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Background: Accurate assessment of polyphenol intakes is needed in epidemiologic research in order to study their health effects, and this can be particularly challenging in international study settings., Objective: The purpose of this work is to describe the procedures to prepare a comprehensive polyphenol food-composition database that was used to calculate standardized polyphenol intakes from 24-h diet recalls (24HDRs) and dietary questionnaires (DQs) in the European Prospective Investigation into Cancer and Nutrition (EPIC)., Design: With the use of the comparable food classification and facet-descriptor system of the computerized 24HDR program EPIC-Soft (renamed GloboDiet), foods reported in the 24HDR (n = 74,626) were first aggregated following a stepwise process. Multi-ingredient and generic foods were broken down into ingredients or more-specific foods with consideration of regional consumption habits before matching to foods in the Phenol-Explorer database. Food-composition data were adjusted by using selected retention factors curated in Phenol-Explorer. DQ foods (n = 13,946) were matched to a generated EPIC 24HDR polyphenol-composition database before calculation of daily intakes from the 24HDR and DQ., Results: Food matching yielded 2.0% and 2.7% of foods with missing polyphenol content in the 24HDR and DQ food data sets, respectively. Process-specific retention factors for 42 different polyphenol compounds were applied to adjust the polyphenol content in 35 prioritized Phenol-Explorer foods, thereby adjusting the polyphenol content in 70% of all of the prepared 24 food occurrences. A detailed food-composition database was finally generated for 437 polyphenols in 19,899 aggregated raw and prepared foods reported by 10 EPIC countries in the 24HDR., Conclusions: An efficient procedure was developed to build the most-comprehensive food-composition database for polyphenols, thereby standardizing the calculations of dietary polyphenol intakes obtained from different dietary assessment methods and European populations. The whole database is accessible online. This procedure could equally be used for other food constituents and in other cohorts.

Purpose: Various food patterns have been associated with weight change in adults, but it is unknown which combinations of nutrients may account for such observations. We investigated associations between main nutrient patterns and prospective weight change in adults., Methods: This study includes 235,880 participants, 25-70 years old, recruited between 1992 and 2000 in 10 European countries. Intakes of 23 nutrients were estimated from country-specific validated dietary questionnaires using the harmonized EPIC Nutrient DataBase. Four nutrient patterns, explaining 67 % of the total variance of nutrient intakes, were previously identified from principal component analysis. Body weight was measured at recruitment and self-reported 5 years later. The relationship between nutrient patterns and annual weight change was examined separately for men and women using linear mixed models with random effect according to center controlling for confounders., Results: Mean weight gain was 460 g/year (SD 950) and 420 g/year (SD 940) for men and women, respectively. The annual differences in weight gain per one SD increase in the pattern scores were as follows: principal component (PC) 1, characterized by nutrients from plant food sources, was inversely associated with weight gain in men (-22 g/year; 95 % CI -33 to -10) and women (-18 g/year; 95 % CI -26 to -11). In contrast, PC4, characterized by protein, vitamin B2, phosphorus, and calcium, was associated with a weight gain of +41 g/year (95 % CI +2 to +80) and +88 g/year (95 % CI +36 to +140) in men and women, respectively. Associations with PC2, a pattern driven by many micro-nutrients, and with PC3, a pattern driven by vitamin D, were less consistent and/or non-significant., Conclusions: We identified two main nutrient patterns that are associated with moderate but significant long-term differences in weight gain in adults.

Background/objectives: Polyphenols are plant secondary metabolites with a large variability in their chemical structure and dietary occurrence that have been associated with some protective effects against several chronic diseases. To date, limited data exist on intake of polyphenols in populations. The current cross-sectional analysis aimed at estimating dietary intakes of all currently known individual polyphenols and total intake per class and subclass, and to identify their main food sources in the European Prospective Investigation into Cancer and Nutrition cohort., Methods: Dietary data at baseline were collected using a standardized 24-h dietary recall software administered to 36,037 adult subjects. Dietary data were linked with Phenol-Explorer, a database with data on 502 individual polyphenols in 452 foods and data on polyphenol losses due to cooking and food processing., Results: Mean total polyphenol intake was the highest in Aarhus-Denmark (1786 mg/day in men and 1626 mg/day in women) and the lowest in Greece (744 mg/day in men and 584 mg/day in women). When dividing the subjects into three regions, the highest intake of total polyphenols was observed in the UK health-conscious group, followed by non-Mediterranean (non-MED) and MED countries. The main polyphenol contributors were phenolic acids (52.5-56.9 %), except in men from MED countries and in the UK health-conscious group where they were flavonoids (49.1-61.7 %). Coffee, tea, and fruits were the most important food sources of total polyphenols. A total of 437 different individual polyphenols were consumed, including 94 consumed at a level >1 mg/day. The most abundant ones were the caffeoylquinic acids and the proanthocyanidin oligomers and polymers., Conclusion: This study describes the large number of dietary individual polyphenols consumed and the high variability of their intakes between European populations, particularly between MED and non-MED countries.

Objective: Pattern analysis has emerged as a tool to depict the role of multiple nutrients/foods in relation to health outcomes. The present study aimed at extracting nutrient patterns with respect to breast cancer (BC) aetiology., Design: Nutrient patterns were derived with treelet transform (TT) and related to BC risk. TT was applied to twenty-three log-transformed nutrient densities from dietary questionnaires. Hazard ratios (HR) and 95 % confidence intervals computed using Cox proportional hazards models quantified the association between quintiles of nutrient pattern scores and risk of overall BC, and by hormonal receptor and menopausal status. Principal component analysis was applied for comparison., Setting: The European Prospective Investigation into Cancer and Nutrition (EPIC)., Subjects: Women (n 334 850) from the EPIC study., Results: The first TT component (TC1) highlighted a pattern rich in nutrients found in animal foods loading on cholesterol, protein, retinol, vitamins B12 and D, while the second TT component (TC2) reflected a diet rich in β-carotene, riboflavin, thiamin, vitamins C and B6, fibre, Fe, Ca, K, Mg, P and folate. While TC1 was not associated with BC risk, TC2 was inversely associated with BC risk overall (HRQ5 v. Q1=0·89, 95 % CI 0·83, 0·95, P trend<0·01) and showed a significantly lower risk in oestrogen receptor-positive (HRQ5 v. Q1=0·89, 95 % CI 0·81, 0·98, P trend=0·02) and progesterone receptor-positive tumours (HRQ5 v. Q1=0·87, 95 % CI 0·77, 0·98, P trend<0·01)., Conclusions: TT produces readily interpretable sparse components explaining similar amounts of variation as principal component analysis. Our results suggest that participants with a nutrient pattern high in micronutrients found in vegetables, fruits and cereals had a lower risk of BC.

Purpose: Methodological differences in assessing dietary acrylamide (AA) often hamper comparisons of intake across populations. Our aim was to describe the mean dietary AA intake in 27 centers of 10 European countries according to selected lifestyle characteristics and its contributing food sources in the European Prospective Investigation into Cancer and Nutrition (EPIC) study., Methods: In this cross-sectional analysis, 36 994 men and women, aged 35-74 years completed a single, standardized 24-hour dietary recall using EPIC-Soft. Food consumption data were matched to a harmonized AA database. Intake was computed by gender and center, and across categories of habitual alcohol consumption, smoking status, physical activity, education, and body mass index (BMI). Adjustment was made for participants' age, height, weight, and energy intake using linear regression models., Results: Adjusted mean AA intake across centers ranged from 13 to 47 μg/day in men and from 12 to 39 μg/day in women; intakes were higher in northern European centers. In most centers, intake in women was significantly higher among alcohol drinkers compared with abstainers. There were no associations between AA intake and physical activity, BMI, or education. At least 50 % of AA intake across centers came from two food groups "bread, crisp bread, rusks" and "coffee." The third main contributing food group was "potatoes"., Conclusions: Dietary AA intake differs greatly among European adults residing in different geographical regions. This observed heterogeneity in AA intake deserves consideration in the design and interpretation of population-based studies of dietary AA intake and health outcomes.

Background: Dairy product intake may be inversely associated with risk of type 2 diabetes, but the evidence is inconclusive for total dairy products and sparse for types of dairy products., Objective: The objective was to investigate the prospective association of total dairy products and different dairy subtypes with incidence of diabetes in populations with marked variation of intake of these food groups., Design: A nested case-cohort within 8 European countries of the European Prospective Investigation into Cancer and Nutrition Study (n = 340,234; 3.99 million person-years of follow-up) included a random subcohort (n = 16,835) and incident diabetes cases (n = 12,403). Baseline dairy product intake was assessed by using dietary questionnaires. Country-specific Prentice-weighted Cox regression HRs were calculated and pooled by using a random-effects meta-analysis., Results: Intake of total dairy products was not associated with diabetes (HR for the comparison of the highest with the lowest quintile of total dairy products: 1.01; 95% CI: 0.83, 1.34; P-trend = 0.92) in an analysis adjusted for age, sex, BMI, diabetes risk factors, education, and dietary factors. Of the dairy subtypes, cheese intake tended to have an inverse association with diabetes (HR: 0.88; 95% CI: 0.76, 1.02; P-trend = 0.01), and a higher combined intake of fermented dairy products (cheese, yogurt, and thick fermented milk) was inversely associated with diabetes (HR: 0.88; 95% CI: 0.78, 0.99; P-trend = 0.02) in adjusted analyses that compared extreme quintiles., Conclusions: This large prospective study found no association between total dairy product intake and diabetes risk. An inverse association of cheese intake and combined fermented dairy product intake with diabetes is suggested, which merits further study.

Until recently, the study of nutrient patterns was hampered at an international level by a lack of standardization of both dietary methods and nutrient databases. We aimed to describe the diversity of nutrient patterns in the European Prospective Investigation into Cancer and Nutrition (EPIC) study at population level as a starting point for future nutrient pattern analyses and their associations with chronic diseases in multi-center studies. In this cross-sectional study, 36,034 persons aged 35-74 y were administered a single, standardized 24-h dietary recall. Intake of 25 nutrients (excluding intake from dietary supplements) was estimated using a standardized nutrient database. We used a graphic presentation of mean nutrient intakes by region and sex relative to the overall EPIC means to contrast patterns within and between 10 European countries. In Mediterranean regions, including Greece, Italy, and the southern centers of Spain, the nutrient pattern was dominated by relatively high intakes of vitamin E and monounsaturated fatty acids (MUFA), whereas intakes of retinol and vitamin D were relatively low. In contrast, in Nordic countries, including Norway, Sweden, and Denmark, reported intake of these same nutrients resulted in almost the opposite pattern. Population groups in Germany, The Netherlands, and the UK shared a fatty acid pattern of relatively high intakes of PUFA and SFA and relatively low intakes of MUFA, in combination with a relatively high intake of sugar. We confirmed large variability in nutrient intakes across the EPIC study populations and identified 3 main region-specific patterns with a geographical gradient within and between European countries.