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The diet of the DutchResults of the Dutch National Food Consumption Survey 2012-2016

0122

93 Committed to health and sustainability

Published by

National Institute for Public Healthand the Environment, RIVMP.O. Box 1 | 3720 BA BilthovenThe Netherlandswww.rivm.nl/en

September 2020

RIVM report 2020-0083

C.T.M. van Rossum | E.J.M. Buurma-Rethans | C.S. Dinnissen | M.H. Beukers | H.A.M. Brants | A.L.M. Dekkers | M.C. Ocké

The diet of the Dutch Results of the Dutch National Food Consumption Survey 2012-2016

RIVM report 2020-0083 C.T.M. van Rossum et al.


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Colophon

© RIVM 2020 Parts of this publication may be reproduced, provided acknowledgement is given to: National Institute for Public Health and the Environment, along with the title and year of publication.

DOI 10.21945/RIVM-2020-0083

C.T.M. van Rossum (author), RIVM E.J.M. Buurma-Rethans (author), RIVM C.S. Dinnissen (author), RIVM M.H. Beukers (author), RIVM H.A.M. Brants (author), RIVM A.L.M. Dekkers (author), RIVM M.C. Ocké (author), RIVM

Contact: Caroline T.M. van Rossum Voeding, Preventie en Zorg\Voeding en Gezondheid [email protected] or [email protected]

This investigation has been performed by order and for the account of Ministry of Health, Welfare and Sports within the framework of 5.4.1. Monitoring food consumption in the domain of Nutrition and Health. The study was co-supported by the European Food Safety Authority, under contract CFT/EFSA/DCM/2012/01-CT02 ‘Support to national dietary surveys in compliance with the EFSA Guidance on General principles for the collection of national food consumption data in the view of a pan-European dietary survey’.

Published by: National Institute for Public Health and the Environment, RIVM P.O. Box 1 | 3720 BA Bilthoven The Netherlands www.rivm.nl/en

mailto:[email protected]:[email protected]:[email protected]:[email protected]://www.rivm.nl/en


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Synopsis

The diet of the Dutch Results of the Dutch National Food Consumption Survey 2012-2016

The Dutch National food consumption survey 2012-2016 provides insights into the amount of food and drink consumed. The survey also indicates the changes in consumption, since the previous survey in 2007-2010. Information about food consumption in the Netherlands is available on the website https://www.wateetnederland.nl. This report describes the survey method, results and discussion in more detail, addressing an audience of international scientists and policy makers. Moderate improvement The Dutch diet has improved somewhat in recent years. For example, the Dutch have started to eat more fruit and they also seem to eat more vegetables. They also eat less meat and drink less sugar-containing drinks. Yet there is still much to be gained in health because most Dutch people do not adhere to the Guidelines for a healthy diet. If the positive developments continue, this can help prevent obesity and chronic diseases. Nutrients The intake of carbohydrates, proteins, unsaturated fatty acids and trans fatty acids in the Netherlands met the recommendations. However, high intakes of alcohol, sodium, total fat, and saturated fatty acids and low intake of dietary fibre were observed. Certain age groups have low intakes of some minerals and vitamins, such as vitamin A and calcium. There are no concrete indications yet that these low intakes are worrying from a public health point of view. An exception to this is vitamin D for which about half of the women aged 50+ and one in five men aged 70+ complied with the recommendation to take vitamin D supplements. A low vitamin D intake at older age is associated with a higher risk for bone fractures. Population differences In general, women, people of older age, people who are not overweight and the better educated follow the guidelines better than men, young adults and the lower educated. There are no clear differences between regions and between cities and rural areas. Use of the food consumption survey The RIVM has mapped the diet of more than 4000 children and adults. With this data, policymakers and professionals can work on healthy nutrition and sustainable and safe food, product innovation, public information and nutritional research. Keywords: food consumption survey, foods, children, adults, nutrients, changes, food-based dietary guidelines, GloboDiet

http://www.wateetnederland.nl/


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Publiekssamenvatting

Wat eet en drinkt Nederland? Resultaten van de Nederlandse voedselconsumptiepeiling 2012-2016 De Nationale Voedselconsumptiepeiling 2012-2016 laat zien hoeveel en wat mensen in Nederland eten en drinken. De peiling geeft ook aan wat daarin is veranderd sinds de vorige peiling in 2007-2010. Resultaten over deze peiling zijn al eerder gepubliceerd op www.wateetnederland.nl. Dit Engelstalige rapport beschrijft en bediscussieert de onderzoeksmethode en resultaten in detail. Het is bedoeld voor (inter)nationale wetenschappers en professionals. Voorzichtige verbetering De afgelopen jaren is het Nederlandse voedingspatroon voorzichtig verbeterd. Zo zijn Nederlanders meer fruit gaan eten en lijken ze ook meer groenten te eten. Verder eten ze minder vlees en drinken ze minder suikerhoudende dranken. Toch is er nog veel gezondheidswinst te behalen omdat de meeste Nederlanders zich niet aan de Richtlijnen goede voeding houden. Als de positieve ontwikkelingen doorgaan, kan dit helpen om overgewicht en chronische ziekten te voorkomen. Voedingsstoffen Nederlanders krijgen voldoende koolhydraten, eiwitten, onverzadigde vetzuren en niet te veel transvetzuren binnen. Wel drinken ze te veel alcohol en krijgen ze te veel zout, te veel vet en verzadigde vetzuren binnen, en te weinig voedingsvezels. Bepaalde leeftijdsgroepsgroepen krijgen van sommige mineralen en vitamines weinig binnen, zoals van vitamine A en calcium. Er zijn geen concrete aanwijzingen dat dit zorgelijk is voor hun gezondheid. Een uitzondering hierop is vitamine D. Daarvan neemt maar ongeveer de helft van de vrouwen van 50+ en een op de vijf mannen van 70+ voldoende vitamine D-supplementen in. Oudere mensen met een tekort aan vitamine D hebben een groter risico op botbreuken. Bevolkingsverschillen Over het algemeen volgen vrouwen, mensen met hogere leeftijd, mensen zonder overgewicht en hoger opgeleiden beter de richtlijnen dan mannen, jongvolwassenen en lager opgeleiden. Er zijn geen duidelijke verschillen tussen regio’s en tussen steden en landelijk gebied. Gebruik van de voedselconsumptiepeiling Het RIVM bracht het voedingspatroon van ruim 4000 kinderen en volwassenen in kaart. Met deze gegevens kunnen beleidsmakers en professionals werken aan gezonde voeding en duurzaam en veilig voedsel, productinnovatie, voorlichting en voedingsonderzoek. Kernwoorden: voedselconsumptiepeiling, voedingsmiddelen, voedingsstoffen, kinderen, volwassenen, veranderingen, voedingsrichtlijnen, GloboDiet



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Contents

List of abbreviations — 7

Summary — 11

1 Introduction — 13 1.1 Monitoring food consumption — 13 1.2 DNFCS-core survey 2012-2016 — 14 1.3 Outline of the report and other publications of DNFCS 2012-2016 — 14

2 Methods — 17 2.1 Study population and recruitment — 17 2.2 Data collection and data handling — 17 2.3 Data analyses and evaluation — 27

3 Study population — 33 3.1 Introduction — 33 3.2 Key findings — 33 3.3 Response — 33 3.4 Representativeness of the study population — 37

4 General dietary characteristics — 43 4.1 Introduction — 43 4.2 Key findings — 43 4.3 Meal patterns — 43 4.4 Special diet or eating habits — 46 4.5 Discretionary salt use — 46 4.6 Dietary supplements — 47

5 Food and drink — 51 5.1 Introduction — 51 5.2 Key findings — 51 5.3 Food groups — 51 5.4 Consumption by eating occasions and place of consumption — 65 5.5 Differences by population subgroups — 70 5.6 Comparison with previous survey — 75

6 Evaluation of food consumption with the 2015 Dutch dietary guidelines of the Health Council — 79

6.1 Introduction — 79 6.2 Key findings — 80 6.3 Adults — 81 6.4 Children — 96 6.5 Differences by subgroups of adults — 96 6.6 Consumption by adults in 2015-2016 compared to 2012-2014 — 99

7 Macronutrients — 101 7.1 Introduction — 101 7.2 Key findings — 101 7.3 Intake of macronutrients — 102 7.4 Sources of macronutrients — 143


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7.5 Intake of macronutrients by eating occasions and place of consumption — 144

7.6 Differences by population subgroups — 146 7.7 Comparison with previous survey — 149

8 Micronutrients — 153 8.1 Introduction — 153 8.2 Key findings — 153 8.3 Intake of vitamins — 154 8.4 Intake of minerals and trace elements — 186 8.5 Sources of micronutrients — 213 8.6 Intake of micronutrients by eating occasions and place of

consumption — 215 8.7 Differences by population subgroups — 218 8.8 Comparison with previous survey — 222

9 Discussion — 227 9.1 Introduction — 227 9.2 Main findings — 227 9.3 Methodological aspects — 228 9.4 Follow up — 233 9.5 Conclusions — 235

References — 237

Acknowledgement — 243

Appendices — 245 Appendix A List of experts — 246 Appendix B Food groups Dutch dietary guidelines — 247 Appendix C Antropometric and lifestyle characteristics by age and gender groups — 250 Appendix D Dietary characteristics by age and gender groups — 254 Appendix E Food consumption by four age and gender groups — 268 Appendix F Food consumption by 16 age and gender groups — 281 Appendix G Consumption of food groups mentioned in the dietary guidelines 2015 — 284 Appendix H Energy and macronutrients — 334 Appendix I Minerals and vitamins — 345 Appendix J Comparison of iodine and salt with previous survey — 384


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List of abbreviations

AI Adequate intake ALA Alpha-linoleic acid AR Estimated Average Requirement BMI Body Mass Index CBS Statistics Netherlands (Centraal Bureau voor de

Statistiek) DHA Docosahexaenoic acid DNFCS Dutch National Food Consumption Survey DRI Dietary Reference Intake EAR Estimated Average Requirement EFSA European Food Safety Authority EPA Eicosapentaenoic acid EPIC European Prospective Investigation into Cancer and

nutrition GR Health Council of the Netherlands (GezondheidsRaad) IARC International Agency for Research on Cancer IOM US Institute of Medicine Kantar Dutch market research agency LA Linoleic acid ALA Alfa linoleic acid MET Metabolic Equivalent of Task; a physiological measure

expressing the energy cost of physical activities is defined as the ratio of metabolic rate (and therefore the rate of energy consumption) during a specific physical activity and a reference metabolic rate

NNGB The Dutch Standard for Healthy Exercise (Nederlandse Norm Gezond Bewegen)

PAL Physical Activity Level PRI Population Reference Intake RDA Recommended Dietary Allowance RIVM Dutch National Institute for Public Health and the

Environment (Rijksinstituut voor Volksgezondheid en Milieu)

SFA Saturated fatty acid SNAQ Short Nutritional Assessment Questionnaire SPADE Statistical Program to Assess Dietary Exposure SQUASH Short QUestionnaire to ASsess Health enhancing

physical activity TNS Nipo Former name of Kantar Dutch market research agency UL Tolerable Upper intake Level GloboDiet food groups are indicated with the following shorter term: Potatoes 01. Potatoes and other tubers Vegetables 02. Vegetables Legumes 03. Legumes Fruits, nuts, olives 04. Fruits, nuts and seeds, olives Dairy (products) 05. Dairy products and substitutes Cereal (products) 06. Cereals and cereal products Meat (products) 07. Meat, meat products and substitutes Fish and shellfish 08. Fish, shellfish and amphibians

https://en.wikipedia.org/wiki/Physiologicalhttps://en.wikipedia.org/wiki/Exercise


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Egg (products) 09. Eggs and egg products Fats and oils 10. Fats and oils Sugar and confectionery 11. Sugar and confectionery Cakes and sweet biscuits 12. Cakes and sweet biscuits Non-alcoholic beverages 13. Non-alcoholic beverages Alcoholic beverages 14. Alcoholic beverages Sauces and seasonings 15. Sauces and seasonings Stocks 16. Stocks Miscellaneous 17. Miscellaneous Savoury snacks 18. Savoury snacks


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Summary

The aim of the Dutch policy on health and diet is to facilitate a healthy lifestyle in the Dutch society.1 A balanced diet in the population contributes to the prevention of morbidity from conditions such as cardiovascular diseases, cancer, diabetes type 2, and obesity. Moreover, a healthy diet includes a sustainable diet and ‘safe’ foods with no adverse effects on health due to the presence of micro-organisms, residues and contaminants. The Dutch national food consumption surveys conducted by the RIVM provide insights into the amount of food and drink consumed, into the consumption by place and by eating occasion, and into the changes in the consumption of selected food (groups) since the previous survey. This data enables policymakers and health professionals to achieve healthy, sustainable and safe food, food product innovation, and to conduct research on education and nutrition. Information about these surveys are available on the website https://www.wateetnederland.nl). The latest survey was conducted in 2012-2016, and more than 4,000 Dutch children and adults aged 1-79 participated. The data was collected by means of two non-consecutive 24-hour recalls in concordance with the EFSA Guidance for the collection of national food consumption data. This background report describes the survey method, results and discussion in detail, and addresses international scientists and policy makers. The main nutritional conclusions are: Foods As mentioned on the website, in recent years, there has been a cautious improvement in the Dutch diet. The Dutch have started to eat more fruit, eat less meat (including red and processed meat), fat, sugar and sweets, and drink less sugary and alcoholic drinks. These changes can contribute to the prevention of chronic diseases such as cardiovascular diseases, diabetes and certain forms of cancer. Despite the small improvements, a lot of potential health gain is lost because only a few Dutch people meet the Dutch Guidelines for a healthy diet. Particularly the consumption of vegetables, fruit, unsalted nuts, and legumes should increase, and the consumption of sugary drinks and salt should decrease, both in adults and in children. Nutrients As a consequence of the food consumption pattern, the intake of carbohydrates, proteins, unsaturated fatty acids and trans fatty acids in the Netherlands met the recommendations. However, high intakes of alcohol, sodium, total fat, and saturated fatty acids and low intake of dietary fibre were observed. The intakes of several micronutrients were sufficient. Although for some vitamins and minerals low intakes were observed in some age-gender groups, there are no concrete indications that these low intakes are



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worrying from a public health point of view. An exception to this is vitamin D, for which about half of the women aged 50+ and one in five men of 70+ complied with the recommendation to take vitamin D supplements. It is known that a low vitamin D intake at older age is associated with a higher risk for bone fractures. Population subgroups Adherence to the Dutch dietary reference values varied by subgroups of the population. Overall food consumption of women, older adults, those without overweight and higher educated people consumed food and drink more in line with the recommendations, compared to men, younger adults and people with a lower educational level. Differences were observed for other population subgroups, though not consistently in the direction of more or less healthier food consumption patterns.


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1 Introduction

1.1 Monitoring food consumption The aim of the Dutch policy on health and diet is to facilitate a healthy lifestyle in Dutch society.1 A balanced diet in the population contributes to the prevention of morbidity from conditions such as cardiovascular diseases, cancer, diabetes type 2, and obesity. Moreover, a healthy diet includes a sustainable diet and ‘safe’ foods with no adverse effects on health due to the presence of micro-organisms, residues and contaminants. Monitoring food consumption forms the basis of nutrition and food policy.1 Food consumption surveys provide insights into a population’s consumption of foods and into dietary changes. Combining these data with information on foods, the intake of macro and micronutrients, exposure to potentially harmful chemical or microbiological substances, the environmental impact of the diet can be established. Nutritional status monitoring provides important complementary information for nutrition policy2 development. Furthermore, food consumption surveys provide useful information for nutrition education programmes and scientific research in the field of nutrition and health, and stimulate healthier food development. Data on food consumption and nutritional status of the general Dutch population and of specific groups in that population have been collected periodically since 1987 in the Dutch National Food Consumption Surveys (DNFCSs). Since 1998, the designs and methods used in the dietary monitoring system have been revised.2, 3 Since 2003, the data have been collected in a comparable way. The current dietary monitoring system consists of three modules:

• Module 1 is the core food consumption survey among the general population. In this module the method is in accordance with the EFSA European guidance for harmonised food consumption data in European Union member states.4

• Module 2 focuses on the nutritional status of the general population by measuring specific vitamins and minerals in blood and urine.

• Module 3 includes additional research on specific topics. Depending on policy needs, specific dietary issues can be studied. Examples of this are monitoring of dietary habits or biomarkers in specific groups such as young children5, older adults6, persons with a non-western migration background7, infants or pregnant women, and monitoring consumption of specific foods such as energy drinks.8

Monitoring lifestyle in the Netherlands. The food consumption survey is part of the Lifestyle Monitor. The Lifestyle Monitor9 collects annual data on lifestyle-related themes including smoking, alcohol and drug use, exercise, and nutrition, and additional surveys are conducted to collect more detailed data. The annual data is collected with the so-called Health Survey. The food


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consumption survey is one of these additional surveys. In general, the food consumption survey provides a better overview of food consumption, but is performed among less people than the Health survey.

1.2 DNFCS-core survey 2012-2016 In the four years from November 2012 to January 2017, food consumption data among the general Dutch population was collected in the DNFCS 2012-2016. This survey included children and adults aged 1-79, living in the Netherlands. This survey is part of module 1 of the Dutch food monitoring system. The main aim of DNFCS 2012-2016 was to gain insights into the diet of children and adults aged 1-79 living in the Netherlands and to establish:

• the consumption of food groups; • the use of dietary supplements; • the percentage of adults that met the 2015 Dutch dietary

guidelines; • the intake of energy and nutrients from food and drink and the

percentage of children and adults that met the recommendations on energy and nutrients;

• the total intake of nutrients from food, drink and dietary supplements and the percentage of children and adults that met the recommendations;

• the place and moment of consumption of food and drink, energy and nutrients;

• the diet by subgroups of the population, for example subgroups based on socio-demographic factors;

• the changes in food consumption in the last decade. In addition, the DNFCS 2012-2016 dataset is suitable for national and international research questions on food safety, food environmental aspects, for public health programmes, and for scientific nutritional research. DNFCS 2012-2016 was authorised by the Dutch Ministry of Health, Welfare and Sport (VWS) and coordinated by the Dutch National Institute for Public Health and the Environment (RIVM). Part of the work was subcontracted to other organisations:

• Data was collected by the market research agency Kantar (former TNS NIPO; Amsterdam, the Netherlands).

• Software for 24-hour dietary protocols (GloboDiet©, former EPIC-soft©) was provided by the International Agency for Research on Cancer (IARC, Lyon, France).

An Expert Committee (see Appendix A) advised the Ministry of VWS on the scientific aspects of the survey during planning, data collection, data analyses, and result reporting.

1.3 Outline of the report and other publications of DNFCS 2012-2016 The main results of the food consumption survey are available on the DNFCS website10 (https://www.wateetnederland.nl), and in more detail in tables and several publications (https://www.wateetnederland.nl/publicaties-en-datasets).

http://www.wateetnederland.nl/http://www.wateetnederland.nl/file://alt.rivm.nl/data/Uitgeverij/1.%20Orders%20Communicatieloket/9%20Rapporten/012001%20tot%20012500%20rapporten%20verzameld/012293%20rap%202020-0083%20st/www.wateetnederland.nl/publicaties-en-datasetsfile://alt.rivm.nl/data/Uitgeverij/1.%20Orders%20Communicatieloket/9%20Rapporten/012001%20tot%20012500%20rapporten%20verzameld/012293%20rap%202020-0083%20st/www.wateetnederland.nl/publicaties-en-datasets


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The website also includes general information on the DNFCS as well as on the conditions and procedure for obtaining the DNFCS databases. It is also possible to receive newsletters by e-mail in which the reader is notified of newly published topics. See https://www.rivm.nl/abonneren/nieuwsbrief-voeding to subscibe for this newsletter. In addition to the website, this report describes background information of the DNFCS 2012-2016. It descibes the survey methods (Chapter 2), participant response data and characteristics (Chapter 3), characteristics of the diet (Chapter 4), and the consumption of food groups, per day and by place and food consumption moment (Chapter 5). In Chapter 6, food consumption is described and compared with the 2015 food-based dietary guidelines. Chapters 7 and 8 report on the intake of energy and macronutrients, and micronutrients. In all chapters, we reflect on changes in consumption and intake in the last decade. Finally, in Chapter 9, the findings are discussed.

https://www.rivm.nl/abonneren/nieuwsbrief-voeding


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2 Methods

2.1 Study population and recruitment The target population consisted of people living in the Netherlands aged 1-79; pregnant and lactating women were not included. Institutionalised people were also excluded because of their reduced freedom in food choice. Kantar TNS drew respondents from representative consumer panels; they participate in all types of surveys and were not specifically selected on dietary characteristics. The study participants had not been involved in any other type of food consumption survey in the previous four years. Only one person per household was permitted to participate. In addition, the panels only included people with adequate command of the Dutch language. The DNFCS Core Survey 2012-2016 data were collected from November 2012 to January 2017. Per period of four weeks, age and gender stratified samples (16 subgroups) were drawn. These groups were in line with those used by the Health Council in the dietary reference intakes. The survey population was intended to be representative within each of the 16 age categories regarding age and gender, region, degree of urbanisation, and educational level (or the educational level of the parents/caretakers for children aged up to 18 when living with their parents/caretakers). These characteristics were known to Kantar TNS. Therefore, the study population was monitored on these characteristics during recruitment and, if necessary, the sampling was adjusted on these factors. During data collection, 6,733 persons aged 1-79 were invited to participate in the study, of whom 4,313 completed the data collection. The survey consisted of 16 age and gender groups. The aim was to obtain information on 260 persons per age gender group, except for children aged 1-3 where the target was 350 boys and 350 girls. Due to the study design, children were overrepresented. More information about the response is presented in section 3.3. Participants received an incentive bonus (NIPOints to be exchanged for a gift card or coupon). The amount varied between 20 and 57 Euro. For children aged up to 9, both the parent/caretaker and the child received an incentive; the parents/caretaker received NIPOints, the child received a present.

2.2 Data collection and data handling 2.2.1 Overview of data collection

The Utrecht University Medical Ethical Review Committee evaluated that the study was not subject to the Medical Research Involving Human Subjects Act (WMO) of the Netherlands (reference number 12-359/C). Medical-ethical review was therefore not needed. The market research agency invited selected people to participate in the study with an invitation letter, an information leaflet, and a reply card. Shortly after this information was sent, persons received an e-mail with a web link to


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the digital version of the reply card. Those who agreed to participate were sent a questionnaire, whenever possible a digital version. The dietary assessment was based on two non-consecutive 24-hour dietary recalls. The logistics of collecting dietary information and anthropometric information differed by age group (See Figure 2.1).

• For children aged 1-8, the first 24-hour dietary recall was performed at home with one of the parents/caretakers. Children aged 4-8 were present at the interview. During this home visit, both the child’s height and weight were measured (see section 2.2.4). The second 24-hour dietary recall was conducted by telephone. The day before the interviews, parents/caretakers completed a food diary for their child in order to cover any consumption at day-care, school or elsewhere. Instructions for this were given by telephone by the interviewers. The food diary formed the input for the 24-hour dietary recall.

• For children aged 9-15, the two 24-hour dietary recalls were carried out by means of two face-to-face interviews during home visits. The visits were scheduled with a parent or caretaker; the interviews were conducted with the child in their presence. During the first visit, both height and weight were measured (see section 2.2.4).

• Participants aged 16-70 were interviewed twice by telephone, unannounced. Height and weight were self-reported by the respondent.

• Participants aged 71-79 were asked to fill in a food diary on two specified days, prior to the interview days. Instructions were given by telephone. The day after the first registration of consumption in the food diary, a face-to-face interview was carried out at a home visit. The completed diary was used as a memory aid. During the home visit, both weight, arm circumference and waist circumference were measured (see section 2.2.4). For practical reasons, height was not measured because not all respondents were able to stand upright and due to the difficulties of assessing and evaluating the BMI in this age category. If possible, the second 24-hour dietary recall interview was conducted by telephone. Otherwise, a second home visit was arranged.

2.2.2 Panel characteristics

The market research agency used household background information (panel characteristics) on birth date, the place of residence by urbanisation level, region, and educational level during recruitment to strive to attain the best achievable representativeness. The age of the respondent was defined as the age at the first 24-hour recall day. The region classes were based on the Nielsen CBS division: northern, eastern, southern, and western regions (including the three largest cities Amsterdam, Rotterdam and The Hague). The degree of urbanisation was divided into extremely urbanised (2500 or more addresses/km2), strongly (1500-2500 addresses/km2), moderately (1000-1500 addresses/km2), hardly (500-1000 area addresses/km2), and not urbanised (fewer than 500 addresses/km2).


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Figure 2.1 Overview of data collection. The educational level concerned the participants’ highest completed educational level or, in case of participants aged under 19, that of the head of household. Educational level was categorised into low (primary education, lower vocational education, advanced elementary education), middle (intermediate vocational education, higher secondary education) and high (higher vocational education and university).

2.2.3 General and lifestyle questionnaire The participants – or their parents/caretakers in case of young children up to the age of 12 – completed a questionnaire either on paper or online via Kantar TNS website; 98% of the participants used the online questionnaire. The questions covered various background factors such

STEP 1 Request to participate (by post and e-mail)

STEP 2 Questionnaire (online/paper)

STEP 3 1st 24-hour recall Anthropometric measures

STEP 4 2nd 24-hour recall (after 2 to 6 weeks)

1 to 8 year-olds Diary 1st 24-hour recall at home with caretaker (4-8 years in presence of child) Measurement of height and weight

9 to 15 year-olds 1st 24-hour recall at home in presence of caretaker Measurement of height and weight

16 to 70 year-olds 1st 24-hour recall by telephone Self-reported height and weight

71 to 79 year-olds Diary 1st 24-hour recall at home Measurement of weight, waist and upper arm circumference

1 to 8 year-olds Diary 2nd 24-hour recall by telephone with caretaker

9 to 15 year-olds 2nd 24-hour recall at home in presence of caretaker

16 to 70 year-olds 2nd 24-hour recall by telephone

71 to 79 year-olds Diary 2nd 24-hour recall if possible by telephone, otherwise at home


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as educational level, working status, native country, family size, various life style factors, such as patterns of physical activity, smoking, and use of alcoholic beverages. They also covered general dietary characteristics such as special diets and eating habits, breakfast use, food frequencies of fruit, vegetables, fish, and dietary supplements, and the use of salt during preparation of food or at the table. Five different age-specific questionnaires were used, taking into account the different age groups’ way of life (school, work). Thus, the questionnaires differed for children aged 1-3, 4-11, and 12-18, and for adults aged 19-70 and 71-79. Copies of the questionnaires (in Dutch) can be downloaded from the DNFCS website.10 A small number of people completed the questionnaire for a different age category than the one they finally belonged to in the study; the age categories used in this report were based on the participant’s age at the date of the first interview, whereas the questionnaires were sent prior to the interviews. An internal protocol was used to check data from the questionnaires for unrealistic values, inconsistencies, and missing values. If possible, values were checked with the participant or market research organisation and updated. Regarding working status, native country, and educational level, the information from the questionnaire was combined and/or aggregated into fewer categories. Working status was aggregated into employed (paid work or self-employed) or unemployed. For children living with parents or caretakers, information on both caretakers was used and combined into two categories: ‘all carers (1 or 2) are working’ or ‘at least one carer is not working’. A category was included for incomplete information. Native country of the parents was used to determine migration background.11 A distinction was made between Dutch (both parents were born in the Netherlands), non-Western, and Western migration background (Europe, United States, Australia); in the latter categories, at least one parent was born abroad. Although educational level was available in the panel characteristics, a question on this item was also added to the general questionnaire. The highest educational level of the respondent was defined on the answer in the general questionnaire. In case of children, that of the highest educated parent or caretaker was used. Three categories were distinguished: low, middle and high (see section 2.2.2). This item was used for the weighting factor and subgroup analyses. For adults (aged 19-79) the information on physical activity was obtained according to the Squash (Short QUestionnaire to ASsess Health enhancing physical activity) questionnaire.12 Questions on physical activity included activities at work/school, household activities, and activities during leisure time. Respondents were asked to state per activity on how many days they performed the activity, how many hours per day, and what the intensity of the activity was. In the questionnaire for those aged 71-79, the questions on activities during work were left out. Based on the information in the questionnaires, times spent on physical activities were combined (based on the Lifestyle Monitor)9 and evaluated using the guideline on Dutch Standard for Healthy Exercise (NNGB) and the fitness standard.13 For the NNGB, adults aged up to 55


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should have at least 30 minutes of moderate intensive physical activity (≥4 MET) on at least five days a week. For those aged 55 or above, the intensity of physical activity may be lower (≥3 MET). To meet the fitness standard, they should have at least 20 minutes of heavy intensive activity at least three times a week. For the youngest age categories (aged 1-18) the questionnaires in the Dutch Public Health monitor were used.14 These include questions on activities more relevant for these age categories, for example, watching television, computer time, sports at school, walking or cycling to school, sport club activities, and playing outdoors. Based on this information, different categories were used to describe physical activity in this age group: inactive (7 hours/week).15, 16 Other information on lifestyle characteristics concerned smoking and alcohol consumption. Information on these topics together with anthropometry were used in this report to describe the study population and its representativeness, as the questions on these topics were also used in other national life style monitors. The smoking status was divided into three categories: ‘current smoking of at least one cigarette, cigar or pipe a day’, ‘use of tobacco in the past’ and ‘never-smokers’. Information on consumption of alcoholic drinks (from 12 year-olds on) was only used to classify a person as a user or non-user of alcoholic beverages. Usual eating habits were related to having breakfast and dietary habits or restrictions. Frequency of having breakfast was questioned in number of days a week. The type of special diets (e.g. diabetes, energy restricted, cow’s milk protein free, lactose restricted) and special eating habits (e.g. vegetarian, vegan, macrobiotic, anthroposophical) could be filled in. Vegetarian, vegetarian without fish, vegan, macrobiotic were grouped to define those with an eating habit without meat. The questions on the consumption frequency of dietary supplements distinguished between the use of different supplements in the winter and the rest of the year. In this report, a respondent was assumed to be a user if he or she used supplements in the winter and/or in the rest of the year. In addition, the frequency of all supplements containing vitamin D (vitamin D, vitamin A/D, multivitamins and multivitamin/multimineral supplements) was grouped to define a person as a user or non-user of vitamin D containing supplements. The question on the use of salt (including table salt, herb mixes with salt, but not salty seasonings such as soy sauce, bouillon) distinguished whether salt was added in home–prepared meals and/or at the table.

2.2.4 Height, body weight, upper arm and waist circumferences During the first home visits, body weight and height of 1-15 year-olds were measured once. Participants aged 16-70 reported their self-measured height and weight during the first 24-hour dietary recall interviews by telephone. For the 71-79 year-olds, body weight, upper arm circumference, and waist circumference (two times) were measured during the home visits. Height was not measured for this age category, given the difficulties in measuring height in older adults. All


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measurements were taken or reported with an accuracy of 0.1 kg for body weight, and 0.1 cm for height and circumferences. Body mass index (BMI) was calculated per person as the body weight divided by the height squared (kg/m2). Subsequently, the BMIs were evaluated and classified using age and gender specific cut-off values. The categories were: seriously underweight, underweight, normal weight, overweight, and obesity. Cut-off points for children are lower than those for adults.17 For 71-79 year-olds, mid-upper arm circumference was used as indicator of thinness instead of BMI. A mid-upper arm circumference


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complete a 24-hour dietary recall was 45 minutes. The GloboDiet interviews comprised the following:

• General information on the participant and recall day, including height and body weight, special eating habits or special diets on the recalled day and special information on the recall day itself – such as a feast day or holiday, or any illnesses.

• A quick list for each food consumption moment – including the time, place, and main foods and recipes consumed. For young children and older adults, quick list items were entered according to the information in the food diaries.

• Description and quantification of foods and recipes reported in the quick list. Food description consisted of a further specification of all foods consumed, using facets and descriptors such as preparation method and fat content. Portion sizes of the foods and meals could be quantified in several ways: by means of quantities as shown on photos in the picture booklet provided, or in household measures, units and standard portions, by weight and/or volume, and the proportion of a total recipe. Bread shapes were also used to estimate the amount of spreads. The picture booklet included 61 series of food photographs showing four to six photographs of the food in different amounts.

• The possibility for entering notes with further information. • Intake of dietary supplements.

Quality assurance Regular updates of information and different checks were performed for quality assurance of the interviewers. After the initial three-day training period, refresher training was held twice a year, and a newsletter was sent about every two months. During the two-year study period, the interviewers were asked to record an interview on tape once. These tapes were evaluated by RIVM dieticians and feedback was given to the interviewers. Moreover, the interviewers performed three homework assignments that were corrected by the RIVM dieticians and discussed with the interviewers. During the interviews, various quality checks were carried out within the Globodiet system. These consisted of checks on out of range values, missing quantities, empty food consumption occasions, or easily forgotten foods. In addition, a rough check was made at the nutrient level. The roughly estimated energy and macronutrient intakes were compared with standard requirements calculated for the age and gender of the subject. If possible, the interviewer corrected the data or made a note. In addition to the quality checks during the interview within the Globodiet system, other quality checks were conducted on the data entered. Firstly, notes made by the interviewers during the recall were checked and processed. For example, if a specific food could not be chosen in GloboDiet, this was noted and, based on additional information, this new food was added to the GloboDiet databases. Secondly, several standardised quality checks were performed, such as a check on consumed quantities of powdered foods, missing quantities, and correct use of the household measures (for example, not a heaped


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spoon for fluid food). Furthermore, extreme intakes of nutrients were checked. This check was done using the Grubbs’ statistical method.20

Food groups In this report, foods were classified in two ways: the GloboDiet classification of food groups, and the 2015 Dutch dietary guideline. Globodiet classification The GloboDiet food group classification comprises 18 main groups and 78 subgroups. Of these subgroups, 16 were additionally broken down into 55 sub-subgroups. Altogether 151 GloboDiet food groups (main groups, subgroups and sub-subgroups) were distinguished. In the text, the main GloboDiet food groups are indicated with a shorter term (see Abbreviations). Some mixed dishes were considered as recipes in the GloboDiet programme. This means that the ingredients were classified in the food (sub)groups. For some foods, the food group classification was adapted during data handling. For example, syrups used in diluted beverages were added to the group of ‘Non-alcoholic beverages’ instead of in the food group ‘Sugar and confectionery’. Water as an ingredient used in soups, was added to the food group ‘Stocks’ instead of in the food group ‘Non-alcoholic beverages’. Food groups of the 2015 dietary guidelines Table 2.1 shows the food group classification of the 2015 dietary guidelines (see Appendix B for more detail). Information was derived from the 24-hour dietary recalls unless otherwise specified. Habitual intakes rather than two-day averages were considered for the evaluation (see section 2.3.4 for more details). Energy and nutrient intake The selection of nutrients of interest was based on the relevance for policy makers, availability of dietary reference intakes, and the quality of the data. Energy and nutrient intakes were calculated using an extended version of the Dutch Food Composition Database (NEVO-online 2016)21 and the Dutch Supplement Database (NES) dated 1 January 2018.22 The definitions of the nutrients can be found on the NEVO website.23 In total, 39,433 different food items and 804 dietary supplement items were reported during the data collection; these were linked to 1854 NEVO codes and 802 NES codes. The intake from food was calculated for all presented nutrients. In addition, the intake of micronutrients and fish fatty acids from both food and dietary supplements was calculated. For iodine and sodium, the use of discretionary salt and for iodine also the intake of dietary supplements were taken into account (see section 2.3.5). For several nutrients, the intake was calculated as a percentage of the total energy intake or intake per MJ, or per kg body weight. Place of consumption and food consumption occasions The consumption of food and drink was recorded by place, food consumption occasions, and time. In this report, the different categories for place of consumption were aggregated into the following four


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Table 2.1 Indicators for evaluation of the consumption with the 2015 dietary guidelines24, 25. Guideline Indicator for evaluation

(see Appendix B for more detail)

Cut-off for % that meet guideline in adults

Follow a dietary pattern that involves eating more plant-based and less animal-based food, as recommended in the guidelines.

% plant-based protein of total protein

Eat at least 200 g of vegetables daily

Habitual consumption of vegetables in grams/day

≥200 grams/day

Eat at least 200 g of fruit daily

Habitual consumption of fruit in grams/day

≥200 grams/day

Limit the consumption of red meat, particularly processed meat

Habitual consumption of red meat (processed and unprocessed); Habitual consumption of (red and white) processed meat in grams/day

Take a few portions of dairy products daily, including milk or yogurt

Habitual consumption of dairy (incl. cheese) in grams/day; Habitual consumption of milk and yoghurt in grams/day

Eat legumes weekly % days that legumes were consumed (converted to average number of days/week)

Eat at least 15 g of unsalted nuts daily

Habitual consumption of unsalted nuts in grams/day

≥15 grams/day

Replace refined cereal products by wholegrain products

Habitual consumption of bread and cereal products in grams/day; Habitual consumption of brown and whole grain bread and cereal products in grams/day; % brown and whole grain bread and cereal products of total consumption of bread and cereal products for users

Eat at least 90 g of brown bread, whole meal bread or other wholegrain products daily

Habitual consumption of brown and whole grain bread and cereal products in grams/day

≥90 grams/day


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Guideline Indicator for evaluation (see Appendix B for more detail)

Cut-off for % that meet guideline in adults

Replace butter, hard margarines and cooking fats by soft margarines, liquid cooking fats and vegetable oils

Habitual consumption of total spreads, cooking fat and oils in grams/day; Habitual consumption of soft margarines, liquid cooking fats and vegetable oils; Habitual consumption of butter, hard margarines and cooking fats in grams/day; % of soft margarines, liquid cooking fats and vegetable oils of total fats for users

Eat one serving of fish, preferably oily fish, weekly

Frequency distribution of number of servings/week (food frequency questionnaire); % of fatty fish of total fish consumption.

≥ one serving fish/week

Drink three cups of tea daily

Habitual consumption of black and/or green tea in grams/day

≥450 grams/day (assumption of 1 cup=150 grams)

Replace unfiltered coffee by filtered coffee

Information on unfiltered or filtered is not known.

Minimize the consumption of sugar-containing beverages

Habitual consumption of sugar containing beverages in grams/day

Do not drink alcohol, or no more than 1 glass daily

Frequency distribution of use of alcohol and number of glasses by type of alcoholic drinks on week and weekend days. (information from food frequency questionnaire)

drinking no alcohol or ≤1.0 glass/daya

Limit salt intake to 6 g daily

Habitual intake of salt in grams/day from food and added salt during preparation or at table. (see also paragraph 2.3.5)

≤6 grams/day

Nutrient supplements are not needed, except for people who belong to a group for which supplementation applies

Use of dietary supplements (in general and specific for vitamin D-containing supplements; information from food frequency questionnaire).

% 70-79 year-old men and 50-79 year-old women meeting the advice to take vitamin D supplements.

a ≤1.0 glass/day of all type op drinks as well as ≤1.0 glass/day for each type of drink at a weekday or weekend day


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categories: at home (includes at home and at the home of friends/ family), in a restaurant (includes fast-food, bar/café and self-service restaurant), at school/work, and outside and traveling (includes on the street and car, boat, plane, train). The different food consumption occasions were classified as the three main meals (breakfast, lunch and dinner) and in between main meals (before breakfast, during morning, during afternoon and evening/at night). The main meals were defined according to the time of day, so both lunch (meal around midday) and dinner (evening meal) could consist of a cold or warm meal.

2.3 Data analyses and evaluation Most results were calculated for all 16 age gender group separately. However, for the readability of the chapters the results are described in more aggregated age gender groups or for the whole population. Statistical analyses were performed using SAS, version 9.4. Habitual intake distributions were estimated using SPADE, version SPADE.RIVM_3.2.

2.3.1 Dutch reference population All results were weighted for deviances in the distribution of participants across gender, age groups, region, level of education, urbanisation, season of data collection, and if applicable, for day of the week in order to give results representative for the Dutch population and for all days of the week (aggregated into two weekdays, two weekend days, and one week and one weekend day), and for the season. A weighting factor for each registration day per person was only used for analyses on consumption on consumption days. For children aged up to 18, the educational level of the head of household was used in the weighting. Each respondent was classified into a season based on the day of the first 24-hour recall. For day of the week, the days were aggregated into weekdays and weekend days. Census data from 2014 was used as reference population to derive the survey weights.11

2.3.2 Characteristics of study population and some dietary habits Frequency distributions and means of socio-demographic and dietary characteristics, such as use of breakfast or use of added salt, anthropometry, dietary supplement use, physical activity and smoking were calculated for the 16 separate and the aggregated age gender groups.

2.3.3 Food consumption by GloboDiet classification For the Globodiet classification food groups, the average food consumption over two days was calculated for each participant. From this, the mean consumption in grams per day per food (group) was calculated for each age gender group. As the distributions were skewed, these means should be interpreted with caution. Therefore, the 5th percentile, the median (50th percentile) and 95th percentile of consumption are also given. So, in contrast to the information on the 2015 dietary guidelines food groups (see section 2.3.4), the intake of foods classified in GloboDiet food groups was based on two-day averages rather than habitual intake.


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Additionally, the percentage of consumption days of food groups was also calculated by dividing the number of recalled days on which a food in the food group was consumed by the total number of recalled days. Subsequently the percentage of consumption days was converted into average number of days per week. For instance, if a food was consumed at 50% of the recalled days, we assumed that this food was consumed on 3.5 days per week (50*7/100= 3.5). Moreover, the mean, the 5th percentile, median and 95th percentile of the consumption on the consumption days only were calculated.

2.3.4 Evaluation of food consumption against dietary guidelines The DNFCS 2012-2016 provided two-day dietary consumption data, in other words the observed consumption. However, for many purposes, it is not the observed consumption that is relevant but the habitual (long-term mean) consumption. The variance in the observed consumption comprised both the intra-individual (or day-to-day) variance and the inter-individual (or between subjects) variance. For habitual consumption the intra-individual variance is not relevant. The habitual consumption distribution of food groups in the food-based dietary guidelines was estimated from the observed daily intake by correction for the intra-individual (day-to-day) variance using SPADE (Statistical Program to Assess Dietary Exposure, RIVM).26 Using SPADE, the habitual intake distribution was modelled age-dependently by gender. This resulted in habitual intake distributions by gender for each year of age separately. For the food groups, the mean, median, 5th, 25th, 75th, and 95th percentile of the habitual intake distribution are presented by gender. A two-part model was applied for most food groups mentioned in the dietary guidelines. This model can be used to estimate consumption of food groups consumed episodically.2 In this model the distribution of probability of consumption was modelled separately from the distribution of consumed amounts, before combining the two distributions. As fat, dairy, and cereal products were consumed daily by almost all participants, the one-part model was used for these food groups. The evaluation of the guidelines on the consumption of alcoholic drinks, fish and dietary supplements was based on information from the food frequency questionnaire. Frequency distributions were calculated for the different age gender groups. In addition, for each user of fats and oil, the contribution of soft margarines, liquid cooking fats and vegetable oils as part of the total fats and oils consumption was calculated. This was based on the observed intake. Subsequently, the mean of these contributions was calculated. A similar approach was used for the mean percentage of whole meal bread and grain products as part of the total cereal products. The percentage of fatty fish was estimated based on the total mean intake of fatty fish based on 24-hour recall data as part of the total mean fish consumption (and not based on the individual percentages).


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2.3.5 Evaluation of dietary intake of energy and nutrients against dietary reference values Habitual intake The habitual intake of energy and nutrients was also estimated from the observed daily intake by correction for the intra-individual (day-to-day) variance using SPADE26 (see also section 2.3.4). The results of the habitual intake distribution were presented by means of mean, median and 5th, 25th, 75th, 95th percentiles. The SPADE one-part model was used for most nutrients. For folic acid, a nutrient with relatively more nonconsumers, the habitual intake was calculated using a two-part model in which the distribution of probability of consumption was modelled separately from the distribution of consumption amounts, before combining the two distributions. The habitual intake of micronutrients, dietary fibre and fish fatty acids from both food and dietary supplements was calculated via SPADE using a three-part model. Data from the additional questionnaire on the frequencies of use of dietary supplements in winter and the rest of the year was used in combination with data from the 24-hour recall. The habitual intake of ethanol, iodine and sodium was modelled using the SPADE multi-part model in order to estimate the intake from different food sources. For ethanol, additional data from the lifestyle questionnaire on the use of alcoholic beverages were used to identify the non-users. For sodium, intake from food and discretionary used salt at home was combined (dietary supplements were not taken into account). For iodine, intake from iodine naturally present in foods, industrially added iodised salt to foods, discretionary added iodised salt, and dietary supplements were aggregated. The approach was slightly modified from that of Verkaik27 and Van Rossum.28 Dietary reference values To evaluate the diet, the habitual intake distributions of nutrients were compared to the Dutch dietary reference intakes set by the Health Council29, 30; see Chapters 7 and 8 for the specific reference values used. To determine the proportion of the Dutch population that may be potentially at risk of adverse effects due to excessive intake of a nutrient, the habitual intake distributions were compared to the tolerable upper intake level (UL) for nutrients as set by EFSA.31-35 Age differences In this report the differences by age are described using the terms ‘decrease’ and ‘increase’ by age. This should be interpreted as lower or higher values observed in the older age groups based on cross-sectional data, respectively. Evaluation methods The approach to evaluate the diet differed according to the type of dietary reference value used, as recommended by the US Institute of Medicine (IOM). See text box 2.1. for an explanation of these different


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Text box 2.1 Dietary reference intakes for nutrients and their relation to the probability of health effects following the definitions of the Health Council (www.gezondheidsraad.nl). Dietary Reference Intakes (DRI): refers to a set of reference values for nutrients for use in dietary evaluation. Estimated Average Requirement (EAR): the intake level at which 50% of people would have enough for their own requirements, but the other 50% would not. Average requirements are always relatively strongly substantiated. (in Dutch: ’Gemiddelde behoefte’). Also indicated in international literature with AR. Population reference intake (PRI): level that is considered adequate for virtually everyone in the population group in question. By definition, this reference value is only established if there is sufficient data from scientific research to be able to estimate an average requirement. Accordingly, this also involves relatively strongly substantiation. In theory, the population reference intake is the intake level that is adequate for exactly 97.5% of the group concerned. However, because of uncertainties in the studies on which the average requirements and population reference intakes are based, it is better to express this as ‘virtually’ everyone in the population group in question. (in Dutch: ’Aanbevolen dagelijkse hoeveelheid’). Adequate Intake (AI): a level of intake that can be assumed to meet the needs of virtually everyone in the population group in question. This type of dietary reference value is established if neither the average requirement nor – as a result – the population reference intake can be determined. Adequate intakes are sometimes relatively strongly substantiated and sometimes weakly substantiated. Tolerable Upper intake Level (UL): the highest intake level at which long-term exposure is not expected to produce any adverse health effects. The tolerable upper intake level is not the ideal intake level, as raising intake above the population reference intake or adequate intake, is not expected to produce any further health gains. Moreover, intakes in excess of the tolerable upper intake level are potentially unhealthy. The highest average daily nutrient intake level likely to pose no risk of adverse health effects to almost all individuals in the general population. (In Dutch: ’Aanvaardbare bovengrens van inneming’). types.36 The evaluation of the intake was performed qualitatively or quantitatively depending on the type of dietary reference value:

• When an estimated average requirement (EAR) of a nutrient was available, the habitual intake was evaluated using the EAR cut point approach. The proportion of subjects with inadequate (insufficient) intake was estimated. If this percentage was less than 10%, intake was considered adequate. The cut point approach is inappropriate for the energy intake as this depends on a person’s physical activity. Therefore, the proportion of the population with an inadequate energy intake could not be estimated. For iron values, not all assumptions for the EAR-cut


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point approach were valid; see the results sections for more details.

• If an adequate intake (AI) was available, the inake was evaluated qualitatively. A group with a median intake at or above the AI can generally be assumed to have low prevalence of inadequate intakes. In this study, this is indicated with ‘seems adequate’. If the median was lower than the AI, the adequacy of the diet could not be evaluated (‘no statement’).

• If a tolerable upper intake level (UL) of a nutrient was available, the proportion of the population above the UL was calculated. This proportion represents the part of the population potentially at risk of adverse effects due to excess intake, which does not mean that adverse health effects actually occur. For the proportions presented, the modelling uncertainty is shown as a 95% confidence interval. If the proportion was larger than 2.5%, the intake was considered high (‘high intakes’). If the proportion was lower, the intakes were considered as tolerable.

A comparison of consumption data with dietary reference values can never irrefutably determine whether the intake is adequate/tolerable or not. It can only indicate the probability of inadequate or high intakes. Therefore, in order to find out whether an intake of a particular nutrient is adequate or tolerable, for instance biochemical measurements are needed as additional evidence.

2.3.6 Comparison with previous survey To investigate the change in consumption in the last decade, the mean consumption of main food groups in DNFCS 2012-2016 and that in DNFCS 2007-2010 were compared with each other. As the GloboDiet classification in DNFCS 2012-2016 slightly differed from the classification in DNFCS 2007-2010, all foods in the DNFCS 2007-2010 were reclassified in the 2012-2016 GloboDiet classification. The comparison was made for 9-18 year-olds, 19-50 year-olds, and 51-69 year-olds. These age groups are represented in both surveys. We assumed that the skewness in the distributions did not affect the comparison. Arbitrarily, comparisons are only reported for food groups with an average consumption of more than 25 g/day by the 9-69 year-olds. Differences were statistically tested (F-test using a p-value of 0.05) and differences larger than 7% were assumed to be relevant. For the evaluation of the change in the habitual intakes of nutrients between the two surveys, the 95% confidence intervals of the mean intake and median intake in DNFCS 2012-2016 and that in DNFCS 2007-2010 were compared. For these analyses, the data of 7-69 year-olds were used. In this case the 7-8 year-olds were not excluded because one model was used for all age groups. With no overlap in the confidence intervals and an average decrease or increase of more than 7% compared to the previous survey (about 1% per year), the difference was assumed to be relevant and statistically significant. These calculations were performed with SPADE. These data were also weighted for socio-demographic characteristics, season, and day of the week. Period-specific reference values were used in these comparison


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analyses. As a consequence, the population in 2012-2016 was somewhat higher educated. In addition, to gain insights in the recent changes in habitual intake of the food groups mentioned in the Health Council dietary guidelines, the consumption during the first two years of the data collection was also compared with that during the latest two years of the DNFCS 2012-2016 study.

2.3.7 Sources of nutrients In order to gain insights into the main sources of nutrients, the contribution of each food group to the total energy and nutrient intake on each of the two recall days was calculated for each participant. Dietary supplements were also considered to be one of the sources. Subsequently, the mean contribution of the food groups and the supplements for each person was calculated over the two recall days. Finally, the group mean contribution was calculated by averaging all individual percentage contributions.

2.3.8 Food consumption and intake by place and food consumption occasion The averages of the individual contributions of consumption by food groups or nutrient intake were calculated at various food consumption occasions and places of consumption to the total consumption of food groups or nutrient intake. Place was categorised into two groups: At home and Not at home. Food consumption occasions were classified into the three main meals (Breakfast, Lunch and Dinner) and In between the main meals (see section 2.2.5). The number of separate eating or drinking moments by time and by food consumption occasion was also calculated based on the 24-hour recalls. We did not apply a minimum energy criterion for an eating occasion.

2.3.9 Subgroups of the population The mean food intake was also described for several subgroups of the population. The following factors were investigated: gender, age and gender groups, educational level, body mass index, region and urbanisation (see section 2.2.2 for categorisation of these factors). Only differences in means larger than 10% and statistically significant were assumed to be relevant. The differences across the subgroups were tested for significance using the overall F-test using a p-value of 0.05. In addition, the evaluation of the habitual intake of nutrients and consumption of food groups of the dietary guidelines of the Health Council were performed for the subgroups in the population. Only nutrients with low or high intakes or no statement for the general population were selected. The percentages below an AR or above the UL were calculated for each subgroup. If 95%-confidence intervals of these percentages did not overlap, differences were statistically significant. For those nutrients with an AI, non-overlapping confidence intervals of the medians were considered statistically significant. These confidence intervals were calculated with SPADE bootstrap analyses.26 Due to the complexity of the estimation of the intake of iodine, this was only estimated for age and gender groups.


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3 Study population

3.1 Introduction This chapter presents the response and representativeness of the participants in the DNFCS 2012-2016. The chapter starts by describing the key findings, followed by the response to the recruitment and the representativeness of the study population. The distribution of 24-hour dietary recalls across day of the week and season is given. Furthermore, several socio-demographic, anthropometric and lifestyle characteristics of the study population are described; these are compared to those in other national studies. Data were based on participant information from the completed questionnaires and from information available at Kantar.

3.2 Key findings • The study population consisted of 4,313 respondents. • The response was 65%. • The study population was representative for the population in the

Netherlands regarding age, level of education, region of residence, and for the diet across a calendar year (season and day of the week).

• Based on the comparison on lifestyle characteristics, we observed some differences between the study population and other national studies. However, it is unclear in which direction this may have affected the results.

• By study design, the results are not fully representative for migration background, nor for pregnant and lactating women. Specific food consumption surveys need to be carried out to assess the dietary intake of these groups.

3.3 Response The response to the DNFCS 2012-2016 recruitment is shown in Table 3.1. Of the 6,733 invited people 5,095 were eligible and willing to participate in the study (145 subjects were ineligible, 601 were not reached, and 892 refused to participate). Table 3.1 Response of invitees (DNFCS 2012-2016).

Total Boys/Men Girls/Women n % n % n %

Overall sample 6,733 100 3,462 100 3,271 100 - Ineligible* 145 2 61 2 84 3 Adjusted sample 6,588 100 3,401 100 3,187 100 - Non contacts 601 9 324 10 277 9 - Refusals 892 14 509 15 383 12 - Participants with incomplete material

779 12 402 12 377 12

- Participants with invalid data

3 0 1 0 2 0

- Participants with complete material

4,313 65 2,165 64 2,148 67


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Table 3.2 Response and representativeness on socio-demographic characteristics of participants in DNFCS 2012-2016.

Overall sample Net

sample Weighted

sample

Number % Response

% Number % %

Total 6,588 100 65 4,313 100 100 Gender/Age groupa Boys, 1-3 469 7 74 332 8 2 Girls, 1-3 475 7 74 340 8 2 Boys, 4-8 396 6 63 261 6 3 Girls, 4-8 376 6 68 259 6 3 Boys, 9-13 411 6 63 259 6 3 Girls, 9-13 403 6 65 260 6 3 Boys, 14-18 520 8 52 270 6 3 Girls, 14-18 435 7 58 254 6 2 Men, 19-30 y 510 8 50 260 6 8 Women, 19-30 447 7 58 256 6 8 Men, 31-50 401 6 64 259 6 15 Women, 31-50 369 6 69 264 6 14 Men, 51-70 343 5 77 264 6 14 Women, 51-70 325 5 79 258 6 14 Men, 71-79 351 5 74 260 6 3 Women, 71-79 357 5 72 257 6 4 Educational levelb, c Low 1,764 27 62 815 19 24 Middle 2,739 42 64 1,610 37 43 High 2,073 31 70 1,888 44 33 Data not available 12 0 58 0 0 0 Regionc West 2,922 44 66 1,931 45 45 North 693 11 66 459 11 10 East 1,440 22 66 949 25 21 South 1,533 23 64 974 23 24 Urbanisationc Extremely/ Strongly urbanised 3,115 47 64 1,996 46 48 Moderately urbanised 1,305 20 67 871 20 20 Hardly/not urbanised 2,168 33 67 1,446 34 32

a Age: Age of overall sample was determined at the moment of screening; Age of net sample or weighted sample was determined on the first recall day. b Education: For children (aged 1-18), the highest education level of parents or carers is presented; Education of overall sample was available at the moment of screening from panel information, education of the net sample and weighted sample was determined based on the general questionnaire. c Format of educational level, region and degree of urbanisation is described in section 2.2.2. However, not all 5,095 respondents completed the two 24-hour dietary recalls and the general questionnaire in January 2017 (n=779). For three participants, the data were judged as unreliable. Therefore, the net response of the population of the DNFCS 2012-2016 was 65% (n=4,313 with complete data).


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Table 3.2 presents the response and representativeness of the participants of the DNFCS 2012-2016 by gender, age and socio-demographic characteristics. The response varied most across the age and gender groups. It was the lowest among men aged 19-30 (50%). In children aged 1-3, and women aged 51-70, the response was the highest (74% and 79% respectively). Furthermore, the response was slightly higher among people with a higher educational level (70%) versus lower educated persons (62%), and almost similar by region and urbanisation. Table 3.3.a Distribution of recall days (days of the week) in DNFCS 2012-2016.

Total Boys/

Men Girls/

Women Face to

face Telephone

n=8,626 n=4,330 n=4,296 n=3,386 n=5,240 n % N % n % n % n %

Day of the week Monday 1,328 15 671 15 657 15 484 14 844 16 Tuesday 1,336 15 658 15 678 16 516 15 820 16 Wednesday 1,219 14 603 14 616 14 451 13 768 15 Thursday 1,227 14 614 14 613 14 540 16 687 13 Friday 1,165 14 609 14 556 13 538 16 627 12 Saturday 1,111 13 560 13 551 13 425 13 686 13 Sunday 1,240 14 615 14 625 15 432 13 808 15

Table 3.3.b Distribution of combination of recall days (days of the week) and season in DNFCS 2012-2016.

Total Boys/ Men

Girls/ Women

n=4,313 n=2,165 n=2,148 n % n % n %

Day of the week 1 weekday, 1 weekenda day 1,968 46 992 46 976 45

2 weekdays 1,571 36 777 36 794 37 2 weekend days 774 18 396 18 378 18 Seasonb Spring 1,022 24 511 24 511 24 Summer 992 23 496 23 496 23 Autumn 1,031 24 531 25 500 23 Winter 1,268 29 627 29 641 30

a Weekend day= Friday, Saturday and Sunday b Spring = March, April, May; Summer = June, July, August; Autumn = September, October, November; Winter= December, January, February.


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Table 3.4 Characteristics of Dutch children and adults aged 1-79 (DNFCS 2012-2016), weighted for socio-demographic characteristics and season.

Boys, 1-18

n=1,122

Girls, 1-18

n=1,113

Men, 19-79

n=1,043

Women, 19-79

n=1,035 % % % % Size of household One person 16 20 Two or three persons 27 24 61 57 Four persons 46 47 16 18 Five or more persons 27 29 6 6 Highest educational level of carer(s)/Highest educational levela

Low 11 11 25 31 Middle 44 43 44 41 High 46 46 31 29

Men,

19-70 n=783

Women, 19-70

n=778 Working status Working 68 58 Not working 32 42

Boys, 1-18

n=1,122

Girls, 1-18

n=1,113

Men, 19-79

n=1,043

Women, 19-79

n=1,035 % % % % Working status (of carer(s)b All carers (one or two) are working

72 69

At least one carer is not working

28 31

At least for one carer unknown

0 0

Region West 45 44 44 45 North 10 10 10 10 East 22 23 21 21 South 22 23 24 24 Urbanisation Extremely urbanised 16 16 20 19 Strongly urbanised 29 29 28 30 Moderately urbanised 21 21 20 20 Hardly urbanised 21 22 22 22 Not urbanised 13 12 11 10 Migration background Dutch 92 92 90 92 Western 2 2 3 2 Non-Western 6 6 4 6

a Missing information for 6 men and 5 women aged 19-30 b No information available on working status aged 71 onwards


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3.4 Representativeness of the study population 3.4.1 Distribution across day of the week and season

Tables 3.3.a and 3.3.b show the number and distribution of the recalled days by day of the week and season. Respondents aged 1-15 and those aged 71 or older were visited at least once at home, while respondents aged 16-69 were interviewed by telephone. The distributions of the recalled days by day of the week were almost optimal. The recalled days were fairly equally spread over the year; slightly more interviews were conducted during the winter (29%).

3.4.2 Socio-demographic characteristics Table 3.4 presents several socio-demographic characteristics by age gender group. Three-quarters of the children lived in households of four people or more. For 11% of the children, the highest educational level of the carers was low, whereas 46% of the children had at least one carer who was highly educated. For more than two-thirds of the children, both carers were working. Most of the children were living in the western part of the Netherlands (about 45%). About 45% lived in extremely or strongly urbanised areas, whereas about 12-13% lived in non-urbanised areas. The study population aged under 19 included 6% with a non-Western migration background. For adults, about 60% lived in households of two to three people. One in four men and one in three women were low-educated. About 30% of the adults were higher educated. About 45% lived in the western part of the Netherlands and in extremely or strongly urbanised areas. About 5% of the adults had a non-Western migration background. 68% of men aged 19-70 and 58% of the women in that age group were working. The study design ensured a representative distribution among region, and urbanisation and educational level within all age-gender groups. Small deviances in the distributions occurred compared to the targets for region, urbanisation and level of education and based on national figures from CBS11 (see Table 3.2; personal communication with CBS). The results were weighted for these deviances in age gender and the other factors in order to give representative results for the Dutch population. However, among the nationwide population, the percentage of people with a non-western background is about twice as high11 as in this study.

3.4.3 Anthropometry Mean self-reported and measured height and body weight and an evaluation of the body mass index (BMI) are presented in Table 3.5.a for children and adults aged up to 70. Table 3.5.b shows the mean measured weight, waist and upper arm circumferences for 71-79 year-olds. The percentage of overweight and obesity was 14% and 18% for boys and girls, respectively, while this was almost 60% among the adults aged 19-70. The percentage increased with age from 7% of boys aged 1-3 to about 70% of adults aged 50-70 (see Appendix C). Percentages of overweight were somewhat lower in boys and girls aged 14-18 than in other age groups. The method of measurement might explain this


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Table 3.5.a Mean height, weight and BMI of Dutch children and adults aged 1-70 (DNFCS 2012-2016), weighted for socio-demographic characteristics and season. Height and weight were measured for children aged 1-15 and self-reported for children aged 16-18 and adults. Boys,

1-18 n=1,122

Girls, 1-18

n=1,113

Men, 19-70

n=783

Women, 19-70, n=778

mean mean mean mean Height (cm) 140.6 137.2 182.0 168.5 Body weight (kg) 39.2 37.8 87.4 76.4 BMI (kg/m2)a 18.1 18.4 26.4 26.9 Evaluation of BMIab % % % % Seriously underweight 1 2 0 0 Underweight 7 8 1 1 Normal weight 77 73 42 40 Overweight 11 15 39 33 Obesity 3 3 18 25

a Missing information on BMI for 1 person aged 1-3 and 1 person aged 4-8 b BMI for children is based on the Extended International (IOTF) body mass cut-offs17 The evaluation is dependent on age and gender. Cut-off points for children were lower than those for adults. BMI cut-offs for adults: Seriously underweight


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difference, as for children aged up to 15, body weight was measured, whereas for children aged 16-18 and adults, this was self-reported. About 8 to 10% of the children aged up to 19 were (seriously) underweight. To assess weight status among the 71-79 year-olds, waist circumference was taken into account rather than height and weight.37 Of the men and women aged 71-79, 59% and 78% had a waist circumference of ≥102 and ≥88 cm respectively. However, there is no current consensus on the waist circumference cut-offs for overweight therefore results should be interpreted with caution. About 13% of the 71-79 year-olds were undernourished, based on cut-off level of a mid-upper arm circumference below or equal to 25 cm or unintended weight loss of at least 4 kg in 6 months. Compared to the figures in the previous DNFCSs,38, 6 the mean body weights and the prevalence of obesity in this study were comparable for most age groups. However, for the older adults, the body weights were slightly higher. For example, in the DNFCS 2007-2010, the percentage of obese women aged 51-70 was 23% versus 31% in the current survey. Waist circumference was also slightly larger in this study population compared to the DNFCS among adults aged 70 and older.6 The percentage of older persons with risk of undernutrition was also higher compared to that in the previous survey among older adults where relatively more vital adults were represented. 6 Thus, possibly the current survey included a more representative selection of the older adult population. Compared to the figures of the Lifestyle Monitor11, 39, in 2013/2016 the mean body weights and also the prevalence of obesity in the DNFCSs study were higher for most adult age groups. In both studies, anthropometric information was self-reported for these age groups.

3.4.4 Lifestyle characteristics Although in the current food consumption survey data were collected on alcohol, physical activity and obesity, other surveys (as part of the Lifestyle Monitor) have been designated as the source for the (annual) key figure on these themes. These data were used in this study to get more insights in the representativeness of the study population. Physical activity Results on physical activity are shown in Tables 3.6.a and 3.6.b for children and adults respectively (see Appendix C for more detail). More age groups are presented due to the age-specific questionnaires. 55% of the 1-3 year-olds were moderately active for 3.5-14 hours per week. Of the children aged 4-11, 73% met the Dutch Physical Activity norm. This number was higher than in those aged 12 18 (57% for boys and 47% for girls). The time spent on sedentary activities increased with age: 10% of the 1-3 year-olds watched TV/Video/DVD/PC for more than 14 hours a week, of the 4-11 year-olds this was 34%, and for the 12-18 year-olds this was 74% for boys and 58% for girls. For adults, 73% of the 19-50 year-olds and 84% of the 51-79 year-olds met the Physical Activity Norm. Moreover, 14% of men aged 19-50 and 6% of the women in that age group met the fitnorm of at least 20 minutes of heavy intensive activity at least three times a week. This


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percentage was higher in the older age groups; however, the definition of intensive activity was more lenient for older age groups. About half of the 51-79 year-olds met the fit norm. More than three quarters of the adult population met the NNGB or the fit norm. Adherence to both norms was higher than reported by the national reference dataset 2014/1511. In 2014/15, around half of the adults (aged 20-55) and one third of adolescents (aged 12-20) complied with the recommendations. Furthermore, three quarters of the older adults (55-75) complied with recommendations compared with 82% to 83% in our study population. Table 3.6.a Characteristics of physical activity in Dutch children aged 1-18 (DNFCS 2012-2016), weighted for socio-demographic characteristics and season.

Boys and

girls, 1-3

n=672a

Boys and girls, 4-11

n=794b

Boys, 12-18

n=402

Girls,

12-18 n=367

% % % % TV/Video/DVD/PC Few (


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Table 3.6.b Characteristics of physical activity of Dutch adults aged 19-79 (DNFCS 2012-2016), weighted for socio-demographic characteristics and season.

Men, 19-50

n=519 %

Women, 19-50

n=520 %

Men, 51-79

n=524 %

Women, 51-79

n=515 %

NNGBa Inactive 5 4 3 2 Semi-active 23 23 13 14 Norm-active 72 72 84 84 Fitness standard Inactive 68 78 27 33 Semi-active 18 16 24 19 Norm-active 14 6 49 48 Compliance to NNGB or fitness standard

74 73 85 84

a. Dutch Standard for Healthy Exercise (NNGB) Smoking Information on smoking among the adolescent and adult population is presented in Table 3.7 (see Appendix C for more detail). For children aged under 12, no information was gathered on tobacco use through the general questionnaire. In adolescents aged 12-18, 85% of the boys and 87% of the girls reported that they had never smoked. About 5% of the boys and girls in this age group was a current smoker. In the 19-50 age group, the percentage of smokers was the highest, 27% for men and 25% for women. About half of the population in this age group had never used tobacco. From those aged 51 onwards, more men than women had quit smoking at some point in their lives, 62% for men and 44% for women. The number of current smokers, stopped smokers and non-smokers was comparable to the reference data on smoking in the Netherlands from 2014/2015.11 Table 3.7 Smoking by the Dutch population aged 12-79 (DNFCS 2012-2016), weighted for socio-demographic characteristics and season.

Boys, 12-18

n=402 %

Girls, 12-18

n=367 %

Men, 19-50

n=519 %

Women, 19-50

n=520 %

Men, 51-79

n=524 %

Women, 51-79

n=515 %

Yes 6 5 27 25 16 20 No, but did use tobacco in the past

9 8 23 23 62 44

No, never used tobacco 85 87 49 52 21 36


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Alcoholic beverages Information in the general questionnaires on the use of alcoholic beverages by the adolescent and adult population is presented in Table 3.8 (see Appendix C and Chapter 6 for more detail). The number of adult non-users of alcoholic drinks was somewhat higher compared with the 2014/15 reference data on alcohol use in the Netherlands11. However, due to age-specific questionnaires, this difference can be due to methodological aspects. In the 2014/15 survey, about two thirds of the adolescents (aged 12-18) indicated they had not consumed any alcohol. For adults aged 20-75, the percentage of non-users varied between 14-20%, whereas in the DNFCS 2012-2016 this varied between 17-37%. Table 3.8 Alcohol use by the Dutch population aged 12-79 (DNFCS 2012-2016), weighted for socio-demographic characteristics and season.

Boys, 12-18

n=402 %

Girls, 12-18

n=367 %

Men, 19-50

n=519 %

Women, 19-50

n=520 %

Men, 51-79

n=524 %

Women, 51-79

n=515 %

No use of alcoholic drinks

80 80 18 34 17 37


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4 General dietary characteristics

4.1 Introduction This chapter presents general characteristics of the Dutch diet. It describes meal patterns, type of special diets and eating habits, use of discretionary salt, and the consumption of dietary supplements. Data are based on participant information from both the completed demographic and lifestyle questionnaire and the 24-hour recalls.

4.2 Key findings • 5% of the Dutch population never had breakfast. • Most people started their breakfast between 7:30 and 9:00,

lunch between 12:00 and 13:00 and dinner between 17:30 and 18:30. These patterns differ by age. This was less uniform for adolescents and young adults.

• 13% of the Dutch population reported having a special diet, and 3% have a food consumption pattern without meat.

• About one quarter indicated not adding salt during preparation of the meal or during the meal.

• About two in five reported the use of dietary supplements. The most commonly taken dietary supplements in all age groups are supplements with multivitamins/minerals, vitamin C or vitamin D.

• The use of supplements has not changed in the last five years. However, the percentage older adults using vitamin D containing supplements has increased in the last five years. For instance, the increase in those aged 70-79 was more than 7 percent points.

4.3 Meal patterns Information on general characteristics of the diet, based on information from the questionnaire, are presented in Table 4.1. About 9 in 10 children consume breakfast daily. This percentage was lower during adolescence (see Appendix D). One quarter of the men and one in six women did not breakfast every day. Children (2%) and adults (6%) reported that they (almost) never had breakfast. A comparison with the previous survey in 2007-201038, 6 suggests that more adults aged 19-50 eat breakfast daily. For instance, in 2007-2010, this was 52% and 65% for young male and female adults respectively; in 2012-2016 this was 63% and 74% respectively. On average, each person had 9.3 food consumption occasions per

the diet of the dutchthe dutch diet has improved somewhat in recent years. for example, the dutch...

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