title: Assessing dietary variety in children: development and validation of a predictive equation.
abstract: 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.
authors.affiliation: Department of Nutritional Sciences, University of Cincinnati, College of Allied Health Sciences, 3202 Eden Ave, Cincinnati, OH 45267-0394, USA. grace.falciglia@uc.edu
authors.forename: Grace A
authors.initials: GA
authors.lastname: Falciglia
authors.forename: Stacie L
authors.initials: SL
authors.lastname: Horner
authors.forename: Juan
authors.initials: J
authors.lastname: Liang
authors.forename: Sarah C
authors.initials: SC
authors.lastname: Couch
authors.forename: Linda S
authors.initials: LS
authors.lastname: Levin