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Developing an FFQ: A 10-Step Guide
- 1. Developing a Food Frequency Questionnaire: Step-by-Step Guide Mohd Razif Shahril, PhD School of Nutrition and Dietetics Faculty of Medicine and Health Sciences Universiti Sultan Zainal Abidin E-mail: razifshahril@yahoo.com / razifshahril@unisza.edu.my
- 2. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N Food Frequency Questionnaire • A food frequency questionnaire (FFQ) is a common method used to assess individual long- term dietary intake of foods and nutrients. • The questionnaire elicit a subjectively reported “usual frequency” of consuming an item from a list of foods (Willett 1998).
- 3. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N Step 1: Outlining the Target • Purpose of developing this FFQ? ▫ Assessing habitual intake. Time frame? ▫ Correlate with disease risk? • Who is the user or target population? ▫ Children? Adults? Elderly? • Type? ▫ Self-administered? Computerized? • What type of data targeted? ▫ Energy, protein, total fat, carbohydrate, other nutrients ? ▫ Food item/food groups servings per day? ▫ Food item/food groups frequency of intake?
- 4. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N Step 2: Pooling Food Intake Data • Collect 24hr Diet Recall from a representative sample of population • How many sample needed? ▫ n=500 (Jayawardena 2012), n=600 (Kobayashi 2010), n=800-1000 (Shahar 2003) • What data to be pooled? ▫ List of food items (raw data) ▫ Reported intake of food items (gram) ▫ Energy and nutrient intake of each subject • Is there any important unreported food items left-out? (ask the experts) e.g. Alcohol? Supplements? Ethnic foods?
- 5. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N Step 3: Aggregating Food Items • Conceptually similar foods aggregated into groups on the basis of their fat, carbohydrate, protein, dietary fibre and energy content per portion eaten. • Fruits and vegetables aggregated on the basis of their dietary fibre, vitamins and minerals content per portion. ▫ Conceptually similar foods are food items sharing features of both nutritional content and manner of serving. • Quality control of aggregated food items ▫ Examine range of fat and energy content per portion and look for outliers ▫ Sent the food items for evaluation and feedback from professional and lay person
- 6. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N Step 4: Selecting Food Items • Remove foods reported by less than 15 person. • Identification of foods contributing to between- person variation for each nutrients ▫ Foods in the model that explained 90% of the between-person variability were considered for the final questionnaire. ▫ Using stepwise multiple regression analysis. • Traditional method by Block et al. (1986) by ranking of food items based on the percentage of nutrients that each food item contributed to the total nutrient intake of all the subjects ▫ Cut-off 90% contribution, analysis using MS Excel
- 7. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N Step 5: Develop Nutrient Database • Source of database? • Depending on types of nutrients included in FFQ ▫ Basic – Malaysian Food Composition Table (Tee et al. 1997) ▫ Advanced – USDA Database, Singapore Food Facts • Nutrition Information Panels of commercial food products • Mixed dishes – standard recipe calculation (verified by professional) – cook, weight, analyze
- 8. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N Step 6: Determine Portion Size • Standard reference size ▫ Mean portion size data from subjects in FFQ development phase • Small, Medium, Large size ▫ Small = 25th percentile, ▫ Medium = Median, ▫ Large = 75th percentile • Photograph?
- 9. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N Step 7: Put Everything Together • How to measure kuah? ▫ E.g. Kari ayam, how much ayam, how much kuah? • Cooking method? ▫ Various types of vegetables but similar cooking method. How to measure? Type of oil used? • Cognitive aspects to help users estimate intake. • Cross checking and adjustment item. • Seasonal or festival dietary habits? • How is frequency of intake estimated? E.g. ▫ 2 times per week OR ▫ 1 – 3 times per week • Machine readable form?
- 10. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N Example:
- 11. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N Example:
- 12. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N Step 8: Test for Acceptance • Test the newly developed for face validity among users with the same demography, n= 25 – 30 (Jayawardena 2012) • Ask expert opinion
- 13. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N Step 9: Refine • Improve FFQ based results from Step 8. • Document changes and the reason for change. • Test for acceptance again
- 14. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N Step 10: Reliability and Validity Study • Reliability ▫ How good is the FFQ in giving a reproducible data of dietary intake • Validity ▫ How good is the FFQ in assessing nutrient intake compared to a reference method
- 15. S C H O O L O F N U T R I T I O N A N D D I E T E T I C S • U N I V E R S I T I S U L T A N Z A I N A L A B I D I N THANK YOU