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 healthconscious 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.

Aims The aim of this study was to develop, validate, and illustrate an updated prediction model (SCORE2) to estimate 10-year fatal and non-fatal cardiovascular disease (CVD) risk in individuals without previous CVD or diabetes aged 40–69 years in Europe. Methods and results  We derived risk prediction models using individual-participant data from 45 cohorts in 13 countries (677 684 individuals, 30 121 CVD events). We used sex-specific and competing risk-adjusted models, including age, smoking status, systolic blood pressure, and total- and HDL-cholesterol. We defined four risk regions in Europe according to country-specific CVD mortality, recalibrating models to each region using expected incidences and risk factor distributions. Region-specific incidence was estimated using CVD mortality and incidence data on 10 776 466 individuals. For external validation, we analysed data from 25 additional cohorts in 15 European countries (1 133 181 individuals, 43 492 CVD events). After applying the derived risk prediction models to external validation cohorts, C-indices ranged from 0.67 (0.65–0.68) to 0.81 (0.76–0.86). Predicted CVD risk varied several-fold across European regions. For example, the estimated 10-year CVD risk for a 50-year-old smoker, with a systolic blood pressure of 140 mmHg, total cholesterol of 5.5 mmol/L, and HDL-cholesterol of 1.3 mmol/L, ranged from 5.9% for men in low-risk countries to 14.0% for men in very high-risk countries, and from 4.2% for women in low-risk countries to 13.7% for women in very high-risk countries. Conclusion  SCORE2—a new algorithm derived, calibrated, and validated to predict 10-year risk of first-onset CVD in European populations—enhances the identification of individuals at higher risk of developing CVD across Europe.

OBJECTIVEThe long-term association between dietary protein and type 2 diabetes incidence is uncertain. We aimed to investigate the association between total, animal, and plant protein intake and the incidence of type 2 diabetes. RESEARCH DESIGN AND METHODSThe prospective European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study consists of 12,403 incident type 2 diabetes cases and a stratified subcohort of 16,154 individuals from eight European countries, with an average follow-up time of 12.0 years. Pooled country-specific hazard ratios (HRs) and 95% CI of prentice-weighted Cox regression analyses were used to estimate type 2 diabetes incidence according to protein intake. RESULTSAfter adjustment for important diabetes risk factors and dietary factors, the incidence of type 2 diabetes was higher in those with high intake of total protein (per 10 g: HR 1.06 [95% CI 1.02-1.09], P trend < 0.001) and animal protein (per 10 g:

Irrespective of BMI, metabolically unhealthy individuals had higher CHD risk than their healthy counterparts. Conversely, irrespective of metabolic health, overweight and obese people had higher CHD risk than lean people. These findings challenge the concept of 'metabolically healthy obesity', encouraging population-wide strategies to tackle obesity.