IMR Press / FBL / Volume 28 / Issue 2 / DOI: 10.31083/j.fbl2802030
Open Access Original Research
Parametric and Semiparametric Approaches to Analyzing Device-Based Measures of Energy Expenditure in Zucker Diabetic Fatty Rats
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1 Department of Allergy and Clinical Immunology, Asan Medical Center, 05505 Seoul, Republic of Korea
2 Department of Epidemiology and Biostatistics, Indiana University, School of Public Health, Bloomington, IN 47405, USA
3 Department of Animal Science, Texas A&M University, College Station, TX 77843, USA
*Correspondence: (Carmen D. Tekwe)
Front. Biosci. (Landmark Ed) 2023, 28(2), 30;
Submitted: 30 June 2022 | Revised: 28 December 2022 | Accepted: 13 January 2023 | Published: 20 February 2023
Copyright: © 2023 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.

Background: Obesity results from a chronic imbalance between energy intake and energy expenditure. Total energy expenditure for all physiological functions combined can be measured approximately by calorimeters. These devices assess energy expenditure frequently (e.g., in 60-second epochs), resulting in massive complex data that are nonlinear functions of time. To reduce the prevalence of obesity, researchers often design targeted therapeutic interventions to increase daily energy expenditure. Methods: We analyzed previously collected data on the effects of oral interferon tau supplementation on energy expenditure, as assessed with indirect calorimeters, in an animal model for obesity and type 2 diabetes (Zucker diabetic fatty rats). In our statistical analyses, we compared parametric polynomial mixed effects models and more flexible semiparametric models involving spline regression. Results: We found no effect of interferon tau dose (0 vs. 4 μg/kg body weight/day) on energy expenditure. The B-spline semiparametric model of untransformed energy expenditure with a quadratic term for time performed best in terms of the Akaike information criterion value. Conclusions: To analyze the effects of interventions on energy expenditure assessed with devices that collect data at frequent intervals, we recommend first summarizing the high dimensional data into epochs of 30 to 60 minutes to reduce noise. We also recommend flexible modeling approaches to account for the nonlinear patterns in such high dimensional functional data. We provide freely available R codes in GitHub.

energy expenditure
mixed effects models
spline regression
truncated splines
1R01DK132385-01/National Institute of Diabetes and Digestive and Kidney Diseases
10GRNT4480020/American Heart Association
11GRNT7930004/American Heart Association
Fig. 1.
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