Simple measures of dietary variety are associated with improved dietary quality.
The objective of this study was to identify a measure of dietary variety that was associated with improved dietary quality and easily understood by consumers. Dietary quality was measured by nutrient adequacy and intakes of added sugars, saturated fat, cholesterol, and sodium. We developed four definitions of dietary variety: (a) a count of basic commodities consumed; (b) a count of food codes reported; (c) a count of five Food Guide Pyramid (FGP) food groups consumed; and (d) a count of 22 FGP subgroups consumed. The analysis sample included 4,964 men and 4,797 women aged 19 years and older who participated in the Continuing Survey of Food Intakes by Individuals 1994-96. For each day of dietary data, we examined associations of each type of dietary variety with several measures of dietary quality using Spearman's correlations and multivariate linear regression models. After adjusting for energy intake and the number of FGP food group servings, all types of dietary variety were positively associated with mean nutrient adequacy across 15 nutrients, but associations were strongest for commodity-based variety and for 22 FGP subgroup consumption variety. Likewise, all variety measures were inversely associated with intakes of added sugars and saturated fat, with commodity-based variety and 22 FGP subgroup variety the strongest. We conclude that variety measured using 22 FGP subgroups is preferable because it is a good predictor of dietary quality, is relatively simple to calculate, and is easy to explain to consumers.
Murphy
Suzanne P
SP
Cancer Research Center of Hawaii, Honolulu 96813, USA. suzanne@crch.hawaii.edu
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Janet A
JA
Wilkens
Lynne R
LR
Basiotis
P Peter
PP
Carlson
Andrea
A
White
Kami K L
KK
Yonemori
Kim M
KM
D000328:Adult; D017677:Age Distribution; D004032:Diet / Q000592:standards*; D004034:Diet Surveys; D002149:Energy Intake; D005260:Female; D005502:Food / Q000145:classification* / Q000592:standards; D006801:Humans; D016014:Linear Models; D008297:Male; D018673:Nutrition Policy; D009751:Nutritional Requirements; D009753:Nutritive Value; D011237:Predictive Value of Tests; D017678:Sex Distribution; D018709:Statistics, Nonparametric; D014481:United States