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Implications of the variation in biological 18 O natural abundance in body water to inform use of Bayesian methods for modelling total energy expenditure when using doubly labelled water
Author(s) -
Singh Priya A.,
Orford Elise R.,
Donkers Kevin,
Bluck Leslie J.C.,
Venables Michelle C.
Publication year - 2018
Publication title -
rapid communications in mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.528
H-Index - 136
eISSN - 1097-0231
pISSN - 0951-4198
DOI - 10.1002/rcm.8291
Subject(s) - statistics , bayesian probability , abundance (ecology) , coefficient of variation , chemistry , zoology , cohort , doubly labeled water , body weight , energy expenditure , mathematics , ecology , medicine , biology
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.

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