Hillesheim Elaine, Ryan Miriam F, Gibney Eileen, Roche Helen M, Brennan Lorraine
UCD Institute of Food and Health, UCD School of Agriculture and Food Science, UCD, Dublin 4, Belfield Ireland.
UCD Conway Institute of Biomolecular and Biomedical Research, UCD, Dublin 4, Belfield Ireland.
Nutr Metab (Lond). 2020 Sep 29;17:82. doi: 10.1186/s12986-020-00499-z. eCollection 2020.
Targeted nutrition is defined as dietary advice tailored at a group level. Groups known as metabotypes can be identified based on individual metabolic profiles. Metabotypes have been associated with differential responses to diet, which support their use to deliver dietary advice. We aimed to optimise a metabotype approach to deliver targeted dietary advice by encompassing more specific recommendations on nutrient and food intakes and dietary behaviours.
Participants (n = 207) were classified into three metabotypes based on four biomarkers (triacylglycerol, total cholesterol, HDL-cholesterol and glucose) and using a k-means cluster model. Participants in metabotype-1 had the highest average HDL-cholesterol, in metabotype-2 the lowest triacylglycerol and total cholesterol, and in metabotype-3 the highest triacylglycerol and total cholesterol. For each participant, dietary advice was assigned using decision trees for both metabotype (group level) and personalised (individual level) approaches. Agreement between methods was compared at the message level and the metabotype approach was optimised to incorporate messages exclusively assigned by the personalised approach and current dietary guidelines. The optimised metabotype approach was subsequently compared with individualised advice manually compiled.
The metabotype approach comprised advice for improving the intake of saturated fat (69% of participants), fibre (66%) and salt (18%), while the personalised approach assigned advice for improving the intake of folate (63%), fibre (63%), saturated fat (61%), calcium (34%), monounsaturated fat (24%) and salt (14%). Following the optimisation of the metabotype approach, the most frequent messages assigned to address intake of key nutrients were to increase the intake of fruit and vegetables, beans and pulses, dark green vegetables, and oily fish, to limit processed meats and high-fat food products and to choose fibre-rich carbohydrates, low-fat dairy and lean meats (60-69%). An average agreement of 82.8% between metabotype and manual approaches was revealed, with excellent agreements in metabotype-1 (94.4%) and metabotype-3 (92.3%).
The optimised metabotype approach proved capable of delivering targeted dietary advice for healthy adults, being highly comparable with individualised advice. The next step is to ascertain whether the optimised metabotype approach is effective in changing diet quality.
目标营养被定义为在群体层面量身定制的饮食建议。可以根据个体代谢谱识别出称为代谢型的群体。代谢型与对饮食的不同反应有关，这支持了利用它们来提供饮食建议。我们旨在优化一种代谢型方法，通过纳入关于营养素和食物摄入量以及饮食行为的更具体建议来提供有针对性的饮食建议。
参与者（n = 207）基于四种生物标志物（三酰甘油、总胆固醇、高密度脂蛋白胆固醇和葡萄糖）并使用k均值聚类模型被分为三种代谢型。代谢型1的参与者平均高密度脂蛋白胆固醇最高，代谢型2的三酰甘油和总胆固醇最低，代谢型3的三酰甘油和总胆固醇最高。对于每位参与者，使用决策树为代谢型（群体层面）和个性化（个体层面）方法分配饮食建议。在信息层面比较两种方法之间的一致性，并对代谢型方法进行优化，以纳入仅由个性化方法和当前饮食指南分配的信息。随后将优化后的代谢型方法与手动编制的个性化建议进行比较。
代谢型方法包括改善饱和脂肪（69%的参与者）、纤维（66%）和盐（18%）摄入量的建议，而个性化方法分配了改善叶酸（63%）、纤维（63%）、饱和脂肪（61%）、钙（34%）、单不饱和脂肪（24%）和盐（14%）摄入量的建议。在优化代谢型方法后，针对关键营养素摄入量给出的最常见建议是增加水果和蔬菜、豆类和豆类、深绿色蔬菜以及油性鱼类的摄入量，限制加工肉类和高脂肪食品，并选择富含纤维的碳水化合物、低脂乳制品和瘦肉（60 - 69%）。代谢型方法与手动方法之间的平均一致性为82.8%，在代谢型1（94.4%）和代谢型3（92.3%）中一致性极佳。
优化后的代谢型方法被证明能够为健康成年人提供有针对性的饮食建议，与个性化建议高度可比。下一步是确定优化后的代谢型方法在改变饮食质量方面是否有效。
