METHODS: Individual participant data meta-analysis included 362,114 participants (43% women), from seven prospective cohort studies, free from cancer at enrollment. The WCRF/AICR diet score was based on: (i) energy-dense foods and sugary drinks, (ii) plant foods, (iii) red and processed meat, and (iv) alcoholic drinks. Cox proportional hazards regression was used to examine the association between the diet score and cancer risks. Adjusted, cohort-specific HRs were pooled using random-effects meta-analysis. Risk advancement periods (RAP) were calculated to quantify the time period by which the risk of cancer was postponed among those adhering to the recommendations.

RESULTS: After a median follow-up of 11 to 15 years across cohorts, 70,877 cancer cases were identified. Each one-point increase in the WCRF/AICR diet score [range, 0 (no) to 4 (complete adherence)] was significantly associated with a lower risk of total cancer [HR, 0.94; 95% confidence interval (CI), 0.92-0.97], cancers of the colorectum (HR, 0.84; 95% CI, 0.80-0.89) and prostate (HR, 0.94; 95% CI, 0.92-0.97), but not breast or lung. Adherence to an additional component of the WCRF/AICR diet score significantly postponed the incidence of cancer at any site by 1.6 years (RAP, -1.6; 95% CI, -4.09 to -2.16).

CONCLUSIONS: Adherence to WCRF/AICR dietary recommendations is associated with lower risk of cancer among older adults.

METHODS: This study examined polyphenol intake estimated from 3- and 7-day food diaries in a sample of 246 UK women aged 18-50 years. Estimation of the intake of 20 polyphenol subclasses commonly present in foods consumed by the sample studied was done using Phenol-Explorer(®) and USDA polyphenol databases. Women were participants in the Leeds Women's Wellbeing Study (LWW) (n = 143), a dietary intervention study aimed at overweight women (mean age 37.2 ± 9.4 years; mean BMI 30.8 ± 3.1 kg/m(2)), and the Diet and Health Study (DH) (n = 103) which aimed to examine the relationship between polyphenol intake and cognitive function (mean age 25.0 ± 9.0 years; mean BMI 24.5 ± 4.6 kg/m(2)).

METHODS: An exhaustive literature search was performed, in order to identify the relevant studies describing the epidemiology, pathogenesis, nutritional intervention and outcome of PEW in ESRD on hemodialysis.

OBJECTIVE: The study aimed to derive dietary patterns empirically and to examine the consistency and generalizability of patterns across sex, ethnicity, and urban status in a working population.

DESIGN: This was a cross-sectional study using data from the Clustering of Lifestyle Risk Factors and Understanding its Association with Stress on Health and Well-Being among School Teachers in Malaysia study collected between August 2014 and November 2015. Dietary intake was assessed using a food frequency questionnaire, and dietary patterns were derived using factor analysis.

PARTICIPANTS/SETTING: Participants were teachers from selected public schools from three states in Peninsular Malaysia (n=4,618).

MAIN OUTCOME MEASURES: Dietary patterns derived using factor analysis.

STATISTICAL ANALYSES PERFORMED: Separate factor analysis was conducted by sex, ethnicity, and urban status to identify dietary patterns. Eigenvalue >2, scree plot, Velicer's minimum average partial analysis, and Horn's parallel analysis were used to determine the number of factors to retain. The interpretability of each dietary pattern was evaluated. The consistency and generalizability of dietary patterns across subgroups were assessed using the Tucker congruence coefficient.

RESULTS: There was no subgroup-specific dietary pattern found. Thus, dietary patterns were derived using the pooled sample in the final model. Two dietary patterns (Western and Prudent) were derived. The Western dietary pattern explained 15.4% of total variance, characterized by high intakes of refined grains, animal-based foods, added fat, and sugar-sweetened beverages as well as fast food. The Prudent dietary pattern explained 11.1% of total variance and was loaded with pulses, legumes, vegetables, and fruits.

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.

METHODS: A cross-sectional study was conducted in the Kandy district, Sri Lanka. The nutritional status of older persons was assessed using the Mini Nutritional Assessment -Short Form (MNA-SF). A standardised questionnaire was used to record factors associated with malnutrition: demographic characteristics, financial characteristics, food and appetite, lifestyle, psychological characteristics, physical characteristics, disease and care, oral health, and social factors. Complex sample multinomial logistic regression analysis was performed.

RESULTS: Among the 999 participants included in the study, 748 (69.3%) were females and 251 (25.1%) were males. The mean age was 70.80 years (95% CI: 70.13, 71.47). The prevalence of malnutrition, risk of malnutrition and well-nutrition was 12.5%, 52.4% and 35.1% respectively. In the multivariate model, hypertension (adjusted OR = 1.71; 95% CI: 1.02, 2.89), alcohol consumption (aOR = 4.06; 95% CI: 1.17, 14.07), and increased age (aOR = 1.06; 95% CI: 1.01, 1.11) were positively associated with malnutrition. An increased number of people living with the older person (aOR: 0.91; 95% CI: 0.85, 0.97) was a protective factor among those at risk for malnutrition.

METHODS: We recruited 54 abdominally obese subjects to participate in a prospective cross-over design, single-blind trial comparing isocaloric 2000 kcal MUFA or carbohydrate-enriched diet with SFA-enriched diet (control). The control diet consisted of 15E% protein, 53E% carbohydrate and 32E% fat (12E% SFA, 13E% MUFA). A total of ∼7E% of MUFA or refined carbohydrate was exchanged with SFA in the MUFA-rich and carbohydrate-rich diets respectively for 6-weeks. Blood samples were collected at fasting upon trial commencement and at week-5 and 6 of each dietary-intervention phase to measure levels of cytokines (IL-6, IL-1β), C-reactive protein (CRP), thrombogenic markers (E-selectin, PAI-1, D-dimer) and lipid subfractions. Radial pulse wave analysis and a 6-h postprandial mixed meal challenge were carried out at week-6 of each dietary intervention. Blood samples were collected at fasting, 15 and 30 min and hourly intervals thereafter till 6 h after a mixed meal challenge (muffin and milkshake) with SFA or MUFA (872.5 kcal, 50 g fat, 88 g carbohydrates) or CARB (881.3 kcal, 20 g fat, 158 g carbohydrates)- enrichment corresponding to the background diets.

METHODS: A nested case-control study in nonsmoking postmenopausal women (334 cases, 417 controls) was conducted within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Unconditional logistic regression models were used to estimate ORs and 95% confidence intervals (CI) for the association between HbAA, HbGA, HbAA+HbGA, and HbGA/HbAA and EOC and invasive serous EOC risk.

RESULTS: No overall associations were observed between biomarkers of acrylamide exposure analyzed in quintiles and EOC risk; however, positive associations were observed between some middle quintiles of HbGA and HbAA+HbGA. Elevated but nonstatistically significant ORs for serous EOC were observed for HbGA and HbAA+HbGA (ORQ5vsQ1, 1.91; 95% CI, 0.96-3.81 and ORQ5vsQ1, 1.90; 95% CI, 0.94-3.83, respectively); however, no linear dose-response trends were observed.

CONCLUSION: This EPIC nested case-control study failed to observe a clear association between biomarkers of acrylamide exposure and the risk of EOC or invasive serous EOC.