Devaluing Foods to Change Eating Behavior
Condition: Overweight and Obesity; Cancer
MeSH terms: Overweight
Study type: Interventional

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.
    

Intervention name(s): Devaluing energy-dense foods for cancer-control
Intervention type(s): Behavioral
Intervention description(s): 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.
Other intervention name(s): Devaluing foods to change eating behavior
Allocation: Randomized
Intervention model: Factorial Assignment
Intervention model description: Quantify the degree to which cognitive and behavioral interventions alter the valuation of cancer-risk foods relative to an active control. We will recruit 300 overweight/obese adults who are at risk for eating- and obesity-related cancers and randomize them to a (a) behavioral response training toward low cancer-risk foods and away from high cancer-risk foods, (b) cognitive reappraisal intervention focused on cancer-risk foods (experimental arms), or (c) non-food inhibitory control training (active control arm). Valuation, our primary mediating process as implicated in the incentive sensitization model, will be measured using behavioral economics tasks and functional magnetic resonance imaging (fMRI) of the vmPFC at pre- and posttraining. Proximal, intervention-specific mediators will also be indexed with fMRI. A final analysis will compare the potency of the intervention-specific neural systems to alter valuation via connectivity to vmPFC.
Masking: None (Open Label)
Primary purpose: Treatment
Keywords: eating; overweight; obesity; cancer risk; translational neuroscience; cognitive reappraisal; functional magnetic resonance imaging (fMRI); vmPFC; inhibitory control; valuation