Modelling individual responses to healthier diets: new ways to quantify the importance of physiology and behaviour for successful dietary changes

饮食是健康的主要决定因素。传统上，饮食对健康参数的影响被确定为人群中的平均反应。然而，据估计，只有40%的人口对饮食干预有反应。精确营养方法通过单一受试者研究对个体水平的影响。在这些所谓的n-of-1试验中，随着个体接受不同的治疗，随着时间的推移，会收集到多个数据。这使我们能够研究遗传、表型和环境因素如何塑造个人的反应，以及这与普通人群对饮食干预的反应有多大不同。如果在足够长的时间内收集了足够多的数据，并通过寻找多个n-of-1研究的共性，可以汇总数据以预测饮食干预在特定人群中的有效性。Food4Me的研究表明，基于预测的个人反应的个性化饮食可以成为改善个人健康的有效策略。该项目的目标是量化个体之间对特定饮食变化的健康反应的差异，并确定哪些个人生理特征和因素决定了这种差异。我们还将调查心理和行为因素与生理决定因素有关的对个人反应的重要性。这项计划将包括三个相互关联的阶段，开发新的数学方法，并结合生理和行为科学。为了更好地理解是什么推动了饮食变化的个体影响和成功。在第一阶段，我们将利用来自随机对照干预研究的相关结果的重复测量的可用的高质量数据集来重新分析具有n-of-1统计的数据，随后聚集多个n-of-1试验，以调查生理和行为因素如何影响代谢标记物的反应。我们假设，这种方法将能够准确预测个体对饮食干预的反应。在该项目的第二阶段，我们将进行一项原则证明‘n-of-1’饮食干预研究，在该研究中，将在有限数量的受试者中测量对饮食的大量反应。这将揭示所观察到的感兴趣的健康结果的变化是否确实是由饮食治疗引起的，还是仅仅是由于正常的生物波动造成的。这位博士生将与联合利华研发的消费者科学小组合作，探索心理和行为因素的作用，这些因素决定了个人对短期或长期消费更健康食品的反应。为了实现这一点，将在原则验证研究中衡量行为方面(知识、感知、自我效能、社会规范和意图以及奖励)。

Diet is a major determinant of health. Traditionally, effects of diet on health parameters are determined as the average response in a population. However, it is estimated that only 40% of any population responds to a dietary intervention. Precision nutrition approaches investigate effects on the individual level by single subject studies. In these so-called 'n-of-1 trials', multiple data are collected over time as the individual undergoes different treatments. This enables us to study how genetic, phenotypic and environmental factors shape an individual's response, and to what extent this differs from the average population responses, to dietary interventions. If enough data are collected over a sufficiently long time, and by looking for commonalities across multiple n-of-1 studies, the data can be aggregated to predict effectiveness of dietary interventions in defined population groups. The Food4Me study showed that personalised diets, based on predicted individual responsiveness, can be an effective strategy to improve individual health. The objective of this project is to quantify differences in health responses to specific dietary changes between individuals, and to identify which personal physiologic characteristics and factors determine this variation. We will also investigate the importance of psychological and behavioural factors, in relation to physiological determinants, for individual responsive.This project will consist of three interlinked phases that exploit new mathematical methodologies and combine physiological and behavioural sciences. to better understand what drives individual effects and success of dietary changes. In the first phase we will make use of available high-quality datasets with repeated measurements of relevant outcomes from randomised controlled intervention studies to re-analyse data with n-of-1 statistics, followed by aggregation of multiple n-of-1 trials to investigate how physiological and behavioural factors contribute to responses in metabolic markers. We postulate that this approach will enable accurate prediction of individual responses to dietary interventions. In the second phase of the project we will conduct a proof-of-principal 'n-of-1' dietary intervention study in which a large number of responses to a diet will be measured in a limited number of subjects. This will reveal whether an observed change in a health outcome of interest is indeed caused by the dietary treatment or just due to normal biological fluctuations. In collaboration with the consumer science group at Unilever R&D, the PhD student will explore the role of psychological and behavioural factors that determine individual responses to short- or long-term consumption of healthier foods. To achieve this, both behavioural aspects (knowledge, perception, self-efficacy, social norms and intentions and reward will be measured in the proof-of-principle study.