Improvement of comparability of dietary intake assessment using currently available individual food consumption surveys.
BACKGROUND
Food consumption data are used for monitoring dietary indicators of health. In this context, there is a need for comparable (individual) data at the European level. The preference is to perform a pan-European survey able to generate data collected on the same basis. Until this can be realized, the existing data have to be made as comparable as possible.


OBJECTIVE
To identify solutions; to make existing food consumption data from nationally representative databases more comparable.


METHODS
General guidelines for the comparison of food intake data using currently available data were discussed and agreed upon in the EFCOSUM project team.


CONCLUSIONS
Criteria were assessed with regard to the population involved, age of the survey, method of data collection, duration of the survey, the food classification system and the food composition tbl Based on these criteria, a maximum of 15 countries could provide food consumption data that can be made comparable at the individual level for the adult population. It is recommended to make data comparable at the food level, starting with vegetables (excluding potatoes), fruits (excluding fruit juices), fish (including shellfish) and bread. Comparability of foods is only possible at the 'raw edible' ingredient level. To achieve this, a large amount of work has to be undertaken. The approach of the EFG (Euro Food Groups) system is considered to be the best compromise between the different classification systems. Comparability at the nutrient level has to wait for the availability of a European Nutrient Database, like the one that is being developed within the EPIC context.
Verger
Ph
P
INRA, Paris Cedex, France. philippe.verger@paris.inra.fr
Ireland
J
J
Møller
A
A
Abravicius
J A
JA
De Henauw
S
S
Naska
A
A
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001939:Bread; D002648:Child; D002675:Child, Preschool; D003625:Data Collection / Q000379:methods* / Q000592:standards; D003627:Data Interpretation, Statistical; D016208:Databases, Factual / Q000592:standards*; D004034:Diet Surveys; D002149:Energy Intake; D005062:European Union; D005260:Female; D005502:Food / Q000145:classification*; D005504:Food Analysis / Q000592:standards; D005638:Fruit; D006801:Humans; D007223:Infant; D008297:Male; D008875:Middle Aged; D017747:Seafood; D014675:Vegetables