Abstract
RATIONALE: Variation in (18) O natural abundance can lead to errors in the calculation of total energy expenditure (TEE) when using the doubly labelled water (DLW) method. The use of Bayesian statistics allows a distribution to be assigned to (18) O natural abundance, thus allowing a best-fit value to be used in the calculation. The aim of this study was to calculate within-subject variation in (18) O natural abundance and apply this to our original working model for TEE calculation. METHODS: Urine samples from a cohort of 99 women, dosed with 50 g of 20% (2) H(2) O, undertaking a 14-day breast milk intake protocol, were analysed for (18) O. The within-subject variance was calculated and applied to a Bayesian model for the calculation of TEE in a separate cohort of 36 women. This cohort of 36 women had taken part in a DLW study and had been dosed with 80 mg/kg body weight (2) H(2) O and 150 mg/kg body weight H(2) (18) O. RESULTS: The average change in the δ(18) O value from the 99 women was 1.14‰ (0.77) [0.99, 1.29], with the average within-subject (18) O natural abundance variance being 0.13‰(2) (0.25) [0.08, 0.18]. There were no significant differences in TEE (9745 (1414), 9804 (1460) and 9789 (1455) kJ/day, non-Bayesian, Bluck Bayesian and modified Bayesian models, respectively) between methods. CONCLUSIONS: Our findings demonstrate that using a reduced natural variation in (18) O as calculated from a population does not impact significantly on the calculation of TEE in our model. It may therefore be more conservative to allow a larger variance to account for individual extremes.