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conceptualization and memory errors

principal error is likely to be underreporting within certain subgroups, and any validation study needs to address this. Issues regarding distortion of diet are more difficult to identify, however. Work has been carried out to identify some of the errors associated with perception, conceptualization, and memory in relation to assessment of food portion sizes. Agreement between methods is no guarantee of validity. If the two methods are biased in the same way (e.g., using a diet history to validate a short food frequency questionnaire), then the observed level of agreement is likely to overstate the validity of the new method. If the validation is based on repeated measures and the errors in the reference assessment are repeated (e.g., validating a food frequency questionnaire against repeat 24-h recalls), then the level of agreement between the two methods is likely to underestimate the true correlation between the test measure and the truth because the true variance of diet will be underestimated by the reference measure.

Some types of bias may influence reporting in a similar way in all subjects. For example, if a food frequency questionnaire does not ask for sufficient detail about tropical fruit consumption in a survey of West Indian families living in London, then all responses are likely to be biased in the same way. This will result in nondifferential misclassification: Everyone's intake of tropical fruit (and hence vitamin C and carotene intake) is likely to be similarly misclassified. If, on the other hand, the nature of the bias is likely to be related to individual characteris-tics—for example, West Indian women overreport their tropical fruit consumption compared to West Indian men—then the tropical fruit intake of men and women will be misclassified in different ways in different subgroups. This is known as differential misclassification. If the risks for men and women are being compared in a diet-disease analysis, the errors in the estimates of those risks will not be the same for both groups.

There are many factors in addition to body size or gender that may influence the ability of a dietary measure to estimate accurately the level of food consumption or nutrient intake. Table 3 lists the potential confounders of good dietary reporting that may affect validation studies. If there is concern about misclassification in one group (e.g., smokers) being different from misclassification in another group (e.g., nonsmokers), then validation must identify the extent of misclassification in the two groups independently so that it can be compensated for in any subsequent analyses. It is therefore important to measure all of the potential confounders that may be a source of misclassification (differential or nondifferential).

Table 3 Factors that may influence the reliability and validity of dietary assessments and that may need to be measured in a validation study

Related to the subject Related to the measuring process

Table 3 Factors that may influence the reliability and validity of dietary assessments and that may need to be measured in a validation study

Related to the subject Related to the measuring process

Age

Portion size

Gender

Interviewer

Height, weight, etc.

Learning effects

Region

Recency effects

Social class

Lag time

Education

Number of foods on an FFQ

Language

Nutrient database

Culture and ethnic

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