1. Status on statistical methods in dietary assessment and Multiple Source Method Heiner Boeing German Institute of Human Nutrition Potsdam- Rehbrücke Department of Epidemiology

2. Dietary assessment „Proper assessment of dietary intakes is critical in epidemiologic research that examines the relationships between diet and disease risk“ NCI Web site

3. Long term average dietary assessment The concept of long-term average daily intake, or "usual intake," is important because diet-health hypotheses are based on dietary intakes over the long term. However, until recently, sophisticated efforts to capture this concept have been limited at best. NCI Web site

4. Dietary assessment of usual intake for large-scale prospective studies

5. Concepts of proper dietary assessment in cohort studies Correction of the effect measures (Validation studies) Use of a reference instrument in a subgroup to apply information to the full cohort (calibration/standardisation) Best estimate of individual intake in the full cohort (reduction of assessment bias)

6. Calibration Referenz Instrument Calibrated Instrument

7. Consequences of calibration Assessment Instrument Exposition time Ranking Bias FFQ Long term Good ranking Large bias Reference instrument Short term Bad ranking Small bias Calibrated FFQ Long term Good ranking Small bias

8. How to calibrate Use of a reference instrument (R) Selection of a subgroup with simultaneous use of Q and R Determination of a mathematical function for the Q value that fit the R value (Calibration function)

9. Calibration functions Calibration function 1) Linear regression calibration (1 day) 2) Linear regression calibration (2 days) 3) Use of standardisation functions (mean, variance, skewness, curtosis) R = Q +  Q cal = sqrt(q*VAR(R)/VAR(Q))*(Q-AM(Q))+AM(R) f(Q) Calibration does not change ranking by Q q = 1/sqrt(1+VAR INTRA /VAR INTER )

10. Multiple Source Method

11. Structure of the algorithm Usual intake = probability of a consumption day * usual intake on consumption day Usual intake = probability of a consumption day * usual intake on consumption day Observed positive daily intake data Observed consumption days Probability of consumption Usual intake on consumption days First step Second step Third step Parallel steps

12. First step Observed consumption days Probability of consumption Partition of observations Transformation Shrinkage of transformed data Back transformation Composition of components

13. Second step Observed positive daily intake data Usual intake on consumption days Partition of observations Transformation Shrinkage of transformed data Back transformation Composition of components

14. Third step Usual intake = usual intake on consumption day * probability of a consumption day Usual intake = usual intake on consumption day * probability of a consumption day Usual intake on consumption days Probability of consumption

15. Example fresh fruits

16. Example fish

17. Example breakfast cereals

18. Summary There are several strategies available to improve dietary assessment in cohort studies There is currently a lack of empirical data that have compared the strategies The Multiple Source Method is a new promising tool for dietary assessment in epidemiological studies