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Food-frequency questionnaires: a review of their design, validation and utilisation
J E Cade1, V J Burley, D L Warm
1Nutritional Epidemiology Group, University of Leeds, Leeds LS2 9JT, UK. j.e.cade@leeds.ac.uk
Nutrition Research Reviews
|December 17, 2008
Summary
This review examined food-frequency questionnaires (FFQ), finding that larger FFQs and interviewer administration improve nutrient correlation. Recommendations for FFQ design, validation, and use were established.
Area of Science:
- Nutrition science
- Epidemiology
- Dietary assessment methodology
Background:
- Food-frequency questionnaires (FFQ) are widely used for dietary assessment.
- Existing literature on FFQ design, utilization, and validation requires synthesis.
- Understanding optimal FFQ characteristics is crucial for accurate dietary research.
Purpose of the Study:
- To conduct a semi-systematic literature review on FFQ design, utilization, and validation.
- To identify key factors influencing FFQ accuracy and application.
- To develop expert consensus and recommendations for FFQ development and use.
Main Methods:
- Searched databases for FFQ studies from 1980 to 1999.
- Reviewed 227 validation studies and 164 utilization studies.
- Evaluated design parameters like portion size description, administration method, and number of items.
- Assessed validation techniques, comparing FFQ to other methods and biomarkers.
Main Results:
- Larger FFQs and interviewer administration generally yielded higher nutrient correlations.
- Self-defined portion sizes showed higher mean correlations.
- Calcium and fat showed highest correlation coefficients; Vitamin A and vegetables showed lowest.
- FFQs were predominantly used in cross-sectional surveys, often disease-specific.
Conclusions:
- FFQ design significantly impacts data quality; larger, interviewer-administered questionnaires with clear portion size descriptions are preferable.
- Current validation practices often rely on correlation coefficients, with limited use of biomarkers.
- Expert consensus provides recommendations for optimizing FFQ development, validation, and application in nutritional research.
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