Policy Research for Front of Package Nutrition Labeling: Developing and Testing a Summary System Algorithm. 4.3.2 Plots of Predicted HEI Scores

05/01/2011

Figure 4-4 illustrates the prediction of HEI scores by the covariates only (age, gender, and race), which explained 4.17% of the variance in HEI scores. To illustrate good prediction of the algorithm score at the high and low ends of actual HEI scores, Figure 4-5 displays HEI scores predicted by the modified algorithm on a per 100 kcal basis with vitamin C added.


Figure 4-4. Plot of Predicted HEI Scores with Covariates Only (Age, Gender, Race)

The figure shows a scatterplot for the predicted HEI scores (on the vertical axis) from a regression model with only the covariates, age, gender, and race as independent variables. The actual HEI scores are on the horizontal axis. The diagonal line shows theoretical perfect prediction of the HEI. The model showed that the covariates alone predicted only 4.17% of variation in the HEI. Data are from 16,587 participants in NHANES 2005 to 2008.

The figure shows a scatterplot for the predicted HEI scores (on the vertical axis) from a regression model with only the covariates, age, gender, and race as independent variables. The actual HEI scores are on the horizontal axis. The diagonal line shows theoretical perfect prediction of the HEI. The model showed that the covariates alone predicted only 4.17% of variation in the HEI. Data are from 16,587 participants in NHANES 2005-2008.



Figure 4-5. Plot of Predicted HEI Scores with Modified Algorithm on per 100 Kcal with Vitamin C Added

The figure shows a scatterplot for the predicted HEI scores (on the vertical axis) from a regression model for a modified algorithm on a per 100 kcal basis with vitamin C added (NDS4CKCAL). The actual HEI scores are on the horizontal axis. The diagonal line shows theoretical perfect prediction of the HEI. The model showed that the algorithm accounted for 45.59% of variation in the HEI. Agreement was reasonably good at high and low HEI values, as shown by points lying near the diagonal line. Data are from 16,587 participants in NHANES 2005 to 2008.

The figure shows a scatterplot for the predicted HEI scores (on the vertical axis) from a regression model for a modified algorithm on a per 100 kcal basis with vitamin C added (NDS4CKCAL). The actual HEI scores are on the horizontal axis. The diagonal line shows theoretical perfect prediction of the HEI. The model showed that the algorithm accounted for 45.59% of variation in the HEI. Agreement was reasonably good at high and low HEI values, as shown by points lying near the diagonal line. Data are from 16,587 participants in NHANES 2005-2008.