Assessing dietary variety in children: development and validation of a predictive equation.
BACKGROUND
Research indicates that the length of time needed to describe dietary diversity is approximately 2 weeks. This is the first study conducted to develop a dietary variety measurement tool that is sensitive to the effect of time on dietary variety without the burden of gathering data for 2 weeks.


OBJECTIVE
To determine whether 3 days of 24-hour dietary recall logs collected during a 15-day period would predict food variety as well as 15 consecutive days. The study also determined which set of 3 days (consecutive vs interval days) within a 15-day period would better predict 15-day food variety.


METHODS
Prospective survey of the dietary practices of children.


METHODS
Seventy-two children aged 9 to 12 years attending fourth and fifth grades in a public elementary school in a Midwestern town in the fall of 2005.


METHODS
Predicted 15-day cumulative dietary variety score from 3 consecutive days and 3 interval days of dietary data.


METHODS
Two prediction models were obtained from multiple linear regression analyses in which natural log-transformed (log(e)) 15-day variety scores were regressed on log(e) 3-day variety scores (consecutive and interval days). The ability of each model to predict the 15-day cumulative variety score was assessed by comparisons of mean bias, mean-squared error, coefficient of determination (R(2)), and Pearson product-moment correlation coefficients.


RESULTS
Three days of dietary data accurately estimated dietary variety over time for this sample of 9- to 12-year-old children using the predictive equation generated in this study. Three interval days predicted 15-day food variety more precisely than 3 consecutive days.


CONCLUSIONS
The predictive equation is accurate in estimating food variety over time for this population and, if validated in independent samples, could be applied to similar populations.
Falciglia
Grace A
GA
Department of Nutritional Sciences, University of Cincinnati, College of Allied Health Sciences, 3202 Eden Ave, Cincinnati, OH 45267-0394, USA. grace.falciglia@uc.edu
Horner
Stacie L
SL
Liang
Juan
J
Couch
Sarah C
SC
Levin
Linda S
LS