Use of model-based compartmental analysis and a super-child design to study whole-body retinol kinetics and Vitamin A total body stores in children from 3 lower-income countries

Background: Model-based compartmental analysis has been used to describe and quantify whole-body Vitamin A metabolism and estimate total body stores (TBS) in animals and humans. Objectives: We applied compartmental modeling and a super-child design to estimate retinol kinetic parameters and TBS for young children in Bangladesh, Guatemala, and the Philippines. Methods: Children ingested [¹³C₁₀]retinyl acetate and 1 or 2 blood samples were collected from each child from 6 h to 28 d after dosing. Temporal data for fraction of dose in plasma [¹³C₁₀]retinol were modeled using WinSAAM software and a 6-component model with Vitamin A intake included as weighted data. Results: Model-predicted TBS was 198, 533, and 1062 μmol for the Bangladeshi (age, 9-17 mo), Filipino (12-18 mo), and Guatemalan children (35-65 mo). Retinol kinetics were similar for Filipino and Guatemalan groups and generally faster for Bangladeshi children, although fractional transfer of plasma retinol to a larger exchangeable storage pool was the same for the 3 groups. Recycling to plasma from that pool was ∼2.5 times faster in the Bangladeshi children compared with the other groups and the recycling number was 2-3 times greater. Differences in kinetics between groups are likely related to differences in Vitamin A stores and intakes (geometric means: 352, 727, and 764 μg retinol activity equivalents/d for the Bangladeshi, Filipino, and Guatemalan children, respectively). Conclusions: By collecting 1 or 2 blood samples from each child to generate a composite plasma tracer data set with a minimum of 5 children/time, group TBS and retinol kinetics can be estimated in children by compartmental analysis; inclusion of Vitamin A intake data increases confidence in model predictions. The super-child modeling approach is an effective technique for comparing Vitamin A status among children from different populations.