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  1. Obón-Santacana M, Lujan-Barroso L, Freisling H, Cadeau C, Fagherazzi G, Boutron-Ruault MC, et al.
    Eur J Nutr, 2017 Apr;56(3):1157-1168.
    PMID: 26850269 DOI: 10.1007/s00394-016-1165-5
    PURPOSE: Acrylamide was classified as 'probably carcinogenic' to humans in 1994 by the International Agency for Research on Cancer. In 2002, public health concern increased when acrylamide was identified in starchy, plant-based foods, processed at high temperatures. The purpose of this study was to identify which food groups and lifestyle variables were determinants of hemoglobin adduct concentrations of acrylamide (HbAA) and glycidamide (HbGA) in 801 non-smoking postmenopausal women from eight countries in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

    METHODS: Biomarkers of internal exposure were measured in red blood cells (collected at baseline) by high-performance liquid chromatography/tandem mass spectrometry (HPLC/MS/MS) . In this cross-sectional analysis, four dependent variables were evaluated: HbAA, HbGA, sum of total adducts (HbAA + HbGA), and their ratio (HbGA/HbAA). Simple and multiple regression analyses were used to identify determinants of the four outcome variables. All dependent variables (except HbGA/HbAA) and all independent variables were log-transformed (log2) to improve normality. Median (25th-75th percentile) HbAA and HbGA adduct levels were 41.3 (32.8-53.1) pmol/g Hb and 34.2 (25.4-46.9) pmol/g Hb, respectively.

    RESULTS: The main food group determinants of HbAA, HbGA, and HbAA + HbGA were biscuits, crackers, and dry cakes. Alcohol intake and body mass index were identified as the principal determinants of HbGA/HbAA. The total percent variation in HbAA, HbGA, HbAA + HbGA, and HbGA/HbAA explained in this study was 30, 26, 29, and 13 %, respectively.

    CONCLUSIONS: Dietary and lifestyle factors explain a moderate proportion of acrylamide adduct variation in non-smoking postmenopausal women from the EPIC cohort.

  2. Kliemann N, Murphy N, Viallon V, Freisling H, Tsilidis KK, Rinaldi S, et al.
    Int J Cancer, 2020 Aug 01;147(3):648-661.
    PMID: 31652358 DOI: 10.1002/ijc.32753
    Emerging evidence suggests that a metabolic profile associated with obesity may be a more relevant risk factor for some cancers than adiposity per se. Basal metabolic rate (BMR) is an indicator of overall body metabolism and may be a proxy for the impact of a specific metabolic profile on cancer risk. Therefore, we investigated the association of predicted BMR with incidence of 13 obesity-related cancers in the European Prospective Investigation into Cancer and Nutrition (EPIC). BMR at baseline was calculated using the WHO/FAO/UNU equations and the relationships between BMR and cancer risk were investigated using multivariable Cox proportional hazards regression models. A total of 141,295 men and 317,613 women, with a mean follow-up of 14 years were included in the analysis. Overall, higher BMR was associated with a greater risk for most cancers that have been linked with obesity. However, among normal weight participants, higher BMR was associated with elevated risks of esophageal adenocarcinoma (hazard ratio per 1-standard deviation change in BMR [HR1-SD ]: 2.46; 95% CI 1.20; 5.03) and distal colon cancer (HR1-SD : 1.33; 95% CI 1.001; 1.77) among men and with proximal colon (HR1-SD : 1.16; 95% CI 1.01; 1.35), pancreatic (HR1-SD : 1.37; 95% CI 1.13; 1.66), thyroid (HR1-SD : 1.65; 95% CI 1.33; 2.05), postmenopausal breast (HR1-SD : 1.17; 95% CI 1.11; 1.22) and endometrial (HR1-SD : 1.20; 95% CI 1.03; 1.40) cancers in women. These results indicate that higher BMR may be an indicator of a metabolic phenotype associated with risk of certain cancer types, and may be a useful predictor of cancer risk independent of body fatness.
  3. Zamora-Ros R, Knaze V, Rothwell JA, Hémon B, Moskal A, Overvad K, et al.
    Eur J Nutr, 2016 Jun;55(4):1359-75.
    PMID: 26081647 DOI: 10.1007/s00394-015-0950-x
    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.

  4. Moskal A, Freisling H, Byrnes G, Assi N, Fahey MT, Jenab M, et al.
    Br J Cancer, 2016 Nov 22;115(11):1430-1440.
    PMID: 27764841 DOI: 10.1038/bjc.2016.334
    BACKGROUND: Much of the current literature on diet-colorectal cancer (CRC) associations focused on studies of single foods/nutrients, whereas less is known about nutrient patterns. We investigated the association between major nutrient patterns and CRC risk in participants of the European Prospective Investigation into Cancer and Nutrition (EPIC) study.

    METHODS: Among 477 312 participants, intakes of 23 nutrients were estimated from validated dietary questionnaires. Using results from a previous principal component (PC) analysis, four major nutrient patterns were identified. Hazard ratios (HRs) and 95% confidence intervals (CIs) were computed for the association of each of the four patterns and CRC incidence using multivariate Cox proportional hazards models with adjustment for established CRC risk factors.

    RESULTS: During an average of 11 years of follow-up, 4517 incident cases of CRC were documented. A nutrient pattern characterised by high intakes of vitamins and minerals was inversely associated with CRC (HR per 1 s.d.=0.94, 95% CI: 0.92-0.98) as was a pattern characterised by total protein, riboflavin, phosphorus and calcium (HR (1 s.d.)=0.96, 95% CI: 0.93-0.99). The remaining two patterns were not significantly associated with CRC risk.

    CONCLUSIONS: Analysing nutrient patterns may improve our understanding of how groups of nutrients relate to CRC.

  5. Freisling H, Pisa PT, Ferrari P, Byrnes G, Moskal A, Dahm CC, et al.
    Eur J Nutr, 2016 Sep;55(6):2093-104.
    PMID: 26303194 DOI: 10.1007/s00394-015-1023-x
    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.

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