Agreement on nutrient intake between the databases of the First National Health and Nutrition Examination Survey and the ESHA Food Processor

Am J Epidemiol. 2002 Jul 1;156(1):78-85. doi: 10.1093/aje/kwf003.

Abstract

The objective of this study was to assess agreement on nutrient intake between the nutrient database of the First National Health and Nutrition Examination Survey (NHANES I) and an up-to-date (December 1998) nutrient database, the ESHA Food Processor. Analysis was conducted among 11,303 NHANES I participants aged 25-74 years in 1971-1975 who had undergone dietary assessment. A list of all unique foods consumed was obtained from a single 24-hour dietary recall questionnaire administered during the baseline NHANES I visit. Foods on the list were matched to foods in the ESHA Food Processor software. Agreement between participants' nutrient intakes as calculated with the NHANES I and ESHA nutrient databases was assessed using intraclass correlation analysis, linear regression analysis, and graphic methods. Intraclass correlation analysis demonstrated excellent concordance between most nutrient intakes, with coefficients above 0.95 for intakes of energy, carbohydrates, protein, cholesterol, and calcium; coefficients between 0.90 and 0.95 for intakes of total fat, saturated fat, potassium, and vitamin C; and coefficients of approximately 0.85 for intakes of sodium and vitamin A. Graphic methods and regression analyses also showed good-to-excellent correspondence for most nutrients. These findings support the validity of expanding existing nutrient intake databases to explore current hypotheses, provided that food formulation, enrichment, and fortification practices have not changed substantially over time.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Aged
  • Cohort Studies
  • Data Collection / methods
  • Databases, Factual*
  • Female
  • Humans
  • Linear Models
  • Male
  • Mental Recall
  • Middle Aged
  • Nutrition Surveys*
  • Reproducibility of Results
  • Software
  • Statistics, Nonparametric
  • United States