A brief dietary screener: appropriate for overweight Latino adolescents?

J Am Diet Assoc. 2009 Apr;109(4):725-9. doi: 10.1016/j.jada.2008.12.025.

Abstract

The objective of this article is to assess whether a brief dietary screener designed to assess fast-food and beverage consumption in a primarily white, adolescent population, is also valid and reliable in an overweight, adolescent Latina population. This screener was developed by the University of Minnesota to assess beverage consumption (nine items) and fast-food consumption (13 items) in normal weight, primarily white adolescents (ages 11 to 18 years). Thirty-five at risk for overweight (body mass index > or = 85th percentile) adolescent (ages 14 to 17 years) Latina females were recruited from East Los Angeles, CA, and completed the screener twice, approximately 7 to 14 days apart, during the fall of 2007. Dietary intake was also assessed by 3-day diet records. Spearman correlation and simple kappa were employed for test-retest assessment and comparisons between the screener and the records. Test-retest assessment yielded a mean Spearman or kappa statistic of 0.49 with 17 of 21 responses being significant (P<0.05). Validity was much lower and yielded a kappa statistic of only 0.08 and no responses were significant. Although this screener appeared to be a valid and reliable measure to assess beverage and fast-food consumption in a primarily white, adolescent population, it does not appear to be appropriate for an overweight Latina female adolescent population.

Publication types

  • Research Support, N.I.H., Extramural
  • Validation Study

MeSH terms

  • Adolescent
  • Adolescent Nutritional Physiological Phenomena / physiology*
  • Beverages / statistics & numerical data
  • Body Mass Index
  • Diet Records
  • Diet Surveys*
  • Energy Intake / physiology
  • Feeding Behavior
  • Female
  • Hispanic or Latino*
  • Humans
  • Los Angeles
  • Mass Screening / standards*
  • Nutrition Assessment*
  • Overweight / diagnosis
  • Overweight / epidemiology
  • Reproducibility of Results
  • Restaurants
  • Sensitivity and Specificity
  • Statistics, Nonparametric
  • Weight Gain