title: The impact of conventional dietary intake data coding methods on foods typically consumed by low-income African-American and White urban populations.
abstract: OBJECTIVE
  Analysing dietary data to capture how individuals typically consume foods is dependent on the coding variables used. Individual foods consumed simultaneously, like coffee with milk, are given codes to identify these combinations. Our literature review revealed a lack of discussion about using combination codes in analysis. The present study identified foods consumed at mealtimes and by race when combination codes were or were not utilized.
  
  
  METHODS
  Duplicate analysis methods were performed on separate data sets. The original data set consisted of all foods reported; each food was coded as if it was consumed individually. The revised data set was derived from the original data set by first isolating coded foods consumed as individual items from those foods consumed simultaneously and assigning a code to designate a combination. Foods assigned a combination code, like pancakes with syrup, were aggregated and associated with a food group, defined by the major food component (i.e. pancakes), and then appended to the isolated coded foods.
  
  
  METHODS
  Healthy Aging in Neighborhoods of Diversity across the Life Span study.
  
  
  METHODS
  African-American and White adults with two dietary recalls (n 2177).
  
  
  RESULTS
  Differences existed in lists of foods most frequently consumed by mealtime and race when comparing results based on original and revised data sets. African Americans reported consumption of sausage/luncheon meat and poultry, while ready-to-eat cereals and cakes/doughnuts/pastries were reported by Whites on recalls.
  
  
  CONCLUSIONS
  Use of combination codes provided more accurate representation of how foods were consumed by populations. This information is beneficial when creating interventions and exploring diet-health relationships.
authors.affiliation: 1Laboratory of Epidemiology and Population Sciences,National Institute on Aging,National Institutes of Health,Baltimore,MD USA.
authors.forename: Marc A
authors.initials: MA
authors.lastname: Mason
authors.affiliation: 2Department of Behavioral Health and Nutrition,010 Carpenter Sports Building,University of Delaware,Newark,DE 19716,USA.
authors.forename: Marie
authors.initials: M
authors.lastname: Fanelli Kuczmarski
authors.affiliation: 2Department of Behavioral Health and Nutrition,010 Carpenter Sports Building,University of Delaware,Newark,DE 19716,USA.
authors.forename: Deanne
authors.initials: D
authors.lastname: Allegro
authors.affiliation: 1Laboratory of Epidemiology and Population Sciences,National Institute on Aging,National Institutes of Health,Baltimore,MD USA.
authors.forename: Alan B
authors.initials: AB
authors.lastname: Zonderman
authors.affiliation: 1Laboratory of Epidemiology and Population Sciences,National Institute on Aging,National Institutes of Health,Baltimore,MD USA.
authors.forename: Michele K
authors.initials: MK
authors.lastname: Evans
mesh_terms: D001741:Black or African American; D059019:Clinical Coding; D066264:Datasets as Topic; D015930:Diet Records; D004034:Diet Surveys / Q000379:methods*; D002149:Energy Intake; D005260:Female; D005502:Food / Q000145:classification*; D006801:Humans; D008297:Male; D062407:Meals; D008875:Middle Aged; D011203:Poverty; D014481:United States; D014505:Urban Population; D044465:White People
keywords: African Americans; Dietary assessment methods; Eating occasion; Food coding; Food preferences