OBJECTIVE: We examined the association between sweet-beverage consumption (including total, sugar-sweetened, and artificially sweetened soft drink and juice and nectar consumption) and pancreatic cancer risk.
DESIGN: The study was conducted within the European Prospective Investigation into Cancer and Nutrition cohort. A total of 477,199 participants (70.2% women) with a mean age of 51 y at baseline were included, and 865 exocrine pancreatic cancers were diagnosed after a median follow-up of 11.60 y (IQR: 10.10-12.60 y). Sweet-beverage consumption was assessed with the use of validated dietary questionnaires at baseline. HRs and 95% CIs were obtained with the use of multivariable Cox regression models that were stratified by age, sex, and center and adjusted for educational level, physical activity, smoking status, and alcohol consumption. Associations with total soft-drink consumption were adjusted for juice and nectar consumption and vice versa.
RESULTS: Total soft-drink consumption (HR per 100 g/d: 1.03; 95% CI: 0.99, 1.07), sugar-sweetened soft-drink consumption (HR per 100 g/d: 1.02; 95% CI: 0.97, 1.08), and artificially sweetened soft-drink consumption (HR per 100 g/d: 1.04; 95% CI: 0.98, 1.10) were not associated with pancreatic cancer risk. Juice and nectar consumption was inversely associated with pancreatic cancer risk (HR per 100 g/d: 0.91; 95% CI: 0.84, 0.99); this association remained statistically significant after adjustment for body size, type 2 diabetes, and energy intake.
CONCLUSIONS: Soft-drink consumption does not seem to be associated with pancreatic cancer risk. Juice and nectar consumption might be associated with a modest decreased pancreatic cancer risk. Additional studies with specific information on juice and nectar subtypes are warranted to clarify these results.
METHODS AND FINDINGS: The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed.
CONCLUSIONS: These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.
RESULTS: Higher total neopterin concentrations were associated with reduced HDLC (9.7 %, p
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.
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.
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.
METHODS: This study was conducted within the European Prospective Investigation into Nutrition and Cancer cohort, comprising male and female participants from 10 European countries. Between 1992 and 2000, there were 477,312 participants without cancer who completed a dietary questionnaire and were followed up to determine pancreatic cancer incidence. Coffee and tea intake was calibrated with a 24-hour dietary recall. Adjusted hazard ratios (HRs) were computed using multivariable Cox regression.
RESULTS: During a mean follow-up period of 11.6 y, 865 first incidences of pancreatic cancers were reported. When divided into fourths, neither total intake of coffee (HR, 1.03; 95% confidence interval [CI], 0.83-1.27; high vs low intake), decaffeinated coffee (HR, 1.12; 95% CI, 0.76-1.63; high vs low intake), nor tea were associated with risk of pancreatic cancer (HR, 1.22, 95% CI, 0.95-1.56; high vs low intake). Moderately low intake of caffeinated coffee was associated with an increased risk of pancreatic cancer (HR, 1.33; 95% CI, 1.02-1.74), compared with low intake. However, no graded dose response was observed, and the association attenuated after restriction to histologically confirmed pancreatic cancers.
CONCLUSIONS: Based on an analysis of data from the European Prospective Investigation into Nutrition and Cancer cohort, total coffee, decaffeinated coffee, and tea consumption are not related to the risk of pancreatic cancer.
METHODS: Over half a million participants from 10 European countries were followed up for over 11 years, after which 865 newly diagnosed exocrine pancreatic cancer cases were identified. Adherence to the MD was estimated through an adapted score without the alcohol component (arMED) to discount alcohol-related harmful effects. Cox proportional hazards regression models, stratified by age, sex and centre, and adjusted for energy intake, body mass index, smoking status, alcohol intake and diabetes status at recruitment, were used to estimate hazard ratios (HRs) associated with pancreatic cancer and their corresponding 95% confidence intervals (CIs).
RESULTS: Adherence to the arMED score was not associated with risk of pancreatic cancer (HR high vs low adherence=0.99; 95% CI: 0.77-1.26, and HR per increments of two units in adherence to arMED=1.00; 95% CI: 0.94-1.06). There was no convincing evidence for heterogeneity by smoking status, body mass index, diabetes or European region. There was also no evidence of significant associations in analyses involving microscopically confirmed cases, plausible reporters of energy intake or other definitions of the MD pattern.
CONCLUSIONS: A high adherence to the MD is not associated with pancreatic cancer risk in the EPIC study.
METHODS: To address these aspects, an untargeted nuclear magnetic resonance metabolomic approach was applied to pre-diagnostic serum samples obtained from first incident, primary HCC cases (n = 114) and matched controls (n = 222) identified from amongst the participants of a large European prospective cohort.
RESULTS: A metabolic pattern associated with HCC risk comprised of perturbations in fatty acid oxidation and amino acid, lipid, and carbohydrate metabolism was observed. Sixteen metabolites of either endogenous or exogenous origin were found to be significantly associated with HCC risk. The influence of hepatitis infection and potential liver damage was assessed, and further analyses were made to distinguish patterns of early or later diagnosis.
CONCLUSION: Our results show clear metabolic alterations from early stages of HCC development with application for better etiologic understanding, prevention, and early detection of this increasingly common cancer.
METHODS: The analysis was performed within the European Investigation into Cancer and Nutrition prospective cohort study, which enrolled >500,000 women and men from 1992 to 2000, who were residing in a given town/geographic area in 10 European countries. The current analysis included 322,972 eligible women aged 25-70 years with 99 % complete follow-up for vital status. We assessed reproductive characteristics reported at the study baseline including parity, age at the first birth, breastfeeding, infertility, oral contraceptive use, age at menarche and menopause, total ovulatory years, and history of oophorectomy/hysterectomy. Hazard ratios (HRs) and 95 % confidence intervals (CIs) for mortality were determined using Cox proportional hazards regression models adjusted for menopausal status, body mass index, physical activity, education level, and smoking status/intensity and duration.
RESULTS: During a mean follow-up of 12.9 years, 14,383 deaths occurred. The HR (95 % CI) for risk of all-cause mortality was lower in parous versus nulliparous women (0.80; 0.76-0.84), in women who had ever versus never breastfed (0.92; 0.87-0.97), in ever versus never users of oral contraceptives (among non-smokers; 0.90; 0.86-0.95), and in women reporting a later age at menarche (≥15 years versus <12; 0.90; 0.85-0.96; P for trend = 0.038).
CONCLUSIONS: Childbirth, breastfeeding, oral contraceptive use, and a later age at menarche were associated with better health outcomes. These findings may contribute to the development of improved strategies to promote better long-term health in women.