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PurposeVarious 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.MethodsThis 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.ResultsMean 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.ConclusionsWe identified two main nutrient patterns that are associated with moderate but significant long-term differences in weight gain in adults.

Background/objectivesPolyphenols 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.MethodsDietary 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.ResultsMean 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.ConclusionThis 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. [ABSTRACT FROM AUTHOR]

Background: Compared to food patterns, nutrient patterns have been rarely used particularly at international level. We studied, in the context of a multi-center study with heterogeneous data, the methodological challenges regarding pattern analyses. Methodology/Principal Findings: We identified nutrient patterns from food frequency questionnaires (FFQ) in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study and used 24-hour dietary recall (24-HDR) data to validate and describe the nutrient patterns and their related food sources. Associations between lifestyle factors and the nutrient patterns were also examined. Principal component analysis (PCA) was applied on 23 nutrients derived from country-specific FFQ combining data from all EPIC centers (N = 477,312). Harmonized 24-HDRs available for a representative sample of the EPIC populations (N = 34,436) provided accurate mean group estimates of nutrients and foods by quintiles of pattern scores, presented graphically. An overall PCA combining all data captured a good proportion of the variance explained in each EPIC center. Four nutrient patterns were identified explaining 67% of the total variance: Principle component (PC) 1 was characterized by a high contribution of nutrients from plant food sources and a low contribution of nutrients from animal food sources; PC2 by a high contribution of micro-nutrients and proteins; PC3 was characterized by polyunsaturated fatty acids and vitamin D; PC4 was characterized by calcium, proteins, riboflavin, and phosphorus. The nutrients with high loadings on a particular pattern as derived from country-specific FFQ also showed high deviations in their mean EPIC intakes by quintiles of pattern scores when estimated from 24-HDR. Center and energy intake explained most of the variability in pattern scores. Conclusion/Significance: The use of 24-HDR enabled internal validation and facilitated the interpretation of the nutrient patterns derived from FFQs in term of food sources. These outcomes open research opportunities and perspectives of using nutrient patterns in future studies particularly at international level. [ABSTRACT FROM AUTHOR]

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; f-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. [ABSTRACT FROM AUTHOR]

Highlights • The BBMRI-LPC project analyzed the gaps and needs involved in transnational access. • Legal and ethical frameworks form an obstacle for effective transnational sharing. • Practical solutions for streamlined access governance are urgently needed. Abstract Biobank samples and data from studies of large prospective cohorts (LPC) represent an invaluable resource for health research. Efficient sharing and pooling of samples and data is a central pre-requisite for new advances in biomedical science. This requirement, however, is not compatible with the present scattered and traditional access governance structures, where legal and ethical frameworks often form an obstacle for effective sharing. Moreover, the EU General Data Protection Regulation (GDPR) is demanding increasingly rigorous administration from all those organisations processing personal data. The BBMRI-LPC project (Biobanking and Biomolecular Research Infrastructure ― Large Prospective Cohorts) assembled 21 LPCs from 10 countries and two EU-wide multinational cohort networks with a key objective to promote collaborative innovative transnational research proposed by external researchers on the broad field of common chronic diseases, and analyze the gaps and needs involved. BBMRI-LPC organized three scientific calls to offer European investigators an opportunity to gain free of charge transnational access to research material available in the participating cohorts. A total of 11 high-quality research proposals involving multiple prospective cohorts were granted, and the access process in the individual projects carefully monitored. Divergent access governance structures, complex legal and ethical frameworks and heterogeneous procedures were identified as currently constituting substantial obstacles for sample and data transfer in Europe. To optimize the scientific value and use of these research resources, practical solutions for more streamlined access governance in collaborative projects are urgently needed. A number of infrastructure developments could be made to improve time-efficiency in access provision. [ABSTRACT FROM AUTHOR]

The effect of multivariate adjustment including folate on the strong protective effect of fiber in foods on colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition was investigated in 1,721 cases identified in the latest follow-up. The inclusion of an additional 656 cases confirmed our previously published results, with a strong and significant reduction in colorectal cancer risk of approximately 9% for each uncalibrated quintile increase in fiber (P(linear trend) < 0.001) compared with an 8% reduction in our previous report, which had not been adjusted for folate. Inclusion of the other covariates (physical activity, alcohol, smoking, and red and processed meat) confirmed this significant inverse association for colon cancer and strengthened the association with left-sided colon cancer (P < 0.001). After maximum adjustment, the association between fiber and rectal cancer was not significant, as in our previous analysis. The association with fiber from different food sources was analyzed, but again, there were no significance trends after maximum adjustment.