Next Article in Journal
Placing Salt/Soy Sauce at Dining Tables and Out-Of-Home Behavior Are Related to Urinary Sodium Excretion in Japanese Secondary School Students
Previous Article in Journal
Integrated Immunomodulatory Mechanisms through which Long-Chain n-3 Polyunsaturated Fatty Acids Attenuate Obese Adipose Tissue Dysfunction
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Adult Nutrient Intakes from Current National Dietary Surveys of European Populations

1
Nutritional Epidemiology Group (NEG), School of Food Science and Nutrition, University of Leeds, Leeds LS2 9JT, UK
2
Division of Noncommunicable Diseases and Promoting Health through the Life-Course, World Health Organization Regional Office for Europe, UN City, Marmorvej 51, DK-2100 Copenhagen, Denmark
*
Author to whom correspondence should be addressed.
Nutrients 2017, 9(12), 1288; https://doi.org/10.3390/nu9121288
Submission received: 13 October 2017 / Revised: 16 November 2017 / Accepted: 22 November 2017 / Published: 27 November 2017

Abstract

:
The World Health Organization (WHO) encourages countries to undertake national dietary survey (NDS) but implementation and reporting is inconsistent. This paper provides an up-to-date review of adult macro and micronutrient intakes in European populations as reported by NDS. It uses WHO Recommended Nutrient Intakes (RNIs) to assess intake adequacy and highlight areas of concern. NDS information was gathered primarily by internet searches and contacting survey authors and nutrition experts. Survey characteristics and adult intakes by gender/age group were extracted for selected nutrients and weighted means calculated by region. Of the 53 WHO Europe countries, over a third (n = 19), mainly Central & Eastern European countries (CEEC), had no identifiable NDS. Energy and nutrient intakes were extracted for 21 (40%) countries but differences in age group, methodology, under-reporting and nutrient composition databases hindered inter-country comparisons. No country met more than 39% WHO RNIs in all age/gender groups; macronutrient RNI achievement was poorer than micronutrient. Overall RNI attainment was slightly worse in CEEC and lower in women and female elderly. Only 40% countries provided adult energy and nutrient intakes. The main gaps lie in CEEC, where unknown nutrient deficiencies may occur. WHO RNI attainment was universally poor for macronutrients, especially for women, the female elderly and CEEC. All countries could be encouraged to report a uniform nutrient set and sub-analyses of nationally representative nutrient intakes.

1. Introduction

The burden of malnutrition in the form of overweight and obesity, nutrient deficiency and preventable diet-related non-communicable diseases (NCDs) is significant and worsening [1]. An unhealthy diet is one of the four major behavioral risk factors for NCDs in all WHO regions [2], with the European region proportionately suffering the greatest burden. Here, the four most common NCDs account for 77% of disease and almost 86% premature mortality [1]. The World Health Organization (WHO) European Food and Nutrition Action Plan aims to ‘significantly reduce’ the human, economic and social costs of all forms of malnutrition in the WHO European region [1].
National diet surveys (NDS) have an important role to play in assessing dietary patterns and intakes in populations and informing policy decisions; the WHO European Food & Nutrition Action Plan [1] explicitly encourages member states to ‘strengthen and expand nationally representative diet and nutrition surveys.’ Nutrition and health surveys formed the main source of information for dietary risk factors and physical inactivity in a systematic analysis of disease risk in 21 regions worldwide between 1990–2010 [3]. NDS can help monitor NCDs and malnutrition, identify specific areas of concern, highlight inequalities, guide interventions and evaluate policy impact, thereby ultimately contributing to the promotion of best practice across the region [1]. Imamura et al. [4] evaluated change in global diet patterns over time through either greater consumption of healthy or lesser consumption of unhealthy items and assessed heterogeneity by age, gender, national income and dietary pattern. Higher national income was associated with better diet quality via greater consumption of healthier items but also with higher intake of unhealthy items, demonstrating that socio-economic inequalities persist.
NDS provision across Europe is inconsistent. A recent review found that less than two thirds of countries in WHO Europe have nationally representative NDS and that the majority of gaps lie in Central & Eastern European countries (CEEC) [5]. This is concerning, as nutrition policies in these countries may therefore lack an appropriate evidence base. Novakovic et al. [6] examined selected micronutrient intakes in CEEC compared to other European countries and found that CEEC lacked intake data across all ages. Only 40% of countries in the WHO Europe remit reported adult energy and nutrient intakes from NDS conducted post-2000 and in these, macronutrients were more widely reported than micronutrients [5]. The Global Dietary Database (GDD) houses information on food and nutrient intakes in countries across the world but only includes broad food categories with limited nutrient data and is limited by the inclusion of some regional rather than national data [7].
A comprehensive, updated review of total nutrient intakes across different European populations and subgroups is therefore needed, the results of which could identify where in Europe there is a need to improve diets and whether inequalities exist. This review aims to examine macro and selected micronutrient adult intakes in countries across WHO Europe via the latest NDS for which nutrient intake data is available.

2. Materials and Methods

2.1. Identifying National Diet Surveys (NDS)

The methods for identifying and accessing NDS have been reported [5]. Briefly, authors of national surveys within WHO Europe were identified using listed contact names and other information from two main reports of NDS [8,9]. Where no response was obtained from authors, further general internet searches were performed on organizations specializing in nutrition to find other potentially useful contact details. Additionally, country responses to WHO questionnaires were mined to obtain relevant references to NDS. Contacts identified were asked to complete a questionnaire to provide information on nationally representative dietary surveys conducted at an individual level since 1990, including links or references to relevant reports. For countries without usable contact details, a systematic database search was performed across Web of Science, Medline and Scopus for nationally representative dietary surveys of adults and children that collected data at an individual level from 1990 to June 2016.
Papers returned were screened for relevance according to the criteria in Table 1. We found 109 nationally representative surveys that collected data on whole diets at an individual level since 1990 across 34 of the 53 countries in the WHO office region; 86 of these included adults. Of these, 78 were conducted since 2000, 60 of which included adults. Further details of all the surveys found are presented in Rippin et al. (in submission) [5].

2.2. Data Extracted

Where available, estimated energy and nutrient intake (excluding supplements) by age group and gender was extracted and graphically presented from the latest NDS collected after 2000; for adults, this included surveys from 21 countries. These countries were grouped into regions—Western, Northern and Central & Eastern Europe. For some countries, more recent surveys have been conducted but intake data was not yet available. For example, the Spanish ANIBES survey (2013) did not include micronutrients, so the ENIDE (2011) survey was used instead. Mean intake values were reported by the majority of the 21 countries but where medians were the sole measure of central tendency, these were extracted and used instead. Where energy intakes were given in kcal, these were converted to MJ for consistency across studies.
All macronutrients reported by the 21 countries were included in the data extraction but micronutrients extracted (see Table 2) were limited to those explicitly mentioned in the WHO European Food and Nutrition Action Plan [1] as being currently important to population health in the region. Where possible, WHO nutrient-based guidelines—hereby referred to as Recommended Nutrient Intakes (RNIs)—were used to assess intake adequacy and to highlight areas of concern [10,11,12,13,14], although WHO RNIs for iron are given for different bioavailabilities, so UK Reference Nutrient Intakes (RNIs) were used instead [15]. The RNI for monounsaturated fats (MUFAs) is calculated by the difference between total fat and the sum of saturates (SFA), polyunsaturated fats (PUFA) and trans fats (TFAs), so has not been included. The WHO RNI for free sugars [14] has been adopted as the RNI for added sugars, as no WHO RNI exists for added sugars, yet all surveys that reported sugar in this way used the added rather than free sugar definition. The definition for added sugars is similar but more restrictive to that of free sugars, meaning that free sugar intake would not be overestimated. Depending on the nutrient, the RNIs were variously maximum, minimum or target amounts.
To harmonize data where possible, units of measurement were converted to a common standard unit. Energy intakes and selected nutrients by age group and gender as reported in these latest surveys collected after 2000 were graphed. Omega-3 and omega-6 fatty acids were reported in surveys in various ways, including omega-3, omega-6, linoleic acid and α-linolenic acid in g/day and percentage energy (%E) and eicosapentaenoic acid + docosahexaenoic acid (EPA + DHA) in mg/day. These were converted to grams and %E and grouped into omega-3 and omega-6 fatty acids for clarity. Additionally, mean intakes by age group and gender were weighted by number of individuals surveyed in each group to produce weighted means by country. Regional and overall European weighted means were calculated by multiplying the male/female mean for each country by the latest total national population numbers from 2016 [16], adding this figure for each country and dividing by the total sum of the national populations in each region.
Characteristics of the surveys from the 21 countries were also extracted and reported: these were country name, survey name, year of survey (data collection), dietary methodology, age range and sample size. The percentage WHO RNIs not met by all gender/age groups was recorded. Where reported, surveys presenting nutrient intakes by socio-economic group (SEG) based on social class, income (continuous or grouped) and education level were also noted.

3. Results

3.1. Data Extracted

Results of NDS coverage across Europe have previously been documented [5]. Adult energy and nutrient intakes (excluding supplements) were extracted from 21 surveys across 21 countries from three regions: five (100%) of Northern European countries (Denmark, Finland, Iceland, Norway, Sweden); 11 (65%) of Western European countries (Andorra, Austria, Belgium, France, Germany, Ireland, Italy, The Netherlands, Portugal, Spain, UK) and five (16%) of CEEC (Estonia, Hungary, Latvia, Lithuania, Turkey). Table 3 shows the characteristics of these surveys. Adult energy and nutrient intakes could not be extracted for 60% (32) of European countries; 19 of these, mainly CEEC, had no identifiable nationally representative survey, making up over a third of WHO Europe countries.
All 21 surveys that reported nutrient information included energy and also carbohydrate, fiber, fat and protein intakes (see Table 4). Most surveys (n = 20) included intake data on saturates, MUFAs and PUFAs (Germany did not); however, less than half (n = 9) surveys included TFA intakes. The majority of surveys (n = 17) included intake levels of sugars, either as total sugars or as added sugars/sucrose; however, Germany, Latvia, Spain and Turkey included neither. Few surveys (n = 5) included starch intake data. Half the countries included either omega-3 (n = 10) or omega-6 (n = 9) fatty acid intakes in some form; eight surveys included both.
All surveys included some micronutrients of interest (see Table 5). Vitamin B12, vitamin D, calcium and iron intakes were reported by all surveys; potassium (not Belgium), folate and sodium (not Italy) were each reported by all but one survey and zinc by all but two (not Belgium and Norway). Iodine was the least reported micronutrient extracted (n = 14), though it was still reported by more than half the surveys. Considering all macro and micronutrients investigated, no country met more than 39% WHO RNIs in all age/gender groups.
Of the 21 countries for which nutrient intakes were extracted, seven reported intakes by SEG in addition to age and gender (Estonia, Finland, France, Ireland, The Netherlands, Norway, UK). Whilst this comprises a third of countries listed in Table 3, only 13% of the 53 countries in the WHO remit represented nutrient intakes by SEG.

3.2. Energy and Nutrient Intakes

3.2.1. Energy

Energy intakes reported from the NDS have previously been documented [5]. Briefly, daily mean/median energy intakes were higher in adult males and decreased with age for all age groups in all 21 countries; however, age groupings reported were not consistent across countries (see Figure 1, Figure 2 and Figure 3).

3.2.2. Macronutrients

For all macronutrients, with the exception of sugars and fibre in older age groups, males tended to have a higher intake than females in all countries across all age groups. In this section means reported are estimated weighted European means (see Table 4 and Table 5 for total weighted means by nutrient and broken down by country) and those in brackets are the ranges of gender and age group means provided in the country reports.
Attainment of the WHO macronutrient RNIs [10] was generally poor across all regions and marginally worse in CEEC. All age groups in all countries were comfortably over the lower 10%E protein RNI in men and women. Just over half of countries met or exceeded the upper RNI of 15%E, though there was no regional pattern. No country met the lower carbohydrate RNI of 55%E in any age group (Figure 4). The mean carbohydrate intake was 209 g, (range 156–265 g) for women and 264 g (range 173–342 g) for men. Most countries fell short of the fibre RNI in all ages; only Norway (all ages), Germany (women aged 51–64 and men across the lifespan) and Hungary (non-elderly men) met the 25 g target (Figure 5). Mean fibre intakes were 19 g (range 13–26 g) for women and 21 g (range 15–29 g) in men. All countries that reported added sugars (n = 7) were over the 5% recommended RNI, although only Estonian and Finnish women were above the 10% maximum (Figure 6). Mean added sugar intakes were 41 g (range 30–49 g) for women and 48 g (38–69 g) in men.
All countries exceeded the WHO upper fat limit of 30%E except Portuguese elderly men (Figure 7). The mean total fat intake was 73 g (51–95 g) in women and 94 g (61–127 g) in men. The majority of countries were also above the 10%E RNI for saturates; only Portuguese elderly men were below (Figure 8). The mean saturates intake was 25 g (16–33 g) for women and 32 g (20–45 g) for men. Only Lithuanian men exceeded the upper PUFA RNI of 10%E and just under half the countries were below the lower RNI of 6%E, leaving around half of countries with optimum intakes between the two RNIs; there was no regional pattern. The greatest WHO RNI compliance was in TFAs, where only Icelandic elderly men exceeded the <1%E limit with intakes at 1%E. However, only nine countries reported TFAs; the CEEC region had fewest countries reporting intakes.
Omega fats RNI attainment was mixed; 60% of countries that reported n-3 intakes were between the 1%–2%E RNI bands, mostly in Northern Europe, whilst 4 countries did not meet the lower RNI. Turkey and Hungary exceeded the upper n-6 limit of 8%E but fewer countries achieved intakes within the lower and upper RNI bands in the majority of age/gender groups than for n-3. There was no age or gender pattern but Northern European countries had higher n-3 and lower n-6 intakes.

3.2.3. Micronutrients

Micronutrient RNI [11,12,13] attainment was slightly better than macronutrient, though the variation in male/female intake patterns was higher and there were no clear age patterns.
All countries comfortably met the 4.9 mg female and 7 mg male RNI for zinc. The majority of countries met the 2.4 μg RNI for vitamin B12; only Lithuanian and Turkish older and elderly women and elderly men fell short. Fulfilment of iron, iodine and potassium RNIs was mixed and women generally had poorer attainment—particularly younger women (Figure 9, Figure 10 and Figure 11 respectively). For iron, only younger Irish women met the 14.8 mg UK RNI [15] for women aged 19–50, though all countries met the 8.7 mg RNI for women aged 51–65 y and 65+ y except elderly Turkish women. All countries met the 8.7 mg male RNI for iron. Mean intakes were 10.9 mg (8.1–15.1 mg) in women and 13.4 mg (9.9–18.1 mg) in men.
Just under half of countries that reported iodine met the 150 μg RNI; more men and younger age groups exceeded the RNI but there were no regional patterns. The mean iodine intake was 127 μg (28–227 μg) in women and 156 μg (33–268 μg) in men. No countries met the 3510 mg RNI for potassium in women; half of countries met the RNI in at least some male age groups, though there was no regional pattern between countries. Mean intakes were 2771 mg (1855–3500 mg) in women and 3245 mg (2192–4300 mg) in men.
Few countries and no women of any nationality met the 400 μg RNI for folic acid; only young and elderly Irish men and middle-aged Lithuanian and Turkish men had adequate intakes (Figure 12). The mean folic acid intake was 268 μg (129–399 μg) in women and 318 μg (142–643 μg) in men. The majority of countries over-consumed sodium; all male age groups exceeded the 3000 mg RNI and in women only the UK and younger Estonian and Latvian women did not (Figure 13). Mean sodium intakes were 2341 mg (1426–5200 mg) in women and 3163 mg (1811–7400 mg) in men.
Assessing RNI attainment in vitamin D and calcium (Figure 14 and Figure 15) is made more difficult by different ages having different RNIs—where age groupings span RNI categories it cannot be specified whether or not the RNI is met. Where this could be assessed, few countries met the RNI for the age range in question, particularly in women and the elderly, where no countries met the RNI. Mean vitamin D intakes were 2.7 μg (0.5–9.1 μg) in women and 3.3 μg (0.6–13.4 μg) in men. Mean calcium intakes were 799 mg (457–1206 mg) for women and 908 mg (555–1424 mg) in men.

4. Discussion

4.1. Data Extracted

This review details the provision of energy and nutrient intake data in nationally representative surveys across the 53 countries of the WHO Europe region for nutrients of particular concern to the WHO European Region [1]. Only 40% (n = 21) of countries provided intake data by gender and age group for adults; the majority of these were Western and Northern European countries. This implies that nutrition policies in the remaining 60% of countries without intake data may be based on limited evidence, particularly in CEEC. This is a concern, as overweight and obesity have tripled in some of these countries since 1980 and NCD prevalence rates are reaching those of Western Europe [1]. Additionally, unknown pockets of micronutrient deficiencies may exist in some countries.
Although the surveys used different dietary methodologies, we felt it important to report intakes in their publicly available format. Of the 21 surveys for which intakes were extracted, energy, macro and micronutrients were generally well represented and there were no apparent regional patterns in nutrient intake gaps. This provides a good basis for assessing population status and identifying vulnerable gender/age groups in these countries (see Appendices A & B). The biggest gaps in macronutrient provision were TFA, omega fatty acids and sugar, the latter particularly in CEEC, which have been identified as nutrients of concern [1,49]. These are therefore important knowledge gaps, as without intake data, population and subgroup status cannot be known or appropriate policies devised. Iodine was reported by the least surveys; deficiencies remain frequent in WHO Europe [1] and even mild-moderate maternal deficiency is associated with decreased cognitive function in children [50]. This gap therefore limits effective policy formation to address population groups most in need.
A third of countries, or just 13% of the 53 WHO Europe countries, reported energy and nutrient intakes by SEG (Table 3). This is concerning, as whilst NDS could be used to identify subgroups lacking nutrients based on gender and age, few can gauge the potential for NDS to capture socio-economic inequalities. In addition, different, often multiple variables were used to represent SEG, making inter-country comparisons difficult. Consequently, vulnerable groups across Europe may be at risk of malnutrition through under or over-nutrition and related NCDs, with limited means for governments and health bodies to measure, monitor or address in policy.

4.2. Energy Intakes

Energy intakes did not vary substantially by European region, although the different dietary assessment methodologies employed by surveys may make inter-country comparisons unreliable. In addition, under-reporting is associated with all dietary assessment methods, including the 24 h recall and food diaries used by the surveys in question [51], which could impact on the validity of intake data and the conclusions derived from it. Most surveys either included under-reporters or did not specify—only Belgium explicitly excluded under-reporters, which may elevate Belgian intakes compared to the other countries.

4.3. Nutrient Intakes and WHO RNI Status

WHO RNI attainment was low across all regions—only Finland and The Netherlands met more than a third of WHO RNIs in all gender/age groups, suggesting that nutritional concerns exist across WHO Europe and that population groups within countries are not impacted equally. Turkey had the lowest intakes in most nutrients, potentially because it reported the oldest age grouping (75+ y) who may be likely to consume less than younger adults. However, the Turkish 65–74 y group also had low intakes for multiple nutrients compared to equivalent age groups in other countries.

4.4. Carbohydrates and Fats

The majority of countries did not meet the carbohydrate, sugar or fiber guidelines. This suggests a potential under-consumption of complex carbohydrates, going against established dietary advice [10], particularly The Netherlands, which had a lower fiber but high sugar intake.
Most countries exceeded fat and saturates guidelines. Andorra and Lithuania had modest absolute but high %E intakes, suggesting a diet with an unfavorable fatty acid composition, particularly in Andorra, which does not have the high %E in PUFA evident in Lithuania. This could lead to increased susceptibility to NCDs like coronary heart disease (CHD) [52]. Similarly, Denmark, Norway and Iceland had a high saturates intakes without correspondingly high unsaturated fat intakes. This suggests that Northern European countries may have higher saturated fat intakes as a proportion of total fat, possibly reflecting unfavorable national dietary patterns, though diet is one of many contributors to disease susceptibility.
Spain, Italy and Andorra had high MUFA intakes, which could indicate a Mediterranean diet pattern, linked to reduced all-cause mortality and NCD risk [53,54]. Hungary, Lithuania and Turkey had high PUFA intakes, which could indicate a regional influence based on CEEC diet patterns, particularly in Turkey, which had low intakes for most macronutrients other than PUFA. This pattern is also evident in n-6 intakes—both Turkey and Hungary exceeded the upper WHO RNI. TFAs had the greatest RNI compliance, possibly due to a combination of health bodies like WHO calling for a wholesale TFA reduction [1] and widespread TFA-reduction policies across Europe, including bans, labelling initiatives and voluntary product reformulation [55,56,57,58].
Of those reporting omega fats, Northern European countries had higher n-3 but lower n-6 intakes. This could potentially be a function of national diet patterns such as high oily fish consumption in Scandinavia; of the five European countries participating in the European Food Consumption Validation Project (EFCOVAL), Norway had the highest fish consumption [59]. Although some countries reported different n-3 and n-6 variants, the highest intakes were not necessarily those that included multiple variants. Therefore, although amalgamated n-3 and n-6 levels may not represent the full population omega intake, this does not necessarily invalidate inferences made. It does, however, highlight the need for a common methodological approach to conducting dietary surveys and gathering nutrient intake data.

4.5. Micronutrients

The percentage of CEEC that surveyed micronutrients generally had lower micronutrient intakes than the other regions, particularly Lithuania and Turkey—exceptions were relatively high Lithuanian folate and Hungarian, particularly male, sodium intakes. This suggests the potential for population groups to have suboptimum diets with excessive or inadequate intakes of particular nutrients. More research is necessary to determine whether this is a function of typical regional diet patterns and to inform debate on potential solutions such as food-based compared to fortification and/or supplementation for specific at-risk groups.
The majority of countries not meeting the iodine RNI were CEEC (Figure 10); this could be attributed to regional differences in salt iodization practices. However, patterns are difficult to elucidate, as salt-iodization programs are not uniform within or between countries and even where countries have policies, household coverage may be low [60]. For sodium only the UK and CEEC females did not exceed the RNI, although sodium intakes from dietary records may be unreliable. This could reflect generally low CEEC intakes and also the UK being an early adopter of a comprehensive voluntary salt reduction program since 2008 [61,62], which is credited with facilitating a reduction in salt intakes [63]. However, care must be taken when considering salt reduction, as salt iodization is a primary means of improving iodine intakes [64]. European iodine status is concerning; of the WHO regions Europe has the highest deficiency level. Potential solutions for compatibility, such as increasing the concentration of iodine in salt or using alternative vehicles, may need to be considered in countries where iodine status is poor.
Nordic countries had higher mineral intakes, whilst different national fortification practices may explain some variations in vitamin intake. Scandinavian vitamin D intakes were relatively high, with the exception of Denmark and Swedish vitamin D fortification is more extensive than Danish [65]. Northern European countries have less sunlight, meaning populations are likely to need more vitamin D from food, so where fortification is low, intakes are likely to be lower. This review includes fortification in base diet, as most countries’ food composition databases do not separate this out [66].
Our findings support the identification of iodine, iron and vitamin D by WHO as nutrients of concern [1], particularly in CEEC, women and the female elderly respectively. Women and the female elderly appear to be the most vulnerable groups across the countries, with additional risk of potassium, calcium and folate deficiency. The latter is of particular concern in women of reproduction age as it can prevent neural tube defects in offspring [67]. Nutrients of universal concern were carbohydrates, fats and sodium. In addition to improving micronutrient intakes, increasing complex carbohydrate and fiber consumption and reduction of sodium, fat and saturates should be a priority across the majority of European population groups.

4.6. Strengths and Limitations

The strengths of this review are that it provides a unique, current account of reported energy and nutrient intakes for adults across whole populations and subgroups in Europe, with reference to WHO RNI attainment. The review will help identify where there is a need to improve diets and could enable governments and health bodies to better use NDS to reduce NCDs and related conditions across Europe. It also details where surveys report nutrient intakes by SEG—future work could present and assess intakes by SEG in more detail.
A limitation is that inconsistent age groupings across countries made inter-country comparisons difficult. In Andorra, the youngest age group spanned both adults and children, invalidating conclusions regarding adults aged 18–24. Further investigations using raw data could obtain more reliable conclusions via consistent age groups. Differences in dietary assessment methodologies present further limiting factors when making inter-country comparisons. For example, mean energy intakes in young Norwegian men were 3.4MJ higher than in the same age group in Sweden, despite being neighboring countries whose NDS were conducted in the same years. These differences could therefore be either due to the different methodological approaches employed, or a genuine intake disparity. In addition, collection over more days better reflects usual intake due to greater control over day-to-day variation [68]. However, most countries did not employ usual intake procedures such as the Statistical Programme to Assess Dietary Exposure (SPADE) [68]. This could affect intakes, although the impact would be greater on the distribution rather than the mean values. Some countries did not report overall country means for nutrients by gender, so a consistent weighting method was used for all countries. However, the overall country means we tabled are approximations based on the assumption that the numbers in each age group are proportionate to those in the total population. Due to availability, we used total national population numbers, which included adults and children, to calculate weighted regional and overall European means; therefore, means of countries with larger proportions of children in their populations may be given more weighting than required in these approximations.
Lack of alignment and completeness of national food composition databases and classification systems represents a further limitation. Sweden used sucrose as a proxy for added sugar [45], whilst others did not specify, so the number of mono and disaccharides included may differ and intake levels be incomparable. In this review, sucrose was equated with added sugars. If differences like these exist in other countries, estimated intake levels may vary as a result. Different composition databases may represent nutrients to different degrees; of the 14 countries reporting iodine, for example, not all may have iodine values for all foods. Consequently, intake values for particular nutrient in certain countries may be less accurate. In addition, the nutrient values underpinning food composition databases may be derived from different analytical methods, as with folate, preventing true data harmonization and potentially skewing intakes. This could explain the particularly low UK fiber intakes; the UK survey used the Englyst method, whereas other countries may have used AOAC or other methods. Whilst there is good agreement between methods in most foods, the Englyst method produces lower results in certain cereals, fruits, white beans and peanuts, which may affect fiber intake levels [69]. Additionally, food composition databases may not accurately reflect fortification—not all countries’ food composition databases account for iodine fortification, potentially depressing intake estimates [70]. Some food composition databases may not be updated to account for reformulated products; for instance, TFA values reported may be higher than those found in purchased products [71].
Future research could investigate how methodological differences impact on intake estimates in European populations—low Turkish intakes may have been due to either socioeconomic or methodological factors, using only a single 24 h recall [70]. Ireland had high vitamin intakes and was the only country that used weighed intake; the majority of countries used 24 h recall [5], which Holmes & Nelson [72] rank as less likely than weighed intakes to generate accurate portion size data.

5. Conclusions

This review has found that adult energy and nutrient intakes could only be extracted from 21 (40%) of the 53 WHO Europe countries and that methodological and other differences make inter-country comparisons difficult. The main gaps lie in CEEC, where nutrition policies may therefore be based on limited evidence, with a lack of data meaning potential unknown nutrient deficiencies may exist. Macro and micronutrients of interest were reported by most countries with intake data, though TFAs, omega fats, sugars and iodine had the least coverage. WHO RNI attainment was generally poor, particularly for macronutrients and was most notably lacking in women. Concerning micronutrients, the same was seen and was most prominent amongst the elderly female population and CEEC. Only 13% of WHO Europe countries reported intakes by SEG and by different methods. Consequently, the majority of WHO Europe countries are unable to adequately assess and address nutrient deficiencies in vulnerable SEGs. Future efforts should encourage WHO Europe countries to report a full range of nutrient intakes, including by SEG, in a uniform way.

Acknowledgments

This research was funded by the WHO Regional Office for Europe.

Author Contributions

All authors have contributed to the concept and design of the research and to the writing and/or revision of the manuscript and have approved the manuscript for submission.

Conflicts of Interest

The authors declare no conflict of interest. The co-authors Joao Breda and Jo Jewell are staff members of the World Health Organization Regional Office for Europe; however, the authors are responsible for the views expressed in this publication and they do not necessarily represent the decisions or stated policy of WHO.

Appendix A. Mean Macronutrient Intakes across Dietary Surveys

COUNTRYSURVEYYEAREnergy (MJ)Energy (Kcal)Protein (g)CHO (g)Sugars (g)Sucrose (g)Starch (g)Fiber (g)Total Fat (g)Saturates (g)MUFA (g)PUFA (g)TFAs (g)n-3 (g)n-6 (g)
AndorraEvaluation of the nutritional status of the Andorran population2004–2005
female: 25–44 y6.916508316575 15.87323.432.510.2
female: 45–64 y6.816288116277 17.67322.332.810.6
female: 65–75 y6.415187116583 21.36518.331.28.6
male: 25–44 y8.8209310020588 16.88530.742.713.8
male: 45–64 y8.019199018884 17.18626.539.312.1
male: 65–75 y7.016798317380 18.37420.834.912.0
AustriaAustrian nutrition report2010–2012
female: 18–24 y8.0191772225 43 22.07732.025.614.9 1.512.6
female: 25–50 y7.8185470218 46 22.07430.924.712.4 1.512.2
female: 51–64 y7.7182664219 46 22.07330.422.314.2 1.512.0
female: 65–80 y7.0167563188 38 19.06929.822.313.0 1.410.4
male: 18–24 y10.1240390282 60 24.09137.429.416.0 1.613.9
male: 25–50 y9.1217281239 54 20.08938.629.014.5 1.512.5
male: 51–64 y9.4224584236 45 22.09239.929.915.0 1.513.0
male: 65–80 y8.0192067216 38 20.07532.023.512.8 1.411.1
BelgiumThe Belgian food consumption survey 2014–20152014–2015
female: 18–39 y8.219557121499 11617.37929.029.014.00.8
female: 40–64 y7.618267119089 10018.87527.026.014.00.8
male: 18–39 y11.1265295291131 15519.310036.038.018.01.0
male: 40–64 y10.7254796253115 13720.110437.036.019.01.1
DenmarkDanish Dietary habits 2011–20132011–2013
female: 18–75 y8.4200876211 43 21.08333.031.013.01.3
male: 18–75 y11.22677101269 56 24.011145.041.017.01.7
EstoniaNational Dietary Survey2014–2015
female: 18–24 y6.8162564200 48 15.16425.522.810.90.51.68.6
female: 25–29 y7.6181871217 54 17.17630.527.212.10.61.99.2
female: 30–34 y7.3176271210 49 18.17329.626.411.60.61.88.9
female: 35–39 y7.2173068205 48 17.87229.126.411.90.62.29.1
female: 40–44 y6.4152960188 41 17.36124.421.810.40.51.87.7
female: 45–49 y6.2148859177 38 16.66023.621.910.30.51.87.7
female: 50–54 y6.3150560183 42 17.66123.322.310.80.51.87.8
female: 55–59 y6.4153764185 38 18.16224.622.610.70.51.58.0
female: 60–64 y6.2147461179 39 17.05922.52210.20.51.77.6
female: 65–69 y6.3150962186 36 17.85923.321.410.30.51.97.5
female: 70–74 y5.5133055168 32 16.65120.318.38.90.41.56.7
male: 18–24 y9.72326102266 58 18.19235.834.416.40.62.813.2
male: 25–29 y9.5227794239 55 16.89336.935.214.70.83.511.4
male: 30–34 y8.6205885234 52 17.7843331.314.40.72.611.2
male: 35–39 y9.5227994252 55 19.79436.934.716.80.64.412.3
male: 40–44 y8.7208589229 45 19.38131.830.913.40.63.010.0
male: 45–49 y8.6206879242 47 20.18029.731.3140.63.610.5
male: 50–54 y8.9212589233 46 20.48933.933.814.90.64.611.1
male: 55–59 y8.2196575221 44 19.27627.629140.53.510.5
male: 60–64 y8.1194181226 40 20.67529.628.112.60.62.99.3
male: 65–69 y7.8186578213 34 19.57429.827.412.40.62.69.0
male: 70–74 y7.6181475213 36 19.67329.127.512.70.52.49.4
FinlandThe national FINDIET 2012 survey2012
female: 25–34 y7.8186476199 49 19.07831.027.013.41.03.09.8
female: 35–44 y7.7184077195 46 20.07529.027.013.00.92.99.6
female: 45–54 y7.0167368180 44 21.06726.024.011.60.82.78.4
female: 55–64 y6.6157767171 36 22.06324.022.011.60.72.88.5
female: 65–74 y6.2148262166 35 21.05722.020.010.60.72.57.6
male: 25–34 y10.22449106249 55 19.010240.037.016.91.33.712.5
male: 35–44 y9.5227596237 54 21.09336.034.015.61.13.511.4
male: 45–54 y9.5228296237 52 23.09336.034.016.21.13.611.8
male: 55–64 y8.6205385207 45 23.08633.030.014.91.03.510.8
male: 65–74 y8.2195480212 43 24.07729.028.013.70.93.49.7
FranceINCA22006–2007
female: 18–79 y7.618097419989 10516.08032.128.612.3
male: 18–79 y9.82348100262101 15319.210041.235.714.5
GermanyGerman National Nutrition Survey II2005–2007
female: 19–24 y8.4199665252 21.774
female: 25–34 y8.5203170251 24.077
female: 35–50 y8.2194869231 24.776
female: 51–64 y7.8185667217 26.172
female: 65–80 y7.3175362209 24.969
male: 19–24 y12.02872102331 24.6110
male: 325–34 y11.6278399318 25.8110
male: 35–50 y11.0264094294 27.3106
male: 51–64 y10.0240086262 27.496
male: 65–80 y9.2219178241 27.388
HungaryHungarian Dietary Survey 20092009
female: 19–30 y9.1217581265 49 20.78826.226.822.8 0.922.1
female: 31–60 y9.0215181254 44 21.08825.927.122.7 0.922.0
female: 60+8.6205575245 41 20.68425.026.321.2 0.920.4
male: 19–30 y12.52988112334 64 25.512437.539.830.0 1.229.1
male: 31–60 y12.32940109322 49 25.412737.641.430.4 1.229.5
male: 60+10.5251092277 40 23.110731.735.125.5 1.024.6
IcelandThe Diet of Icelanders—a national dietary survey 2010–20112010–2011
female: 18–30 y8.0189575222108 16.27127.623.212.41.32.69.7
female: 31–60 y7.517957619086 16.57429.723.412.51.63.09.4
female: 61–80 y6.716107116174 14.86928.421.910.71.62.97.6
male: 18–30 y11.12635116288129 19.110138.932.517.12.13.513.6
male: 31–60 y10.12402107242105 17.610140.532.316.22.23.912.3
male: 61–80 y8.720819719280 16.79439.130.113.72.34.09.5
IrelandNational adult nutrition survey2008–2010
female: 18–64 y7.217217020081 11517.36828.927.413.91.11.6
female: 18–35 y7.517936920684 11715.97029.929.414.81.11.6
female: 36–50 y7.116977119777 11517.56728.626.413.21.01.6
female: 51–64 y7.016737319583 10919.56527.925.813.51.01.8
female: 65+ y6.515546918780 10318.46126.522.611.71.01.7
male: 18–64 y10.12414100266102 16021.19238.736.416.91.62.0
male: 18–35 y10.72557105281108 16721.39539.538.317.91.72.0
male: 36–50 y9.723189925998 15721.09238.635.616.21.51.9
male: 51–64 y9.322239324998 14821.08637.433.615.91.52.0
male: 65+ y8.319848522689 13319.67835.629.813.11.41.6
ItalyThe third Italian National food consumption survey INRAN-SCAI2005–2006
female: 18–64.98.119397623780 14217.77924.438.310.0
female: 65+7.718347123479 13918.77022.234.18.0
male: 18–64.910.023909328386 17919.69529.745.912.2
male: 65+9.622968827582 17421.68726.843.510.4
LatviaLatvian National Food Consumption Survey 2007–20092007–2009
female: ALL6.7161355190 15.86828.124.010.8
male: ALL9.1217179246 20.29338.133.414.8
female: 17–26 y7.11690
female: 27–36 y6.41523
female: 37–46 y6.51562
female: 47–56 y6.71608
female: 57–64 y6.41530
male: 17–26 y10.02394
male: 27–36 y10.02393
male: 37–46 y9.72319
male: 47–56 y9.32230
male: 57–64 y8.92121
LithuaniaStudy and evaluation of actual nutrition and nutrition habits of Lithuanian adult population2013–2014
female: 19–75 y6.515615617856 14.67121.926.815.5
male: 19–75 y9.221887522455 17.210833.541.123.8
all: 19–34 y8.119366520958 15.49228.434.820.1
all: 35–49 y7.818556619756 16.19027.734.019.7
all: 50–64 y7.417636319155 15.88325.931.718.3
all: 65–75 y6.716005718351 15.17222.327.315.8
The NetherlandsDutch National Food Consumption Survey (DNFCS) 2007–20102007–2010
female: 19–30 y8.5202873242121 18.07729.026.914.81.31.512.3
female: 31–50 y8.3198375222104 18.97729.626.614.61.31.711.9
female: 51–69 y7.918747719592 18.87227.824.013.81.41.811.3
male: 19–30 y11.9284798342152 22.410939.339.121.71.72.318.1
male: 31–50 y11.1265197285126 23.710438.336.221.01.62.317.4
male: 51–69 y10.2242597246107 21.69435.432.218.61.62.215.4
NorwayNorkost32010–2011
female: 18–70 y8.0191281205 36 22.07529.025.013.0
male: 18–70 y10.92605112278 48 26.010239.034.018.0
female: 18–29 y8.1193680221 46 21.07328.025.013.0
female: 30–39 y8.4200883232 42 24.07529.025.014.0
female: 40–49 y8.1193683202 32 22.07730.026.014.0
female: 50–59 y7.9188881194 33 22.07528.026.014.0
female: 60–70 y7.4176977182 30 22.07228.024.013.0
male: 18–29 y12.83059130339 69 29.011444.038.021.0
male: 30–39 y11.52749118298 49 26.010842.037.019.0
male: 40–49 y10.62533107275 51 25.010038.034.019.0
male: 50–59 y10.42486109259 41 26.09937.033.018.0
male: 60–70 y9.92366102247 39 27.09436.031.017.0
PortugalNational Food and Physical Activity Survey (IAN-AF)2015–2016
female: 18–64 y7.317478019978 16.96123.425.211.10.9 9.9
female: 65–84 y6.515557018073 18.15317.321.79.10.6 7.9
male: 18–64 y10.1239811125589 19.98128.933.913.71.1 13.1
male: 65–84 y8.520309121271 20.66320.926.410.80.7 9.6
SpainENIDE 20112009–2010
female: 18–24 y9.2218688209 17.19527.540.113.0
female: 25–44 y9.2218788202 18.99426.238.912.4
female: 45–64 y9.1216288193 19.79124.238.112.6
male: 18–24 y10.12402117275 20.512739.653.317.1
male: 25–44 y9.82340109248 20.411733.649.115.7
male: 45–64 y9.62281106222 21.710829.045.114.5
SwedenRiksmaten 2010–11 Swedish Adult Dietary Survey2010–2011
female: 18–30 y7.6181969205 44 17.37227.427.112.0 2.49.2
female: 31–44 y7.6182073199 38 18.57227.826.911.6 2.48.7
female: 45–64 y7.3175573182 34 19.37026.526.011.7 2.58.7
female: 65–80 y7.1170370186 34 20.06524.923.910.6 2.67.6
male: 18–30 y9.4224695241 45 18.68834.132.814.0 2.710.6
male: 31–44 y9.8234395250 43 21.39235.034.914.9 2.911.4
male: 45–64 y9.4225493237 41 21.88733.732.813.9 2.910.3
male: 65–80 y8.7208384223 38 22.58030.529.613.4 3.19.7
TurkeyTurkey nutrition and health survey 2010 (TNHS)2010
female: 19–30 y6.9164952204 19.06721.723.117.4 1.216.1
female: 31–50 y6.9163852205 20.36521.122.417.3 1.216.0
female: 51–64 y6.4153349195 21.05919.521.514.2 1.113.1
female: 65–74 y5.9140946183 19.35316.819.013.4 0.912.4
female: 75+ y5.1122339156 16.54716.017.210.7 0.89.8
male: 19–30 y9.4224271282 22.48628.330.021.9 1.620.2
male: 31–50 y9.2220373278 23.78327.429.320.4 1.518.8
male: 51–64 y8.0191964242 24.07223.826.517.1 1.315.7
male: 65–74 y7.1170556220 22.96421.523.415.0 1.113.7
male: 75+ y6.7160652207 21.46120.124.013.0 1.111.9
UKNational Diet and Nutrition Survey (NDNS) Years 1–42008–2012
female: 19–646.816136519785 11312.86022.121.710.61.11.88.8
female: 65+ y6.415106418788 9813.15823.019.69.51.21.87.7
male: 19–648.9211185251106 14614.77828.428.513.41.52.211.2
male: 65+ y8.1193578231102 12914.97428.725.812.41.52.310.1
all: 19–647.818617522495 12913.76925.225.112.01.32.010.0
all: 65+ y7.116977020695 11213.96525.522.310.71.32.08.7

Appendix B. Mean Micronutrient Intakes across Dietary Surveys

COUNTRYSURVEYYEARFolic Acid (μg)Vitamin B12 (μg)Vitamin D (μg)Calcium (mg)Potassium (mg)Sodium (mg)Iron (mg)Iodine (μg)Zinc (mg)
AndorraEvaluation of the nutritional status of the Andorran population2004–2005
female: 25–44 y2275.33.47932751266210.8 8.4
female: 45–64 y2585.82.07722912240110.9 7.9
female: 65–75 y2544.60.78343252203010.5 7.4
male: 25–44 y2487.15.18633124327213.2 10.4
male: 45–64 y2488.12.97973102283513.4 9.7
male: 65–75 y3027.41.57373179264413.8 7.8
AustriaAustrian nutrition report2010–2012
female: 18–24 y2293.62.09562562300011.416110.4
female: 25–50 y2164.02.88382632280010.91309.7
female: 51–64 y1933.32.77862623260010.31419.1
female: 65–80 y1944.83.26322288348010.21248.6
male: 18–24 y2555.54.09913329340013.916012.4
male: 25–50 y1975.33.68812768324011.814311.4
male: 51–64 y2225.04.68022820332011.614211.9
male: 65–80 y2034.03.9692259342009.91429.2
BelgiumThe Belgian food consumption survey 2014–20152014–2015
female: 18–39 y1893.63.4704 20768.5123
female: 40–64 y1913.73.6737 20478.8132
male: 18–39 y2285.04.0842 273111.0171
male: 40–64 y2245.54.6795 274811.4177
DenmarkDanish Dietary habits 2011–20132011–2013
female: 18–75 y3295.64.310383200320010.022710.5
male: 18–75 y3708.05.311883900440013.026814.1
EstoniaNational Dietary Survey2014–2015
female: 18–24 y1594.43.1671280017379.61127.8
female: 25–29 y1785.84.57293200189012.01239.2
female: 30–34 y1745.64.67303200182011.91199.3
female: 35–39 y1726.24.27153200187811.61179.0
female: 40–44 y1675.53.76203100184710.31078.0
female: 45–49 y1645.94.6595300016879.6937.7
female: 50–54 y1757.45.35913000165710.2967.9
female: 55–59 y1735.74.46143100171810.21028.4
female: 60–64 y1525.54.35662900182710.01028.0
female: 65–69 y1567.54.96013000190912.91028.3
female: 70–74 y1435.03.8545270017009.1857.4
male: 18–24 y2196.64.39503900257114.814912.1
male: 25–29 y2107.65.08333800279813.513411.7
male: 30–34 y2099.14.07883800241214.213211.1
male: 35–39 y2037.84.78943900260814.315112.4
male: 40–44 y1947.55.67293800239613.413011.5
male: 45–49 y1965.95.76853900241613.112511.2
male: 50–54 y20510.96.47774000301413.713512.0
male: 55–59 y1867.07.66213500260712.912010.4
male: 60–64 y1919.76.66523700258013.112111.1
male: 65–69 y1737.97.97203600239612.213410.4
male: 70–74 y1828.46.66363400239513.012510.8
FinlandThe national FINDIET 2012 survey2012
female: 25–34 y2435.38.212063500260010.019011.0
female: 35–44 y2335.19.011553400270011.019011.0
female: 45–54 y2304.98.29523300250010.019010.0
female: 55–64 y2334.79.110023400250010.019010.0
female: 65–74 y2195.18.7921320022009.01739.0
male: 25–34 y2776.910.714244200370012.023514.0
male: 35–44 y2727.311.512514100340013.023513.0
male: 45–54 y2778.011.211954200370013.023513.0
male: 55–64 y2576.411.910993900330012.023512.0
male: 65–74 y2556.712.810563900310012.020912.0
FranceINCA22006–2007
female: 18–79 y2685.12.48502681253311.51179.1
male: 18–79 y3076.52.79843287344714.913612.4
GermanyGerman National Nutrition Survey II2005–2007
female: 19–24 y3184.02.010392997235511.61739.1
female: 25–34 y3114.42.610613260253312.61929.8
female: 35–50 y2854.42.710673331257912.82009.8
female: 51–64 y2814.63.410113391252212.62049.6
female: 65–80 y2644.33.49183125237611.41908.8
male: 19–24 y3946.93.012813812373915.625713.2
male: 325–34 y3726.93.512523890362015.925513.2
male: 35–50 y3376.53.811673939358215.725612.7
male: 51–64 y3166.44.210713769334614.724611.7
male: 65–80 y2825.94.49703498305813.623210.9
HungaryHungarian Dietary Survey 20092009
female: 19–30 y1303.12.0691260050009.6 7.9
female: 31–60 y1332.92.0647260052009.7 7.7
female: 60+1292.61.9636260049009.2 7.0
male: 19–30 y1673.62.87723200710012.8 10.6
male: 31–60 y1663.92.76983200740012.9 10.5
male: 60+1423.02.36352900620011.1 8.8
IcelandThe Diet of Icelanders—a national dietary survey 2010–20112010–2011
female: 18–30 y2704.64.69302543267710.31169.4
female: 31–60 y2595.36.4840270826319.71389.1
female: 61–80 y2096.68.6694251724748.21687.8
male: 18–30 y3437.56.612153429405713.316913.9
male: 31–60 y3097.79.310473489377512.920012.4
male: 61–80 y25810.813.48473308352011.020411.2
IrelandNational adult nutrition survey2008–2010
female: 18–64 y3398.03.98242690226813.7 9.0
female: 18–35 y33711.13.17942507238515.1 8.5
female: 36–50 y3015.43.58242781222012.8 8.7
female: 51–64 y3996.96.08742855214512.8 10.1
female: 65+ y3576.58.59952721203513.8 10.7
male: 18–64 y4077.34.610603491312215.1 11.8
male: 18–35 y4267.43.911223568329115.6 12.4
male: 36–50 y3837.44.710363463312314.8 11.6
male: 51–64 y4047.25.79813388281714.3 11.2
male: 65+ y4276.45.29083038268918.1 10.2
ItalyThe third Italian National food consumption survey INRAN-SCAI2005–2006
female: 18–64.9 5.52.37302861 10.4 10.6
female: 65+ 4.41.87542822 10.0 9.9
male: 18–64.9 6.62.67993218 12.6 12.6
male: 65+ 6.52.58253300 13.2 12.2
LatviaLatvian National Food Consumption Survey 2007–20092007–2009
female: ALL 4572250 9.1537.2
male: ALL 5552868 12.16810.1
female: 17–26 y2183.31.4 2240
female: 27–36 y2143.61.6 1920
female: 37–46 y2133.91.9 2640
female: 47–56 y2123.72.5 2320
female: 57–64 y2084.52.2 2160
male: 17–26 y2183.31.4 3480
male: 27–36 y2143.61.6 3960
male: 37–46 y2133.91.9 3680
male: 47–56 y2123.72.5 3400
male: 57–64 y2084.52.2 3600
LithuaniaStudy and evaluation of actual nutrition and nutrition habits of Lithuanian adult population2013–2014
female: 19–75 y4811.23.45352556284210.3308.1
male: 19–75 y3661.03.1506232223488.9287.0
all: 19–34 y6431.53.75762887253812.2339.6
all: 35–49 y3501.43.2575265424510.7308.6
all: 50–64 y4591.01.55312625293510.7328.3
all: 65–75 y6691.24.95182519288210.0307.7
The NetherlandsDutch National Food Consumption Survey (DNFCS) 2007–20102007–2010
female: 19–30 y2323.92.8954284724299.31569.2
female: 31–50 y2434.33.19933112242810.11589.5
female: 51–69 y2814.83.510313296230110.41609.9
male: 19–30 y2935.33.911333774339411.621012.0
male: 31–50 y3025.43.911714048317712.420212.5
male: 51–69 y3305.84.411493866292011.819212.3
NorwayNorkost32010–2011
female: 18–70 y2316.04.9811340025009.9
male: 18–70 y2798.96.710384200360013.0
female: 18–29 y2195.73.9834310025009.4
female: 30–39 y2475.34.38363400260011.0
female: 40–49 y2316.15.08283400260010.0
female: 50–59 y2336.45.27843500250010.0
female: 60–70 y2246.45.8768340023009.3
male: 18–29 y3148.95.512484300400014.0
male: 30–39 y2958.96.112024200400013.0
male: 40–49 y2578.46.010094200350012.0
male: 50–59 y2758.97.39554300350012.0
male: 60–70 y2699.17.89004300310012.0
PortugalNational Food and Physical Activity Survey (IAN-AF)2015–2016
female: 18–64 y245.74.83.57312990269010.9 9.4
female: 65–84 y260.14.23.57243044244910.3 8.3
male: 18–64 y285.75.74.18303901370014.2 12.4
male: 65–84 y264.64.83.87643639326013.4 10.2
SpainENIDE 20112009–2010
female: 18–24 y2345.23.27892590232812.5758.6
female: 25–44 y2655.83.58512838242014.1878.8
female: 45–64 y2816.74.08393007228313.8878.7
male: 18–24 y2877.74.19582905275615.99511.2
male: 25–44 y2887.94.38982998273016.110010.4
male: 45–64 y3098.14.38403160265216.210310.1
SwedenRiksmaten 2010–11 Swedish Adult Dietary Survey2010–2011
female: 18–30 y2234.05.2806265927678.9 9.2
female: 31–44 y2474.86.2849286528769.7 9.9
female: 45–64 y2635.06.6805297127559.9 9.7
female: 65–80 y2756.47.6826301325469.4 9.1
male: 18–30 y2445.86.69753139364910.8 12.6
male: 31–44 y2635.56.99913433381911.7 13.0
male: 45–64 y2716.17.79373523363811.9 12.6
male: 65–80 y2796.69.18853392321411.0 10.9
TurkeyTurkey nutrition and health survey 2010 (TNHS)2010
female: 19–30 y3083.10.9566221115969.9578.4
female: 31–50 y3342.70.96052311168610.4608.6
female: 51–64 y3352.30.76062357163610.3598.2
female: 65–74 y2962.00.5547206315729.5537.6
female: 75+ y2712.01.0495185514268.1496.3
male: 19–30 y3854.41.16762511241112.46711.2
male: 31–50 y4104.71.37442717235313.07411.5
male: 51–64 y4003.71.37132687219712.26810.3
male: 65–74 y3752.81.26772537193811.1649.2
male: 75+ y3292.30.65932192181110.2558.4
UKNational Diet and Nutrition Survey (NDNS) Years 1–42008–2012
female: 19–642284.62.6728253219959.61407.6
female: 65+ y2415.52.9796264926809.41697.6
male: 19–642875.73.18883039260011.71809.7
male: 65+ y2957.63.99243063348011.12139.2
all: 19–642585.12.88072785229710.71608.6
all: 65+ y2656.43.38522831304010.21888.3

References

  1. WHO. European Food and Nutrition Action Plan 2015–2020; WHO Regional Office for Europe: Copenhagen, Denmark, 2014. [Google Scholar]
  2. Alwan, A. Global Status Report on Noncommunicable Diseases 2010; World Health Organization: Geneva, Switzerland, 2011. [Google Scholar]
  3. Lim, S.S.; Vos, T.; Flaxman, A.D.; Danaei, G.; Shibuya, K.; Adair-Rohani, H.; AlMazroa, M.A.; Amann, M.; Andersson, H.R.; Andrews, K.G.; et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 2013, 380, 2224–2260. [Google Scholar] [CrossRef]
  4. Imamura, F.; Micha, R.; Khatibzadeh, S.; Fahimi, S.; Shi, P.; Powles, J.; Mozaffarian, D.; Global Burden of Diseases Chronic Expert Group. Dietary quality among men and women in 187 countries in 1990 and 2010: A systematic assessment. Lancet Glob. Health 2015, 3, e132–e142. [Google Scholar] [CrossRef]
  5. Rippin, H.L.; Hutchinson, J.; Evans, C.E.; Jewell, J.; Breda, J.J.; Cade, J.E. How much do we know about dietary intake across Europe? A review and characterisation of national surveys. Food Nutr. Res. 2017. submitted. [Google Scholar]
  6. Novaković, R.; Cavelaars, A.E.J.M.; Bekkering, G.E.; Roman-Vinas, B.; Ngo, J.; Gurinovic, M.; Glibetic, M.; Nikolic, M.; Golesorkhi, M.; Medina, M.W. Micronutrient intake and status in Central and Eastern Europe compared with other European countries, results from the EURRECA network. Public Health Nutr. 2013, 16, 824–840. [Google Scholar]
  7. Del Gobbo, L.C.; Khatibzadeh, S.; Imamura, F.; Micha, R.; Shi, P.; Smith, M.; Myers, S.S.; Mozaffarian, D. Assessing global dietary habits: A comparison of national estimates from the FAO and the Global Dietary Database. Am. J. Clin. Nutr. 2015, 101, 1038–1046. [Google Scholar] [CrossRef] [PubMed]
  8. EFCOSUM. European Food Consumption Survey Method Final Report; TNO Nutrition and Food Research: Zeist, The Netherlands, 2001. [Google Scholar]
  9. Micha, R.; Khatibzadeh, S.; Shi, P.; Fahimi, S.; Lim, S.; Andrews, K.G.; Engell, R.E.; Powles, J.; Ezzati, M.; Mozaffarian, D. Global, regional, and national consumption levels of dietary fats and oils in 1990 and 2010: A systematic analysis including 266 country-specific nutrition surveys. BMJ 2014, 348, g2272. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  10. FAO; WHO. Diet, Nutrition and the Prevention of Chronic Diseases; WHO Technical Report Series 916; WHO: Geneva, Switzerland, 2003. [Google Scholar]
  11. FAO; WHO. WHO Expert Consultation on Human Vitamin and Mineral Requirements. Vitamin and Mineral Requirements in Human Nutrition; World Health Organization: Geneva, Switzerland; Food and Agriculture Organization of the United Nations: Rome, Italy, 2004; pp. 45–58. [Google Scholar]
  12. WHO. Guideline: Potassium Intake for Adults and Children; World Health Organization: Geneva, Switzerland, 2012. [Google Scholar]
  13. WHO. Guideline: Sodium Intake for Adults and Children; World Health Organization: Geneva, Switzerland, 2012. [Google Scholar]
  14. WHO. Guideline: Sugars Intake for Adults and Children; World Health Organization: Geneva, Switzerland, 2015. [Google Scholar]
  15. Committee on Medical Aspects of Food Policy. Dietary Reference Values for Food Energy and Nutrients for the United Kingdom: Report of the Panel on Dietary Reference Values of the Committee on Medical Aspects of Food Policy; HM Stationery Office: London, UK, 1991.
  16. World Bank Group. Population, Total. Available online: http://data.worldbank.org/indicator/SP.POP.TOTL?page=2 (accessed on 14 July 2017).
  17. Ministeri de Salut, B.S.i.F. Evaluation of the Nutritional Status of the Andorran Population. Available online: http://www.salut.ad/images/microsites/AvaluacioNutricional_04-05/index.html (accessed on 28 February 2017).
  18. Elmadfa, I.; Hasenegger, V.; Wagner, K.; Putz, P.; Weidl, N.-M.; Wottawa, D.; Kuen, T.; Seiringer, G.; Meyer, A.L.; Sturtzel, B.; et al. Austrian Nutrition Report 2012; Institute of Nutrition: Vienna, Austria, 2012. [Google Scholar]
  19. Bel, S.; Van den Abeele, S.; Lebacq, T.; Ost, C.; Brocatus, L.; Stievenart, C.; Teppers, E.; Tafforeau, J.; Cuypers, K. Protocol of the Belgian food consumption survey 2014: Objectives, design and methods. Arch. Public Health 2016, 74, 20. [Google Scholar] [CrossRef] [PubMed]
  20. De Ridder, K. Food Consumption Survey 2014–2015: Food Consumption, in Report 4; WIV-ISP: Brussels, Belgium, 2016. [Google Scholar]
  21. Pedersen, A.; Christensen, T.; Matthiesen, J.; Knudsen, V.K.; Rosenlund-Sorensen, M.; Biltoft-Jensen, A.; Hinsch, H.J.; Ygil, K.H.; Korup, K.; Saxholt, E.; et al. Danskernes Kostvaner 2011–2013; DTU Fødevareinstitute: Søborg, Denmark, 2015. [Google Scholar]
  22. Helldán, A.; Raulio, S.; Kosola, M.; Tapanainen, H.; Ovaskainen, M.L.; Virtanen, S. Finravinto 2012—Tutkimus—The National FINDIET 2012 Survey; Raportti 2013_016; Suomen Yliopistopaino Oy: Tampere, Finland, 2013. [Google Scholar]
  23. Agence Française de Sécurité Sanitaire des Aliments (AFSSA). Étude Individuelle Nationale des Consommations Alimentaires 2 (INCA2) (2006–2007); AFSSA: Maisons-Alfort, France, 2009; pp. 1–28. [Google Scholar]
  24. Hartmann, B.M.; Heuer, T.; Hoffmann, I. The German Nutrient Database: Effect of different versions on the calculated energy and nutrient intake of the German population. J. Food Compos. Anal. 2015, 42, 26–29. [Google Scholar] [CrossRef]
  25. Nationale Verzehrsstudie II. Ergebnisbericht Teil 1; Max Rubner-Institut Karlsruhe: Karlsruhe, Germany, 2008. [Google Scholar]
  26. Bíró, L.; Szeitz-Szabo, M.; Biro, G.; Sali, J. Dietary survey in Hungary, 2009. Part II: Vitamins, macro- and microelements, food supplements and food allergy. Acta Aliment. 2011, 40, 301–312. [Google Scholar] [CrossRef]
  27. Szeitz-Szabó, M.; Biro, L.; Biro, G.; Sali, J. Dietary survey in Hungary, 2009. Part I. Macronutrients, alcohol, caffeine, fibre. Acta Aliment. 2011, 40, 142–152. [Google Scholar] [CrossRef]
  28. Steingrimsdottir, L.; Valgeirsdottir, H.; Halldorsson, P.I.; Gunnarsdottir, I.; Gisladottir, E.; Porgeirsdottir, H.; Prosdottir, I. National nutrition surveys and dietary changes in Iceland. Læknablaðið 2014, 100, 659–664. [Google Scholar]
  29. Þorgeirsdóttir, H.; Valgeirsdottir, H.; Gunnarsdottir, I.; Gisladottir, E.; Gunnarsdottir, B.E.; Porsdottir, I.; Stefansdottir, J.; Steingrimsdottir, L. Hvað Borða Íslendingar? Könnun á Mataræði Íslendinga 2010–2011 Helstu Niðurstöður; Embætti landlæknis, Matvælastofnun, Rannsóknastofa í næringarfræði við Háskóla Íslands, Landspítala-háskólasjúkrahús: Reykjavík, Iceland, 2011. [Google Scholar]
  30. Irish Universities Nutrition Alliance (IUNA). National Adult Nutrition Survey: Summary Report on Food and Nutrient Intakes, Physical Measurements, Physical Activity Patterns and Food Choice Motives; Irish Universities Nutrition Alliance: Dublin, Ireland, 2011. [Google Scholar]
  31. Li, K.; McNulty, B.A.; Tiernery, A.M.; Devlin, N.F.C.; Joyce, T.; Leite, J.C.; Flynn, A.; Walton, J.; Brennan, L.; Gibney, M.J. Dietary fat intakes in Irish adults in 2011: How much has changed in 10 years? Br. J. Nutr. 2016, 115, 1798–1809. [Google Scholar] [CrossRef] [PubMed]
  32. Sette, S.; Le Donne, C.; Piccinelli, R.; Arcella, D.; Turrini, A.; Leclercq, C. The third Italian National Food Consumption Survey, INRAN-SCAI 2005-06—Part 1: Nutrient intakes in Italy. Nutr. Metab. Cardiovasc. Dis. 2011, 21, 922–932. [Google Scholar] [CrossRef] [PubMed]
  33. Joffe, R.; Ozolins, G.; Santare, D.; Bartkevics, V.; Mike, L.; Briska, I. The National Food Consumption Survey of LATVIA, 2007–2009; National Diagnostic Centre, Food and Veterinary Service Food Centre, Eds.; Zemkopibas Ministrija: Riga, Latvia, 2009.
  34. Barzda, A.; Bartkeviciute, R.; Baltusyte, I.; Stukas, R.; Bartkeviciute, S. Suaugusių ir pagyvenusių Lietuvos gyventojų faktinės mitybos ir mitybos įpročių tyrimas. Visuom. Sveik. 2016, 72, 85–94. [Google Scholar]
  35. Van Rossum, C.; Fransen, H.P.; Verkaik-Kloosterman, J.; Buurma, E.M.; Ocke, M. Dutch National Food Consumption Survey 2007–2010: Part 6 Micronutrients; RIVM: Bilthoven, The Netherlands, 2011.
  36. Van Rossum, C.; Fransen, H.P.; Verkaik-Kloosterman, J.; Buurma, E.M.; Ocke, M. Dutch National Food Consumption Survey 2007–2010: Part 5 Macronutrients; RIVM: Bilthoven, The Netherlands, 2011.
  37. Van Rossum, C.; Fransen, H.P.; Verkaik-Kloosterman, J.; Buurma-Rethans, E.J.M.; Ocke, M.C. Dutch National Food Consumption Survey 2007–2010: Diet of Children and Adults Aged 7 to 69 Years; RIVM: Bilthoven, The Netherlands, 2011.
  38. Totland, T.; Melnaes, B.K.; Lundberg-Hallen, N.; Helland-Kigen, K.M.; Lund-Blix, N.A.; Myhre, J.B.; Johansen, A.M.W.; Loken, E.B.; Andersen, L.F. Norkost 3. En Landsomfattende Kostholdsundersøkelse Blant Menn og Kvinner i Norge i Aldermen; Helsedirektoratet: Oslo, Norway, 2012; pp. 18–70. [Google Scholar]
  39. Lopes, C.; Torres, D.; Oliveira, A.; Severo, M.; Alarcao, V.; Guiomar, S.; Mota, J.; Teixeira, P.; Ramos, E.; Rodrigues, S.; et al. Inquérito Alimentar Nacional e de Atividade Física (IAN-AF), 2015–2016 Part 1 Methodological Report; University of Porto: Porto, Portugal, 2017. [Google Scholar]
  40. Lopes, C.; Torres, D.; Oliveira, A.; Severo, M.; Alarcao, V.; Guiomar, S.; Mota, J.; Teixeira, P.; Rodrigues, S.; Lobato; et al. Inquérito Alimentar Nacional e de Atividade Física (IAN-AF), 2015–2016 Part 2 Report; University of Porto: Porto, Portugal, 2017. [Google Scholar]
  41. AESAN; ENIDE. Encuesta Nacional de Ingesta Dietética Española 2011; Ministerio de Sanidad, Politica Social e Igualdad: Madrid, Spain, 2011. [Google Scholar]
  42. AESAN. Evaluación Nutricional de la Dieta Española. i Energía y Macronutrientes Sobre Datos de la Encuesta Nacional de Ingesta Dietética (ENIDE); Ministerio de Sanidad, Servicios Sociales e Igualdad: Madrid, Spain, 2011.
  43. AESAN. Evaluación Nutricional de la Dieta Española. ii Micronutrientes Sobre Datos de la Encuesta Nacional de Ingesta Dietética (ENIDE); Ministerio de Sanidad, Servicios Sociales e Igualdad: Madrid, Spain, 2011.
  44. Estévez-Santiago, R.; Beltrán-de-Miguel, B.; Olmedilla-Alonso, B. Assessment of dietary lutein, zeaxanthin and lycopene intakes and sources in the spanish survey of dietary intake (2009–2010). Int. J. Food Sci. Nutr. 2016, 67, 305–313. [Google Scholar] [CrossRef] [PubMed]
  45. Amcoff, E. Riksmaten-Vuxna 2010–2011 Livsmedels-Och Näringsintag Bland Vuxna i Sverige; Livsmedelsverket: Stockholm, Sweden, 2012.
  46. Güler, S.; Budakoglu, I.; Besler, H.T.; Pekcan, A.G.; Turkyilmaz, A.S.; Cingi, H.; Buzgan, T.; Zengin, N.; Dilmen, U.; Tosun, N.; et al. Methodology of National Turkey Nutrition and Health survey (TNHS) 2010. Med. J. Islam. World Acad. Sci. 2014, 22, 7–29. [Google Scholar] [CrossRef]
  47. Turkey Ministry of Health. Türkiye Beslenme ve Sağlık Araştırması 2010: Beslenme Durumu ve Alışkanlıklarının Değerlendirilmesi Sonuç Raporu; Türkiye Cumhuriyeti Sağlık Bakanlığı Sağlık: Ankara, Turkey, 2014.
  48. Bates, B.; Lennox, A.; Prentice, A.; Bates, C.; Page, P.; Nicholson, S.; Swan, G. National Diet and Nutrition Survey: Results from Years 1, 2, 3 and 4 Combined of the Rolling Program (2008/9–2011/12); Public Health England: London, UK, 2014.
  49. Lavie, C.J.; Milani, R.V.; Mehra, M.R.; Ventura, H.O. Omega-3 polyunsaturated fatty acids and cardiovascular diseases. J. Am. Coll. Cardiol. 2009, 54, 585–594. [Google Scholar] [CrossRef] [PubMed]
  50. Bath, S.C.; Steer, C.D.; Golding, J.; Emmett, P.; Rayman, M.P. Effect of inadequate iodine status in UK pregnant women on cognitive outcomes in their children: Results from the Avon Longitudinal Study of Parents and Children (ALSPAC). Lancet 2013, 382, 331–337. [Google Scholar] [CrossRef]
  51. Poslusna, K.; Ruprich, J.; de Vries, J.H.M.; Jakubikova, M.; van’t Veer, P. Misreporting of energy and micronutrient intake estimated by food records and 24 hour recalls, control and adjustment methods in practice. Br. J. Nutr. 2009, 101, S73–S85. [Google Scholar] [CrossRef] [PubMed]
  52. Mozaffarian, D.; Wilson, P.W.; Kannel, W.B. Beyond established and novel risk factors lifestyle risk factors for cardiovascular disease. Circulation 2008, 117, 3031–3038. [Google Scholar] [CrossRef] [PubMed]
  53. Knoops, K.T.; de Groot, L.C.P.G.M.; Kromhout, D.; Perrin, A.-E.; Moreiras-Varela, O.; Menotti, A.; Van Staveren, W.A. Mediterranean diet, lifestyle factors, and 10-year mortality in elderly European men and women: The HALE project. JAMA 2004, 292, 1433–1439. [Google Scholar] [CrossRef] [PubMed]
  54. Sofi, F.; Cesari, F.; Abbate, R.; Gensini, G.F.; Casini, A. Adherence to Mediterranean diet and health status: Meta-analysis. BMJ 2008, 337, a1344. [Google Scholar] [CrossRef] [PubMed]
  55. Department of Health (DH). F3(a). Non use of artificial trans fat; Department of Health: London, UK, 2014.
  56. Restrepo, B.J.; Rieger, M. Denmark’s policy on artificial trans fat and cardiovascular disease. Am. J. Prev. Med. 2016, 50, 69–76. [Google Scholar] [CrossRef] [PubMed]
  57. Temme, E.H.; Millenaar, I.L.; Van Donkersgoed, G.; Westenbrink, S. Impact of fatty acid food reformulations on intake of Dutch young adults. Acta Cardiol. 2011, 66, 721. [Google Scholar] [CrossRef] [PubMed]
  58. WHO. Eliminating Trans Fats in Europe. A Policy Brief. WHO Regional Office for Europe: Copenhagen, Denmark. 2015. Available online: http://www.euro.who.int/__data/assets/pdf_file/0010/288442/Eliminating-trans-fats-in-Europe-A-policy-brief.pdf?ua=1 (accessed on 5 April 2016).
  59. Crispim, S.; de Vries, J.H.M.; Geelen, A.; Souverein, O.W.; Hulshof, P.J.M.; Lafay, L.; Rousseau, A.-S.; Lillegaard, I.T.L.; Andersen, L.F.; Huybrechts, I.; et al. Biomarker-based evaluation of two 24-h recalls for comparing usual fish, fruit and vegetable intakes across European centers in the EFCOVAL Study. Eur. J. Clin. Nutr. 2011, 65, S38. [Google Scholar] [CrossRef] [PubMed]
  60. WHO; UNICEF. Iodine Deficiency in Europe: A Continuing Public Health Problem; Anderson, M., de Benoist, B., Darnton-Hill, I., Delange, F., Eds.; World Health Organisation: Geneva, Switzerland, 2007. [Google Scholar]
  61. DH. F2. Salt Reduction Pledge. 2011. Available online: https://responsibilitydeal.dh.gov.uk/ledges/pledge/?pl=9 (accessed on 24 October 2016).
  62. WHO. Successful Nutrition Policies—Country Examples; WHO: Copenhagen, Denmark, 2014. [Google Scholar]
  63. He, F.; Brinsden, H.; MacGregor, G. Salt reduction in the United Kingdom: A successful experiment in public health. J. Hum. Hypertens. 2014, 28, 345–352. [Google Scholar] [CrossRef] [PubMed]
  64. Andersson, M.; Karumbunathan, V.; Zimmermann, M.B. Global iodine status in 2011 and trends over the past decade. J. Nutr. 2012, 142, 744–750. [Google Scholar] [CrossRef] [PubMed]
  65. Fagt, S. Nordic Dietary Surveys: Study Designs, Methods, Results and Use in Food-Based Risk Assessments; Nordic Council of Ministers: Copenhagen, Denmark, 2012. [Google Scholar]
  66. Mensink, G.; Fletcher, R.; Gurinovic, M.; Huybrechts, I.; Lafay, L.; Serra-Majem, L.; Szponar, L.; Tetens, I.; Verkaik-Kloosterman, J.; Baka, A. Mapping low intake of micronutrients across Europe. Br. J. Nutr. 2013, 110, 755–773. [Google Scholar] [CrossRef] [PubMed]
  67. Busby, A.; Abramsky, L.; Dolk, H.; Armstrong, B. Preventing neural tube defects in Europe: Population based study. BMJ 2005, 330, 574–575. [Google Scholar] [CrossRef] [PubMed]
  68. Dodd, K.W.; Guenther, P.M.; Freedman, L.S.; Subar, A.F.; Kipnis, V.; Midthune, D.; Tooze, J.A.; Krebs-Smith, S.M. Statistical methods for estimating usual intake of nutrients and foods: A review of the theory. J. Am. Diet. Assoc. 2006, 106, 1640–1650. [Google Scholar] [CrossRef] [PubMed]
  69. Mongeau, R.; Brassard, R. A comparison of three methods for analyzing dietary fiber in 38 foods. J. Food Compos. Anal. 1989, 2, 189–199. [Google Scholar] [CrossRef]
  70. Merten, C.; Ferrari, P.; Bakker, M.; Boss, A.; Hearty, A.; Leclercq, C.; Lindtner, O.; Tlustos, C.; Verger, P.; Volatier, J.-L. Methodological characteristics of the national dietary surveys carried out in the European Union as included in the European Food Safety Authority (EFSA) Comprehensive European Food Consumption Database. Food Addit. Contam. Part A 2011, 28, 975–995. [Google Scholar] [CrossRef] [PubMed]
  71. Hutchinson, J.; Rippin, H.; Jewell, J.; Breda, J.; Cade, J.E. Comparison of high and low trans fatty acid consumers: Analyses of UK National Diet and Nutrition Surveys before and after product reformulation. Public Health Nutr. 2017. [Google Scholar] [CrossRef] [PubMed]
  72. Holmes, B.; Nelson, M. The strengths and weaknesses of dietary survey methods in materially deprived households in England: A discussion paper. Public Health Nutr. 2009, 12, 1157–1164. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Mean/median* adult energy intake (MJ/day) for Western European countries (excluding supplements). * Figures for Spain are based on median rather than mean values.
Figure 1. Mean/median* adult energy intake (MJ/day) for Western European countries (excluding supplements). * Figures for Spain are based on median rather than mean values.
Nutrients 09 01288 g001
Figure 2. Mean/median adult energy intake (MJ/day) for Northern European countries (excluding supplements).
Figure 2. Mean/median adult energy intake (MJ/day) for Northern European countries (excluding supplements).
Nutrients 09 01288 g002
Figure 3. Mean/median adult energy intake (MJ/day) for Central & Eastern European countries (excluding supplements).
Figure 3. Mean/median adult energy intake (MJ/day) for Central & Eastern European countries (excluding supplements).
Nutrients 09 01288 g003
Figure 4. Mean/median* adult carbohydrate intake (g/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Figure 4. Mean/median* adult carbohydrate intake (g/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Nutrients 09 01288 g004
Figure 5. Mean/median* adult fibre intake (g/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Figure 5. Mean/median* adult fibre intake (g/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Nutrients 09 01288 g005
Figure 6. Mean/median adult added sugars intake (g/day) (excluding supplements).
Figure 6. Mean/median adult added sugars intake (g/day) (excluding supplements).
Nutrients 09 01288 g006
Figure 7. Mean/median* adult fat intake (g/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Figure 7. Mean/median* adult fat intake (g/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Nutrients 09 01288 g007
Figure 8. Mean/median* adult saturates intake (g/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Figure 8. Mean/median* adult saturates intake (g/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Nutrients 09 01288 g008
Figure 9. Mean/median* adult iron intake (mg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Figure 9. Mean/median* adult iron intake (mg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Nutrients 09 01288 g009
Figure 10. Mean/median* adult iodine intake (μg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Figure 10. Mean/median* adult iodine intake (μg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Nutrients 09 01288 g010
Figure 11. Mean/median* adult potassium intake (mg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Figure 11. Mean/median* adult potassium intake (mg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Nutrients 09 01288 g011
Figure 12. Mean/median* adult folic acid intake (μg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Figure 12. Mean/median* adult folic acid intake (μg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Nutrients 09 01288 g012
Figure 13. Mean/median* adult sodium intake (mg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Figure 13. Mean/median* adult sodium intake (mg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Nutrients 09 01288 g013
Figure 14. Mean/median* adult vitamin D intake (μg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Figure 14. Mean/median* adult vitamin D intake (μg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Nutrients 09 01288 g014
Figure 15. Mean/median* adult calcium intake (mg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Figure 15. Mean/median* adult calcium intake (mg/day) (excluding supplements). * Figures for Spain are based on median rather than mean values.
Nutrients 09 01288 g015
Table 1. Survey inclusion and exclusion criteria.
Table 1. Survey inclusion and exclusion criteria.
IncludedExcluded
Surveys conducted at an individual levelSurveys collected at group i.e. household level
Nationally representative surveysNon-nationally representative, regional only surveys
Results of surveys reported by published and unpublished reports, academic journals and websitesSurveys with data collected prior to 1990
Surveys that included individuals >2 ySurveys with samples exclusively <2 y
Surveys based on whole diet rather than specific food groupsSurveys with incomplete food group coverage
Surveys with small sample sizes (n < 200)
Table 2. Nutrients of interest in dietary surveys.
Table 2. Nutrients of interest in dietary surveys.
MacronutrientsRNIMicronutrientsRNI
Energy (MJ and kcal)N/AFolic acid (μg)Minimum
Carbohydrates (g and %Energy (E))TargetVitamin B12 (μg)Minimum
Sugars (g)MaximumVitamin D (μg)Target
Sucrose (g)MaximumCalcium (mg)Minimum
Starches (g)N/APotassium (mg)Minimum
Fiber (g)TargetSodium (mg)Maximum
Total fat (g)MaximumIron (mg)Minimum
Saturates (g)MaximumIodine (μg)Minimum
Monounsaturated fatty acids (MUFA) (g)N/AZinc (mg)Minimum
Polyunsaturated fatty acids (PUFA) (g)Target
Trans Fatty Acids (TFAs) (g)Maximum
Protein (g)Target
Omega fatty acids (g)Target
Table 3. National diet surveys across countries in WHO Europe 1990–2016 with nutrient intakes reported.
Table 3. National diet surveys across countries in WHO Europe 1990–2016 with nutrient intakes reported.
CountrySurvey NameSurvey YearSource *Sample SizeSample AgeDietary MethodologyNutrient Reference DatabaseNutrient Intakes by SEG Y/N **WHO RNIs Not Met by All Age Groups (%) ϮReference
AndorraEvaluation of the Nutritional Status of the Andorran Population2004–2005490012–7524 h recall (×2 for 35% sample), FFQCESNID. Tablas de composición de alimentos. Barcelona: Edicions Universitat de Barcelona-Centre d’Ensenyament Superior de Nutrició i Dietètica, 2002N83[17]
AustriaAustrian nutrition report 2012 (OSES)2010–2012210027–14; 18–803-day diary (consecutive) (children); 2*24 h recall (adults).Analysis run with software “(nut.s) science” based on Bundeslebensmittelschlüssel 3.01/Goldberg cut-offs for data cleaningN72[18]
BelgiumBelgium National Food Consumption Survey (BNFCS) 20142014–20151/231463–642*24 h recallThe NIMS Belgian Table of Food Composition (Nubel); Dutch NEVON78[19,20]
DenmarkDanish National Survey of Diet and Physical Activity (DANSDA) 2011–20132011–2013239464–757-day diary (consecutive)Danish Food Composition DatabankN67[21]
EstoniaNational Dietary Survey2014–2015149064 m–74 y2*24 h recall (age > 10); 2*24 h food diary (age < 10); FFQ (age > 2) Y—income, poverty threshold, education78
FinlandThe National FINDIET 2012 survey (FINRISK)20122170825–7448 h recallFineli 7 Food Composition DatabaseY—education61[22]
FranceIndividual National Food Consumption Survey (INCA2)2006–2007240793–797-day diary (consecutive)Food Composition Database of CIQUAL of AfssaY—education83[23]
GermanyGerman National Nutrition Survey (Nationale Verzehrstudie) II (NVSII)2005–20071/315,37114–80DISHES diet history interview, 24 h-recall, diet weighing diary (2*4 days)Bundeslebensmittelschlüssel (BLS)N78[24,25]
HungaryHungarian dietary survey 200920092307719–30, 31–60, 60+3-day diary, FFQ,Új tápanyagtáblázatN72[26,27]
IcelandThe Diet of Icelanders—a national dietary survey 2010–20112010–20111131218–802*24 h recall + FFQIcelandic Database of Food Ingredients (ÍSGEM); Public Health Institute for Raw Materials in the Icelandic MarketN72[28,29]
IrelandNational adult nutrition survey 2011 (NANS)2008–20101150018–904-day semi weighed food diary (consecutive)McCance and Widdowson’s The Composition of Foods 5&6 editionsY—social class and education72[30,31]
ItalyThe third Italian National food consumption survey INRAN-SCAI 2005–20062005–2006233230.1–97.73-day diary (consecutive)Banca Dati di Composizione degli AlimentiN83[32]
LatviaLatvian National Food Consumption Survey 2007–20092008119497–642*24 h recall, FFQLatvian National Food Composition Database 2009N78[33]
LithuaniaStudy of actual nutrition and nutrition habits of Lithuanian adult population2013–20141251319–7524 h recall + questionnaireEuroFIR Food ClassificationN83[34]
The NetherlandsDutch National Food Consumption Survey 2007–2010 (DNFCS 2007–2010)2007–20101/238197–692*24 h recallsDutch Food Composition Database (NEVO)Y—education61[35,36,37]
NorwayNorwegian national diet survey NORKOST32010–20112178718–702*24 h recall and FFQThe Norwegian Food Composition TablesY—education83[38]
PortugalNational Food and Physical Activity Survey (IAN-AF)2015–2016442213 m–84 y2*24 h recall (non-consecutive) and FPQ (electronic interview) 2-day food diary for children <10 yPortuguese Food Composition Table (INSA)N78[39,40]
SpainENIDE study (Sobre datos de la Encuesta Nacionalde Ingesta Dietética)2009–20102300018–24; 25–44; 45–643-day diary + 24 h recall (consecutive)Tablas de Composición de Alimentos, 15th edN83[41,42,43,44]
SwedenRiksmaten 2010–2011 Swedish Adults Dietary Survey2010–20112179718–804-day food diary (consecutive)NFA Food Composition DatabaseN78[45]
TurkeyTurkey nutrition and health survey 2010 (TNHS)2010214,2480–10024 h recall, FFQBEBS Nutritional Information System Software; Turkish Food Composition DatabaseN78[46,47]
UKNational Diet and Nutrition Survey Rolling Programme (NDNS RP 2008–2012)2008–2012268281.5–944-day diary (consecutive)McCance and Widdowson’s The Composition of Foods integrated datasetY—income72[48]
* 1 = email contacts; 2 = general internet searches; 3 = Micha et al. [9]; 4 WHO Global Nutrition Policy Review 2017 extracted information. ** Countries that have reported nutrient intakes by socio-economic group (SEG) in addition to age and gender. Ϯ For those countries that do not report all nutrients, the RNIs for nutrients not reported are considered not met.
Table 4. Weighted means * by country for macronutrient in 21 national dietary surveys in the WHO Europe region.
Table 4. Weighted means * by country for macronutrient in 21 national dietary surveys in the WHO Europe region.
COUNTRYEnergy (MJ)Protein (g)CHO (g)Sugars (g)Sucrose (g)Starch (g)Fibre (g)Total Fat (g)Saturates (g)MUFA (g)PUFA (g)TFA (g)n-3 (g)n-6 (g)
EstoniaNational Dietary Survey 2014–2015
Female6.764194 17652624110.51.88.2
Male8.786235 19833231140.63.210.9
HungaryHungarian Dietary Survey 2009
Female8.979253 44 2187262722 0.921.6
Male12.0106315 50 25122364029 1.228.4
LatviaLatvian National Food Consumption Survey 2007–2009
Female6.455190 1668282411
Male8.979246 2093383315
LithuaniaStudy and evaluation of actual nutrition and nutrition habits of Lithuanian adult population 2013–2014
Female6.55617856 1571222716
Male9.27522455 17108344124
TurkeyTurkey nutrition and health survey 2010 (TNHS)
Female6.550197 2061202216 1.114.5
Male8.667260 2378262819 1.417.4
CEEC TOTAL Female6.7532025644 20642123160.51.115.2
CEEC TOTAL Male9.0722645550 23842830200.61.418.5
DenmarkDanish Dietary habits 2011–2013
Female8.476211 43 21833331131.3
Male11.2101269 56 241114541171.7
FinlandThe national FINDIET 2012 survey
Female7.070181 42 21672624120.82.88.7
Male9.191225 49 22883432151.13.511.0
IcelandThe Diet of Icelanders—a national dietary survey 2010–2011
Female7.47618887 16722923121.52.99.0
Male10.0106240104 18994032162.23.811.9
NorwayNorkost3 2010–2011
Female8.081205 36 2275292514
Male10.9112278 48 27102393419
SwedenRiksmaten 2010–2011 Swedish Adult Dietary Survey
Female7.472193 37 1970272612 2.58.6
Male9.392238 41 2187333314 2.910.5
NORTH TOTAL Female7.6741978739 20732826131.12.68.6
NORTH TOTAL Male10.09825010447 23953735161.43.110.7
AndorraEvaluation of the nutritional status of the Andorran population 2004–2005
Female6.88116477 1775223210
Male8.49519786 1784284113
AustriaAustrian nutrition report 2010–2012
Female7.567209 43 2172312413 1.411.6
Male8.979235 48 2186372814 1.512.3
BelgiumThe Belgian food consumption survey 2014–2015
Female7.97120294 18772828140.8
Male10.995274124 201023637181.0
FranceINCA2 2006–2007
Female7.67419989 1680322912
Male9.8100262101 19100413615
GermanyGerman National Nutrition Survey II 2005–2007
Female7.967227 2574
Male10.589279 27100
IrelandNational adult nutrition survey 2008–2010
Female7.17019881 18662927141.01.6
Male9.898260100 21903835161.61.9
ItalyThe third Italian National food consumption survey INRAN-SCAI 2005–2006
Female8.07523679 1877243710
Male9.99228285 2094294612
The NetherlandsDutch National Food Consumption Survey (DNFCS) 2007–2010
Female8.275220106 19762926141.31.711.8
Male11.198291128 231033836201.62.217.0
PortugalNational Food and Physical Activity Survey (IAN-AF) 2015–2016
Female7.27819577 17602225110.8 9.5
Male9.810624685 20772732131.0 12.3
Spain **ENIDE 2011
Female9.28819972 1993263913
Male9.810924276 21115334815
UKNational Diet and Nutrition Survey (NDNS) Y1-4 2008–2012
Female6.76519585 13602221101.11.88.6
Male8.783247105 15772828131.52.211.0
WEST TOTAL Female7.8732128443 19752630121.11.79.5
WEST TOTAL Male9.8942649648 21963338141.42.112.2
EUROPE TOTAL Female7.6692098441 19732528131.11.511.9
EUROPE TOTAL Male9.7902649648 21943236161.41.914.9
* For each country weighted means were calculated for each nutrient by multiplying the male/female mean for each age group by the number of men/women in that age group, then dividing the total by the total number of men/women in the country in question. For each nutrient regional weighted means were calculated by multiplying the male/female mean for each country by the total national population [16], adding this figure for each country and dividing by the total sum of the national populations in that region. For each nutrient total European weighted means were calculated by multiplying the male/female mean for each age country by the total national population [16], adding this figure for each country and dividing by the total sum of the national populations in all three European regions. ** Figures for Spain are based on median rather than mean values.
Table 5. Weighted means* by country for micronutrient in 21 national dietary surveys in the WHO Europe region.
Table 5. Weighted means* by country for micronutrient in 21 national dietary surveys in the WHO Europe region.
SURVEYFolic Acid (μg)Vitamin B12 (μg)Vitamin D (μg)Calcium (mg)Potassium (mg)Sodium (mg)Iron (mg)Iodine (μg)Zinc (mg)
EstoniaNational Dietary Survey 2014–2015
Female1665.84.36483037180110.81088.4
Male1988.05.77673761256213.613411.4
HungaryHungarian Dietary Survey 2009
Female1312.82.0651260050869.5 7.5
Male1613.72.67013140710012.5 10.2
LatviaLatvian National Food Consumption Survey 2007–2009
Female2143.71.9457225022839.1537.2
Male2143.71.95552868359812.16810.1
LithuaniaStudy and Evaluation of Actual Nutrition and Nutrition Habits of Lithuanian Adult Population 2013–2014
Female3661.03.1506232223488.9287.0
Male6431.53.75762887253812.2339.6
TurkeyTurkey Nutrition and Health Survey 2010 (TNHS)
Female3202.50.85832242162510.0588.2
Male3934.01.27042608255212.36910.7
CEEC TOTAL Female2982.61.1586229220199.9588.1
CEEC TOTAL Male3703.91.56982692304112.36910.6
DenmarkDanish Dietary Habits 2011–2013
Female3295.64.310383200320010.022710.5
Male3708.05.311883900440013.026814.1
FinlandThe National FINDIET 2012 Survey
Female2315.08.710403352249210.018610.2
Male2667.011.811784037340012.422812.7
IcelandThe Diet of Icelanders—a National Dietary Survey 2010–2011
Female2495.56.6820263226009.41428.8
Male3048.49.710343433377312.519512.4
NorwayNorkost3 2010–2011
Female2316.04.98113374251010.0
Male2798.86.710384263355812.5
SwedenRiksmaten 2010–2011 Swedish Adult Dietary Survey
Female2525.06.4825288727669.6
Male2666.07.69453410359111.5
NORTH TOTAL Female2605.36.1912314227519.820510.3
NORTH TOTAL Male2917.27.810643812372112.224713.4
AndorraEvaluation of the Nutritional Status of the Andorran Population 2004–2005
Female2415.42.67902867249510.8 8.1
Male2557.44.18313126308613.3 9.9
AustriaAustrian Nutrition Report 2010–2012
Female2064.12.87712504302710.61339.3
Male2094.93.98212775353211.414411.0
BelgiumThe Belgian Food Consumption Survey 2014–2015
Female1903.73.5720 20628.6127
Male2265.24.2821 273911.1174
FranceINCA2 2006–07
Female2685.12.48502681253311.51179.1
Male3076.52.79843287344714.913612.4
GermanyGerman National Nutrition Survey II 2005–2007
Female2854.43.010203272250212.41969.5
Male3276.43.911153779341815.024812.1
IrelandNational Adult Nutrition Survey 2008–2010
Female3427.84.78512694223113.7 9.2
Male4107.24.710383426306015.5 11.6
ItalyThe third Italian National Food Consumption Survey INRAN-SCAI 2005–2006
Female 5.32.27352853 10.3 10.5
Male 6.62.68033231 12.7 12.5
The NetherlandsDutch National Food Consumption Survey (DNFCS) 2007–2010
Female2524.33.1993308623869.91589.5
Male3085.54.111513895316511.920112.3
PortugalNational Food and Physical Activity Survey (IAN-AF) 2015–2016
Female2484.73.57302999264710.8 9.2
Male2815.54.08163845360514.0 11.9
Spain **ENIDE 2011
Female2666.13.78352865234713.7858.7
Male2967.94.38843049270216.110010.4
UKNational Diet and Nutrition Survey (NDNS) Y1-4 2008–2012
Female2314.82.7743255821489.61467.6
Male2896.13.38963044279311.61879.6
WEST TOTAL Female2595.02.88462869240511.31439.1
WEST TOTAL Male3026.53.59513349315313.817811.5
EUROPE TOTAL Female2684.52.77992771234110.91278.9
EUROPE TOTAL Male3166.03.39083245316313.415611.4
* For each country, weighted means were calculated for each nutrient by multiplying the male/female mean for each age group by the number of men/women in that age group, then dividing the total by the total number of men/women in the country in question. For each nutrient regional weighted means were calculated by multiplying the male/female mean for each country by the total national population [16], adding this figure for each country and dividing by the total sum of the national populations in that region. For each nutrient total European weighted means were calculated by multiplying the male/female mean for each age country by the total national population [16], adding this figure for each country and dividing by the total sum of the national populations in all three European regions. ** Figures for Spain are based on median rather than mean values.

Share and Cite

MDPI and ACS Style

Rippin, H.L.; Hutchinson, J.; Jewell, J.; Breda, J.J.; Cade, J.E. Adult Nutrient Intakes from Current National Dietary Surveys of European Populations. Nutrients 2017, 9, 1288. https://doi.org/10.3390/nu9121288

AMA Style

Rippin HL, Hutchinson J, Jewell J, Breda JJ, Cade JE. Adult Nutrient Intakes from Current National Dietary Surveys of European Populations. Nutrients. 2017; 9(12):1288. https://doi.org/10.3390/nu9121288

Chicago/Turabian Style

Rippin, Holly L., Jayne Hutchinson, Jo Jewell, Joao J. Breda, and Janet E. Cade. 2017. "Adult Nutrient Intakes from Current National Dietary Surveys of European Populations" Nutrients 9, no. 12: 1288. https://doi.org/10.3390/nu9121288

APA Style

Rippin, H. L., Hutchinson, J., Jewell, J., Breda, J. J., & Cade, J. E. (2017). Adult Nutrient Intakes from Current National Dietary Surveys of European Populations. Nutrients, 9(12), 1288. https://doi.org/10.3390/nu9121288

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop