Diets composition will also be tailored to help improve TEF and RQ. Behavioral Skills Training: This will be based on an evidence-based behavioral weight-loss program developed in our lab. This treatment has shown clinically significant weight loss with positive effects sustained over 10-years. The specific includes lessons on self-monitoring, developing alternatives to foods, meal-planning, goal setting, episodic future thinking, physical activity, and self-reinforcement. |
7 sessions including: Hunger and fullness, eating on a budget, traffic light eating plan, menu planning, creating alternatives to food, financial planning, and changing the environment.
3 meals a day consisting of low energy dense, nutrient rich, ready to eat, low GI, foods delivered to the participants' homes.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Change in body weight
Time Frame: Through study completion, an average of 25 weeks
|
measured in kgs using a weight scale.
|
Through study completion, an average of 25 weeks
|
|
change in HBA1C
Time Frame: Through study completion, an average of 25 weeks.
|
measured via a finger-prick blood sample analyzed using a point-of-care device
|
Through study completion, an average of 25 weeks.
|
|
Change in respiratory quotient
Time Frame: Through study completion, an average of 25 weeks.
|
will be measured in morning fasting state using the Breezing Pro, an FDA approved device for portable metabolic measures
|
Through study completion, an average of 25 weeks.
|
|
change in TEF
Time Frame: Through study completion, an average of 25 weeks.
|
will be measured in morning fasting state using the Breezing Pro, an FDA approved device for portable metabolic measures
|
Through study completion, an average of 25 weeks.
|
|
Change in delay discounting
Time Frame: Through study completion, an average of 25 weeks.
|
will be measured using the adjusting amount delay discounting task that presents participants with choices between a fraction of the total delayed amount of money now or the full amount ($100 &/ $1000) at a future delayed time for five different periods from 30 days, 180 days, 365 days (1 year), 1095 days (3 years), 1825 days (5 years) (order randomized).
|
Through study completion, an average of 25 weeks.
|
|
Change in RRE
Time Frame: Through study completion, an average of 25 weeks.
|
RRE will be assessed through a survey that will use participants' preferred snack foods that are classified as either hyperpalatable or healthy.
Scores have no fixed minimum or maximum, as they are determined by the highest ratio completed before the participant stops working for the food reward.
Higher scores indicate greater reinforcing efficacy and a stronger motivational drive for the food reward, which is considered a worse outcome in this context.
|
Through study completion, an average of 25 weeks.
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
change in stress
Time Frame: Through study completion, an average of 25 weeks.
|
measured using the Perceived Stress Scale.
The Perceived Stress Scale is a validated 10-item questionnaire that measures the perception of stress over the past month.
Scores range from 0 to 40, where higher scores indicate greater perceived stress and worse outcomes.
|
Through study completion, an average of 25 weeks.
|
|
change in physical activity
Time Frame: Through study completion, an average of 25 weeks.
|
measured using a Fitbit activity monitor
|
Through study completion, an average of 25 weeks.
|
Collaborators and Investigators
Publications and helpful links
General Publications
- Farshchi HR, Taylor MA, Macdonald IA. Decreased thermic effect of food after an irregular compared with a regular meal pattern in healthy lean women. Int J Obes Relat Metab Disord. 2004 May;28(5):653-60. doi: 10.1038/sj.ijo.0802616.
- Farshchi HR, Taylor MA, Macdonald IA. Regular meal frequency creates more appropriate insulin sensitivity and lipid profiles compared with irregular meal frequency in healthy lean women. Eur J Clin Nutr. 2004 Jul;58(7):1071-7. doi: 10.1038/sj.ejcn.1601935.
- Ellis AC, Hyatt TC, Hunter GR, Gower BA. Respiratory quotient predicts fat mass gain in premenopausal women. Obesity (Silver Spring). 2010 Dec;18(12):2255-9. doi: 10.1038/oby.2010.96. Epub 2010 May 6.
- Pannacciulli N, Salbe AD, Ortega E, Venti CA, Bogardus C, Krakoff J. The 24-h carbohydrate oxidation rate in a human respiratory chamber predicts ad libitum food intake. Am J Clin Nutr. 2007 Sep;86(3):625-32. doi: 10.1093/ajcn/86.3.625.
- Raynor HA, Epstein LH. The relative-reinforcing value of food under differing levels of food deprivation and restriction. Appetite. 2003 Feb;40(1):15-24. doi: 10.1016/s0195-6663(02)00161-7.
- Green L, Myerson J, Lichtman D, Rosen S, Fry A. Temporal discounting in choice between delayed rewards: the role of age and income. Psychol Aging. 1996 Mar;11(1):79-84. doi: 10.1037//0882-7974.11.1.79.
- Bickel WK, Freitas-Lemos R, Tomlinson DC, Craft WH, Keith DR, Athamneh LN, Basso JC, Epstein LH. Temporal discounting as a candidate behavioral marker of obesity. Neurosci Biobehav Rev. 2021 Oct;129:307-329. doi: 10.1016/j.neubiorev.2021.07.035. Epub 2021 Aug 3.
- Myers CA, Beyl RA, Martin CK, Broyles ST, Katzmarzyk PT. Psychological mechanisms associated with food security status and BMI in adults: a mixed methods study. Public Health Nutr. 2020 Oct;23(14):2501-2511. doi: 10.1017/S1368980020000889. Epub 2020 Jun 29.
- Rodriguez LR, Rasmussen EB, Kyne-Rucker D, Wong M, Martin KS. Delay discounting and obesity in food insecure and food secure women. Health Psychol. 2021 Apr;40(4):242-251. doi: 10.1037/hea0001042.
- Epstein LH, Truesdale R, Wojcik A, Paluch RA, Raynor HA. Effects of deprivation on hedonics and reinforcing value of food. Physiol Behav. 2003 Feb;78(2):221-7. doi: 10.1016/s0031-9384(02)00978-2.
- Crandall AK, Temple JL. Experimental scarcity increases the relative reinforcing value of food in food insecure adults. Appetite. 2018 Sep 1;128:106-115. doi: 10.1016/j.appet.2018.05.148. Epub 2018 May 29.
- Myers KP, Majewski M, Schaefer D, Tierney A. Chronic experience with unpredictable food availability promotes food reward, overeating, and weight gain in a novel animal model of food insecurity. Appetite. 2022 Sep 1;176:106120. doi: 10.1016/j.appet.2022.106120. Epub 2022 Jun 6.
- Crandall AK, Ziegler AM, Mansouri T, Matteson J, Isenhart E, Carter A, Balantekin KN, Temple JL. Having less and wanting more: an investigation of socioeconomic status and reinforcement pathology. BMC Public Health. 2021 Feb 25;21(1):402. doi: 10.1186/s12889-021-10430-7.
- Lin H, Carr KA, Fletcher KD, Epstein LH. Food reinforcement partially mediates the effect of socioeconomic status on body mass index. Obesity (Silver Spring). 2013 Jul;21(7):1307-12. doi: 10.1002/oby.20158. Epub 2013 Jun 11.
- Nettle D, Bateson M. Food-Insecure Women Eat a Less Diverse Diet in a More Temporally Variable Way: Evidence from the US National Health and Nutrition Examination Survey, 2013-4. J Obes. 2019 Oct 1;2019:7174058. doi: 10.1155/2019/7174058. eCollection 2019.
- Chaput JP, Tremblay A. The glucostatic theory of appetite control and the risk of obesity and diabetes. Int J Obes (Lond). 2009 Jan;33(1):46-53. doi: 10.1038/ijo.2008.221. Epub 2008 Nov 11.
- Flatt JP. The difference in the storage capacities for carbohydrate and for fat, and its implications in the regulation of body weight. Ann N Y Acad Sci. 1987;499:104-23. doi: 10.1111/j.1749-6632.1987.tb36202.x.
- Booker JM, Chang DC, Stinson EJ, Mitchell CM, Votruba SB, Krakoff J, Gluck ME, Cabeza de Baca T. Food insecurity is associated with higher respiratory quotient and lower glucagon-like peptide 1. Obesity (Silver Spring). 2022 Jun;30(6):1248-1256. doi: 10.1002/oby.23437.
- Bateson M, Andrews C, Dunn J, Egger CBCM, Gray F, Mchugh M, Nettle D. Food insecurity increases energetic efficiency, not food consumption: an exploratory study in European starlings. PeerJ. 2021 May 28;9:e11541. doi: 10.7717/peerj.11541. eCollection 2021.
- Calcagno M, Kahleova H, Alwarith J, Burgess NN, Flores RA, Busta ML, Barnard ND. The Thermic Effect of Food: A Review. J Am Coll Nutr. 2019 Aug;38(6):547-551. doi: 10.1080/07315724.2018.1552544. Epub 2019 Apr 25.
- Morales ME, Berkowitz SA. The Relationship between Food Insecurity, Dietary Patterns, and Obesity. Curr Nutr Rep. 2016 Mar;5(1):54-60. doi: 10.1007/s13668-016-0153-y. Epub 2016 Jan 25.
- Franklin B, Jones A, Love D, Puckett S, Macklin J, White-Means S. Exploring mediators of food insecurity and obesity: a review of recent literature. J Community Health. 2012 Feb;37(1):253-64. doi: 10.1007/s10900-011-9420-4.
- Nettle D, Andrews C, Bateson M. Food insecurity as a driver of obesity in humans: The insurance hypothesis. Behav Brain Sci. 2017 Jan;40:e105. doi: 10.1017/S0140525X16000947. Epub 2016 Jul 28.
- Bateson M, Pepper GV. Food insecurity as a cause of adiposity: evolutionary and mechanistic hypotheses. Philos Trans R Soc Lond B Biol Sci. 2023 Oct 23;378(1888):20220228. doi: 10.1098/rstb.2022.0228. Epub 2023 Sep 4.
- Epstein LH, Rizwan A, Paluch RA, Temple JL. Delay Discounting and the Income-Food Insecurity-Obesity Paradox in Mothers. J Obes. 2023 Sep 19;2023:8898498. doi: 10.1155/2023/8898498. eCollection 2023.
- Epstein LH, Jankowiak N, Lin H, Paluch R, Koffarnus MN, Bickel WK. No food for thought: moderating effects of delay discounting and future time perspective on the relation between income and food insecurity. Am J Clin Nutr. 2014 Sep;100(3):884-90. doi: 10.3945/ajcn.113.079772. Epub 2014 Jul 9.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Estimated)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- STUDY00008988
- 1UM1TR005296-01 (U.S. NIH Grant/Contract)
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
IPD Sharing Time Frame
IPD Sharing Access Criteria
Qualified Researchers: Access will be granted to researchers affiliated with academic, non-profit, or governmental institutions conducting non-commercial research. Researchers must demonstrate a legitimate scientific purpose for using the data.
Individual Participant Data (IPD):
De-identified data for all primary and secondary outcome measures (e.g., respiratory quotient, thermic effect of food, body weight, relative reinforcing value of food, and delay discounting).
Accompanying metadata and codebooks for proper interpretation of the data.
Supporting Information:
Study Protocol: Detailed description of the study design and methodology. Statistical Analysis Plan (SAP): Comprehensive explanation of the planned statistical analyses for all outcomes.
Informed Consent Form (ICF): Template of the consent form used during the study.
Analytic Code: Scripts used for data cleaning and statistical analyses, enabling reproducibility of results.
IPD Sharing Supporting Information Type
- STUDY_PROTOCOL
- SAP
- ICF
- ANALYTIC_CODE
- CSR
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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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