一种新的(聚)酚富集饮食评分的开发及其与尿(聚)苯酚代谢产物的关系。

IF 5.1 1区 农林科学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Food & Function Pub Date : 2023-09-20 DOI:10.1039/D3FO01982A
Yifan Xu, Yong Li, Jiaying Hu, Rachel Gibson and Ana Rodriguez-Mateos
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引用次数: 0

摘要

背景:由于饮食评估工具不足和食物含量数据有限,估计(聚)苯酚摄入量具有挑战性。目前,缺乏表征(多)苯酚丰富饮食的先验饮食评分。本研究旨在开发一种新的(多)苯酚富集饮食评分(PPS),并探讨其与循环(多)酚代谢产物的关系。方法:共有543名18-80岁的健康自由生活参与者完成了食物频率问卷(FFQ)(EPIC Norfolk),并提供了24小时的尿液样本。PPS是根据英国饮食中丰富的20种选定的(聚)苯酚丰富食物的相对摄入量(五分位数)制定的,包括茶、咖啡、红酒、全谷物、巧克力和可可制品、浆果、苹果和果汁、梨、葡萄、李子、柑橘类水果和果汁、土豆和胡萝卜、洋葱、辣椒、大蒜、绿色蔬菜、豆类、大豆和豆制品、坚果和橄榄油。PPS中包含的食品是根据其(聚)酚含量、(聚)苯酚的主要来源和英国人群的消费频率来选择的。采用调整能量摄入的线性模型和多重测试(FDR调整p<0.05)研究了PPS与尿酚类代谢产物之间的相关性。结果:PPS总分在25至88分之间,平均得分为54分。共有51种尿液代谢产物与PPS显著相关,包括39种酚酸、5种黄酮类化合物、3种木脂素、2种白藜芦醇和2种其他(多)酚代谢产物。FFQ得出的总(聚)酚摄入量也与PPS呈正相关(stdBeta 0.32,95%CI(0.24,0.40),p<0.01)。在估计的(聚)苯酚摄入量和PPS的27个类别和亚类别中,有24个类别和子类别观察到显著的正相关,标准β值范围从茶黄素/茶红素的0.12(0.040.20)到黄酮醇的0.43(0.34,0.51)(p<0.01)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Development of a novel (poly)phenol-rich diet score and its association with urinary (poly)phenol metabolites†

Background: Estimating (poly)phenol intake is challenging due to inadequate dietary assessment tools and limited food content data. Currently, a priori diet scores to characterise (poly)phenol-rich diets are lacking. This study aimed to develop a novel (poly)phenol-rich diet score (PPS) and explore its relationship with circulating (poly)phenol metabolites. Methods: A total of 543 healthy free-living participants aged 18–80 years completed a food frequency questionnaire (FFQ) (EPIC-Norfolk) and provided 24 h urine samples. The PPS was developed based on the relative intake (quintiles) of 20 selected (poly)phenol-rich food items abundant in the UK diet, including tea, coffee, red wine, whole grains, chocolate and cocoa products, berries, apples and juice, pears, grapes, plums, citrus fruits and juice, potatoes and carrots, onions, peppers, garlic, green vegetables, pulses, soy and soy products, nuts, and olive oil. Foods included in the PPS were chosen based on their (poly)phenol content, main sources of (poly)phenols, and consumption frequencies in the UK population. Associations between the PPS and urinary phenolic metabolites were investigated using linear models adjusting energy intake and multiple testing (FDR adjusted p < 0.05). Result: The total PPS ranged from 25 to 88, with a mean score of 54. A total of 51 individual urinary metabolites were significantly associated with the PPS, including 39 phenolic acids, 5 flavonoids, 3 lignans, 2 resveratrol and 2 other (poly)phenol metabolites. The total (poly)phenol intake derived from FFQs also showed a positive association with PPS (stdBeta 0.32, 95% CI (0.24, 0.40), p < 0.01). Significant positive associations were observed in 24 of 27 classes and subclasses of estimated (poly)phenol intake and PPS, with stdBeta values ranging from 0.12 (0.04, 0.20) for theaflavins/thearubigins to 0.43 (0.34, 0.51) for flavonols (p < 0.01). Conclusion: High adherence to the PPS diet is associated with (poly)phenol intake and urinary biomarkers, indicating the utility of the PPS to characterise diets rich in (poly)phenols at a population level.

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来源期刊
Food & Function
Food & Function BIOCHEMISTRY & MOLECULAR BIOLOGY-FOOD SCIENCE & TECHNOLOGY
CiteScore
10.10
自引率
6.60%
发文量
957
审稿时长
1.8 months
期刊介绍: Food & Function provides a unique venue for physicists, chemists, biochemists, nutritionists and other food scientists to publish work at the interface of the chemistry, physics and biology of food. The journal focuses on food and the functions of food in relation to health.
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