MPC Member Publications

This database contains a listing of population studies publications written by MPC Members. Anyone can add a publication by an MPC student, faculty, or staff member to this database; new citations will be reviewed and approved by MPC administrators.

Full Citation

Title: Can Ultrasound Measures of Muscle and Adipose Tissue Thickness Predict Body Composition of Premature Infants in the Neonatal Intensive Care Unit?

Citation Type: Journal Article

Publication Year: 2021

ISSN: 19412444

DOI: 10.1002/jpen.1829

PMID: 32255211

Abstract: Background: Premature infants are at risk for adverse metabolic and neurodevelopmental outcomes due to growth alterations in early infancy. Monitoring body composition by tracking gains in fat mass (FM) and fat-free mass (FFM) may assist clinicians in preventing obesity and metabolic disease while promoting optimal growth and development. A prospective, observational study was conducted to determine the ability of ultrasound (US) measurements of muscle and adipose tissue thickness to predict whole-body composition (FFM, FM, percent body fat [%BF]). Methods: Sixty-three healthy premature infants were recruited from the University of Minnesota's Neonatal Intensive Care Unit. Anthropometric measurements, air displacement plethysmography, and US measurements of abdomen, biceps, and quadriceps muscle and of adipose tissue thickness were conducted when infants were medically stable. The relationship between US measurements and body composition was assessed using stepwise linear regression analysis. Results: In linear regression analyses, biceps adipose and the sum of adipose thickness measurements were significant predictors of %BF, but prediction models had low R2 (0.17 and 0.16, respectively) and high root-mean-square error. US measurements of muscle thickness were not predictive of whole-body FFM. Conclusion: US measurements of muscle and adipose tissue thickness at the examined sites are not adequate surrogates for whole-body composition in preterm infants. Exploration of alternate measurement sites may improve predictive ability.

Url: https://pubmed.ncbi.nlm.nih.gov/32255211/

User Submitted?: No

Authors: Nagel, Emily M.; Hickey, Marie; Teigen, Levi; Kuchnia, Adam; Holm, Tara; Earthman, Carrie; Demerath, Ellen W.; Ramel, Sara E.

Periodical (Full): Journal of Parenteral and Enteral Nutrition

Issue: 2

Volume: 45

Pages: 323-330

Countries:

IPUMS NHGIS NAPP IHIS ATUS Terrapop