title: Dietary intake estimates in the National Health Interview Survey, 2000: methodology, results, and interpretation.
abstract: OBJECTIVE
  To describe the implementation of the Multifactor Screener in the 2000 National Health Interview Survey (NHIS); to provide intake estimates for fruits and vegetables, fiber, and percentage of energy from fat by various demographic and behavioral characteristics; and to discuss the strengths and weaknesses of the method.
  
  
  METHODS
  The 2000 NHIS was conducted in 38,632 households in a clustered sample representative of the 48 contiguous states in the United States. The Cancer Control Module was administered to adults (18 years and older) and included 17 dietary intake questions.
  
  
  METHODS
  After excluding individuals with missing data or unlikely values on the diet questions, we computed individual intake of servings of fruits and vegetables, percentage of energy from fat, and grams of fiber. We estimated median intakes and distributions of intakes using adjusted variance estimates. We present bivariate relationships between diet and demographics and diet and behavioral characteristics in almost 30,000 adults in the United States.
  
  
  RESULTS
  In general, intakes of these dietary factors were closer to recommendations among well-educated individuals, those engaged in other healthful behaviors, and underweight and normal weight individuals. Latinos had higher intakes of fruits and vegetables (men: 6 servings; women: 4.8 servings) and fiber (men: 23 g; women: 17 g), and generally a lower percentage of energy intake from fat (men: 33.7%; women: 32.1%) than did non-Latino whites (men: 5.4 servings; women: 4.5 servings; men: 19 g; women: 14 g; men: 33.9%; women: 32.0%) and non-Latino blacks (men: 5.4 servings; women: 4.4 servings; men: 19 g; women: 13 g; men: 34.7%; women: 33.5%). The strengths and limitations of the short dietary assessment method are discussed.
  
  
  CONCLUSIONS
  The Multifactor Screener in NHIS, when used in conjunction with external reference data, provides reasonable estimates for three dietary factors and suggests relationships between intakes and other characteristics that are consistent with other data. Thus, these NHIS estimates could provide useful national benchmarks for local surveys using the same instrument.
authors.affiliation: National Cancer Institute, Bethesda, MD 20892, USA. ThompsoF@mail.NIH.GOV
authors.forename: Frances E
authors.initials: FE
authors.lastname: Thompson
authors.forename: Douglas
authors.initials: D
authors.lastname: Midthune
authors.forename: Amy F
authors.initials: AF
authors.lastname: Subar
authors.forename: Timothy
authors.initials: T
authors.lastname: McNeel
authors.forename: David
authors.initials: D
authors.lastname: Berrigan
authors.forename: Victor
authors.initials: V
authors.lastname: Kipnis
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D016000:Cluster Analysis; D004034:Diet Surveys; D004041:Dietary Fats / Q000008:administration & dosage*; D004043:Dietary Fiber / Q000008:administration & dosage*; D004522:Educational Status; D002149:Energy Intake; D005260:Female; D005638:Fruit; D015438:Health Behavior; D006306:Health Surveys; D006630:Hispanic or Latino; D006801:Humans; D007407:Interviews as Topic; D008297:Male; D008875:Middle Aged; D011795:Surveys and Questionnaires; D014481:United States; D014675:Vegetables; D044465:White People
chemical_list: D004041:Dietary Fats; D004043:Dietary Fiber