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[Differences in nutrient intake using different nutrient databases-- an example]

J Linseisen1, G Wolfram

  • 1Institut für Ernährungswissenschaft der TU München, Freising-Weihenstephan.

Zeitschrift Fur Ernahrungswissenschaft
|June 1, 1997
PubMed
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Nutrient intake data varies significantly across different databases, impacting accuracy for key nutrients like zinc and fluoride. Careful selection of food composition databases is crucial for reliable dietary assessments.

Area of Science:

  • Nutritional Science
  • Food Science
  • Public Health Nutrition

Background:

  • Accurate dietary intake assessment relies on comprehensive nutrient databases.
  • Variations in database content and methodology can lead to discrepancies in calculated nutrient intakes.
  • Previous studies have highlighted potential differences between various food composition databases.

Purpose of the Study:

  • To compare nutrient intake data calculated from three different food composition databases: modified Souci/Fachmann/Kraut (mSFK) 1986/87, Bundeslebensmittelschlüssel (BLS) version 2.1, and BLS version 2.2.
  • To identify specific nutrients with the greatest discrepancies across these databases.
  • To evaluate the impact of database revisions (BLS 2.1 vs. 2.2) on nutrient intake calculations.

Main Methods:

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  • Utilized 25 7-day food records from a study group.
  • Calculated mean dietary intake for 27 nutrients using three distinct nutrient databases: mSFK (1986/87), BLS (v2.1), and BLS (v2.2).
  • Performed comparative analysis to identify deviations and statistically significant differences in nutrient intake values.

    • Main Results:

    • Comparable results were found for only 4 out of 27 nutrients across the three databases.
    • Greatest deviations were observed for zinc, fluoride, iodine, vitamin D, vitamin C, and dietary fiber.
    • Comparing BLS v2.2 with mSFK showed markedly lower differences for fluoride, iodine, and dietary fiber than BLS v2.1.
    • Statistically significant differences for vitamins C and A (equivalents) disappeared between BLS v2.2 and mSFK.
    • Underestimation of trace elements (zinc, fluoride, iodine) was noted with mSFK due to missing analytical data.

    Conclusions:

    • Significant variations exist in nutrient intake data depending on the food composition database used.
    • The revised BLS version 2.2 demonstrates improved agreement with mSFK compared to BLS version 2.1 for certain nutrients.
    • Caution is advised when interpreting nutrient intake data derived from BLS 2.1, particularly for trace elements and specific vitamins.
    • Database selection is critical for accurate dietary assessment and nutritional research.