Objective: The main objective of the study was to develop appropriate dietary assessment instruments for the French Mediterranean region and to validate the measurements they provide.
Subjects and methods: Three different assessment methods were submitted to a sample of 150 male and female volunteers. 98 completed the protocol, which consisted of a 4 d weighed dietary record (PETRA) and a 7 d estimated-diet record (S7) based on a check list and a set of photographs, both these records being completed once in each season of the year, and a semi-quantitative (standard portion) food-frequency questionnaire (FFQ) including questions eliciting socio-demographic and anthropometric data, which was completed once only. The days when PETRA was used to evaluate food consumption coincided with the first 4 d of S7 (S4).
Results: Validation was based on nutrients and foods. Energy-adjusted Pearson correlation coefficients between S4 and PETRA ranged from 0.32 for vitamin E to 0.81 for vitamin C (mean: 0.65 for 21 nutrients). There was practically no misclassification in opposite extreme quartiles. Spearman correlation coefficients ranged from 0.63 for fish and sea-food to 0.90 for wine (mean: 0.76 for 16 food groups). There was practically no misclassification in opposite extreme quartiles. De-attenuated energy-adjusted Pearson correlation coefficients between FFQ and S7 ranged from 0.22 for proteins and monounsaturated fatty acids to 0.80 for iron (mean: 0.45). 10% or less of subjects were misclassified in opposite extreme quartiles (except for vitamin C, 12%). Spearman correlation coefficients ranged from 0.25 for green-yellow-red raw vegetables to 0.76 for wine (mean: 0.42). 8% or less of subjects were misclassified in opposite extreme quartiles (except for citrus fruit, 11%).
Conclusions: Portion estimation using the set of photographs was validated by the correlation between S4 and PETRA for both nutrients and foods. The FFQ provides a reasonably reliable measure of macronutrient intake and a good measure of micronutrient intake when compared with the data in the literature. It performs less well for food intake. Better results can be achieved for FFQ: (i) by using the set of photographs instead of standard portions and (ii) by adding further questions on foods which are insufficiently covered.