In the evaluation of dietary intake of populations, one is often interested in the habitual (usual) intake, i.e. the long-term average intake. For example to estimate the proportion of a population that meets nutritional recommendations. In food consumption surveys, dietary intake is generally collected with short-term measurements, 24-hr recalls or food records. The dietary intake of an individual can vary considerably from day to day. Consequently, intake measured over a limited number of days will be a poor indicator of the individual habitual intake. Statistical modelling makes it possible to estimate the habitual intake distribution of a population from repeated short-term measurements. In this course the focus will be on statistical modelling of habitual intake using SPADE (Statistical Program to Assess Dietary Exposure).
PhD candidates, postdocs, or other researchers interested in this course should work on statistical analyses of food consumption data and have a basic understanding of applied statistics.
Participants will learn
1) the principles of habitual intake modelling for populations
2) the use of SPADE for habitual intake modelling of foods, food groups, energy and nutrients (from foods and/or dietary supplements).
The course is a 2.5 days hands-on course with a maximum of 25 participants (PhD’s, postdocs, other researchers). The course will consist of a combination of lectures on general principles of modelling habitual intake, lectures on how to use SPADE, and practical exercises with SPADE. There is the option to bring your own data and practice with these data during the last day of the course.
We will teach you hands on experience in using SPADE. SPADE is implemented in a freely available, open-source software R for statistical computing. See for more information
- Principles of habitual intake modelling
- Installing SPADE, R, and R-studio
- Habitual intake modelling for daily intakes
- Habitual intake modelling for episodical intakes
- Bootstrap procedures to estimate confidence intervals
- Habitual intake modelling for intakes from multiple sources, e.g. foods and dietary supplements
- Dr. Marga Ocké, RIVM/Division of Human Nutrition, WUR
- Dr. Arnold Dekkers, RIVM
- Dr Janneke Verkaik-Kloosterman, RIVM
Date & duration
The course will be held From Monday morning 13 November till noon on Wednesday 15 November (2.5 days)
The study load of this course is 0.8 ECTS credits.
The course language will be English.
Information concerning the course contents can be obtained from Dr Marga Ocké, firstname.lastname@example.org.
For organisational matters please contact:
Mrs. Ingeborg van Leeuwen-Bol, email@example.com
Location & accommodation
Lectures will be given at Wageningen University & Research.
The town of Wageningen is 5 km from Ede-Wageningen railway station, with transport options being taxi or bus. Ede-Wageningen railway station is about one and a half hours from Amsterdam Schiphol Airport. For train schedules visit: www.ns.nl.
A number of hotel rooms have been blocked at Hof van Wageningen. Accommodation costs are € 75, - (single room; bed & breakfast) per night. Participants have to book their own room by sending an e-mail to: firstname.lastname@example.org. Please book your room before 1 October 2017 and mention booking code MHDI-17
Registration & course fee
The number of participants to the course is limited to 25.
To register please complete the electronic reply form before 9 October 2017.
Applicants will be informed of acceptance of their registration at the latest on 19 October 2017. They will receive instructions for payment and further course details.
Course fee includes printed materials, coffee/tea during breaks, lunches and the course dinner but does not cover accommodation. The course fee depends on the participant's affiliation:
|VLAG/WU PhD candidates
|| € 150
|| € 350
|Postdocs/Staff from HNE and RIVM
|| € 250
|Postdocs/university staff and others not affiliated with HNE and RIVM
|| € 500
- No charge until 9 October 2017
- 25% of the course fee paid or due till 19 October 2017
- No refund after 19 October 2017
Substitutions for participants may be made at any time until the start of the course.