. "7 Specific Applications: Assessing Nutrient Intakes of Groups Using the Dietary Reference Intakes." Dietary Reference Intakes: Applications in Dietary Assessment. Washington, DC: The National Academies Press, 2000.
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DRI DIETARY REFERENCE INTAKES: Applications in Dietary Assessment
other factors that affect nutrient intake. This analysis involves comparing changes to the tail of the intake distributions. In the context of the FSP, the question is whether the proportion of individuals with usual intakes below the EAR is different between FSP participants and nonparticipants, after controlling for other factors that affect nutrient intake.
A proposed approach that enables users to control for effects ofpotentially confounding variables through regression analysis isoutlined below, using the FSP as an example. The required data include:
one day of intake data for each person
two independent days of intake for at least a subsample of each group(however, one day of intake data on each individual suffices if onlythe difference in group mean intake is of interest)
each person's values for each of the potentially confounding variables (e.g.,income, education, age, etc.), or at least a reliably imputed value,as well as an indicator for FSP participation status (e.g., participant,non-participant).
Step 1. First, a regression equation is fitted to the observed intake data. Variables in the regression model would include FSP participation (coded as 0 or 1) and any other variables thought to affect intakes. For example, if age were the only other variable considered relevant, the equation would be:
The fitted regression equation would contain estimated values for the constant and the regression coefficients for FSP participation and for any other variable that was included in the model. These estimated values are denoted as b1, b2, b3, etc.
Step 2. Given the estimated regression coefficients from the first step, a standard predicted intake value is generated for each individual by inserting the values of the covariates for the individual, appropriately centered, into the fitted regression equation. The modifier “standard” is used because in this step, one standardizes individual intakes to those that would be observed if everyone in the sample had been, for example, the same age and had the same income. Suppose that the sample consisted of all women aged 20 to 50. A good centering or standardizing age would be 35, the midpoint of