Autor: |
Singh, Priya A., Orford, Elise R., Donkers, Kevin, Bluck, Leslie J.C., Venables, Michelle C. |
Předmět: |
|
Zdroj: |
Rapid Communications in Mass Spectrometry: RCM; 12/30/2018, Vol. 32 Issue 24, p2122-2128, 7p |
Abstrakt: |
Rationale: Variation in 18O 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 18O 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 18O 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% 2H2O, undertaking a 14‐day breast milk intake protocol, were analysed for 18O. 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 2H2O and 150 mg/kg body weight H218O. Results: The average change in the δ18O value from the 99 women was 1.14‰ (0.77) [0.99, 1.29], with the average within‐subject 18O 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 18O 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. [ABSTRACT FROM AUTHOR] |
Databáze: |
Complementary Index |
Externí odkaz: |
|