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Rapid Commun Mass Spectrom. 2018 Jan 15;32(1):23-32. doi: 10.1002/rcm.8013.

Application of Bayesian analysis to the doubly labelled water method for total energy expenditure in humans.

Author information

1
University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science and Department of Paediatrics, University of Cambridge, Cambridge, CB2 0QQ, UK.
2
MRC Elsie Widdowson Laboratory (formerly MRC Human Nutrition Research), Fulbourn Road, Cambridge, CB1 9NL, UK.
3
School of Food Science and Nutrition, Faculty of Mathematics and Physical Sciences, University of Leeds, Leeds, LS2 9JT, UK.
4
MRC Biostatistics Unit, Cambridge Institute of Public Health, Forvie Site Robinson Way, Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK.

Abstract

RATIONALE:

The doubly labelled water (DLW) method is the reference method for the estimation of free-living total energy expenditure (TEE). In this method, where both 2 H and 18 O are employed, different approaches have been adopted to deal with the non-conformity observed regarding the distribution space for the labels being non-coincident with total body water. However, the method adopted can have a significant effect on the estimated TEE.

METHODS:

We proposed a Bayesian reasoning approach to modify an assumed prior distribution for the space ratio using experimental data to derive the TEE. A Bayesian hierarchical approach was also investigated. The dataset was obtained from 59 adults (37 women) who underwent a DLW experiment during which the 2 H and 18 O enrichments were measured using isotope ratio mass spectrometry (IRMS).

RESULTS:

TEE was estimated at 9925 (9106-11236) [median and interquartile range], 9646 (9167-10540), and 9,638 (9220-10340) kJ·day-1 for women and at 13961 (12851-15347), 13353 (12651-15088) and 13211 (12653-14238) kJ·day-1 for men, using normalized non-Bayesian, independent Bayesian and hierarchical Bayesian approaches, respectively. A comparison of hierarchical Bayesian with normalized non-Bayesian methods indicated a marked difference in behaviour between genders. The median difference was -287 kJ·day-1 for women, and -750 kJ·day-1 for men. In men there is an appreciable compression of the TEE distribution obtained from the hierarchical model compared with the normalized non-Bayesian methods (range of TEE 11234-15431 kJ·day-1 vs 10786-18221 kJ·day-1 ). An analogous, yet smaller, compression is seen in women (7081-12287 kJ·day-1 vs 6989-13775 kJ·day-1 ).

CONCLUSIONS:

The Bayesian analysis is an appealing method to estimate TEE during DLW experiments. The principal advantages over those obtained using the classical least-squares method is the generation of potentially more useful estimates of TEE, and improved handling of outliers and missing data scenarios, particularly if a hierarchical model is used.

PMID:
29027729
PMCID:
PMC5765481
DOI:
10.1002/rcm.8013
[Indexed for MEDLINE]
Free PMC Article

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