Lanuza Fabian, Bondonno Nicola P, Zamora-Ros Raul, Rostgaard-Hansen Agnetha Linn, Tjønneland Anne, Landberg Rikard, Halkjær Jytte, Andres-Lacueva Cristina
Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, Food Innovation Network (XIA), Faculty of Pharmacy and Food Sciences, Institute of Nutrition and Food Safety (INSA-UB), University of Barcelona, Barcelona, Spain.
CIBER of Frailty and Healthy Aging (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain.
Front Nutr. 2022 Apr 4;9:873774. doi: 10.3389/fnut.2022.873774. eCollection 2022.
Flavonoids are bioactive plant compounds that are widely present in the human diet. Estimating flavonoid intake with a high degree of certainty is challenging due to the inherent limitations of dietary questionnaires and food composition databases. This study aimed to evaluate the degree of reliability among flavonoid intakes estimated using four different approaches based on the two most comprehensive flavonoid databases, namely, United States Department of Agriculture (USDA) and Phenol Explorer (PE). In 678 individuals from the MAX study, a subcohort of the Diet, Cancer and Health-Next Generations cohort, dietary data were collected using three 24-h diet recalls over 1 year. Estimates of flavonoid intake were compared using flavonoid food content from PE as (1) aglycones (chromatography with hydrolysis), (2) aglycones transformed (converted from glycosides by chromatography without hydrolysis), (3) as they are in nature (glycosides, aglycones, and esters), and 4) using flavonoid content from USDA as aglycones (converted). Spearman's intra-class correlation (ICC) coefficient and weighted kappa (K) coefficient were calculated for the reliability analysis. When comparing PE total aglycones to USDA total aglycones, there was a moderate reliability when a continuous variable was used [ICC: 0.73, 95% confidence interval (CI): 0.70-0.76] and an excellent reliability when flavonoid intake was modeled as a categorical variable (K: 0.89, 95% CI: 0.88-0.90). The degree of reliability among all methods of estimated flavonoid intakes was very similar, especially between database pairs, for the flavanol subclass, while larger differences were observed for flavone, flavonol, and isoflavone subclasses. Our findings indicate that caution should be taken when comparing the results of the associations between flavonoid intakes and health outcomes from studies, when flavonoid intakes were estimated using different methods, particularly for some subclasses.
黄酮类化合物是具有生物活性的植物化合物，广泛存在于人类饮食中。由于膳食问卷和食物成分数据库的固有局限性，要高度准确地估计黄酮类化合物的摄入量具有挑战性。本研究旨在基于两个最全面的黄酮类化合物数据库，即美国农业部（USDA）和酚类物质探索者（PE），评估使用四种不同方法估计的黄酮类化合物摄入量之间的可靠程度。在饮食、癌症与健康-下一代队列研究的子队列MAX研究中的678名个体中，通过1年期间三次24小时饮食回顾收集膳食数据。使用PE中的黄酮类食物含量，将黄酮类化合物摄入量的估计值进行比较，具体如下：（1）苷元（水解色谱法），（2）转化后的苷元（通过非水解色谱法从糖苷转化而来），（3）天然存在形式（糖苷、苷元和酯），以及（4）使用USDA中的黄酮类化合物含量作为转化后的苷元。计算Spearman组内相关（ICC）系数和加权kappa（K）系数进行可靠性分析。当将PE总苷元与USDA总苷元进行比较时，使用连续变量时可靠性中等[ICC：0.73，95%置信区间（CI）：0.70 - 0.76]，将黄酮类化合物摄入量建模为分类变量时可靠性极佳（K：0.89，95% CI：0.88 - 0.90）。所有估计黄酮类化合物摄入量方法之间的可靠程度非常相似，尤其是对于黄烷醇亚类，在数据库对之间更是如此，而对于黄酮、黄酮醇和异黄酮亚类则观察到较大差异。我们的研究结果表明，当使用不同方法估计黄酮类化合物摄入量时，尤其是对于某些亚类，在比较黄酮类化合物摄入量与健康结果之间关联的研究结果时应谨慎。
