Development of a food frequency questionnaire for the estimation of dietary (poly)phenol intake

Background: (Poly)phenol intake has been associated with reduced risk of non-communicable diseases in epidemiological studies. However, there are currently no dietary assessment tools specifically developed to estimate (poly)phenol intake in the UK population. Objectives: This study aimed to develop a novel food frequency questionnaire (FFQ) to capture the dietary (poly)phenol intake in the UK and assess its relative validity with 7 day diet diaries (7DDs) and plasma and urine (poly)phenol metabolites. Methods: The KCL (poly)phenol FFQ (KP-FFQ) was developed based on the existing EPIC (European Prospective Investigation into Diet and Cancer)-Norfolk FFQ, which has been validated for energy and nutrient intake estimation in the UK population. Participants aged 18-29 years (n = 255) completed both the KP-FFQ and the EPIC-Norfolk FFQ. In a subgroup (n = 60), 7DD, spot urine, and fasting plasma samples were collected. An in-house (poly)phenol database was used to estimate (poly)phenol intake from FFQs and 7DDs. Plasma and urinary (poly)phenol metabolite levels were analysed using a validated ultra-high-performance liquid chromatography-triple quadrupole mass spectrometry method. The agreements between (poly)phenol intake estimated using the KP-FFQ, EPIC-Norfolk FFQ and 7DDs, as well as plasma and urinary biomarkers, were evaluated by intraclass correlation coefficients (ICC), weighted kappa, quartile cross-classification, and Spearman's correlations, and the associations were investigated using linear regression models adjusting for energy intake and multiple testing (false discovery rate (FDR) < 0.05). Results: The mean (standard deviation, SD) of total (poly)phenol intake estimated from KP-FFQs was 1366.5 (1151.7) mg d ⁻¹. Fair agreements were observed between ten (poly)phenol groups estimated from KP-FFQs and 7DDs (kappa: 0.41-0.73), including total (poly)phenol intake (kappa = 0.45), while the agreements for the rest of the 17 classes and subclasses were poor (kappa: 0.07-0.39). Strong positive associations with KP-FFQ were found in ten (poly)phenols estimated from 7DDs, including dihydroflavonols, theaflavins, thearubigins, flavones, isoflavonoids, ellagitannins, hydroxyphenylacetic acids, total stilbenes, resveratrol, and tyrosols with stdBeta ranged from 0.61 (95% confidence interval CI: 0.42 to 0.81) to 0.95 (95% CI: 0.86 to 1.03) (all FDR adjusted p < 0.05). KP-FFQs estimated (poly)phenol intake exhibited positive associations with 76 urinary metabolites (stdBeta: 0.28 (95% CI: 0.07-0.49) to 0.81 (0.62-1.00)) and 19 plasma metabolites (stdBeta: 0.40 (0.17-0.62)-0.83 (0.64-1.02)) (all FDR p < 0.05). The agreement between KP-FFQs and the EPIC-Norfolk FFQs was moderate (ICC 0.51-0.69) for all (poly)phenol subclasses after adjusting for energy intake. Compared with the EPIC-Norfolk FFQs estimated (poly)phenol intake, stronger and more agreements and associations were found in KP-FFQs estimated (poly)phenol with 7DDs and biomarkers. Conclusion: (Poly)phenol intake estimated from KP-FFQ exhibited fair agreements and moderate to strong associations with 7DDs and biomarkers, indicating the novel questionnaire may be a promising tool to assess dietary (poly)phenol intake.