• Energy Research

AbstractWe assessed hepatocellular carcinoma (HCC) risk associated with smoking and alcohol consumption and their interactions, using both questionnaire data and objective serum biomarkers. Information on smoking and alcohol consumption was collected at baseline from 450,112 participants of the EPIC cohort, among whom 255 developed HCC after a median follow‐up of 14 years. In a nested case–control subset of 108 HCC cases and 108 matched controls, known biomarkers of smoking (cotinine, nicotine) and habitual alcohol consumption (2‐hydroxy‐3‐methylbutyric acid) were annotated from untargeted metabolomics features. Multivariable‐adjusted hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were computed, and multiplicative and additive interaction parameters were calculated. Compared to never smokers, current smokers had a higher HCC risk (HR = 2.46, 95% CI = 1.77–3.43) dose‐dependently with the number of cigarettes smoked per day (Ptrend <.001). Compared to light drinkers, HCC risk was higher in former (HR = 3.20, 95% CI = 1.70–6.03), periodically heavy (HR = 1.98, 95% CI = 1.11–3.54), and always heavy (HR = 5.51, 95% CI = 2.39–12.7) drinkers. Higher HCC risk was also observed in the highest versus the lowest tertiles of cotinine (OR = 4.88, 95% CI = 1.52–15.70), nicotine (OR = 5.80, 95% CI = 1.33–25.30) and 2‐hydroxy‐3‐methylbutyric acid (OR = 5.89, 95% CI = 1.33–26.12). Questionnaire‐assessed smoking and alcohol exposures did not demonstrate an HCC risk interaction at the multiplicative (MI = 0.88, 95% CI = 0.40–1.96) or additive (RERI = 0.71, 95% CI = −10.1 to 23.6; attributable proportion = 0.17, 95% CI = −0.52 to 1.16; synergy index = 1.27, 95% CI = 0.98–1.66) scales. Similar analyses with cotinine, nicotine, and 2‐hydroxy‐3‐methylbutyric acid also did not show interactions between smoking and alcohol consumption on HCC risk. Smoking and alcohol consumption are strong independent risk factors for HCC and do not appear to synergistically impact its risk, but larger studies are needed.

Dietary fiber may play a role in obesity prevention. Until now, the role that fiber from different sources plays in weight change had rarely been studied.Our aim was to investigate the association of total dietary fiber, cereal fiber, and fruit and vegetable fiber with changes in weight and waist circumference.We conducted a prospective cohort study with 89,432 European participants, aged 20-78 y, who were free of cancer, cardiovascular disease, and diabetes at baseline and who were followed for an average of 6.5 y. Dietary information was collected by using validated country-specific food-frequency questionnaires. Multiple linear regression analysis was performed in each center studied, and estimates were combined by using random-effects meta-analyses. Adjustments were made for follow-up duration, other dietary variables, and baseline anthropometric, demographic, and lifestyle factors.Total fiber was inversely associated with subsequent weight and waist circumference change. For a 10-g/d higher total fiber intake, the pooled estimate was -39 g/y (95% CI: -71, -7 g/y) for weight change and -0.08 cm/y (95% CI: -0.11, -0.05 cm/y) for waist circumference change. A 10-g/d higher fiber intake from cereals was associated with -77 g/y (95% CI: -127, -26 g/y) weight change and -0.10 cm/y (95% CI: -0.18, -0.02 cm/y) waist circumference change. Fruit and vegetable fiber was not associated with weight change but had a similar association with waist circumference change when compared with intake of total dietary fiber and cereal fiber.Our finding may support a beneficial role of higher intake of dietary fiber, especially cereal fiber, in prevention of body-weight and waist circumference gain.

Incidence rates of differentiated thyroid carcinoma (TC) have increased in many countries. Adiposity and dietary risk factors may play a role, but little is known on the influence of energy intake and macronutrient composition. The aim of this study was to investigate the associations between TC and the intake of energy, macronutrients, glycemic index (GI) and glycemic load in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. The study included 477,274 middle-age participants (70.2% women) from ten European countries. Dietary data were collected using country-specific validated dietary questionnaires. Total carbohydrates, proteins, fats, saturated, monounsaturated and polyunsaturated fats (PUFA), starch, sugar, and fiber were computed as g/1,000 kcal. Multivariable Cox regression was used to calculate multivariable adjusted hazard ratios (HR) and 95% confidence interval (CI) by intake quartile (Q). After a mean follow-up time of 11 years, differentiated TC was diagnosed in 556 participants (90% women). Overall, we found significant associations only with total energy (HRQ4 vs .Q1 , 1.29; 95% CI, 1.00-1.68) and PUFA intakes (HRQ4 vs .Q1 , 0.74; 95% CI, 0.57-0.95). However, the associations with starch and sugar intake and GI were significantly heterogeneous across body mass index (BMI) groups, i.e., positive associations with starch and GI were found in participants with a BMI ≥ 25 and with sugar intake in those with BMI < 25. Moreover, inverse associations with starch and GI were observed in subjects with BMI < 25. In conclusion, our results suggest that high total energy and low PUFA intakes may increase the risk of differentiated TC. Positive associations with starch intake and GI in participants with BMI ≥ 25 suggest that those persons may have a greater insulin response to high starch intake and GI than lean people.

There is inconsistent evidence regarding the relationship between higher intake of nuts, being an energy-dense food, and weight gain. We investigated the relationship between nut intake and changes in weight over 5 years.This study includes 373,293 men and women, 25-70 years old, recruited between 1992 and 2000 from 10 European countries in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Habitual intake of nuts including peanuts, together defined as nut intake, was estimated from country-specific validated dietary questionnaires. Body weight was measured at recruitment and self-reported 5 years later. The association between nut intake and body weight change was estimated using multilevel mixed linear regression models with center/country as random effect and nut intake and relevant confounders as fixed effects. The relative risk (RR) of becoming overweight or obese after 5 years was investigated using multivariate Poisson regressions stratified according to baseline body mass index (BMI).On average, study participants gained 2.1 kg (SD 5.0 kg) over 5 years. Compared to non-consumers, subjects in the highest quartile of nut intake had less weight gain over 5 years (-0.07 kg; 95% CI -0.12 to -0.02) (P trend = 0.025) and had 5% lower risk of becoming overweight (RR 0.95; 95% CI 0.92-0.98) or obese (RR 0.95; 95% CI 0.90-0.99) (both P trend <0.008).Higher intake of nuts is associated with reduced weight gain and a lower risk of becoming overweight or obese.

Several studies in recent years have investigated the relationship between alcohol intake and melanoma risk, with conflicting results. To help clarify this issue, we conducted a literature review and dose-response meta-analysis of studies published until June 30th, 2017, that examined the association between alcohol intake (overall and by beverage type) and melanoma risk.We used random effect models with maximum likelihood estimation to calculate summary relative risk (SRR) and 95% confidence intervals (95%CI).We included 20 independent studies (encompassing 10,555 melanoma cases and over 1.6 million non-cases/controls) published during 1986-2016, of which six had a prospective cohort study design. Adjustment for phenotypic characteristics and sunlight exposure was performed in 11 and nine studies, respectively. Alcohol intake was moderately associated with melanoma risk: the SRR were 1.29 (95% CI 1.14-1.45) for those in the highest vs. lowest category of current alcohol intake, and 1.96 (95% CI 1.02-3.76, I2 = 0%) for cumulative intake. In the dose-response analysis, the increase in risk associated with a 10 g increment in daily alcohol intake was 1.07 (95% CI 1.03-1.11). Risk estimates did not differ by gender, study design and adjustment for confounders; between-studies heterogeneity was acceptable, and there was no evidence of publication bias.Our findings suggest that alcohol drinking may be moderately associated with increased melanoma risk, although residual confounding and bias cannot be ruled out. Further research is needed to confirm these findings, clarify the role of the different alcohol sources, and investigate the interaction with known melanoma risk factors.

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