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A systematic method to evaluate the dietary intake data coding process used in the research setting

Journal Article


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Abstract


  • Accurate dietary intake data are the basis for investigating diet-disease relationships. Data

    coding is a critical step of generating dietary intake data for analyses in nutrition research.

    However, there is currently no systematic method for assessing dietary intake data coding

    process. The aim of this study was to explore discrepancies in dietary intake data coding

    process through source data verification. A 1% random sample of paper-based diet history

    records (source data) from participants (n=377) in a registered clinical trial was extracted as a

    pilot audit to explore potential discrepancy types. Another 10% random sample (n=38) of

    baseline dietary source data from the same trial was extracted developing the method. All

    items listed in the source data underwent a 100% manual verification check with food output

    data from FoodWorks software applied to the piloted discrepancy types. The identified

    discrepancies were categorized into food groups based on modified major groups of

    AUSNUT 2011–13. Free vegetables, meat, savory sauces and condiments, as well as cereals

    were found to be more prone to coding discrepancies than other food groups. A more detailed

    dietary intake data coding protocol is required prior to dietary data collection and coding

    process to ensure data coding quality.

Publication Date


  • 2017

Citation


  • Guan, V., Probst, Y., Neale, E., Martin, A. & Tapsell, L. C. (2017). A systematic method to evaluate the dietary intake data coding process used in the research setting. Journal of Food Composition and Analysis, 64 (Part 1), 27-32.

Scopus Eid


  • 2-s2.0-85026313922

Ro Full-text Url


  • http://ro.uow.edu.au/context/smhpapers/article/5854/type/native/viewcontent

Ro Metadata Url


  • http://ro.uow.edu.au/smhpapers/4816

Number Of Pages


  • 5

Start Page


  • 27

End Page


  • 32

Volume


  • 64

Issue


  • Part 1

Place Of Publication


  • United States

Abstract


  • Accurate dietary intake data are the basis for investigating diet-disease relationships. Data

    coding is a critical step of generating dietary intake data for analyses in nutrition research.

    However, there is currently no systematic method for assessing dietary intake data coding

    process. The aim of this study was to explore discrepancies in dietary intake data coding

    process through source data verification. A 1% random sample of paper-based diet history

    records (source data) from participants (n=377) in a registered clinical trial was extracted as a

    pilot audit to explore potential discrepancy types. Another 10% random sample (n=38) of

    baseline dietary source data from the same trial was extracted developing the method. All

    items listed in the source data underwent a 100% manual verification check with food output

    data from FoodWorks software applied to the piloted discrepancy types. The identified

    discrepancies were categorized into food groups based on modified major groups of

    AUSNUT 2011–13. Free vegetables, meat, savory sauces and condiments, as well as cereals

    were found to be more prone to coding discrepancies than other food groups. A more detailed

    dietary intake data coding protocol is required prior to dietary data collection and coding

    process to ensure data coding quality.

Publication Date


  • 2017

Citation


  • Guan, V., Probst, Y., Neale, E., Martin, A. & Tapsell, L. C. (2017). A systematic method to evaluate the dietary intake data coding process used in the research setting. Journal of Food Composition and Analysis, 64 (Part 1), 27-32.

Scopus Eid


  • 2-s2.0-85026313922

Ro Full-text Url


  • http://ro.uow.edu.au/context/smhpapers/article/5854/type/native/viewcontent

Ro Metadata Url


  • http://ro.uow.edu.au/smhpapers/4816

Number Of Pages


  • 5

Start Page


  • 27

End Page


  • 32

Volume


  • 64

Issue


  • Part 1

Place Of Publication


  • United States