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National Nutrition Survey menuCH 2014-2015

Switzerland, 2014 - 2015
Research datasets
Center for Primary Care and Public Health (Unisanté), University of Lausanne, Switzerland (Unisanté), Swiss Federal Food Safety and Veterinary Office (FSVO)
Created on August 08, 2016 Last modified July 28, 2022 Page views 27443 Download 19331 Documentation in PDF Study website Metadata DDI/XML JSON
  • Study description
  • Documentation
  • Get Microdata
  • Related Publications
  • Identification
  • Version
  • Scope
  • Coverage
  • Producers and sponsors
  • Sampling
  • Data Collection
  • Questionnaires
  • Data Processing
  • Data Appraisal
  • Access policy
  • Disclaimer and copyrights
  • Metadata production

Identification

Survey ID Number
CHE-FSVO-MENUCH-2014-2015_V5.0
Title
National Nutrition Survey menuCH 2014-2015
Translated Title
Nationale Ernährungserhebung menuCH = Enquête nationale sur l'alimentation menuCH = Sondaggio nazionale sull’alimentazione menuCH
Country
Name Country code
Switzerland CHE
Abstract
National Nutrition Survey menuCH

Nutrition and physical activity directly affect health and quality of life. But what do people living in Switzerland usually eat and drink? The National Nutrition Survey menuCH pursued these questions and collected data concerning nutrition and physical activity behaviors of the Swiss population.

menuCH inquired men and women aged between 18 and 75 years living in the German, French or Italian parts of Switzerland, about what they ate the previous day (i.e., 24-hour dietary recall) and their eating and drinking habits but also about their physical activity. Anthropometric measurements were taken in addition. Survey participation was voluntary.

menuCH inquired 2000 participants in 10 study centers. The study centers were located all over Switzerland so that most participants could reach them within reasonable time. The survey took place between January 2014 and February 2015.

Aims

„What and how much do people living in Switzerland usually eat and drink, when and where?” With this and other questions regarding eating and drinking habits, it should possible to...

- evaluate better the nutrition situation;

- keep high and improve food safety;

- detect faster possible risks associated with food;

- verify and adapt if necessary the present dietary recommendations;

- improve the food range and composition;

- develop and implement effective nutrition strategies and measures to promote health and quality of life;

- support research and development in the fields of nutrition, food and behavior sciences with up-to-date and nationally representative data.

For more information see :
https://www.blv.admin.ch/blv/de/home/lebensmittel-und-ernaehrung/ernaehrung/menuCH.html (German)
https://www.blv.admin.ch/blv/fr/home/lebensmittel-und-ernaehrung/ernaehrung/menuCH.html (French)
https://www.blv.admin.ch/blv/it/home/lebensmittel-und-ernaehrung/ernaehrung/menuCH.html (Italian)


For first results from the questionnaire about nutrition behavior and physical activity in Switzerland see:
Bochud et al. (2017) Anthropometric characteristics and indicators of eating and physical activity behaviors in the Swiss adult population. Results from menuCH 2014-2015. Report on behalf of the Federal Office of Public Health and the Food Safety and Veterinary Office. Published online 16. March 2017. (Available: https://menuch.unisante.ch/index.php/catalog/4/download/58)

The list of publications on menuCH data can be found under the following link : https://www.blv.admin.ch/blv/de/home/lebensmittel-und-ernaehrung/ernaehrung/menuCH/menuch-publikationen-daten-forschung.html
Unit of Analysis
Individuals

Version

Version Description
Fifth version of menuCH 2014-2015 Data suitable for micronutrients and macronutrients analyses. Some variables may change and some others may be added in the future.
Version Date
2022-07-04

Scope

Keywords
Keyword
Nutrition survey
Dietary survey
Swiss diet
24h dietary recall
Switzerland

Coverage

Geographic Coverage
Switzerland (46° 57' N, 7° 25' E)
Universe
Food consumption of Swiss residents, male and female from three language regions, between 18 and 75 years of age

Producers and sponsors

Primary investigators
Name Affiliation
Center for Primary Care and Public Health (Unisanté), University of Lausanne, Switzerland (Unisanté) UNIL
Swiss Federal Food Safety and Veterinary Office (FSVO) FDHA
Producers
Name Affiliation Role
Center for Primary Care and Public Health (Unisanté), University of Lausanne, Switzerland (Unisanté) UNIL Original producer
Institut für Sozial- und Präventivmedizin (ISPM) University of Bern Survey collaborator
Swiss Federal Food Safety and Veterinary Office (FSVO) The Federal Department of Home Affairs (FDHA) Data proprietary and data linkage with Swiss Food Composition Database
Funding Agency/Sponsor
Name Abbreviation Role
Swiss Federal Food Safety and Veterinary Office FSVO Primary Funder
Swiss Federal Office of Public Health FOPH Co-Funder
Other Identifications/Acknowledgments
Name Affiliation Role
Center for Primary Care and Public Health (Unisanté), University of Lausanne, Switzerland (Unisanté) UNIL Survey management, data cleaning and hosting, weighting strategy
Institut für Sozial- und Präventivmedizin (ISPM) University of Bern Survey collaboration
Fachbereich Gesundheit Bern University of Applied Sciences (BUAS) Survey collaboration, data cleaning
Swiss Federal Food Safety and Veterinary Office (FSVO) The Federal Department of Home Affairs (FDHA) Survey management, survey collaboration, data linkage and documentation

Sampling

Sampling Procedure
Sampling was carried out by the Federal Statistical Office (FSO) using the sampling frame for individual and household surveys (SRPH, Stichprobenrahmen für Personen und Haushaltserhebungen, https://menuch.unisante.ch/index.php/catalog/4/download/62) database. The three-step sampling procedure for the survey was as follows:

1. The first stratum consisted of the seven Swiss major regions (Lake Geneva region, Midland, Northwest Switzerland, Zurich, Eastern Switzerland, Central Switzerland and Ticino*). To facilitate logistics, only the most populous cantons of each major region were considered. The number of cantons was chosen so that they represent at least half of the population of the corresponding major region (Table 1). The sampling frame of the main study consisted of participants living in the cantons of Vaud (VD), Geneva (GE), Neuchâtel (NE), Jura (JU), Berne (BE), Basel-Land (BL), Basel-Stadt (BS), Zürich (ZH), St. Gallen (SG), Aargau (AG), Luzern (LU) and Ticino (TI).
* Source : Swiss Federal Statistical Office, Available : https://menuch.unisante.ch/index.php/catalog/4/download/65

Table 1. Major regions of Switzerland and cantons selected for menuCH
https://menuch.unisante.ch/index.php/catalog/4/download/80


2. Within the first stratum, a second stratification was conducted, taking into account gender- and age groups. For each major region, the final sample aimed to achieve a comparable number of men and women, with an age group distribution comparable to the one observed within the administrative regions.
3. The 24-hour dietary recall interviews were as evenly distributed as possible throughout the week in order to capture all days of the week. The number of interviews conducted on Mondays was twice as large as for the other days, in order to cover the food consumption on Saturdays and Sundays. For participants interviewed on Mondays, the day of the interview (Saturday or Sunday) was randomly chosen.

Overall, the target was to recruit a total of 2'000 participants with two appointments/interviews each, following quotas by canton of residence (Table 2; Table 3).

Table 2. Survey sampling frame overall and by linguistic region
https://menuch.unisante.ch/index.php/catalog/4/download/81

Table 3. Target number of participants by administrative region and canton of residence
https://menuch.unisante.ch/index.php/catalog/4/download/82
Weighting
As in most sampling surveys, subjects do not all have the same probability to be part of the sample. This is why weights must be considered and applied to the data. The principle of weighting is about assigning different weights to survey participants based on their probabilities of inclusion in the sample and participation in the survey.

Weighting strategy in menuCH involves three steps:
1. Calculation of the sampling weights
2. Correction of non-response
3. Calibration on marginal totals of the sampling frame

These three steps define, for each person who participated in the survey, an extrapolation weight. This latter is used to extrapolate the results of the investigation to the target population.

In addition, food consumption data from 24-hour dietary recalls can be weighted to provide information that is balanced across seasons (and weekdays).

Detailed description of methods and calculations are available here: https://menuch.unisante.ch/index.php/catalog/4/download/17 and under “documentation” section.

Data Collection

Dates of Data Collection
Start End
2014-01-27 2015-02-28
Data Collection Mode
Computer Assisted Personal Interview [capi]
Data Collection Notes
The Federal Office of Statistic (FSO) provided a population-based random sample of 13,606 addresses of adults, aged 18-75 years from seven administrative regions representing the three main linguistic regions of Switzerland (German, French, Italian). The invitation letter, sent to the sampled addresses, included a reply card to either specify the preferred way and time of contact, in case of participation interest or else to declare no interest. Then, potential participants were contacted by phone from a centrally located recruitment center (CATI Laboratory) to arrange the first of two appointments.
Trained dietitians collected data on food consumption between January 2014 and February 2015. The first 24-hour dietary recall was administered face-to-face and the second by telephone on two non-consecutive days, that is, at least two weeks apart and if possible on different weekdays. The 24-hour period was defined as from when the participant got up the day prior to the face-to-face/telephone interview date until the time the respondent got up on the interview day. Since interviews were conducted from Monday to Saturday only, on Monday either the food intake of Saturday (for participants with even ID number) or Sunday (for participants with uneven ID number) was assessed. No detailed information on dietary supplement use was collected.

Several computer-assisted as well as paper-based instruments were used in the survey:

Scheduling Tool
In order to allocate the survey participants to the 15 dieticians across the 10 study centers at different days of the week in a well-coordinated and efficient way, a web-based Scheduling Tool was developed.


Anthropometry
Body weight (kg), height (cm), waist (cm) and hip (cm) circumferences were measured using calibrated devices according the WHO-MONICA protocol, available at https://menuch.unisante.ch/index.php/catalog/4/download/59


GloboDiet® (formerly EPIC-Soft®)
The software GloboDiet® developed by the International Agency on Research on Cancer (Slimani et al. 1999; https://doi.org/10.1016/S0169-2607(98)00088-1) allows the standardized collection and management of 24-hour dietary recall data. Applying GloboDiet® survey participants are asked to describe consumed foods and beverages according to a predefined sequence of questions/facets with pre-defined answers/descriptors (see lists of facets (available: https://menuch.unisante.ch/index.php/catalog/4/download/64) and descriptors (available: https://menuch.unisante.ch/index.php/catalog/4/download/63) available for menuCH). For menuCH, about seventy common and country-specific GloboDiet® databases on foods, recipes, quantification methods and coefficients were customized to Swiss specific needs and requirements, and translated into German, French and Italian to form the trilingual Swiss version of GloboDiet®. GloboDiet allows choosing among the following six different quantification methods to quantify consumed amounts: gram, volume, standard unit, household measure, photo and shape. Consumed amounts are given in grams after application of conversion factors, if necessary.


Picture book for the estimation of portion sizes
Based on a thoroughly validated and widely applied international picture book for the estimation of portion sizes (Van Kappel AL, Amoyel J, Slimani N, Vozar B and Riboli E. Epic-Soft Picture Book for estimation of Food Portion Sizes. Lyon: International Agency for Research on Cancer; 1995) a Swiss specific picture book was developed and used to help participants estimate the consumed food portions (Camenzind-Frey, E. and Zuberbuehler, C.A. (2014) menuCH - SCHWEIZERISCHES FOTOBUCH / LIVRE PHOTO SUISSE / MANUALE FOTOGRAFICO SVIZZERO. 2. Auflage., Bern, Switzerland: Federal Office of Public Health (FOPH) & Federal Food Safety and Veterinary Office (FSVO)).

Questionnaires

Questionnaires
Non-participant questionnaire (available here https://menuch.unisante.ch/index.php/catalog/4/download/26)
A short non-participant questionnaire was applied orally by the recruiters during the contact call when it became clear that the contacted person was unwilling to participate.

Nutrition behavior and physical activity questionnaire (available in English under the documentation section of this website or in German: https://menuch.unisante.ch/index.php/catalog/4/download/14 ; French: https://menuch.unisante.ch/index.php/catalog/4/download/15 and Italian: https://menuch.unisante.ch/index.php/catalog/4/download/16)


Eating and physical activity behavior were assessed by a 49 question paper/written questionnaire available in three languages. The questionnaire has been developed by FOPH/FSVO and was pre-tested using cognitive interviews. For physical activity, the short version of the IPAQ - International Physical Activity Questionnaire - was considered. For health related questions, reference was made to questions of the Swiss Health Surveys and for diet related questions also standard questions from other nationally or internationally used questionnaires had been included. Thus, comparisons with other studies are possible. The questionnaire was amended by a selection of socio-economic and -demographic questions from the most current Swiss Health Survey 2012, with very few changes applied due to experiences from regional surveys (CoLaus and Bus santé studies).
The questionnaire was sent to the participants by postal delivery together with the confirmation of the first appointment and the instruction to complete it at home and bring it to the appointment. Upon handover, the questionnaire was checked by the dietitian for completeness and clarity. At the end of the appointment the dietitian keyed the information into a central on-line database.

Data Processing

Data Editing
Data editing took place at a number of stages throughout the processing, including:
a) During data entry
b) Structure checking and completeness
c) Secondary editing
d) Structural checking of SQL and STATA data files
Other Processing
Data about participation
A total of 2086 persons initially participated (participation rate: 15%). Please also consult the chapter “Weighting”


A) Data from the dietary behavior and physical activity questionnaire

Missing questionnaires
Out of the 2086 participants 5 participants never gave back their questionnaire. One of them could finally be reached by phone and answered the questions about socio-economic determinants only. This results in a total of 2081 complete questionnaires.

Data cleaning
Data cleaning was done with Stata Statistical Software (Release 13. College Station, TX: StataCorp LP). Most variables were only slightly modified: they were only re-coded with numerical values and labeled in English to facilitate data analysis. For instance, the variable “gender” was initially coded “homme” and “femme” and was re-coded as such: 1 for male and 2 for female. Others variables had to be adapted prior to analysis. These adaptations and explanations of large missing values are described below.

Physical activity (questions 14-20)
Many participants (n=525) claiming they could not estimate how much time they had spent on average doing any of the three activity types of physical activity. In addition, 11 participants had missing or illogical (and deleted) data.

Occupation and socioeconomic background (questions 41-49)
An important limitation of the questionnaire was the instruction for question 46, stating that only people without remunerated professional activity at all should complete questions 46 and next. To comply with this statement, field dietitians were instructed to enter only questions 42 to 45 (and not question 46 and following) if the participant was a student or a housewife, etc. and had part-time paid-work, even if it was only 1 hour per week. Unfortunately, with the statement in the questionnaire plus the systematic correction of field dietitians, many students or retired people, etc. who worked part-time were recorded in the database only as active worker (and not additionally student, retired, etc.). A consequence of this limitation is that the information on occupation is not optimal.
Before data cleaning, the proportion of students was 4%, housewives / househusbands 6% and retired 16%, respectively. In comparison, in the 2012 Swiss Health Survey, for which data were collected by phone among 21'597 people aged 15 years old and over, there was about 10% of students, 20% of housewives/househusbands and 23% of retired people, taking into consideration the ones working. Based on that observation, we went back to all 2081 paper questionnaires and captured answers to question 46 that were not taken into consideration by field dietitians during data entry. Going back to the questionnaires allowed us to recapture participants who had ticked an answer to this question. We created then a new variable for question 46, which was considered of better quality. The initial variable for question 46 was left as such (not cleaned). Furthermore going through the 2081 questionnaires allowed us to identify a few inconsistencies in the questions 41-49, which were also cleaned. Finally, age limit was set for housewives / househusbands at 64 years for women and 65 years for men. Participants above this age were re-coded only as retired.
Although we did our best to capture as much information as possible for variables about occupation and question 46, all data should be interpreted with caution due to limitations of the questionnaire in questions 41-49. For example, we highly suspect that information about housewives / househusbands were partially lost as their percentage is still relatively low compared to the Swiss Health Survey. In addition, 115 participants (almost all women) declared working less than 20 hours/week and did not answer question 46. We may suppose they may be potential housewives / househusbands. Information about retired people are expected to be of good quality after the paper copy checks: more than 96% of people older than 65 years were classified as retired in question 46. Same for students: 7% of students was a very reasonable proportion compared to the Swiss Health Survey results (i.e., 10%).

Age
Participants' age was calculated from their birth date and estimated questionnaire completion date, which corresponds for most to face-to-face appointment date.


B) Data from anthropometry

Missing data
Out of the 2086 participants, 34 weight measures were missing. Following the study protocol, 27 pregnant or lactating women, 6 handicapped participants (e.g. in a wheel chair) were not measured. Only one participant refused to be weighted. For height, there were 7 missing values because height was again impossible to be measured in these 6 handicapped participants plus the same participant who refused weighing.
For waist and hip measures, there were again 34 missing values. The reasons were identical: 27 pregnant or lactating women, 6 handicapped participants and 1 refusal.

Data cleaning
Data were controlled for consistency (e.g., comparison of self-reported vs. measured weight and height) or incorrect rounding. Data were cleaned when necessary, going back to written data on the paper sheet.

Data correction for clothing
Because weight was measured while participants were wearing light clothes (more than underwear), 1.2kg were deducted from measured weight for men, respectively 0.8kg for women, independent of season. This correction for light clothing was performed based on recommendations from the literature and in relation to what was done in other Swiss surveys.
Because waist circumference was taken directly on the skin, we did not apply any correction factor. By contrast, hip circumference was taken while participants were wearing pants or skirts. However, we decided not to correct hip measures for clothing as field dietitians were required to put more tension on the string when the pants/skirts were thick.


C) Food consumption (data from GloboDiet®, 24h dietary recalls)

Missing data
Of the 2086 initial participants 29 participants did not complete the second 24-hour dietary recall by phone. Additionally, one face-to-face (first) 24-hour dietary recall was deleted due to incompleteness. All other 24-hour dietary recalls (4142 in total, 2085 face-to-face and 2057 phone) were considered as valid.

Data cleaning
The 15,637 notes written in GloboDiet® by field dietitians were handled centrally by a senior registered dietitian following IARC guidelines. The latter also checked all 24HDR with extreme energy intakes (n=85). Furthermore, food consumption data were evaluated using all criteria recommended by IARC. Detailed quality control procedures were implemented and published.

Data linkage for energy and nutrient values
Food consumption data e.g. foods, recipes and ingredients (from GloboDiet®) were linked semi-automatically with the most appropriate item from the Swiss Food Composition Database (SFCDB, http://naehrwertdaten.ch) using a developed matching tool on the food information platform FoodCASE (Premotec GmbH). The version 37 of the SFCDB, which is not available on the SFCDB website, was used for this data linkage. The matching tool was programed to provide for each different consumed item a list of possible matches from the SFCDB ranked according to similarity. Whenever possible the exact generic item was selected out of the SFCDB. If neither was available the consumed item was linked with an item similar with regard to the most relevant nutrient. Exceptions are the mineral waters and some breakfast cereals which are registered as branded foods. For menuCH more than 32’000 different items from GloboDiet® were linked in this way.

The actual data subset named res_consumption_data_V05_2022 is matched with generic products with regard to the most relevant nutrient. Therefore, this data subset is suitable for micronutrients and macronutrients analyses. The few branded products, namely mineral water and breakfast cereals have precisely known micronutrients composition like the generic products.

A first data subset (version 2016-08-04) was established in 2016 for macronutrients analysis only. The consumed items were matched as much as possible with branded products from the SFCDB version 20. This data subset is no longer available on the menuCH data repository.
Unfortunately, no insights into micronutrients were possible with this old data subset. This is the reason why the SFCDB was updated. As a result, a new matching was performed with mainly generic products from the SFCDB and the actual res_consumption_data_V05_2022 was created.

For further information regarding the development of the matching tool, please consult the master thesis of Hochuli, Alexandra, 2014, from chapter 4 onward:
https://doi.org/10.3929/ethz-a-010129946.

When using the consumption data of this survey please be aware that:
1. Both recipes and their ingredients have been matched separately to the most appropriate food item and additionally to the most appropriate recipe from the SFCDB. Therefore summing up energy/nutrients of the ingredients may not result in exactly the same figures as are given by summing up the respective recipes.
To avoid duplication of nutrient intake you must either use recipes or ingredients but never both!
2. The Swiss Food Composition Database contains information on the composition of foods that are available in Switzerland. For all the foods contained in the database, complete information is presented on the macronutrients (carbohydrates, proteins, fats) as well as for dietary fibres, water, salt, alcohol and energy content. Fat values include amount of saturated, monounsaturated and polyunsaturated fats, and cholesterol. In addition, the micronutrients, vitamin A, B1, B2, B6, B12, C, D and E, niacin, folate, pantothenic acid as well as potassium, sodium, chloride, calcium, magnesium, phosphorus, iron, iodide and zinc contents are listed for the majority of generic foods (selenium could not be included in the dataset because there are still too many missing values to allow useful calculations). For branded products, however, information about micronutrients is not always available, only if provided or published by the manufacturer (e.g. on packaging or websites).

Data Appraisal

Estimates of Sampling Error
See the document "Weighting strategy” available under "Technical documents” and the document "Codebooks” available under “Other materials” in the “Documentation" section.
Remarks:
1. The variables “sampling_w”, “nonresponse_w” and “nonresponse_w_2rec” are given for information only. These variables should not be used for extrapolation as they correspond to intermediate steps in the calculation of the calibrated weights.
2. For extrapolation always use calibrated weights. As season and weekday influence nutrition, it is preferable to use "sw_calibrated_w" weights rather than "calibrated_w" weights.
3. The statistical program SPADE requires two 24HDR per person for usual intake analyses. For this reason the variables “calibrated_w_2rec” and “sw_calibrated_w_2rec” are provided (see chapter “Weighting for SPADE” in the document “Weighting strategy”).

Access policy

Access authority
Name Affiliation URL
Swiss Federal Food Safety and Veterinary Office (FSVO) The Federal Department of Home Affairs (FDHA) https://www.blv.admin.ch
Contacts
Name Email
Swiss Federal Food Safety and Veterinary Office (FSVO) ernaehrungserhebung@blv.admin.ch
Confidentiality
Confidentiality of respondents is guaranteed by Articles 4 to 15 of the Federal Act on Data Protection (FADP) of 19 June 1992 (Status as of 1 January 2014). Anonymisation and de-identification: the data anonymisation and de-identification was performed by Unisanté team with the help of FSVO collaborators. This dataset contains only de-identified data following the standard for de-identification of protected health information, Section 164.514(a) of the Privacy Rule of the Health Insurance Portability and Accountability Act (HIPAA) (http://www.hhs.gov/hipaa/for-professionals/privacy/special-topics/de-identification/#standard). Under this standard, health information is not individually identifiable if it does not identify an individual and if the covered entity has no reasonable basis to believe it can be used to identify an individual. This is done by removing or recoding, direct and indirect, identifiers in the data. The following types of identifiers are examples, such as those identified by HIPAA, that should be considered for removal or recoding to prevent the risk of association of a participant to his / her data. The list includes, but is not limited to, the following: 1) Names and initials, 2) All elements of dates (except year) which can be directly associated with a specific individual (birthdate, etc.), 3) Kit numbers (diagnostic kits) and device numbers (devices used in the trials), 4) Geographic information such as place of work, trial site location, addresses, zip codes, etc., 5) Telephone numbers, 6) Email addresses, 7) Fax numbers, 8) Account numbers, 9) Social security numbers, 10) Health plan beneficiary numbers, 11) Medical record numbers, 12) Vehicle identifier numbers and serial numbers including license plate numbers, 13) Certificate / license numbers (marriage licenses, etc.) 14) Biometric identifiers including such as MRI, hand voice prints, etc. 15) Full face photographic images or comparable images 16) Web Universal Resource Locators (URLs), 17) Internet Protocol (IP) addresses, and 18) Any other unique identifying number, code or characteristic. All of these 18 items should be considered to be removed from the data set excepting some geographic information about the country of birth and the nationality of participants. This information has been aggregated into larger regions according to WHO regions (http://www.who.int/about/regions/en/ and a new special group for Switzerland and Liechtenstein) not giving away sufficient information to identify individuals: 1. African / Eastern Mediterranean Region, 2. European Region (excepting Switzerland and Liechtenstein,) 3. Western Pacific / South-East Asia Region, 4. Region of the Americas - Switzerland and Liechtenstein. The original subject id of the study was replaced with a new random subject id. Other sensitive information about health status or religion diets have been removed or aggregated in more general groups. The variables having undergone an anonymization treatment could be identified by the term "recoded" added at the end of their name. Before being granted access to the dataset, all users have to formally agree: 1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by the data depositor. 2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files. 3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the data depositor. This statement does not replace a more comprehensive data agreement (see Access conditions).
Access conditions
Licensed datasets, accessible under conditions

To request access to licensed datasets, please register to the website to continue (https://menuch.unisante.ch/index.php/auth/register). Once your registration will be approved you must login and go to the "GET MICRODATA" tab and fill in the application form for access to the licensed dataset.

This form must be filled and submitted by the Lead Researcher in order to initiate the review process. Lead Researcher refers to the person who serves as the main point of contact for all communications involving this agreement. Access to licensed datasets will only be granted when the Lead Researcher is an employee of a legally registered receiving agency (university, research company, research centre, national or international research organization, etc.) on behalf of which access to the data is requested. The Lead Researcher assumes all responsibility for compliance with all terms of this Data Access Agreement by all researchers involved in the respective research project.

This request will be reviewed by the FSVO team, who may decide to approve the request, to deny access to the data, or to request additional information from the Lead Researcher. If your request is reviewed positively, you will receive by e-mail a separate “Data Protection Agreement” to be signed and returned by the Lead Researcher. The FSVO will only then grant access to data download.

Before filling and submitting the request form, please consult the 5 codebooks in order to find out whether or not the available data provide the variable(s) you would need for your project. If in doubt you may contact the FSVO by email (ernaehrungserhebung@blv.admin.ch) for clarification.
Citation requirements
"Swiss National Nutrition Survey menuCH 2014-2015, Version 5.0 of the research use dataset (July 2022), provided by the Swiss Federal Food Safety and Veterinary Office (FSVO). www.blv.admin.ch"

Disclaimer and copyrights

Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Copyright
(c) 2017, Swiss Federal Food Safety and Veterinary Office (FSVO)

Metadata production

DDI Document ID
DDI-CHE-FSVO-MENUCH-2014-2015_V5.0
Producers
Name Abbreviation Affiliation Role
Center for Primary Care and Public Health (Unisanté), University of Lausanne, Switzerland Unisanté UNIL Survey management
Swiss Federal Food Safety and Veterinary Office FSVO FDHA Survey management, survey collaboration, data linkage and documentation
DDI Document version
Version 5 (July 2022)
Swiss Federal Food Safety and Veterinary Office (FSVO)
Risk Assessment Division
Schwarzenburgstrasse 155, 3003 Bern - Switzerland
ernaehrungserhebung@blv.admin.ch