This section describes how to use SAS to identify food group sources of nutrients along with standard errors. To illustrate this, food sources of calcium are identified for the whole population, ages 2 and older, for 2001-2004. In this example, a simplistic food grouping scheme based on the first digit of the USDA food codes, was used for illustrative purposes.
Create a folder to save the dataset, list the contents of each dataset, and create a dataset comprised of 4 years of data. (Program not shown. See the full program in Additional Resources for more information.)
Sort and then merge the demographic and individual food intake datasets. Create new variables, as needed. Note that the food groups are simply characterized by first digit of individual food code: milk and milk products; meat, poultry, fish and mixtures; eggs; legumes, nuts and seeds; grain products; fruits; vegetables; fats, oils and salad dressings; and sugar, sweeteners and beverages. (Program not shown. See the full program in Additional Resources for more information.)
* The SURVEYFREQ procedure in SAS calculates the weighted
contribution of ;
* calcium from each food
group. ;
*
;
* Note that for this analysis, only the data for INCOH=1 is of
interest. ;
* However, this code will also generate data for INCOH=0.
;
*-------------------------------------------------------------------------;
data=FDSRC;
strata
SDMVSTRA;
cluster SDMVPSU;
weight
WTD_CALC;
tables
FOODGRP*INCOH;
title
"Percent calcium by food group, using PROC SURVEYFREQ" ;
;
The SURVEYFREQ Procedure
Data Summary
Number of Strata 30
Number of Clusters 60
Number of Observations 274168
Number of Observations Used 257658
Number of Obs with Nonpositive Weights 16510
Sum of Weights 2.49766E11
Broad food grp based on 1st digit of USDA food code
Weighted Std Dev of Std Error of
FOODGRP Frequency Frequency Wgt Freq Percent Percent
----------------------------------------------------------------------------------------------------
Milk & Milk Products 40207 1.1581E11 6226455948 46.3673 0.4185
Meat, Poultry, Fish & Mixtures 29350 1.77625E10 994172188 7.1117 0.2178
Eggs 4137 4642738173 225930307 1.8588 0.0680
Legumes, Nuts and Seeds 6102 4129696674 251569993 1.6534 0.0707
Grain Products 63548 7.35244E10 3425294440 29.4373 0.3696
Fruits 21721 8017836305 405334291 3.2101 0.1207
Vegetables 41477 1.20417E10 582319600 4.8212 0.1317
Fats, Oils & Salad Dressings 9075 792221049 51116840 0.3172 0.0162
Sugar, Sweeteners & Beverages 42041 1.3045E10 607625180 5.2229 0.1254
Total 257658 2.49766E11 1.1986E10 100.000
---------------------------------------------------------------------------------------------------- Highlights from the output include:
The frequency counts in this analysis represent the number of reports of foods that contain calcium, by food group. It is important to note that the frequencies in the SAS output to do not match those in the SUDAAN output because of special procedures required in SAS to conduct this analysis (see Task 3 in “Module 11: Weighting” in the Continuous NHANES Tutorial for more information). However, the unweighted frequencies are not important to this analysis and they do not represent an estimate for the U.S. population. Therefore, they can be ignored.
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