Author
ANDREWS, KAREN - JOHNS HOPKINS UNIV | |
Roseland, Janet | |
ZHAO, CUIWEI - JOHNS HOPKINS UNIV | |
SCHWEITZER, AMY - JOHNS HOPKINS UNIV | |
Holden, Joanne | |
PERRY, CHARLES - NASS | |
DWYER, JOHANNA - ODS-NIH | |
PICCIANO, MARY FRANCES - ODS-NIH | |
FISHER, KENNETH - ODS-NIH | |
SALDANHA, LEILA - ODS-NIH | |
YETLEY, ELIZABETH - ODS-NIH | |
DOUGLASS, LARRY - UN OF MD |
Submitted to: Experimental Biology
Publication Type: Abstract Only Publication Acceptance Date: 2/7/2008 Publication Date: 3/12/2008 Citation: Andrews, K., Roseland, J.M., Zhao, C., Schweitzer, A., Holden, J.M., Perry, C., Dwyer, J., Picciano, M., Fisher, K., Saldanha, L., Yetley, E., Douglass, L. 2008. Commonly reported U.S. Adult Multivitamin/Mineral (MVM) products: Analysis of labeled vs. analytical values for 19 vitamins and minerals. Experimental Biology 2008, April 5-9, 2008, San Diego, CA. Interpretive Summary: Technical Abstract: Adult MVM products, representing over 55% of the national market share, were analyzed for their nutrient content. Nationally representative samples of each product were obtained in 6 retail locations from various market channels. Products were repackaged and sent to one or more independent laboratories for analysis, along with quality control materials. For each nutrient, mean per cent differences from label (%DL) and among-lot variability were calculated. To identify patterns of variance, regression analyses were applied to %DL vs. labeled values among the 35 products. For 12 nutrients (calcium, copper, iron, magnesium, manganese, niacin, phosphorus, potassium, riboflavin, vitamin C, alpha-tocopherol, and zinc), mean %DLs for all 35 products and residual standard deviations (sd) were <12%. For 7 nutrients (selenium, vitamin B6, chromium, thiamin, vitamin B12, folic acid, iodine), mean %DL ranged from 14% to 46% and residual sd ranged from 9% to 20%. Regression analysis will be applied to analytical data from a further study of MVM products that posses a lower-market-share to determine whether identified patterns in this study can be used to predict %DL for an analytically validated Dietary Supplement Ingredient Database. Funding: USDA & ODS/NIH. |