Reducing Cancer Risk by Training Response Inhibition to Obesogenic Foods

 描述（由申请人提供）：饮食选择，特别是导致肥胖的过量卡路里摄入，是癌症的强烈但可逆的风险因素。例如，富含固体脂肪和添加糖（SoFaS）的食物是低营养、高热量的食物，会通过促进体重增加来增加患癌症的风险。因此，SoFaS的减少与美国癌症研究所和美国癌症协会的饮食建议一致。改变饮食的行为干预措施的长期疗效有限，这很可能是因为饮食决定受自动神经认知过程的控制，而这些过程在传统干预措施中没有得到解决。特别是，人们越来越认识到，避免食用不健康但广泛存在的可口食物的能力取决于抑制性控制，即，这种能力切断了由先天因素引发的行动倾向， 奖励行为的驱动力。我们团队和其他人最近的工作表明，基于计算机的抑制控制训练会导致短期的特定行为变化，例如减少咸味零食、巧克力和酒精饮料的摄入。一种自动化的，基于家用计算机的抑制控制训练提供了一种廉价且高度可传播的方法，可以降低广泛人群的癌症风险。因此，我们的目的是评估的可行性，可接受性，作用机制，有效性和持久性的家庭计算机为基础的抑制控制训练。特别是，我们假设抑制控制的高重复训练将导致对低SoFaS饮食的依从性增加，并且该效果将通过改善抑制控制来介导。我们进一步假设，对于那些抑制控制受损的人，以及那些对美味食物有最强烈欲望的人和那些有最强烈明确健康目标的人，训练将是最有效的。最后，我们的目标是检查抑制控制训练对次要结果的影响，包括对总体热量摄入和短期体重减轻的影响。为了实现这些目标，拟议的研究将招募150名超重和肥胖的人，他们目前吃高SoFaS饮食，并希望改善他们的饮食。参与者将被分配减少SoFaS饮食12周。基线期后，受试者将随机接受6周的抑制对照训练或假训练。为期6周的干预将包括每天15分钟的基于家庭计算机的抑制控制训练，随后是为期2周的加强训练，然后是为期2周的随访期。饮食依从性将通过定制的智能手机应用程序进行测量，该应用程序将提示重复记录目标食物消耗量（即，生态瞬时评估（EMA）和24小时自动食品召回。神经认知变量将在训练前和训练后进行评估，以测试训练的作用机制，适度将通过明确的健康目标，对食欲刺激的内隐态度，男孩质量指数和对食物线索的反应的基线特质测量进行评估。

 DESCRIPTION (provided by applicant): Dietary choices, and in particular, excess calorie intake leading to obesity, are strong, but reversible risk factors for cancer. For example, foods high in solid fats and added sugars (SoFaS) are low-nutrient, high calorie foods that increase the risk of cancer by promoting weight gain. As such, the reduction of SoFaS is consistent with American Institute for Cancer Research and the American Cancer Society dietary recommendations. Behavioral interventions to alter diet have limited long-term efficacy, most likely because eating decisions are governed by automatic neurocognitive processes that are not addressed in conventional interventions. In particular, the ability to refrain from consuming unhealthy, but widely available, palatable foods, is increasingly understood to depend on inhibitory control, i.e., the ability to cut off action tendencies that are put in motion by innate drives towards rewarding behaviors. Recent work by our team and others have demonstrated that computer-based inhibitory control trainings result in short-term, specific changes in behavior, such as reducing intake of salty snack food, chocolate, and alcoholic beverages. An automatized, home computer-based inhibitory control training offers the potential of an inexpensive and highly disseminable method of lowering cancer risk across wide swaths of the population. As such, we aim to evaluate the feasibility, acceptability, mechanism of action, effectiveness and persistence of a home computer-based inhibitory control training. In particular, we hypothesize that a high-repetition training in inhibitory control will result in increased adherence to a low-SoFaS diet, and that effects will be mediated through improved inhibitory control. We further hypothesize the training will be most effective for those starting of with impaired inhibitory control, as well as those with strongest desire for palatable foods and those with strongest explicit health goals. Lastly, we aim to examine the impact of inhibitory control training on secondary outcomes, including on overall caloric intake, and on short-term weight loss. To achieve these aims, the proposed study will recruit 150 overweight and obese individuals who currently eat high-SoFaS diets, and who wish to improve their diets. Participants will be assigned a reduced-SoFaS diet for 12 weeks. After a baseline period, participants will be randomized to receive 6 weeks of either inhibitory control training or a sham training. The 6-week intervention will consist of 15 minutes per day of home computer- based inhibitory control training, and will be followed by a 2-week booster and then 2-week follow-up period. Dietary adherence will be measured via a customized smartphone app that will prompt repeated recording of targeted food consumption (i.e., ecological momentary assessment; EMA) and via automated 24-hour food recall. Neurocognitive variables will be assessed pre and post-training in order to test trainings' mechanism of action, and moderation will be assessed through baseline trait measures of explicit health goals, implicit attitudes towards appetitive stimuli, boy mass index, and responsivity to food cues.