Veronica Lopez-Teros1, Michael H Green2, Marjorie J Haskell3, Joanne Balmer Green2. 1. Department of Chemical and Biological Sciences, Universidad de Sonora, Hermosillo, Sonora, Mexico. 2. Department of Nutritional Sciences, College of Health and Human Development, The Pennsylvania State University, University Park, PA, USA. 3. Institute for Global Nutrition, Department of Nutrition, University of California-Davis, Davis, CA, USA.
Abstract
BACKGROUND: Vitamin A status may influence the choice of a blood sampling time for applying the retinol isotope dilution (RID) equation to predict vitamin A total body stores (TBS) in children. OBJECTIVES: We aimed to identify time(s) after administration of labeled vitamin A that provide accurate estimates of TBS in theoretical children with low or high TBS. METHODS: We postulated 2- to 5-y-old children (12/group) with low (<200 μmol) or high TBS (≥700 μmol) and used compartmental analysis to simulate individual subject values for the RID equation TBS = FaS/SAp (Fa, fraction of dose in stores; S, retinol specific activity in plasma/in stores; SAp, retinol specific activity in plasma). Using individual SAp and group geometric mean FaS values from 1-28 d, we calculated individual and group mean TBS and compared them to assigned values. RESULTS: Mean TBS was accurately predicted for both groups at all times. For individuals, predicted and assigned TBS were closest when the CV% for FaS was low [12-14%; 4-13 d (low), 12-28 d (high)]. The mean percentage error for TBS was <10% from 2-19 d (low) and 7-28 d (high). Predicted TBS was within 25% of assigned TBS for ≥80% of children from 3-23 d (low) and 9-28 d (high). Within groups, RID tended to overestimate lower TBS and underestimate higher TBS. CONCLUSIONS: Using a good estimate for FaS, accurate RID predictions of TBS for individuals will be obtained at many times. If vitamin A status is low, results indicate that early sampling (e.g., 4-13 d) is optimal; if vitamin A status is high, sampling at 12-28 d is indicated. When vitamin A status is unknown, sampling at 14 d is recommended, or a super-subject design can be used to obtain the group mean FaS at various times for RID prediction of TBS in individuals.
BACKGROUND: Vitamin A status may influence the choice of a blood sampling time for applying the retinol isotope dilution (RID) equation to predict vitamin A total body stores (TBS) in children. OBJECTIVES: We aimed to identify time(s) after administration of labeled vitamin A that provide accurate estimates of TBS in theoretical children with low or high TBS. METHODS: We postulated 2- to 5-y-old children (12/group) with low (<200 μmol) or high TBS (≥700 μmol) and used compartmental analysis to simulate individual subject values for the RID equation TBS = FaS/SAp (Fa, fraction of dose in stores; S, retinol specific activity in plasma/in stores; SAp, retinol specific activity in plasma). Using individual SAp and group geometric mean FaS values from 1-28 d, we calculated individual and group mean TBS and compared them to assigned values. RESULTS: Mean TBS was accurately predicted for both groups at all times. For individuals, predicted and assigned TBS were closest when the CV% for FaS was low [12-14%; 4-13 d (low), 12-28 d (high)]. The mean percentage error for TBS was <10% from 2-19 d (low) and 7-28 d (high). Predicted TBS was within 25% of assigned TBS for ≥80% of children from 3-23 d (low) and 9-28 d (high). Within groups, RID tended to overestimate lower TBS and underestimate higher TBS. CONCLUSIONS: Using a good estimate for FaS, accurate RID predictions of TBS for individuals will be obtained at many times. If vitamin A status is low, results indicate that early sampling (e.g., 4-13 d) is optimal; if vitamin A status is high, sampling at 12-28 d is indicated. When vitamin A status is unknown, sampling at 14 d is recommended, or a super-subject design can be used to obtain the group mean FaS at various times for RID prediction of TBS in individuals.
Authors: Reina Engle-Stone; Jody C Miller; Maria Fatima Dolly Reario; Charles D Arnold; Ame Stormer; Eleanore Lafuente; Anthony Oxley; Mario V Capanzana; Carl Vincent D Cabanilla; Jennifer Lynn Ford; Adam Clark; Thirumalaisamy P Velavan; Kenneth H Brown; Georg Lietz; Marjorie J Haskell Journal: Curr Dev Nutr Date: 2022-07-25