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OBJECTIVES: To assess the contribution of out-of-home (OH) energy and nutrient intake to total dietary intake, and to compare out- versus in-home nutrient patterns among 27 centres in 10 countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. METHODS: Between 1995 and 2000, 36,034 participants aged between 35-74 years completed a standardized 24-h dietary recall using a software programme (EPIC-Soft) that recorded the place of food/drink consumption. Eating OH was defined as the consumption of foods and beverages anywhere other than in household premises, irrespective of the place of purchase/preparation. Nutrient intakes were estimated using a standardized nutrient database. Mean intakes were adjusted for age and weighted by season and day of recall. RESULTS: Among women, OH eating contributed more to total fat intake than to intakes of protein and carbohydrates. Among both genders, and particularly in southern Europe, OH eating contributed more to sugar and starch intakes and less to total fibre intake. The contribution of OH eating was also lower for calcium and vitamin C intakes. The composition of diet at home was different from that consumed out of home in southern countries, but was relatively similar in the north. CONCLUSIONS: In northern Europe, OH and in-home eating are homogeneous, whereas southern Europeans consider OH eating as a distinctive occasion. In most centres, women selected more fat-rich items when eating out.

Objective: To describe dietary carbohydrate intakes and their food sources among 27 centres in 10 countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Methods: Between 1995 and 2000, 36 034 subjects, aged between 35-74 years, were administered a standardized, 24-h dietary recall using a computerized interview software programme (EPIC-SOFT). Intakes (g/day) of total carbohydrate, sugars, starch and fibre were estimated using the standardized EPIC Nutrient Database (ENDB). Mean intakes were adjusted for age, total energy intake, height and weight, and were weighted by season and day of recall. Results: Adjusted mean total carbohydrate intakes were highest in Italy and in the UK health-conscious cohort, and were lowest in Spain, Greece and France. Total fibre intakes were highest in the UK health-conscious cohort and lowest in Sweden and the UK general population. Bread contributed the highest proportion of carbohydrates (mainly starches) in every centre. Fruit consumption contributed a greater proportion of total carbohydrates (mainly sugars) among women than among men, and in southern centres compared with northern centres. Bread, fruits and vegetables represented the largest sources of fibre, but food sources varied considerably between centres. In stratified analyses, carbohydrate intakes tended to be higher among subjects who were physically active, never-smokers or non-drinkers of alcohol. Conclusions: Dietary carbohydrate intakes and in particular their food sources varied considerably between these 10 European countries. Intakes also varied according to gender and lifestyle factors. These data will form the basis for future aetiological analyses of the role of dietary carbohydrates in influencing health and disease. European Journal of Clinical Nutrition (2009) 63, S37-S60; doi: 10.1038/ejcn.2009.74

OBJECTIVES: To describe the contribution of highly processed foods to total diet, nutrient intakes and patterns among 27 redefined centres in the 10 countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC). METHODS: Single 24-hour dietary recalls were collected from 36,034 individuals (aged 35-74 years) using a standardized computerized interview programme (EPIC-SOFT). Centre-specific mean food intakes (g/day) were computed according to their degree of food processing (that is, highly, moderately and non-processed foods) using a specifically designed classification system. The contribution (%) of highly processed foods to the centre mean intakes of diet and 26 nutrients (including energy) was estimated using a standardized nutrient database (ENDB). The effect of different possible confounders was also investigated. RESULTS: Highly processed foods were an important source of the nutrients considered, contributing between 61% (Spain) and 78-79% (the Netherlands and Germany) of mean energy intakes. Only two nutrients, beta-carotene (34-46%) and vitamin C (28-36%), had a contribution from highly processed foods below 50% in Nordic countries, in Germany, the Netherlands and the United Kingdom, whereas for the other nutrients, the contribution varied from 50 to 91% (excluding alcohol). In southern countries (Greece, Spain, Italy and France), the overall contribution of highly processed foods to nutrient intakes was lower and consisted largely of staple or basic foods (for example, bread, pasta/rice, milk, vegetable oils), whereas highly processed foods such as crisp bread, breakfast cereals, margarine and other commercial foods contributed more in Nordic and central European centres. CONCLUSIONS: Highly industrially processed foods dominate diets and nutrient patterns in Nordic and central European countries. The greater variations observed within southern countries may reflect both a larger contribution of non/moderately processed staple foods along with a move from traditional to more industrialized dietary patterns.

Objectives:To investigate whether dietary glycaemic index (GI) and glycaemic load (GL) were associated with subsequent weight and waist circumference change.Design:Population-based prospective cohort study.Setting:Five European countries, which are Denmark, Germany, Italy, The Netherlands and the United Kingdom.Participants:A total of 89 432 participants, aged 20-78 years (mean =53 years) at baseline and followed for 1.9-12.5 years (mean=6.5 years). All participants were free of self-reported cancer, cardiovascular diseases and diabetes at baseline.Methods:Glycaemic index and GL were calculated on the basis of dietary intake assessed by food frequency questionnaires and by using a GI table developed for this study with published GI values as the main sources. Anthropometric data were collected both at baseline and at the end of follow-up. Multiple linear regression analyses were conducted in each centre and random-effect meta-analyses were used to combine the effects. Adjustment was made for baseline anthropometrics, demographic and lifestyle factors, follow-up duration and other dietary factors.Results:Mean GI and GL were 57 and 134, respectively. Associations of GI and GL with subsequent changes of weight and waist circumference were heterogeneous across centres. Overall, with every 10-unit higher in GI, weight increased by 34 g per year (95% confidence interval (CI): -47, 115) and waist circumference increased by 0.19 cm per year (95% CI: 0.11, 0.27). With every 50-unit higher in GL, weight increased by 10 g per year (95% CI: -65, 85) and waist circumference increased by 0.06 cm per year (95% CI: -0.01, 0.13).Conclusions:Our findings do not support an effect of GI or GL on weight change. The positively significant association between GI, not GL, and subsequent gain in waist circumference may imply a beneficial role of lower GI diets in the prevention of abdominal obesity. However, further studies are needed to confirm this finding given the small effect observed in this study.International Journal of Obesity advance online publication, 25 August 2009; doi:10.1038/ijo.2009.163.

Objectives: To describe dietary glycaemic index (GI) and glycaemic load (GL) values in the population participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study according to food groups, nutrients and lifestyle characteristics. Methods: Single 24-h dietary recalls (24-HDRs) from 33 566 subjects were used to calculate dietary GI and GL, and an ad hoc database was created as the main reference source. Mean GI and GL intakes were adjusted for age, total energy intake, height and weight, and were weighted by season and day of recall. Results: GI was the lowest in Spain and Germany, and highest in the Netherlands, United Kingdom and Denmark for both genders. In men, GL was the lowest in Spain and Germany and highest in Italy, whereas in women, it was the lowest in Spain and Greece and highest in the UK health-conscious cohort. Bread was the largest contributor to GL in all centres (15-45%), but it also showed the largest inter-individual variation. GL, but not GI, tended to be lower in the highest body mass index category in both genders. GI was positively correlated with starch and intakes of bread and potatoes, whereas it was correlated negatively with intakes of sugar, fruit and dairy products. GL was positively correlated with all carbohydrate components and intakes of cereals, whereas it was negatively correlated with fat and alcohol and with intakes of wine, with large variations across countries. Conclusions: GI means varied modestly across countries and genders, whereas GL means varied more, but it may possibly act as a surrogate of carbohydrate intake. European Journal of Clinical Nutrition (2009) 63, S188-S205; doi: 10.1038/ejcn.2009.81

Objective: This paper describes the ad hoc methodological concepts and procedures developed to improve the comparability of Nutrient databases (NDBs) across the 10 European countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC). This was required because there is currently no European reference NDB available. Design: A large network involving national compilers, nutritionists and experts on food chemistry and computer science was set up for the 'EPIC Nutrient DataBase' (ENDB) project. A total of 550-1500 foods derived from about 37 000 standardized EPIC 24-h dietary recalls (24-HDRS) were matched as closely as possible to foods available in the 10 national NDBs. The resulting national data sets (NDS) were then successively documented, standardized and evaluated according to common guidelines and using a DataBase Management System specifically designed for this project. The nutrient values of foods unavailable or not readily available in NDSs were approximated by recipe calculation, weighted averaging or adjustment for weight changes and vitamin-mineral losses, using common algorithms. Results: The final ENDB contains about 550-1500 foods depending on the country and 26 common components. Each component value was documented and standardized for unit, mode of expression, definition and chemical method of analysis, as far as possible. Furthermore, the overall completeness of NDSs was improved (≥99%), particularly for β-carotene and vitamin E. Conclusion: The ENDB constitutes a first real attempt to improve the comparability of NDBs across European countries. This methodological work will provide a useful tool for nutritional research as well as end-user recommendations to improve NDBs in the future. Chemicals / CAS: alcohol, 64-17-5; alpha tocopherol, 1406-18-4, 1406-70-8, 52225-20-4, 58-95-7, 59-02-9; ascorbic acid, 134-03-2, 15421-15-5, 50-81-7; beta carotene, 7235-40-7; calcium, 7440-70-2; cholesterol, 57-88-5; cyanocobalamin, 53570-76-6, 68-19-9, 8064-09-3; iron, 14093-02-8, 53858-86-9, 7439-89-6; magnesium, 7439-95-4; phosphorus, 7723-14-0; potassium, 7440-09-7; protein, 67254-75-5; pyridoxine, 12001-77-3, 58-56-0, 65-23-6, 8059-24-3; retinol, 68-26-8, 82445-97-4; riboflavin, 83-88-5; starch, 9005-25-8, 9005-84-9; thiamine, 59-43-8, 67-03-8; water, 7732-18-5