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 habitual 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.

In order to use SPADE, the program can be requested. The current version of SPADE is "SPADE  4.1.35" (November 2023). The changelog file of SPADE can be read by attaching SPADE.RIVM and then type command spade.news()