Body composition, energy expenditure and physical activity

Maximizing precision and accuracy of the doubly labeled water method via optimal sampling protocol, calculation choices, and incorporation of 17O measurements

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Abstract

Background/Objectives

The doubly labeled water (DLW) method is the gold standard methodology for determination of free-living, total daily energy expenditure (TEE). However, there is no single accepted approach for either the sampling protocols (daily vs. two-point, in which samples are collected after dosing and at the end of the measurement period) or the calculations used in the determination of the rate of carbon dioxide production (rCO2) and TEE. Moreover, fluctuations in natural background abundances introduce error in the calculation of rCO2 and TEE. The advent of new technologies makes feasible the possibility of including additional isotope measures (17O) to account for background variation, which may improve accuracy.

Subjects/Methods

Sixteen subjects were studied for 7 consecutive days in a whole-room indirect calorimeter (IC) with concurrent measurement of TEE by DLW. Daily urine samples were obtained and isotope ratios were determined using off-axis integrated cavity output spectroscopy (OA-ICOS).

Results

We determined the best combination of approaches for estimating dilution spaces and elimination rates and calculated average daily volume of carbon dioxide production (VCO2) using six different published equations. Using this best combination, multi-point fitting of isotope elimination rates using the daily urine samples substantially improved the average precision (4.5% vs. 6.0%) and accuracy (−0.5% vs. −3.0%) compared with the two-point method. This improvement may partly reflect the less variable day-to-day chamber measurements of energy expenditure. Utilizing 17O measurements to correct for errors due to background isotope fluctuations provided additional but minor improvements in precision (4.2% vs. 4.5%) and accuracy (0.2% vs. 0.5%).

Conclusions

This work shows that optimizing sampling and calculation protocols can improve the accuracy and precision of DLW measurements.

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Funding

This work was supported by an NIH Small Business Innovation (SBIR) Research Grant (R44 DK093362), as well as support from the Colorado Nutrition and Obesity Research Center (P30 DK048520) and the Colorado Clinical and Translational Science Institute (UL1 RR025780). ELM is also supported by resources from the Geriatric Research, Education, and Clinical Center at the Denver VA Medical Center. JRS was supported by a 1000 Talents award from the Chinese government and a Wolfson merit award from the UK royal society.

Author information

Correspondence to John R. Speakman.

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Conflict of interest

At the time the research was conducted, ESFB was employed by ABB/Los Gatos Research, the company that manufactures the OA-ICOS analyzer used for the analyses in this paper. The others declare that they have no conflict of interest.

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