Intake of total, animal and plant proteins, and their food sources in 10 countries in the European Prospective Investigation into Cancer and Nutrition



To describe dietary protein intakes and their food sources among 27 redefined centres in 10 countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC).


Between 1995 and 2000, 36 034 persons, aged between 35 and 74 years, were administered a standardized 24-h dietary recall (24-HDR) using a computerized interview software programme (EPIC-SOFT). Intakes (g/day) of total, animal and plant proteins were estimated using the standardized EPIC Nutrient Database (ENDB). Mean intakes were adjusted for age, and weighted by season and day of recall.


Mean total and animal protein intakes were highest in the Spanish centres among men, and in the Spanish and French centres among women; the lowest mean intakes were observed in the UK health-conscious group, in Greek men and women, and in women in Potsdam. Intake of plant protein was highest among the UK health-conscious group, followed by some of the Italian centres and Murcia, whereas Sweden and Potsdam had the lowest intake. Cereals contributed to the highest proportion of plant protein in all centres. The combined intake of legumes, vegetables and fruit contributed to a greater proportion of plant protein in the southern than in the northern centres. Total meat intake (with some heterogeneity across subtypes of meat) was, with few exceptions, the most important contributor to animal protein in all centres, followed by dairy and fish products.


This study shows that intake of protein, especially of animal origin, differs across the 10 European countries, and also shows some differences in food sources of protein across Europe.


Dietary protein is an important macronutrient, contributing to around 15–20% of the total dietary energy intake in Western countries (CDC, 2004; Elmadfa and Weichselbaum, 2005).

Protein, which contributes essential amino acids, is vital for human metabolism, and protein energy malnutrition is a major issue in developing countries, especially among children (WHO, 2000). Protein deficiency is, however, rare in the Western world, where the mean intake from a mixed diet is usually considerably in excess of recommended protein and amino acid intakes, especially among meat eaters (WHO/FAO/UNU, 2008). Protein-related health issues in the Western world are, therefore, mainly focused on the potential beneficial or harmful effects of high protein intake and whether the source of protein is of importance in relation to disease risk.

As protein is considered to increase thermogenesis and satiety more than other macronutrients, attention has lately turned to its potential beneficial effects on weight loss and maintenance (Halton and Hu, 2004), but evidence regarding this issue is still inconclusive (Nordmann et al., 2006).

Another issue that is still unclear is whether all sources of protein have the same impact on disease outcomes. As an example, one study indicated that plant proteins had a protective effect against coronary heart disease mortality compared with animal proteins, whereas no clear association with cancer incidence and mortality was observed for any subtype of protein (Kelemen et al., 2005).

The association between protein and cancer risk has often been assessed on the basis of the food sources of protein rather than on the nutrient itself. Two of the main contributors to animal protein, red and processed meat, have been found to be consistently positively associated with risk of colorectal cancer (WCRF/AICR, 2007). The main explanation behind this association may, however, not be directly related to animal proteins, but to haem iron and endogenous N-nitroso components present in high concentrations in red and processed meat (Kuhnle and Bingham, 2007). In contrast, some researchers have suggested that other important sources of animal proteins, such as fish, may reduce the risk of colorectal cancer (Geelen et al., 2007) without being able to disentangle any specific beneficial effect of proteins.

In the European Prospective Investigation into Cancer and Nutrition (EPIC) calibration study, a standardized computer-assisted 24-h dietary recall (24-HDR) was administered to almost 37 000 participants on the basis of a representative subsample from 23 centres across 10 European countries, redefined into 27 centres for specific dietary analyses in EPIC (Slimani et al., 2002a). Recently, the EPIC Nutrient Database (ENDB) has harmonized the national nutrient databases, making it possible to compare protein intakes and sources of animal and plant proteins between participating countries (Slimani et al., 2007).

In this descriptive paper, we examine the distribution of intakes of total protein and subtypes of protein across the 27 redefined EPIC centres and different population subgroupings. Furthermore, the contribution to protein intake from different food sources is evaluated.

Materials and methods

Study cohort

The EPIC calibration study is nested within EPIC, which is an ongoing prospective cohort study designed to investigate the associations between diet, lifestyle and cancer throughout 10 Western European countries, namely, Denmark, France, Germany, Greece, Italy, Norway, Spain, Sweden, the Netherlands and the United Kingdom (Riboli and Kaaks, 1997; Riboli et al., 2002). The cohort comprises approximately 370 000 women and 150 000 men, aged 20–85 years, enrolled between 1992 and 2000. Participants were mostly recruited from the general population residing within defined geographical areas, with some exceptions: women members of a health insurance scheme for state school employees (France); women attending breast cancer screening (Utrecht, the Netherlands); blood donors (centres in Italy and Spain); and a cohort consisting predominantly of ovo-lacto vegetarians and vegans (‘health-conscious’ cohort in Oxford, UK) (Riboli et al., 2002). A total of 19 of the 27 redefined EPIC centres had both female and male participants, and 8 centres had only female participants.

Data presented in this paper were derived from the EPIC calibration study (conducted between 1995 and 2000), in which an approximately 8% stratified random sample (on age, gender and centre, and weighted for expected cancer cases in each stratum) of the total cohort completed a standardized, computer-assisted 24-HDR. The calibration study was conducted to improve the comparability of food-frequency-derived dietary data across the EPIC centres and to correct for potential measurement errors arising from country- or centre-specific bias and random and systematic within-person errors (Willett, 1998; Ferrari et al., 2004). Previous publications outline in detail the rationale, methodology and population characteristics of the 24-HDR calibration study (Kaaks et al., 1994, 1995; Slimani et al., 2002a; Ferrari et al., 2008). Approval for the study was obtained from the ethical review boards of the International Agency for Research on Cancer (Lyon, France) and from all local recruiting institutions. All participants provided written informed consent.

Measurements of diet and other lifestyle factors

The 24-HDR was obtained by face-to-face interviews, except in Norway, where a telephone interview was conducted (Brustad et al., 2003). A computerized interview software programme (EPIC-soft) was developed for the calibration study (Slimani et al., 1999, 2000).

Intakes (g/day) of total protein were estimated from the 24-HDRs using, as starting point, country-specific nutrient databases, which were standardized across countries as far as possible to allow calibration at the nutrient level. The ENDB project outlines in detail the methods used to standardize the national nutrient data sets across the 10 countries: EPIC foods were matched to national databases, the nutrient values of unavailable foods were derived and missing values were imputed (Slimani et al., 2007).

All reported foods were classified as being of 100% animal origin (defined as 95% animal origin); 100% plant origin (defined as 95% plant origin); mixed origin; non-organic; or unknown quantities of animal/plant origin (for example, ready-to-eat dishes and cakes without any clear declaration, or containing ingredients of mixed or unknown origin). On the basis of this information, it was possible to estimate the intake of protein of animal and plant origin. In cases in which the origin was unclear (for example, in ready-to-eat dishes and cakes), protein origin was classified as ‘unknown’.

Data on other lifestyle factors, including educational level, total physical activity and smoking history, considered in this analysis were collected at baseline through standardized questionnaires and clinical examinations, and have been described for the calibration sample elsewhere (Riboli et al., 2002; Slimani et al., 2002a; Friedenreich et al., 2007; Haftenberger et al., 2002a, 2002b). Data on age, as well as on body weight and height, were self-reported by participants during the 24-HDR interview. The mean time interval between these baseline questionnaire measures and the 24-HDR interview varied by country, from 1 day to 3 years later (Slimani et al., 2002a).

Statistical methods

A total of 36 034 subjects with 24-HDR data were included in the analyses, after a systematic exclusion of 960 subjects under 35 and over 74 years of age because of low participation of patients in these age categories.

Data are presented as mean (least square means) intakes and s.e. (standard errors), stratified by study centre, gender and age groups, and ordered according to a geographical south–north gradient. Intakes of total protein, animal, plant and unknown proteins are presented on the basis of main protein-providing food groups. The food classification used was adapted from the EPIC-Soft food subgroups described in detail elsewhere (Slimani et al., 2000, 2002b). Food groups that contributed large amounts of protein were further split into subgroups.

‘Minimally adjusted’ intakes were adjusted for age (except when stratified by age) and were weighted by season and day of the week of recall using generalized linear models to control for different distributions of 24-HDR interviews across seasons and days of the week.

We examined the independent effect of adjustment for several potential confounders—including height, weight, total energy intake, body mass index (BMI), smoking status, highest educational level and physical activity—on centre ranking and on the R2 of the model as an estimation of the variability of protein intake that is explained by the potential confounder. In ‘fully adjusted’ models, we decided to retain, in addition to the co-variables used in the ‘minimally adjusted’ model, total energy intake, weight and height. The tables on total protein, animal, plant and unknown mean intakes using the fully adjusted models are available in the Appendix. In this model, tests for gender differences in protein intake were also conducted. We also performed stratified analyses to describe differences in intakes of protein and its subgroups on the basis of BMI category (<25, 25–30 and 30 kg/m2), educational level (none/primary, secondary/technical and university), physical activity (inactive, moderately inactive, moderately active and active) and smoking status (never, former and current smoker). These factors were selected a priori, as it was thought that protein intakes might differ in these subgroups. In the stratified analyses, gender- and country-specific ‘minimally adjusted’ mean intakes were presented across variables of interest. Stratification was also performed for season (spring, summer, autumn and winter) and day of the week of the 24-HDR (Monday to Thursday versus Friday to Sunday). These analyses were weighted for either day or season, and were adjusted for age. If fewer than 20 persons were represented in a cross-classification (for example, centre, gender and age group), the least square mean and s.e. are not presented in the table. Analyses were performed using SAS (version 9.1, SAS Institute, Cary, NC, USA).


Minimal adjusted mean intake of total protein and protein of animal, plant or of unknown origin

Centre-specific mean total protein intakes, stratified by gender, centre and age, and weighted by season and day of the week of recall, are presented in Table 1. For both men and women, the highest mean daily intake of protein was seen in San Sebastian (men 144 g, women 94 g) and the lowest in the UK health-conscious group (men 72 g, women 60 g).

Table 1 Minimally adjusteda mean daily intake of total protein by centre ordered from south to north, gender and age group

Mean intakes and s.e. of protein of animal, plant and of unknown origin, stratified on the basis of gender and centre, are presented in Table 2. (Further stratifications according to age groups are presented on the EPIC website ( As for total protein, the highest intake of animal protein was reported in San Sebastian (men 105 g/day, women 67 g/day) and the lowest among the UK health-conscious participants (17 g/day for both men and women), because their specific eating patterns involve a very low consumption of animal foods (ovo-lacto vegetarians) or none (vegans). Among the remaining centres, the lowest intake of animal protein was seen in Greek men (52 g/day) and in women in Greece and Potsdam (37 g/day).

Table 2 Minimally adjusteda mean daily intake of protein of animal origin, plant origin, or mixed/unknown origin (g/day) and percentage of total protein by centre and gender

For plant protein, the highest mean intake was seen in the UK health-conscious group (men 51 g/day, women 39 g/day). Among the remaining centres, the highest mean intake was reported in Ragusa (men 42 g/day, women 27 g/day) and the lowest in Malmö (men 26 g/day, women 20 g/day). The mean intake of protein of unknown origin was generally low, ranging from 2 to 8 g/day; it was the lowest in Greece and in the Southern Spanish centres, and the highest in the Netherlands and in the UK general population. Within each centre, men had higher absolute intakes than did women of both total protein and different subgroups of protein. Looking across age groups, a tendency towards a lower intake of total protein in older people and a higher intake in younger age groups was observed in most but not all centres. The same tendency, although less clear, was present for animal and plant protein (data not shown but available on the EPIC website ( Figures 1a and b show the minimal adjusted mean intake of total and subtypes of protein expressed as a percentage of total energy (%en), stratified by gender and centre. In most centres, energy from protein contributed 15–20% in both genders. A particularly high percentage of energy intake from total protein was noted in some of the Northern Spanish centres (20–21%en) and from animal protein in the Northern Spanish (14–15%en) and French centres (11–12%en), in contrast to low values in the UK health-conscious group (12–13%en of total protein and 3–4%en from animal protein). The energy percentage from plant protein was fairly stable in most centres and in both genders (about 5–6%en), except in the UK health-conscious population, in which it was higher (8–9%en). The contribution to the total energy of protein of unknown origin was very marginal in all centres (0.3–1.5%en). More details on main nutrient energy sources are provided in a separate paper (Ocké et al, 2009).

Figure 1

Minimally adjusted mean intake of subtypes of protein expressed as percentage of total energy, stratified by centre, adjusted for age and weighted by season and day of dietary recall (a) men and (b) women.

Influence of adjustment for potential confounders

To evaluate whether the observed differences in protein intake could be ascribed to systematic differences in body composition and energy intake between the EPIC centres, further adjustments for body height, weight and total energy intake were performed. The fully adjusted mean intakes of total protein, animal, plant and unknown protein, stratified on the basis of gender and age groups and adjusted for age (in analyses not stratified on age), energy, height and weight and weighted by day of 24-HDR and season, are shown in the Appendix (Tables A1, A2, A3 and A4).

After adjustment, the estimated mean intake of total protein was still highest in the Northern Spanish centres and lowest in the UK health-conscious group. Although most centres were not influenced, a notable impact on the estimated mean protein intake was observed in the Greek centre and in UK health-conscious men, where energy adjustment especially increased the mean intake considerably. In contrast, decreases in mean intake were observed in women and men in Aarhus and in men in Varese and San Sebastian. The same result was observed for animal and plant proteins. Compared with the minimally adjusted models, less clear systematic differences in intake across age groups were observed. To test for any gender-specific effect on protein intake, we tested for an interaction between gender and centre in a fully adjusted model. Gender differences were present for total protein and for both subgroups for both absolute (g/day) and relative (%en) protein intake (P<0.0001).

Dietary sources of protein

Not counting the UK health-conscious group, animal protein accounted for 55–73% of total protein and plant protein accounted for 24–39% (Table 2). In contrast, in the UK health-conscious group, total protein was mostly of plant origin (men 70%, women 65%), and only 23–29% of it was of animal origin. The reverse extreme was observed in men in San Sebastian, with a proportion of 73% animal protein and 24% plant protein. A small percentage of the protein was considered to be of unknown origin (with contribution from cakes being an important factor in all centres), ranging from 2 to 9% of total protein.

Tables 3a and b show the dietary contributors (%) to intake of animal and plant protein in men and women. Dietary contributors to total protein and unknown protein are available on the EPIC website (

Table 3a Percentage contributiona of main food groups or subgroups to the intake of animal protein, adjusted for age and weighted for day of the week and season
Table 3b Percentage contributiona of main food groups to the intake of plant protein, adjusted for age and weighted for day of the week and season

Animal protein

For animal protein, the most important contributing food groups were meat (red meat, poultry, game, processed meat and offal), fish (fish and fish products, molluscs and crustaceans) and dairy products (milk, yoghurt, cheese, cream and dairy cream dessert), which together accounted for 84–96% of animal protein (Table 3a). In addition, eggs contributed 1–6%.

Total meat intake provided the highest contribution to animal protein in all centres, except for the UK health-conscious group and in Greek women, ranging from 39% (Granada) to 57% (Florence) in women and from 41% (Greece) to 64% (Heidelberg and Varese) in men, with some heterogeneity when subtypes of meat were compared. In most centres, the dominant type of meat was red meat, whereas the contribution from poultry varied from <5% of mean animal protein intake in the northern centres of Norway and Sweden to 15–22% in the UK general population and in some Italian centres. The contribution of processed meat to mean animal protein intake also varied markedly across centres, from 3% in Greece to 25–30% in German men.

Dairy products provided the second largest contribution to animal protein after meat, except for Spanish men, and women in San Sebastian (where fish came second), for Greek women (where meat and dairy contributed the same) and for the UK health-conscious group (where dairy products were the main contributors to animal protein).

The mean animal protein intake from fish represented around 5% in the Netherlands, but around 19% or more for women in Spain, Greece and North-West Norway. A similar result was observed for men.

Plant protein

For plant protein, the most important food group was cereals (contributing 42–69% in men and 35–61% in women), but potatoes, vegetables, legumes and fruits also contributed to vegetable protein, with differing importance across centres (Table 3b).

The lowest contribution from cereals (<50%) was observed in Spain (except for men in Navarra, 51%), Germany and in the UK health-conscious group, whereas the highest contributions (>60% for men and >55% for women) were reported in Italy and Greece, and in most of the Scandinavian centres. The contribution from vegetables varied from 5% in Umeå to 13% in Murcia and Turin for men and from 7% in North-West Norway to 24% in Murcia for women. With few exceptions, lower contributions of protein from vegetables were reported in Northern Europe. Among women, vegetables constituted the second highest contributor to plant protein in a majority of centres (clearest exceptions were Umeå and Norway), whereas a more mixed picture was observed for men. After cereals, legumes were the most important contributors to plant protein among men in most Spanish centres; for both men and women, a clear south–north gradient was present for legumes, with the highest contribution in Greece and Spain (6–16%), and the lowest in Scandinavian countries (<1%, except for men in Malmö, 2%). No clear south–north trend was observed for the contribution of fruit, but lower contributions were generally seen in Scandinavian countries for both genders. However, when pooled into one group, the contribution from vegetables, fruits and legumes showed a clear south–north gradient; the contribution was >30% for women and >26% for men in Spain and Greece, between 20 and 30% for women and between 15 and 26% for men in Italy, France, Germany, the United Kingdom and the Netherlands, whereas it was <20% (women) and <15% (men) in Scandinavian countries.

Potatoes contributed 5–10% of plant protein in most countries except in Greece, Italy and France, where the figures were below 5% in almost all centres. An indication of a south–north gradient was seen for potatoes in men, being the second largest contributor to plant protein among men in most of the Scandinavian centres.

Cakes contributed to plant protein in some countries (women 3–8%, men 1–6%) and also non-alcoholic beverages (women 1–11%, men 1–13%, with a maximum in Germany for both genders, followed by Denmark).

Stratified analyses

No systematic differences in total protein intakes were observed when the participants were stratified according to BMI (Table 4a). However, when the origin of protein was considered, the highest mean intake of plant protein was observed in the lowest BMI group in a majority of countries, whereas a slight tendency towards a higher intake of animal protein was seen in the highest BMI group, although this was less consistent than that for plant protein.

Table 4a Minimally adjusteda mean daily intake of total, animal and plant protein by country and BMI groups

When stratifying on the basis of educational level, we saw a clear trend among women for plant protein (Table 4b), wherein the highest intake was seen among women with the highest educational level in most countries (apart from Greece), whereas the lowest intake was primarily observed among the least educated. For men, there was an indication of south–north differences. In southern countries, a lower intake of plant protein was observed among the most educated men, whereas in the more northern countries, the lowest intake of plant protein was reported among the least educated. For animal protein, no clear differences across educational levels were observed for women, whereas among men, the highest intake was mainly observed among the least educated.

Table 4b Minimally adjusteda mean daily intake of total, animal and plant protein by country and educational level

No clear differences across physical activity levels were seen for intake of total protein or its subgroups (Table 4c), except for a weak indication of a higher intake of plant and total protein among men in the two most active groups compared with that in the less active groups.

Table 4c Minimally adjusteda mean daily intake of total, animal and plant protein by country and physical activity levelb

No clear differences in intake of total and animal protein across smoking status groups were present, but the lowest intake of plant protein was observed primarily among current smokers of both genders (Table 4d).

Table 4d Minimally adjusteda mean daily intake of total, animal and plant protein by country and smoking status

Protein intake was also evaluated according to season and day of the 24-HDR. In all countries, the mean intake of total and animal protein was higher on weekends than on weekdays (except in UK health-conscious men and women, and in Dutch women for animal protein) (Table 4e). For plant proteins, the difference between working days and weekend was less pronounced and no clear tendency was observed. A different pattern was observed in the UK health-conscious group, in which the mean intake of plant protein was notably higher at weekends than on working days, whereas intake of animal protein was highest on working days. In contrast to day of the week, no clear trend was observed with regard to the mean intake of protein according to seasons (results not shown).

Table 4e Minimally adjusteda mean daily intake of total, animal and plant protein by country and day of recall of 24-HDR


In this study, some variations were observed across centres in intakes and food sources of total protein, and protein of animal and plant origin. Despite variations in absolute intakes, the intake of animal protein compared with plant protein was mostly seen in a ratio of around 1.5–3 to 1. The only centre that deviated from this was the UK health-conscious group, in which a low intake of meat products resulted in a reverse ratio with a two to three times higher intake of plant protein than animal protein. Thus, they had the lowest total and animal protein intake, but the highest intake of plant protein across all centres.

Owing to cultural differences in eating habits previously reported in the same populations (Slimani et al., 2002b), it was expected that the predominant food items contributing to protein intake across the 27 participating centres would differ. This was clearly seen for plant protein, in which a south–north gradient was present when contributions from vegetables, legumes and fruits were combined. Legume consumption was almost non-existent in Northern Europe, whereas it contributed to a notable percentage in Spain and Greece (women 6–13%, men 8–16%). In contrast, potatoes were of more importance in Nordic countries, especially among men (9–10%).

Apart from the UK health-conscious group, total meat intake contributed the highest proportion to animal protein, as already observed in other studies (Smit et al., 1999), but clear differences were seen in eating patterns across Europe with regard to the types of meat consumed (Linseisen et al., 2002). Processed meat was a very important contributor in Germany and the Netherlands, but was negligible in the Greek diet. The contribution of fish to animal protein varied considerably across countries, as also observed for total fish intake (Welch et al., 2002), although without any clear north–south gradient or a relationship with proximity to the sea, as high contributions from fish were seen in coastal and inland regions in Spain, Greece and Norway, whereas intakes were low in the Netherlands. The different intake patterns of these two animal protein sources are of special interest, as they have been ascribed important roles in diet–disease associations. Processed meat has recently been judged as one of the most cancer-promoting food items (WCRF/AICR, 2007), whereas fish is considered to have beneficial effects in heart disease (He et al., 2004; Whelton et al., 2004) and also potentially in some cancer sites (Norat et al., 2005; Geelen et al., 2007), although possibly because of factors other than protein. Studies of the association between (animal or plant) protein and disease incidence may consequently be less reliable if the contributing protein sources are not evaluated in addition to total protein intakes.

Socioeconomic status is known to influence dietary habits (Lallukka et al., 2007), and in this study, lifestyle factors seemed primarily to influence the intake of plant protein. A lower intake of plant protein was seen among current smokers and among people with a high BMI, whereas a higher intake was observed among well-educated women and among well-educated men in the northern countries. It has been previously shown that socioeconomic status is related positively to the intake of plant protein (Hulshof et al., 2003). In the southern countries, in contrast, the highest intake of plant protein among men was seen among those belonging to the lowest educational levels. This north–south difference among men may stem from the fact that consumption of legumes is common at all social levels in Southern Europe, and may be particularly high in less economically advantaged groups owing to low cost, whereas it may reflect health consciousness in the northern countries.

The population average protein requirement for healthy adults is estimated at 0.66 g/kg body weight and the recommended safe lower level of protein intake was subsequently estimated at 0.83 g/kg body weight in the recently published report on protein and amino acid requirements in human nutrition (WHO/FAO/UNU, 2008). In relative terms, the recommended safe lower level corresponds to around 8–10%en.

In the EPIC calibration study, the mean protein intake per kilogram body weight ranged between 0.91 and 1.83 g/kg across centres in a minimal-adjusted model and was not below 0.83 g/kg in any age group (except in Greek women aged 65–74 years: 0.82 g/kg). Energy percentages ranged from 12 to 23%en across men and women and across different age groups, and are thus above the recommended lower safe intake level, and within the recommended intake range of 10–35%en (US Food and Nutrition Board) and 10–20%en (Nordic Nutrition Recommendations) (Alexander et al., 2004), and at the higher end of the WHO recommendations of 10–15%en (WHO/FAO, 2003). Both men and women in the UK health-conscious group had the lowest energy intake from protein (12–13%en) and also a rather low ratio of g protein/kg body weight. This indicates that a diet low in animal food items may result in a lower protein intake and may also be low in specific essential amino acids. The mean intake is, however, still within the recommended intake range.

Low protein intake in absolute terms might be due to a general or specific underreporting of diet. Among EPIC cohorts, Greek participants seem to have underreported total energy intake to a higher degree than other centres (Ferrari et al, 2002). Greek women also reported a rather low absolute intake of protein and a low ratio of g protein/kg body weight, whereas the %en level was normal. Adjustment for total energy intake increased the estimated mean intake considerably, indicating that protein intake in Greece for a fixed energy intake was not appreciably lower than that in the remaining centres. Thus, adjustment for total energy intake may take care of a part of the measurement errors included in nutrient intake data (Willett, 1998; Spiegelman, 2004) An overestimation of energy percentage from protein may, however, also be present, because of a possible relatively greater underestimation of fat and/or carbohydrate than protein (Heitmann and Lissner, 1995; Heitmann et al., 2000).

Protein deficiency is not a big issue in developed countries, and it would be important to evaluate the upper tolerable intake level and determine whether the optimal level seen in relation to health is higher than the recommended level. The latest WHO/FAO report concludes that current knowledge is still insufficient to permit clear recommendations for either a safe upper limit or an optimal intake level, and this is obviously an important subject for future research (WHO/FAO/UNU, 2008). Furthermore, no specific recommendations for different qualitative protein types or sources (such as those for fat and carbohydrate) exist as yet.

Comparable and detailed information on foods contributing to protein intake across countries is useful for conducting and interpreting the results of large multi-centre dietary studies. One of the strengths of this descriptive paper is the recent creation of the ENDB (Slimani et al., 2007), which harmonized national databases, making it possible to compare the intake of different types of protein across 10 countries and 27 centres. Detailed information with regard to the animal and plant origin of all food items, from which intake of animal and plant protein has been estimated, provides important knowledge for future studies investigating the association between diseases and subgroups of protein. In all centres, a small amount of protein (as for example, from ready-to-eat dishes and cakes without any clear declaration, or containing ingredients of mixed or unknown origin) could not be classified as being from either animal or plant origin. The amounts were, however so relatively small that they would have only a limited influence on the ranking of the centres for animal or plant protein even if all unknown proteins were regarded as being of either plant or animal origin.

Furthermore, the large geographical span makes it possible to study how the different food patterns across Europe contribute to protein intake with different protein-providing food items.

This is the largest study to date describing intake of protein across several European countries. However, as not all the EPIC cohorts are population based, the results cannot be extrapolated to the general population of each region. Another limitation is that each participant provided only one 24-HDR. Intake can, therefore, be evaluated only at the group level.

In this study, we measured diet simultaneously across 10 European countries. These data highlight and quantify the variations and similarities in protein intakes between these countries, and will form the basis for future aetiological analyses on how different types of dietary protein are related to health and disease.

Supplementary information

Supplementary information is available on the EPIC website (

Conflict of interest

S Bingham received grant support from MRC Centre. The remaining authors have declared no financial interests.


  1. Alexander J, Anderssen SA, Aro A, Becker W, Fogelholm M, Lyhne N et al. (2004). Nordic Nutrition Recommendations 2004. Nordic Council of Ministers: Copenhagen.

  2. Brustad M, Skeie G, Braaten T, Slimani N, Lund E (2003). Comparison of telephone vs face-to-face interviews in the assessment of dietary intake by the 24 h recall EPIC SOFT program—the Norwegian calibration study. Eur J Clin Nutr 57, 107–113.

  3. CDC—Centers for Disease Control Prevention (2004). Trends in intake of energy and macronutrients--United States, 1971–2000. MMWR Morb Mortal Wkly Rep 53, 80–82.

  4. Elmadfa I, Weichselbaum E (eds) (2005). Energy and nutrient intake in the European Union 58, In: European Nutrition and Health Report 2004. Karger Forum of Nutrition: Basel. pp 19–46.

  5. Ferrari P, Slimani N, Ciampi A, Trichopoulou A, Naska A, Lauria C et al. (2002). Evaluation of under- and overreporting of energy intake in the 24-h diet recalls in the European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr 5 (Suppl), S1329–S1345.

  6. Ferrari P, Kaaks R, Fahey MT, Slimani N, Day NE, Pera G et al. (2004). Within- and between-cohort variation in measured macronutrient intakes, taking account of measurement errors, in the European Prospective Investigation into Cancer and Nutrition study. Am J Epidemiol 160, 814–822.

  7. Ferrari P, Day NE, Boshuizen HC, Roddam A, Hoffmann K, Thiebaut A et al. (2008). The evaluation of the diet/disease relation in the EPIC study: considerations for the calibration and the disease models. Int J Epidemiol 37, 368–378.

  8. Friedenreich C, Cust A, Lahmann PH, Steindorf K, Boutron-Ruault MC, Clavel-Chapelon F et al. (2007). Physical activity and risk of endometrial cancer: the European Prospective Investigation into Cancer and Nutrition. Int J Cancer 121, 347–355.

  9. Geelen A, Schouten JM, Kamphuis C, Stam BE, Burema J, Renkema JM et al. (2007). Fish consumption, n-3 fatty acids, and colorectal cancer: a meta-analysis of prospective cohort studies. Am J Epidemiol 166, 1116–1125.

  10. Haftenberger M, Lahmann PH, Panico S, Gonzalez CA, Seidell JC, Boeing H et al. (2002a). Overweight, obesity and fat distribution in 50- to 64-year-old participants in the European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr 5 (Suppl), S1147–S1162.

  11. Haftenberger M, Schuit AJ, Tormo MJ, Boeing H, Wareham N, Bueno-de-Mesquita HB et al. (2002b). Physical activity of subjects aged 50-64 years involved in the European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr 5 (Suppl), S1163–S1176.

  12. Halton TL, Hu FB (2004). The effects of high protein diets on thermogenesis, satiety and weight loss: a critical review. J Am Coll Nutr 23, 373–385.

  13. He K, Song Y, Daviglus ML, Liu K, Van HL, Dyer AR et al. (2004). Accumulated evidence on fish consumption and coronary heart disease mortality: a meta-analysis of cohort studies. Circulation 109, 2705–2711.

  14. Heitmann BL, Lissner L (1995). Dietary underreporting by obese individuals--is it specific or nonspecific? Br Med J 311, 986–989.

  15. Heitmann BL, Lissner L, Osler M (2000). Do we eat less fat, or just report so? Int J Obes Relat Metab Disord 24, 435–442.

  16. Hulshof KF, Brussaard JH, Kruizinga AG, Telman J, Lowik MR (2003). Socio-economic status, dietary intake and 10 y trends: the Dutch National Food Consumption Survey. Eur J Clin Nutr 57, 128–137.

  17. Kaaks R, Plummer M, Riboli E, Esteve J, van Staveren W (1994). Adjustment for bias due to errors in exposure assessments in multicenter cohort studies on diet and cancer: a calibration approach. Am J Clin Nutr 59, S245–S250.

  18. Kaaks R, Riboli E, van Staveren W (1995). Calibration of dietary intake measurements in prospective cohort studies. Am J Epidemiol 142, 548–556.

  19. Kelemen LE, Kushi LH, Jacobs Jr DR, Cerhan JR (2005). Associations of dietary protein with disease and mortality in a prospective study of postmenopausal women. Am J Epidemiol 161, 239–249.

  20. Kuhnle GG, Bingham SA (2007). Dietary meat, endogenous nitrosation and colorectal cancer. Biochem Soc Trans 35, 1355–1357.

  21. Linseisen J, Kesse E, Slimani N, Bueno-de-Mesquita HB, Ocke MC, Skeie G et al (2002). Meat consumption in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohorts: results from 24-hour dietary recalls. Public Health Nutr 5 (Suppl), S1243–S1258.

  22. Lallukka T, Laaksonen M, Rahkonen O, Roos E, Lahelma E (2007). Multiple socio-economic circumstances and healthy food habits. Eur J Clin Nutr 61, 701–710.

  23. Norat T, Bingham S, Ferrari P, Slimani N, Jenab M, Mazuir M et al. (2005). Meat, fish, and colorectal cancer risk: the European Prospective Investigation into Cancer and Nutrition. J Natl Cancer Inst 97, 906–916.

  24. Nordmann AJ, Nordmann A, Briel M, Keller U, Yancy Jr WS, Brehm BJ et al. (2006). Effects of low-carbohydrate vs low-fat diets on weight loss and cardiovascular risk factors: a meta-analysis of randomized controlled trials. Arch Intern Med 166, 285–293.

  25. Ocké M, Larrañaga N, Grioni S, van den Berg SW, Ferrari P, Salvini S et al. (2009). Energy intake and sources of energy intake in the European Prospective Investigation into Cancer and Nutrition. Eur J Clin Nutr 63 (Suppl 4), S3–S15.

  26. Riboli E, Kaaks R (1997). The EPIC Project: rationale and study design. European Prospective Investigation into Cancer and Nutrition. Int J Epidemiol 26 (Suppl 1), S6–S14.

  27. Riboli E, Hunt KJ, Slimani N, Ferrari P, Norat T, Fahey M et al. (2002). European Prospective Investigation into Cancer and Nutrition (EPIC): study populations and data collection. Public Health Nutr 5 (Suppl), S1113–S1124.

  28. Slimani N, Deharveng G, Charrondiere RU, van Kappel AL, Ocke MC, Welch A et al. (1999). Structure of the standardized computerized 24-h diet recall interview used as reference method in the 22 centers participating in the EPIC project. European Prospective Investigation into Cancer and Nutrition. Comput Methods Programs Biomed 58, 251–266.

  29. Slimani N, Ferrari P, Ocke M, Welch A, Boeing H, Liere M et al. (2000). Standardization of the 24-hour diet recall calibration method used in the European Prospective Investigation into Cancer and Nutrition (EPIC): general concepts and preliminary results. Eur J Clin Nutr 54, 900–917.

  30. Slimani N, Kaaks R, Ferrari P, Casagrande C, Clavel-Chapelon F, Lotze G et al. (2002a). European Prospective Investigation into Cancer and Nutrition (EPIC) calibration study: rationale, design and population characteristics. Public Health Nutr 5 (Suppl), S1125–S1145.

  31. Slimani N, Fahey M, Welch AA, Wirfalt E, Stripp C, Bergstrom E et al. (2002b). Diversity of dietary patterns observed in the European Prospective Investigation into Cancer and Nutrition (EPIC) project. Public Health Nutr 5 (Suppl), S1311–S1328.

  32. Slimani N, Deharveng G, Unwin I, Southgate DA, Vignat J, Skeie G et al. (2007). The EPIC nutrient database project (ENDB): a first attempt to standardize nutrient databases across the 10 European countries participating in the EPIC study. Eur J Clin Nutr 61, 1037–1056.

  33. Smit E, Nieto FJ, Crespo CJ, Mitchell P (1999). Estimates of animal and plant protein intake in US adults: results from the Third National Health and Nutrition Examination Survey, 1988-1991. J Am Diet Assoc 99, 813–820.

  34. Spiegelman D (2004). Commentary: correlated errors and energy adjustment-where are the data? Int J Epidemiol 33, 1387–1388.

  35. WCRF/AICR (2007). Food, Nutrition, Physical Activity, and the Prevention of Cancer: A Global Perspective. World Cancer Research Fund/American Institute for Cancer Research: Washington DC.

  36. Welch AA, Lund E, Amiano P, Dorronsoro M, Brustad M, Kumle M et al. (2002). Variability of fish consumption within the 10 European countries participating in the European Investigation into Cancer and Nutrition (EPIC) study. Public Health Nutr 5 (Suppl), S1273–S1285.

  37. Whelton SP, He J, Whelton PK, Muntner P (2004). Meta-analysis of observational studies on fish intake and coronary heart disease. Am J Cardiol 93, 1119–1123.

  38. WHO (2000). Nutrition for Health and Development: A Global Agenda for Combating Malnutrition. Progress ReportWHO/NHD/00.6 World Health Organization: Geneva.

  39. WHO/FAO Expert Consultation (2003). Diet, Nutrition and the Prevention of Chronic Diseases WHO Tech Rep Series 916. World Health Organization: Geneva.

  40. WHO/FAO/UNU Expert Consultation (2008). Protein and Amino Acid Requirements in Human Nutrition WHO Technical Report 935 World Health Organization: Geneva.

  41. Willett WC (1998). Nutritional Epidemiology 2nd edn. Oxford University Press: New York.

Download references


This study was carried out with the financial support of the European Commission: Public Health and Consumer Protection Directorate 1993–2004; Research Directorate-General 2005, Ligue contre le Cancer (France); Société 3M (France); Mutuelle Générale de l’Education Nationale; Institut National de la Santé et de la Recherche Médicale (INSERM); Institut Gustave Roussy; German Cancer Aid; German Cancer Research Center; German Federal Ministry of Education and Research; Danish Cancer Society; Health Research Fund (FIS) of the Spanish Ministry of Health; Spanish Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra and the Catalan Institute of Oncology; and ISCIII RETIC (RD06/0020), Spain; Cancer Research UK; Medical Research Council, UK; the Stroke Association, UK; British Heart Foundation; Department of Health, UK; Food Standards Agency, UK; the Wellcome Trust, UK; Greek Ministry of Health; Hellenic Health Foundation; Italian Association for Research on Cancer; Italian National Research Council, Regione Sicilia (Sicilian government); Associazione Iblea per la Ricerca Epidemiologica—ONLUS (Hyblean association for epidemiological research, NPO); Dutch Ministry of Health, Welfare and Sport; Dutch Prevention Funds; LK Research Funds; Dutch ZON (Zorg Onderzoek Nederland); World Cancer Research Fund (WCRF); Swedish Cancer Society; Swedish Research Council; Regional Government of Skane and the County Council of Vasterbotten, Sweden; Norwegian Cancer Society; the Norwegian Research Council and the Norwegian Foundation for Health and Rehabilitation. We thank Sarah Somerville, Nicole Suty and Karima Abdedayem for assistance with editing, and Kimberley Bouckaert and Heinz Freisling for technical assistance.

Author information

Correspondence to J Halkjær.

Additional information

Guarantor: Dr J Halkjær.

Contributors: JH carried out the statistical analysis, prepared the tables and figures and wrote the paper, taking into account comments from all co-authors. NS was the overall coordinator of this project and of the EPIC nutritional databases (ENDB) project. JH, AO, LJB and GD were members of the ‘protein working group’ and gave input on statistical analyses, drafting of the manuscript and interpretation of results. The other co-authors were local EPIC collaborators involved in the collection of data, and in documenting, compiling and evaluating the subset of their national nutrient databases used in the ENDB. ER is the overall coordinator of the EPIC study. All co-authors provided comments and suggestions on the manuscript and approved the final version.



Tables A1, A2, A3 and A4

Table a1 Fully adjusteda mean daily intake of total protein by centre ordered from south to north, gender and age group
Table a2 Fully adjusteda mean daily intake of animal protein by centre ordered from south to north, gender and age group
Table a3 Fully adjusteda mean daily intake of plant protein by centre ordered from south to north, gender and age group
Table a4 Fully adjusteda mean daily intake of protein of unknown source by centre ordered from south to north, gender and age group

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Halkjær, J., Olsen, A., Bjerregaard, L. et al. Intake of total, animal and plant proteins, and their food sources in 10 countries in the European Prospective Investigation into Cancer and Nutrition. Eur J Clin Nutr 63, S16–S36 (2009).

Download citation


  • total proteins
  • animal proteins
  • plant proteins
  • EPIC
  • 24-h dietary recall
  • ENDB

Further reading