Use of semiquantitative food frequency questionnaires to estimate the distribution of usual intake.
The authors consider whether semiquantitative food frequency questionnaires can be used to survey a population to estimate the distribution of usual intake. They take as an assumption that, if they were possible to obtain, the mean of many food records or recalls would be an accurate representation of an individual's usual diet. They then assume that nutrient intake as measured by a questionnaire follows a linear regression model when regressed against the usual intake of that nutrient. If the coefficients in this regression relation were known, then the distribution of usual intake could be constructed from the responses to the questionnaire. Since one generally does not know the values of the coefficients, they need to be estimated from a calibration study in which respondents complete the questionnaire together with multiple food records or recalls. This can be done either through an internal subset of the data or through an independent external study. With an internal substudy, the authors find that food frequency questionnaires typically provide little information about the distribution of usual intake in addition to that obtained from the multiple records or recalls in the substudy. When the substudy is external, if it is small then having very large numbers of subjects completing food frequency questionnaires in the survey is no more efficient than having a few subjects completing food records or recalls. However, if the external substudy is large and accurately characterizes the relation between the questionnaire response and usual intake, food frequency questionnaires can provide a cost-efficient way of estimating the distribution of usual intake. These results do not apply to the different problem of correcting relative risks for the effects of measurement error.
Carroll
R J
RJ
Department of Statistics, Texas A&M University, College Station, USA.
Freedman
L S
LS
Hartman
A M
AM
D015982:Bias; D002138:Calibration; D003362:Cost-Benefit Analysis; D015930:Diet Records; D004034:Diet Surveys; D004041:Dietary Fats / Q000008:administration & dosage; D002149:Energy Intake; D005260:Female; D006801:Humans; D016014:Linear Models; D015203:Reproducibility of Results; D011795:Surveys and Questionnaires / Q000191:economics / Q000592:standards*; D016387:Women's Health
D004041:Dietary Fats