Comparison of Flavonoid Intake Assessment Methods Using USDA and Phenol Explorer Databases: Subcohort Diet, Cancer and Health-Next Generations-MAX Study

Fabian Lanuza; Nicola P Bondonno; Raul Zamora-Ros; Agnetha Linn Rostgaard-Hansen; Anne Tjønneland; Rikard Landberg; Jytte Halkjær; Cristina Andres-Lacueva

doi:10.3389/fnut.2022.873774

Comparison of Flavonoid Intake Assessment Methods Using USDA and Phenol Explorer Databases: Subcohort Diet, Cancer and Health-Next Generations-MAX Study

Front Nutr. 2022 Apr 4:9:873774. doi: 10.3389/fnut.2022.873774. eCollection 2022.

Authors

Fabian Lanuza^{1

2}, Nicola P Bondonno^{3

4}, Raul Zamora-Ros^{1

5}, Agnetha Linn Rostgaard-Hansen³, Anne Tjønneland^{3

6}, Rikard Landberg⁷, Jytte Halkjær³, Cristina Andres-Lacueva^{1

2}

Affiliations

¹ 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.
² CIBER of Frailty and Healthy Aging (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain.
³ Danish Cancer Society Research Center, Copenhagen, Denmark.
⁴ Institute for Nutrition Research, School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia.
⁵ Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain.
⁶ Department of Public Health, Section of Environmental Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
⁷ Division of Food and Nutrition Science, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.

Abstract

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.

Keywords: aglycone; concordance; food composition; glycoside; polyphenol; reliability.