Ultra-processed food reward: neural and metabolic factors

超加工食品的奖励：神经和代谢因素

• 批准号: 10586928
• 负责人: Alexandra Gold DiFeliceantonio
• 金额: $ 43.02万
• 依托单位: VIRGINIA POLYTECHNIC INST AND ST UNIV
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-01 至 2028-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10586928
• 关键词: Affect; Area; Automobile Driving; Behavioral; Brain; Brain region; Calories; Carbohydrates; Cardiovascular Diseases; Cephalic; Confounding Factors (Epidemiology); Consumption; Corpus striatum structure; Cues; Data; Disease; Dopamine; Energy Metabolism; Energy-Generating Resources; Fiber; Food; Food Processing; Food Supply; Formulation; Fortified Food; Functional Magnetic Resonance Imaging; Future; Glucose; Glycemic Index; Goals; Health; Human; Hyperphagia; Incidence; Individual; Individual Differences; Industrialization; Infusion procedures; Intake; Intervention; Learning; Link; Machine Learning; Macronutrients Nutrition; Malignant Neoplasms; Measures; Metabolic; Metabolic dysfunction; Metabolism; Modeling; Modernization; Motivation; Neurobiology; Non-Insulin-Dependent Diabetes Mellitus; Nutrient; Nutrient availability; Obesity; Outcome; Pharmaceutical Preparations; Phase; Physiological; Physiology; Predisposition; Process; Property; Psychological reinforcement; Recording of previous events; Reducing diet; Research; Rewards; Rodent; Role; Signal Transduction; Source; Speed; Surface; System; Testing; Time; Weight Gain; abuse liability; addiction; behavior measurement; blood oxygenation level dependent response; burden of illness; conditioning; density; dietary guidelines; drug of abuse; drug quality; energy density; experimental study; food consumption; food environment; improved; innovation; metabolic rate; mortality; neural; neurobiological mechanism; nutrient absorption; oxidation; predictive modeling; preventable death; response

PROJECT SUMMARY The food environment has changed dramatically and rapidly in the last 50 years. A glance around any grocery store will demonstrate that ultra-processed foods, defined as industrial formulations of sources of energy, nutrients, and additives have come to dominate the food supply. In fact, ultra-processed foods now make up around 58% of total calories consumed in the US. Ultra-processed food consumption has been linked with various forms of cancer, increased cardiovascular disease, and increased all-cause mortality. Therefore, basic understanding of the mechanisms that drive consumption of ultra-processed foods must keep pace with their increasing availability and expanding percentage of the US food supply. The long-term goals of this research are to identify specific properties of ultra-processed foods that support their consumption, the physiological and neurobiological mechanisms they exploit to affect activity in brain reward systems, and the individual factors that drive susceptibility to overconsumption so they can be later targeted for intervention. Our central hypothesis is that ultra-processed foods are enriched in rapidly useable calories, which enhances reward related brain activity to those specific foods (and associated cues and flavors) and renders them more reinforcing. To this end, in Aim 1, we will parametrically vary the speed of nutrient availability and assess brain response to calorie predictive flavors and measure the rewarding properties of those flavors. In Aim 2, by varying the level of processing in foods, while controlling for caloric density and macronutrient profiles, we will directly assess the specific role of food processing on the time course of the metabolic response to consumption and its relation to brain activity and food value. We will use data collected in both aims to create predictive models that will allow us to pinpoint key factors, both within the individual and within the food, that drive food reward. To our knowledge, this proposal is one of the few to assess processing as a key factor, while controlling for other confounding variables such as energy density and macronutrient content. By combining this with an innovative analysis approach we will have a unique opportunity for generating a data driven assessment of key factors in ultra-processed food reward. The data generated in support of this proposal have high potential significance in that they could provide key evidence needed for changing dietary guidelines with the ultimate goal of reducing diet-related mortality and disease.

项目摘要 在过去的50年里，食品环境发生了巨大而迅速的变化。随便逛一家杂货店 商店将展示超加工食品，定义为能源的工业配方， 营养素和添加剂已经开始主导食品供应。事实上，超加工食品 约占美国总卡路里消耗量的58%。超加工食品消费与 各种形式的癌症，心血管疾病增加，全因死亡率增加。因此，基本 对推动超加工食品消费的机制的理解必须跟上他们的步伐。 增加美国食品供应的可用性和扩大百分比。这项研究的长期目标是 是确定超加工食品的特定特性，以支持其消费、生理和 他们利用神经生物学机制来影响大脑奖励系统的活动， 从而使他们更容易过度消费，这样他们以后就可以成为干预的目标。我们的中央 一种假设是，超加工食品富含快速可用的卡路里，这会提高奖励 将大脑活动与这些特定的食物（以及相关的线索和味道）联系起来， 加强。为此，在目标1中，我们将参数化地改变营养可用性的速度，并评估大脑 对卡路里预测口味的反应，并测量这些口味的奖励特性。在目标2中， 改变食品加工水平，同时控制热量密度和常量营养素分布，我们将 直接评估食品加工对代谢反应时间进程的具体作用， 消费量及其与大脑活动和食物价值的关系。我们将使用在这两个目标中收集的数据来创建 预测模型将使我们能够确定关键因素，无论是在个人还是在食物中， 驾驶食物奖励。据我们所知，这一建议是少数几个将处理作为关键因素进行评估的建议之一， 同时控制其它混杂变量，例如能量密度和常量营养素含量。通过 将其与创新的分析方法相结合，我们将有一个独特的机会来生成数据， 驱动超加工食品奖励的关键因素的评估。为支持这一点而生成的数据 该提案具有很高的潜在意义，因为它们可以提供改变饮食所需的关键证据 指导方针，最终目标是减少与饮食有关的死亡率和疾病。