Usual Dietary Intakes: SAS Macros for Analysis of a Single Dietary Component
Three macros are available to support modeling of a single dietary
component (either consumed nearly every day or episodically):
- MIXTRAN Macro: fits a model to obtain parameter estimates and allows for the evaluation of covariate effects.
- DISTRIB Macro: uses parameter estimates from MIXTRAN and a Monte Carlo method to estimate the distribution of usual intake for a food or nutrient.
- INDIVINT Macro*: uses parameter estimates from MIXTRAN or other appropriate model to predict individual food or nutrient intake for use in a disease model.
* Note that the INDIVINT macro requires SAS IML. The SAS Institute has
reported an error that can occur when running SAS IML in SAS 9.2 TS1MO - the
error relates to variables with missing values. Read the SAS Problem Note and get a link
to the Hot Fix. The problem is fixed in SAS 9.2 TS2M2, and this error is
not encountered in SAS 9.1.3.
The MIXTRAN macro alone is sufficient for testing covariate effects on
intakes of a dietary component. The DISTRIB and INDIVINT macros are generally
used in conjunction with the MIXTRAN macro.
Documentation for all three macros is provided in the User's Guide for Analysis of Usual Intakes: For use
with versions 1.1 of the Mixtran, Distrib and Indivint SAS macros (PDF).
Applications of these macros are described in Tooze et al, 2006 and Kipnis et al, 2009.
To help analysts get started, NCI has developed sample programs and analytic
datasets. These programs employ the various macros in conjunction with
preliminary analytic datasets containing data from the National Health and
Nutrition Examination Survey (NHANES). The first three examples use a dataset
that is based on NHANES 2001-04 data; it includes the addition of balanced
repeated replication (BRR) weights, imputed values for some of the MyPyramid
equivalents data, and some variable names that differ from the names used in
the original NHANES file. The last example uses a dataset based on NHANES
2003-04 data, with a small set of variables used to illustrate the method.