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 as well as population’s habitual intake. Statistical modelling makes it possible to estimate the population's habitual intake distribution 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. Since SPADE is an R Package, basic knowledge of R and RStudio is necessary. A dedicated, basic e-learning course on R and R-Studio specifically focused to use SPADE is provided in advance. Participants are expected to follow this e-learning before starting the course.
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.
The course is a 2 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
- Habitual intake modelling for daily intakes
- Habitual intake modelling for episodical intakes
- Bootstrap procedures to estimate confidence intervals
- Principles of 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
- Ir. Marjolein de Jong, RIVM
Date & duration
The course from 12 October till Tuesday 13 October will be postponed! The new dates in 2021 will be announced shortly.
The study load of this course is 0.6 ECTS credits.
The course language will be English.
Information concerning the course contents can be obtained from Dr Marga Ocké
For organisational matters please contact: Cornelia van Bree-Evers
Location & accommodation
Lectures will be given at Wageningen University & Research, Wageningen Campus.
The town of Wageningen is 5 km from Ede-Wageningen railway station, with direct bus links to the Campus.
A number of hotel rooms have been blocked at Wageningen International Congress Center (WICC). Accommodation costs are €82,50 (single room; bed & breakfast) per night. Participants have to book their own room by sending an e-mail to: email@example.com. Please book your room before 1 September 2020 and mention booking code MHDI-20
Registration & course fee
Registration for this postponed event will open soon!
The number of participants to the course is limited to a maximum of 25.
Applicants will be informed of acceptance of their registration. They will receive instructions for payment and further course details.
Course fee includes course 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/EPS/WASS/WIAS/WIMEK-SENSE/PE&RC PhD candidates
|| € 175
|other PhD candidates / Postdocs and staff from VLAG
|| € 400
|Postdocs / University staff / non-profit
|| € 525
|Private sector / for-profit
|| € 800