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Title: Challenges in developing analytically validated laboratory derived dietary supplement databases

Author
item BETZ, JOSEPH - National Institutes Of Health (NIH)
item RIMMER, CATHERINE - National Institutes Of Health (NIH)
item SALDANHA, LEILA - National Institutes Of Health (NIH)
item PHILLIPS, MELISSA - National Institutes Of Health (NIH)
item ANDREWS, KAREN - University Of Maryland
item WISE, STEPHEN - National Institutes Of Health (NIH)
item WOOD, LAURA - National Institutes Of Health (NIH)
item KUSZAK, ADAM - National Institutes Of Health (NIH)
item GUSEV, PAVEL - University Of Maryland
item Pehrsson, Pamela

Submitted to: Journal of Nutrition
Publication Type: Review Article
Publication Acceptance Date: 6/5/2018
Publication Date: 8/3/2018
Citation: Betz, J.M., Rimmer, C.A., Saldanha, L.G., Phillips, M.M., Andrews, K.A., Wise, S.A., Wood, L.J., Kuszak, A.J., Gusev, P.A., Pehrsson, P.R. 2018. Challenges in developing analytically validated laboratory derived dietary supplement databases. Journal of Nutrition. https://doi.org/10.1093/jn/nxy134.
DOI: https://doi.org/10.1093/jn/nxy134

Interpretive Summary: The Dietary Supplement Label Database (DSLD) is sponsored by the Office of Dietary Supplements (ODS) and the National Library of Medicine (NLM). It provides a searchable, free database of the contents of approximately 65,000 supplement labels. Shortly after it was launched, a companion database of analytically verified supplement product labels (the Dietary Supplement Ingredient Database, DSID) was created by ODS, NLM, and the U.S. Department of Agriculture (USDA). There are considerable challenges to populating both databases, but the DSID faces unique analytical chemistry challenges. This manuscript describes the challenges and solutions to performing analytically verified marketplace surveys of dietary supplement product content claims for inclusion in publicly available databases. Nutritionists and public health scientists require information on actual exposures to dietary supplement constituents because labeled content often does not match actual product content. Analytical verification of claimed content in commercially sold supplements is necessary to provide this important link to consumer exposure. An easily accessible public use database of analytically derived dietary supplement content was developed to provide information on actual composition. The DSID has conducted surveys of several types of vitamin and mineral containing dietary supplements, including those for use by adults and children. Results showing label content claims as analytically derived values are available in the current DSID. A recently conducted pilot project explored the feasibility and difficulty of adding botanical dietary supplement products to the DSID. Selection of candidates for future DSID analyses of botanical products will be based on considerations such as size of presence in the marketplace, potential public health impacts, and the availability of validated analytical methods and reference materials. Databases such as the DSID and the DSLD are essential for industrial, academic, and government researchers and clinicians to evaluate intakes. Together, the two databases provide a valuable picture of the commercial dietary supplement landscape. The DSID provides a quantitative survey of the marketplace with the use of validated methods and reference materials. However, many criteria for selection of future botanical supplements for DSID evaluation involve analytical challenges. Even when the appropriate resources are available, method selection and data evaluation are resource and time-consuming.

Technical Abstract: This manuscript describes the challenges and solutions to performing analytically verified marketplace surveys of dietary supplement product content claims for inclusion in publicly available databases. The Dietary Supplement Label Database (DSLD) is sponsored by the Office of Dietary Supplements (ODS) and the National Library of Medicine (NLM). It provides a searchable, free database of the contents of approximately 65,000 supplement labels. Shortly after it was launched, a companion database of analytically verified supplement product labels (the Dietary Supplement Ingredient Database, DSID) was created by ODS, NLM, and the U.S. Department of Agriculture (USDA). There are considerable challenges to populating both databases, but the DSID faces unique analytical chemistry challenges. Nutritionists and public health scientists require information on actual exposures to dietary supplement constituents because labeled content often does not match actual product content. Analytical verification of claimed content in commercially sold supplements is necessary to provide this important link to consumer exposure. An easily accessible public use database of analytically derived dietary supplement content was developed to provide information on actual composition. The DSID has conducted surveys of several types of vitamin and mineral containing dietary supplements, including those for use by adults and children. Results showing label content claims as analytically derived values are available in the current DSID. A recently conducted pilot project explored the feasibility and difficulty of adding botanical dietary supplement products to the DSID. Selection of candidates for future DSID analyses of botanical products will be based on considerations such as size of presence in the marketplace, potential public health impacts, and the availability of validated analytical methods and reference materials. Databases such as the DSID and the DSLD are essential for industrial, academic, and government researchers and clinicians to evaluate intakes. Together, the two databases provide a valuable picture of the commercial dietary supplement landscape. The DSID provides a quantitative survey of the marketplace with the use of validated methods and reference materials. However, many criteria for selection of future botanical supplements for DSID evaluation involve analytical challenges. Even when the appropriate resources are available, method selection and data evaluation are resource and time-consuming.