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SPADE

On this website you will find information on the Statistical Program to Assess Dietary Exposure (SPADE) which is developed by RIVM. With this program the habitual intake distribution for daily and episodically consumed foods or dietary components can be estimated based on intake measured on a limited number of days.

This website will be extended with more information.
The option to download SPADE will follow soon.
Please mail to spade@rivm.nl to mention your interest and you will be informed.

 
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 or that exceeds safe upper intake levels.
 
In food consumption surveys, dietary intake is generally collected with short-term measurements, for example 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.
 
This modelling can be complicated if the intake is derived from several sources; for example micronutrients are naturally present in foods, but they are also available in fortified foods and dietary supplements. For the evaluation of both the adequacy of intakes and the risk of excessive intakes of micronutrients, all potential sources should be included. In the estimation of the habitual intake, this may cause specific challenges like multimodal distributions and heterogeneous variances between the sources.
 
Statistical Program to Assess Dietary Exposure (SPADE) was developed by RIVM. It can be used to estimate the habitual intake distribution for daily and episodically consumed foods or dietary components, similar as other available methods. On top of that, SPADE provides models to estimate habitual intake distributions from different sources separately and adds these habitual intakes in order to get the overall habitual intake distribution.

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