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.
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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Enrollment
253
A 3-arm randomized controlled trial experiment study over 12 months. At baseline, participants will complete behavioral, neural, and self-report measures related to food, specifically measures of food valuation and of the proximal neural systems hypothesized to be linked to each of the 2 experimental arms. We will also measure food intake and body composition at baseline. Then participants will be randomized to one of 3 arms (2 experimental + 1 active control) for 8 30-min sessions to occur twice weekly at the University of Oregon for 30 days. At endpoint (\~1 month following baseline), all behavioral, neural, and self-report measures will be reassessed, as will eating, habit, and body composition measures. Follow-ups at 3, 6, and 12 months will assess all measures except neuroimaging.
University of Oregon, Lewis Integrative Sciences Building
Eugene, Oregon, United States
Change from Baseline Food Intake at 1 month using dietary assessment tool
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.
Time frame: baseline, 1 month
Change from Baseline Food Intake at 1 month, Self-Report Questionnaire
Food-Frequency Questionnaire modified to include cancer risk foods
Time frame: baseline, 1 month
Change from Baseline Body Fat Percent at 1 month
Assessed with a BodPod (body pod) air displacement system
Time frame: baseline, 1 month
Change from Baseline Body Mass Index at 1 month
Index of body composition based on height and weight
Time frame: baseline, 1 month
Change from Baseline Waist-to-Hip Ratio at 1 month
Index of body morphology based on external measurements
Time frame: baseline, 1 month
Change from Baseline Food Approach and Avoidance Behavior at 1 month, Self-Report Questionnaire 2
Barratt Impulsivity self-report questionnaire, measuring the construct of impulsivity. There are three subscales: Attentional impulsivity (8 items), motor impulsivity (10 items) non-planning impulsivity (12 items). Participants respond to each item on a 1-to-4 Likert scale and scores are averaged within subscales (yielding three 1-to-4 average scores) then averaged across the three subscales to yield one 1-to-4 overall score. Higher scores indicate higher impulsivity, which is a worse outcome.
Time frame: baseline, 1 month
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Change from Baseline Food Approach and Avoidance Behavior at 1 month, Self-Report Questionnaire 3
Restraint Scale self-report questionnaire. This questionnaire measures the construct of dietary restraint. There are 2 subscales: concern for dieting and weight fluctuations. Participants answer 6 questions about concern for dieting (1-to-5) that are averaged to create a 1-to-5 score on dieting concern. Dieting concern is expected to be u-shaped in terms of better or worse, where no concern or extreme concern is worse and moderate concern is better. Participants answer 4 questions about weight fluctuations (1-to-5) that are averaged to create a 1-to-5 score for weight fluctuation. Great fluctuation is a worse outcome.
Time frame: baseline, 1 month
Change from Baseline Cognitive Tendencies at 1 month, Self-Report Questionnaire 1
Need for Cognition self-report questionnaire, which measures the construct of cognitive engagement and enjoyment of thinking. Participants complete 18 items on a 9-point Likert scale (-4 to +4) and scores are averaged across all items to create a single score that ranges from -4 to +4. Higher scores indicate a better outcome, indicating more enjoyment of thinking processes.
Time frame: baseline, 1 month
Change from Baseline Cognitive Tendencies at 1 month, Self-Report Questionnaire 2
Craving Regulation Scale self-report questionnaire, which measures the construct of self-regulation of food cravings. There are 24 items total, with 4 items within each of 6 subscales: avoidance of temptation, controlling temptations, distraction, suppression, goal/rule setting, and goal deliberation. Responses are on a 1-to-5 Likert scale and averaged within subscales to create 6 1-to-5 average ratings. Those six averages are also averaged to create an overall score. Greater scores indicate better self-regulation of craving, which is a desired outcome.
Time frame: baseline, 1 month
Change from Baseline Food-related Habitual Behavior at 1 month, Self-report Questionnaire 1
Food version of the Self-Report Habit Index self-report questionnaire. This measures the construct of habitual eating of healthy and unhealthy foods. The scale contains two subscales: healthy foods and unhealthy foods. Each subscale contains 12 items, and responses are on a 1-to-5 Likert scale. Responses are averaged within each subscale to create 1-to-5 average ratings for habitual eating of healthy and unhealthy foods, respectively. The subscales are reported separately and not combined. Greater numbers indicate more habitual eating, so lower averages on the unhealthy subscale and higher averages on the healthy subscale indicate a better outcome.
Time frame: baseline, 1 month
Change from Baseline Cancer Risk and Healthy Food Craving and Valuation at 1 month, Self-report Questionnaire 2
Food Craving Inventory self-report questionnaire measuring craving and valuation in dollars per serving of cancer risk and healthy foods. There are 28 items on each subscale (one for craving and one for valuation), and the items are averaged within each subscale. The range of the craving scale is 1-5 (i.e., average of 28 1-to-5 Likert ratings) and the range of the valuation scale is 1-4 (i.e., average of 28 1-to-4 Likert ratings). The subscales are reported separately and not combined. Greater numbers indicate more craving / value of the unhealthy foods, so lower numbers indicate a better outcome.
Time frame: 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
Performance on a standard inhibitory control task (Stop-Signal) with personal risk cues
Time frame: 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
Performance on a standard inhibitory control task (Go/No-Go) with personal risk cues
Time frame: baseline, 1 month
Change from Baseline Cognitive Reappraisal of Food at 1 month, Behavioral marker
Performance on a Regulation of Craving Task for Food
Time frame: baseline, 1 month
Change from Baseline Valuation of Subjective Value of Various Foods at 1 month, Behavioral marker
Performance on Willingness-to-Pay Task - Food
Time frame: baseline, 1 month
Change from Baseline Habitual Response to Food at 1 month, Behavioral marker
Performance on Speeded Cue-Behavior Association Task
Time frame: 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
Premotor, basal ganglia, dorsal cingulate, and Thalamus Activity during standard inhibitory control task (Stop-Signal) with personal risk cues
Time frame: 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
Premotor, basal ganglia, dorsal cingulate, and Thalamus Activity during standard inhibitory control task (Go/No-Go) with personal risk cues
Time frame: baseline, 1 month
Change from Baseline Cognitive Reappraisal of Food at 1 month, Neural marker
Dorsolateral Prefrontal Cortex and ventrolateral Prefrontal Cortex activity during Regulation of Craving Task for Food
Time frame: baseline, 1 month
Change from Baseline Habitual Response to Food at 1 month, Neural marker
Shift from ventral to dorsal striatum activity during Speeded Cue-Behavior Association Task
Time frame: baseline, 1 month
Change from Baseline Valuation of Subjective Value of Various Foods at 1 month, Neural marker
Ventromedial prefrontal cortex activity during the Willingness-to-Pay Task - Food
Time frame: baseline, 1 month