Creme Global

The Effect Of Diversity In People`s Eating Habits

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Courtesy of Creme Global

The Effect Of Diversity In People's Eating Habits

There are thousands of foods available on the market, with thousands of brands and hundreds of potential hazards in the food chain. Where do you start?

People eat different things on different days, and different people have very different eating habits, not least during holiday seasons. This is natural variability in people's habits and has to be handled in a food safety or benefits assessment. This natural variability is different to uncertainty in that it is not a measurement error and can not be reduced by further measurements. It is a natural effect of people's choices. This variability is included in an exposure assessment if the full food consumption survey is considered in the analysis.

Food consumption surveys are large data sets that take into account the populations' habits over a period of time, including gathering data from different seasons to take into account people's changing eating habits in different seasons.

An effective food safety assessment system should allow you to manage the complexity in the wide range of foods on the market via a food grouping mechanism. Food groups are lists of foods with similar properties either in terms of their composition or their chemical hazard probabilities.

These food groups allow you to handle the large amount of data which emerges from the range of foods involved in an exposure assessment. Once the food groups have been created (for example, 'apple' food group, 'milk products' food group, etc.) chemical concentrations can be linked directly to the food groups and therefore be assigned automatically to the wide range of foods present in the diary. The researcher does not have to spend time assigning concentrations for each food individually.

Creating the food groups to bring order to the wide diversity of food types on the market is an important task. An effective food system should allow the facility to help you to mine or search the data for specific foods. For example, in order to create an apple food group, you may want to search for the word 'apple' in the entire food database including recipe ingredients so that all of the eating habits which are relevant to 'apple' can be placed in the same food group.

Food groups provide a vital link that allows you to manage the diversity in eating events of various populations and to assign ingredients or chemical concentrations in your exposure assessment effectively. CREMe provides comprehensive data mining tools that enable you to automatically create these food groups.

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