Comparisons among Equations Used for Retinol Isotope Dilution in the Assessment of Total Body Stores and Total Liver Reserves.

Vitamin A plays an essential role in animal biology and has negative effects associated with both hypo- and hypervitaminosis A. Many notable interventions are being done globally to eliminate vitamin A deficiency, including supplementation, fortification, and biofortification. At the same time, it is important to monitor vitamin A status in nations where preformed vitamin A intake is high because of consumption of animal source foods (e.g., liver, dairy, eggs), fortified foods (e.g., milk, cereals, oil, sugar, margarine), or vitamin supplements (e.g., one-a-day multivitamins) to ensure the population does not reach hypervitaminosis A. To accurately assess population status and evaluate interventions aimed at improving vitamin A status, accurate assessment methods are needed. The primary storage site of vitamin A is the liver; however, routinely obtaining liver samples from humans is impractical and unethical. Isotope dilution using deuterium- or (13)C-labeled retinol is currently the most sensitive indirect biomarker of vitamin A status across a wide range of liver reserves. The major drawback to its application is the increased technicality in sample analysis and data calculations when compared to less sensitive methodology, such as serum retinol concentrations and dose response tests. Two main equations have emerged for calculating vitamin A body pool size or liver concentrations from isotope dilution data: the "Olson equation" and the "mass balance equation." Different applications of these equations can lead to confusion and lack of consistency if the underlying principles and assumptions used are not clarified. The purpose of this focused review is to describe the evolution of the equations used in retinol stable-isotope work and the assumptions appropriate to different applications of the test. Ultimately, the 2 main equations are shown to be fundamentally the same and differ only in assumptions made for each specific research application.