Devaluing Energy-dense Foods for Cancer-control: Translational Neuroscience
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Overweight and Obesity
- Sponsor
- University of Oregon
- Enrollment
- 253
- Locations
- 1
- Primary Endpoint
- Change from Baseline Food Intake at 1 month using dietary assessment tool
- Status
- Completed
- Last Updated
- 2 years ago
Overview
Brief Summary
Excessive eating of energy-dense foods and obesity are risk factors for a range of cancers. There are programs to reduce intake of these foods and weight loss, but the effects of the programs rarely last. This project tests whether altering the value of cancer-risk foods can create lasting change, and uses neuroimaging to compare the efficacy of two programs to engage the valuation system on a neural level. Results will establish the pathways through which the programs work and suggest specific treatments for individuals based on a personalized profile.
Detailed Description
Obesity and intake of certain foods increase cancer risk, but the most common treatment (behavioral weight loss programs) rarely produces lasting weight loss and eating behavior change, apparently because caloric restriction increases the reward value of food and prompts energy-sparing adaptations. Interventions that reduce the implicit valuation of cancer-risk foods (e.g., red meats, refined sugar) may be more effective. Emerging data suggest that behavioral response training and cognitive reappraisal training reduce valuation of such foods, which leads to decrease intake of these foods and weight loss. Internalized incentive value is reflected in a ventromedial prefrontal cortex (vmPFC) / orbitofrontal cortex valuation system, which encodes the implicit reward value of food and is central to a reinforcement cycle that perpetuates unhealthy eating. Thus, the vmPFC valuation system is a promising target for intervention because changes to the system might disrupt the unhealthy reinforcement cycle. Interestingly, various interventions influence the vmPFC through distinct pathways. Behavioral training alters motor input to valuation regions, whereas cognitive training relies on lateral prefrontal "top-down" regions. The proposed translational neuroscience experiment will compare the efficacy with which two novel treatments cause lasting change in food valuation, and whether a composite of theory-based baseline individual differences in relevant processes (such as response tendencies and cognitive styles) moderate treatment effects. We will randomize 300 overweight/obese adults who are at risk for eating- and obesity-related cancers to behavioral response training toward healthy foods and away from cancer-risk foods, a cognitive reappraisal intervention focused on cancer-risk foods, or non-food inhibitory control training. Aim 1 compares the efficacy and mechanisms of action of these two interventions to reduce valuation of cancer-risk foods relative to the active control condition, using neural, behavioral, self-report, and physiological measures of the process and outcomes. Aim 2 is to establish the temporal pattern and durability of the effects across time; food intake and habits, body fat, BMI, and waist-to-hip ratio will be measured pre, post, and at 3-, 6-, and 12-month follow-up. Aim 3 uses machine learning to build and validate a low-cost, easy-to-administer composite that predicts whether and for how long an individual is likely to respond to intervention, and to which treatment. We hypothesize that self-report measures specifically related to valuation (e.g., willingness-to-pay) and to intervention-specific pathways to valuation (e.g., behavioral response tendencies, cognitive style) will predict differential response. Discovering these individual differences will provide a practical, low-cost tool to help interventionists "match" a given person to an effective treatment for that person. This project is very innovative because no study has directly compared the distinct and common effects of these treatments on valuation, used brain imaging to study the mechanism of effects, tested whether these interventions produce a lasting change in food valuation and body fat, or built and validated a composite that moderates response.
Investigators
Eligibility Criteria
Inclusion Criteria
- •overweight to obese range (BMI 25-35)
Exclusion Criteria
- •metal implants (e.g., braces, permanent retainers, pins)
- •metal fragments, pacemakers or other electronic medical implants
- •claustrophobia
- •weight ˃ 550 lbs.
- •Women who are pregnant or believe they might be pregnant
- •people who have been diagnosed with past or current medical, psychiatric, neurological, eating disorders, or are taking psychotropic medications
- •urine screen to exclude participants who are acutely intoxicated
- •screen for handedness
- •Beyond these criteria, participants will be recruited without exclusions based on gender, race, or ethnicity, so our sample will reflect the diversity in the local population (Lane County, Oregon) with regard to gender, race, and ethnicity.
Outcomes
Primary Outcomes
Change from Baseline Food Intake at 1 month using dietary assessment tool
Time Frame: baseline, 1 month
Assessed with the Automated Self-Administered 24-Hour (ASA24) Dietary Assessment Tool The National Cancer Institutes's standard self-assessment instrument to comprehensively measure food intake.
Change from Baseline Food Intake at 1 month, Self-Report Questionnaire
Time Frame: baseline, 1 month
Food-Frequency Questionnaire modified to include cancer risk foods
Secondary Outcomes
- Change from Baseline Body Fat Percent at 1 month(baseline, 1 month)
- Change from Baseline Body Mass Index at 1 month(baseline, 1 month)
- Change from Baseline Waist-to-Hip Ratio at 1 month(baseline, 1 month)
- Change from Baseline Food Approach and Avoidance Behavior at 1 month, Self-Report Questionnaire 2(baseline, 1 month)
- Change from Baseline Food Approach and Avoidance Behavior at 1 month, Self-Report Questionnaire 3(baseline, 1 month)
- Change from Baseline Cognitive Tendencies at 1 month, Self-Report Questionnaire 2(baseline, 1 month)
- Change from Baseline Habitual Response to Food at 1 month, Behavioral marker(baseline, 1 month)
- Change from Baseline Behavioral Response Biases Toward and Away from Cancer Risk and Healthy Foods at 1 month, Neural marker, Task 1(baseline, 1 month)
- Change from Baseline Cancer Risk and Healthy Food Craving and Valuation at 1 month, Self-report Questionnaire 2(baseline, 1 month)
- Change from Baseline Behavioral Response Biases Toward and Away from Cancer Risk and Healthy Foods at 1 month, Behavioral marker, Task 1(baseline, 1 month)
- Change from Baseline Cognitive Reappraisal of Food at 1 month, Behavioral marker(baseline, 1 month)
- Change from Baseline Valuation of Subjective Value of Various Foods at 1 month, Behavioral marker(baseline, 1 month)
- Change from Baseline Behavioral Response Biases Toward and Away from Cancer Risk and Healthy Foods at 1 month, Neural marker, Task 2(baseline, 1 month)
- Change from Baseline Habitual Response to Food at 1 month, Neural marker(baseline, 1 month)
- Change from Baseline Cognitive Tendencies at 1 month, Self-Report Questionnaire 1(baseline, 1 month)
- Change from Baseline Food-related Habitual Behavior at 1 month, Self-report Questionnaire 1(baseline, 1 month)
- Change from Baseline Behavioral Response Biases Toward and Away from Cancer Risk and Healthy Foods at 1 month, Behavioral marker, Task 2(baseline, 1 month)
- Change from Baseline Cognitive Reappraisal of Food at 1 month, Neural marker(baseline, 1 month)
- Change from Baseline Valuation of Subjective Value of Various Foods at 1 month, Neural marker(baseline, 1 month)