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Updated: Mar 2, 2026
Determining Basal Energy Expenditure and the Capacity of Thermogenic Adipocytes to Expend Energy in Obese Mice
Published on: November 11, 2021
Functional data analysis of sleeping energy expenditure
Jong Soo Lee1, Issa F Zakeri2, Nancy F Butte3
1Department of Mathematical Sciences, University of Massachusetts Lowell, Massachusetts, United States of America.
Insights
Adequate sleep is vital for children's development. This study used functional data analysis to show differences in sleeping energy expenditure (SEE) patterns between obese and non-obese children, suggesting other factors influence weight-adjusted SEE.
Area of Science:
- Pediatric metabolic health
- Sleep science
- Functional data analysis
Background:
- Adequate sleep is essential for children's metabolic health, physical, and cognitive development.
- Inadequate sleep can disrupt metabolic homeostasis and alter sleeping energy expenditure (SEE).
- Understanding SEE patterns in children is crucial for identifying metabolic health disparities.
Purpose of the Study:
- To apply functional data analysis methods to sleeping energy expenditure (SEE) data.
- To elucidate the population structure of SEE in children.
- To discriminate SEE patterns between obese and non-obese children.
Main Methods:
- Minute-by-minute SEE was measured in 109 children (ages 5-18) using room respiration calorimeters.
- Smoothing spline methods and functional principal component analysis (FPCA) were applied to calorimetric data.
- FPCA scores and classifier algorithms (logistic regression, SVM, random forest) were used to analyze and classify SEE.
Main Results:
- Smoothing effectively removed noise, enabling accurate analysis of SEE dynamics.
- SEE exhibited declining, undulating patterns throughout the night.
- While mean SEE was higher in obese children, weight-adjusted SEE was not significantly different.
- FPCA scores differed between obese and non-obese children (p=0.037), and classification rates for weight-adjusted SEE were 62-64%.
Conclusions:
- Functional data analysis revealed distinct SEE structures between obese and non-obese children.
- Differences in weight-adjusted SEE suggest unidentified factors influencing metabolic homeostasis.
- Further research is needed to uncover these factors affecting children's metabolic health.
Abstract:
Adequate sleep is crucial during childhood for metabolic health, and physical and cognitive development. Inadequate sleep can disrupt metabolic homeostasis and alter sleeping energy expenditure (SEE). Functional data analysis methods were applied to SEE data to elucidate the population structure of SEE and to discriminate SEE between obese and non-obese children. Minute-by-minute SEE in 109 children, ages 5-18, was measured in room respiration calorimeters. A smoothing spline method was applied to the calorimetric data to extract the true smoothing function for each subject. Functional principal component analysis was used to capture the important modes of variation of the functional data and to identify differences in SEE patterns. Combinations of functional principal component analysis and classifier algorithm were used to classify SEE. Smoothing effectively removed instrumentation noise inherent in the room calorimeter data, providing more accurate data for analysis of the dynamics of SEE. SEE exhibited declining but subtly undulating patterns throughout the night. Mean SEE was markedly higher in obese than non-obese children, as expected due to their greater body mass. SEE was higher among the obese than non-obese children (p<0.01); however, the weight-adjusted mean SEE was not statistically different (p>0.1, after post hoc testing). Functional principal component scores for the first two components explained 77.8% of the variance in SEE and also differed between groups (p = 0.037). Logistic regression, support vector machine or random forest classification methods were able to distinguish weight-adjusted SEE between obese and non-obese participants with good classification rates (62-64%). Our results implicate other factors, yet to be uncovered, that affect the weight-adjusted SEE of obese and non-obese children. Functional data analysis revealed differences in the structure of SEE between obese and non-obese children that may contribute to disruption of metabolic homeostasis.
