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Abstract：
BACKGROUND: 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.
METHODS: 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.
RESULTS: 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%).
CONCLUSIONS: 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.
METHODS: 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.
RESULTS: 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%).
CONCLUSIONS: 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.
摘要：
背景：目标营养被定义为在群体水平上定制的饮食建议。可以基于个体代谢谱鉴定被称为代谢型的组。代谢型与对饮食的不同反应有关，这支持他们使用提供饮食建议。我们旨在优化代谢型方法，通过包含有关营养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。
方法：参与者（n=207）根据四种生物标志物（三酰甘油，总胆固醇,HDL-胆固醇和葡萄糖），并使用k均值聚类模型。1型的参与者具有最高的平均HDL-胆固醇，在2型中，三酰甘油和总胆固醇最低，在3型中，三酰甘油和总胆固醇最高。对于每个参与者，饮食建议使用决策树为代谢型(组水平)和个性化(个体水平)方法分配.在消息级别比较了方法之间的一致性，并优化了元型方法，以纳入由个性化方法和当前饮食指南专门分配的消息。随后将优化的代谢型方法与手动编译的个性化建议进行比较。
结果：代谢型方法包括改善饱和脂肪摄入量的建议（69％的参与者），纤维(66%)和盐(18%)，虽然个性化方法为提高叶酸的摄入量提供了建议(63%)，纤维（63%），饱和脂肪（61%），钙（34%），单不饱和脂肪(24%)和盐(14%)。在优化代谢型方法之后，分配给解决关键营养素摄入量的最常见信息是增加水果和蔬菜的摄入量，豆类和豆类，深绿色蔬菜,和油性鱼，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%）。代谢型和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％）中具有出色的一致性。
结论：优化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。下一步是确定优化的代谢型方法在改变饮食质量方面是否有效。
方法：参与者（n=207）根据四种生物标志物（三酰甘油，总胆固醇,HDL-胆固醇和葡萄糖），并使用k均值聚类模型。1型的参与者具有最高的平均HDL-胆固醇，在2型中，三酰甘油和总胆固醇最低，在3型中，三酰甘油和总胆固醇最高。对于每个参与者，饮食建议使用决策树为代谢型(组水平)和个性化(个体水平)方法分配.在消息级别比较了方法之间的一致性，并优化了元型方法，以纳入由个性化方法和当前饮食指南专门分配的消息。随后将优化的代谢型方法与手动编译的个性化建议进行比较。
结果：代谢型方法包括改善饱和脂肪摄入量的建议（69％的参与者），纤维(66%)和盐(18%)，虽然个性化方法为提高叶酸的摄入量提供了建议(63%)，纤维（63%），饱和脂肪（61%），钙（34%），单不饱和脂肪(24%)和盐(14%)。在优化代谢型方法之后，分配给解决关键营养素摄入量的最常见信息是增加水果和蔬菜的摄入量，豆类和豆类，深绿色蔬菜,和油性鱼，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%）。代谢型和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％）中具有出色的一致性。
结论：优化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。下一步是确定优化的代谢型方法在改变饮食质量方面是否有效。
