Determination of Nutrient Intakes by a Modified Visual Estimation Method and Computerized Nutritional Analysis for Dietary Assessments

Abstract

Assessing the dietary intake of a military population in the field or in a garrison dining facility presents many problems since data collection cannot interfere with the mission or schedule of the soldier, may be done under widely varying environmental conditions, and is limited by the amount and type of equipment that can be used. In response to this challenge, the modified visual estimation methodology (MVEM) was developed to meet all of the above constraints. This report contains a detailed description of the MVEM, the standardized procedures for training data collectors to be >90% reliable and accurate to within a tenth of a standard portion, and the procedures for analyzing the nutritional data by computer. The computerized nutritional analysis procedures require coding of all food intake data, coding of all recipe preparation data, and analyzing for nutrient intake. Computer analysis of food intake data is not as accurate as chemical analysis; however, these values provide a useful average for population studies, do not delay data processing, and is relatively inexpensive. Using MVEM and observing recipe preparation procedures improve the accuracy of the nutritional analysis information for population dietary assessments. Keywords: Sampling.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1987
Accession Number
ADA192595

Entities

People

  • E. G. Szeto
  • J. C. Buchbinder
  • J. D. Allegretto
  • M. S. Rose
  • T. B. Dugan

Organizations

  • United States Army Research Institute of Environmental Medicine

Tags

Communities of Interest

  • Biomedical
  • Cyber

DTIC Thesaurus Topics

  • Accuracy
  • Chemical Analysis
  • Computer Programming
  • Computer Programs
  • Computers
  • Data Processing
  • Databases
  • Digestive System Processes
  • Digital Information
  • Food Dispensing
  • Food Preparation
  • Meals
  • Military Research
  • Relational Database Management Systems
  • Reliability
  • Statistical Analysis
  • Vegetables

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