Robin P Shook1, Gregory A Hand2, Daniel P O'Connor3, Diana M Thomas4, Thomas G Hurley5, James R Hébert5,6, Clemens Drenowatz7, Gregory J Welk8, Alicia L Carriquiry9, Steven N Blair6,10. 1. Department of Pediatrics, Children's Mercy Hospital, Kansas City, MO. 2. School of Public Health, University of West Virginia, Morgantown, WV. 3. Department of Health and Human Performance, University of Houston, Houston, TX. 4. Department of Mathematics, US Military Academy, West Point, NY. 5. South Carolina Statewide Cancer Prevention and Control Program and Departments of Epidemiology and Biostatistics and Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC. 6. Departments of Epidemiology and Biostatistics and Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC. 7. Pädagogische Hochschule Vorarlberg, Feldkirch, Austria. 8. Departments of Kinesiology and Statistics, Iowa State University, Ames, IA. 9. Departments of Statistics, Iowa State University, Ames, IA. 10. Departments of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC.
Abstract
Background: Assessments of energy intake (EI) are frequently affected by measurement error. Recently, a simple equation was developed and validated to estimate EI on the basis of the energy balance equation [EI = changed body energy stores + energy expenditure (EE)]. Objective: The purpose of this study was to compare multiple estimates of EI, including 2 calculated from the energy balance equation by using doubly labeled water (DLW) or activity monitors, in free-living adults. Methods: The body composition of participants (n = 195; mean age: 27.9 y; 46% women) was measured at the beginning and end of a 2-wk assessment period with the use of dual-energy X-ray absorptiometry. Resting metabolic rate (RMR) was calculated through indirect calorimetry. EE was assessed with the use of the DLW technique and an arm-based activity monitor [Sensewear Mini Armband (SWA); BodyMedia, Inc.]. Self-reported EI was calculated by using dietitian-administered 24-h dietary recalls. Two estimates of EI were calculated with the use of a validated equation: quantity of energy stores estimated from the changes in fat mass and fat-free mass occurring over the assessment period plus EE from either DLW or the SWA. To compare estimates of EI, reporting bias (estimated EI/EE from DLW × 100) and Goldberg ratios (estimated EI/RMR) were calculated. Results: Mean ± SD EEs from DLW and SWA were 2731 ± 494 and 2729 ± 559 kcal/d, respectively. Self-reported EI was 2113 ± 638 kcal/d, EI derived from DLW was 2723 ± 469 kcal/d, and EI derived from the SWA was 2720 ± 730 kcal/d. Reporting biases for self-reported EI, DLW-derived EI, and SWA-derived EI are as follows: -21.5% ± 22.2%, -0.7% ± 18.5%, and 0.2% ± 20.8%, respectively. Goldberg cutoffs for self-reported EI, DLW EI, and SWA EI are as follows: 1.39 ± 0.39, 1.77 ± 0.38, and 1.77 ± 0.38 kcal/d, respectively. Conclusions: These results indicate that estimates of EI based on the energy balance equation can provide reasonable estimates of group mean EI in young adults. The findings suggest that, when EE derived from DLW is not feasible, an activity monitor that provides a valid estimate of EE can be substituted for EE from DLW.
Background: Assessments of energy intake (EI) are frequently affected by measurement error. Recently, a simple equation was developed and validated to estimate EI on the basis of the energy balance equation [EI = changed body energy stores + energy expenditure (EE)]. Objective: The purpose of this study was to compare multiple estimates of EI, including 2 calculated from the energy balance equation by using doubly labeled water (DLW) or activity monitors, in free-living adults. Methods: The body composition of participants (n = 195; mean age: 27.9 y; 46% women) was measured at the beginning and end of a 2-wk assessment period with the use of dual-energy X-ray absorptiometry. Resting metabolic rate (RMR) was calculated through indirect calorimetry. EE was assessed with the use of the DLW technique and an arm-based activity monitor [Sensewear Mini Armband (SWA); BodyMedia, Inc.]. Self-reported EI was calculated by using dietitian-administered 24-h dietary recalls. Two estimates of EI were calculated with the use of a validated equation: quantity of energy stores estimated from the changes in fat mass and fat-free mass occurring over the assessment period plus EE from either DLW or the SWA. To compare estimates of EI, reporting bias (estimated EI/EE from DLW × 100) and Goldberg ratios (estimated EI/RMR) were calculated. Results: Mean ± SD EEs from DLW and SWA were 2731 ± 494 and 2729 ± 559 kcal/d, respectively. Self-reported EI was 2113 ± 638 kcal/d, EI derived from DLW was 2723 ± 469 kcal/d, and EI derived from the SWA was 2720 ± 730 kcal/d. Reporting biases for self-reported EI, DLW-derived EI, and SWA-derived EI are as follows: -21.5% ± 22.2%, -0.7% ± 18.5%, and 0.2% ± 20.8%, respectively. Goldberg cutoffs for self-reported EI, DLW EI, and SWA EI are as follows: 1.39 ± 0.39, 1.77 ± 0.38, and 1.77 ± 0.38 kcal/d, respectively. Conclusions: These results indicate that estimates of EI based on the energy balance equation can provide reasonable estimates of group mean EI in young adults. The findings suggest that, when EE derived from DLW is not feasible, an activity monitor that provides a valid estimate of EE can be substituted for EE from DLW.
Authors: Catarina L Nunes; Filipe Jesus; Ruben Francisco; Mark Hopkins; Luís B Sardinha; Paulo Martins; Cláudia S Minderico; Analiza M Silva Journal: Eur J Nutr Date: 2022-07-14 Impact factor: 4.865
Authors: Ruairi O'Driscoll; Jake Turicchi; Mark Hopkins; Cristiana Duarte; Graham W Horgan; Graham Finlayson; R James Stubbs Journal: JMIR Mhealth Uhealth Date: 2021-08-04 Impact factor: 4.773