Body Composition and Metabolic Assessment After Motor Complete Spinal Cord Injury: Development of a Clinically Relevant Equation to Estimate Body Fat
- PMID: 33814880
- PMCID: PMC7983632
- DOI: 10.46292/sci20-00079
Body Composition and Metabolic Assessment After Motor Complete Spinal Cord Injury: Development of a Clinically Relevant Equation to Estimate Body Fat
Abstract
Background: Obesity is at epidemic proportions in the population with spinal cord injury (SCI), and adipose tissue (AT) is the mediator of the metabolic syndrome. Obesity, however, has been poorly appreciated in SCI because of the lack of sensitivity that body mass index (BMI) conveys for obesity risk in SCI without measuring AT. Objectives: The specific objectives were to compare measures of body composition assessment for body fat with the criterion standard 4-compartment (4C) model in persons with SCI, to develop a regression equation that can be utilized in the clinical setting to estimate fat mass (FM), and to determine cardiometabolic risk using surrogates of obesity in a current model of metabolic syndrome. Methods: Seventy-two individuals with chronic (>1 year) motor complete (AIS A and B) C5-L2 SCI were recruited over 3 years. Subjects underwent assessment with 4C using hydrostatic (underwater) weighing (UWW), dual-energy x-ray absorptiometry (DXA), and total body water (TBW) assessment to determine percent body fat (%BF); fasting glucose and lipid profiles, and resting blood pressure were also obtained. BMI, DXA, bioelectrical impedance analyses (BIA), BodPod, circumferences, diameters, lengths, and nine-site skinfold (SF) were assessed and validated against 4C. A multiple linear regression model was used to fit %BF (dependent variable) using anthropometric and demographic data that had the greatest correlations with variables, followed by a combined forward/backward stepwise regression with Akaike information criterion (AIC) to identify the variables most predictive of the 4C %BF. To allow for a more practical model for use in the clinical setting, we further reduced the AIC model with minimal loss of predictability. Surrogate markers of obesity were employed with metabolic biomarkers of metabolic syndrome to determine prevalence in persons with SCI. Results: Subject characteristics included age 44.4 ± 11.3 years, time since injury (TSI) 14.4 ± 11.0 years, BMI 27.3 ± 5.9 kg/m2; 59 were men and 13 were women. Sitting waist circumference (WCSit ) was 95.5 ± 13.1 cm, supine waist circumference (WCSup) was 93.4 ± 12.7 cm, and abdominal skinfold (ABDSF) was 53.1 ± 19.6 mm. Findings showed 4C %BF 42.4 ± 8.6%, UWW %BF 37.3 ± 9.7%, DXA %BF 39.1 ± 9.4%, BodPod %BF 33.7 ± 11.4%, nine-site SF %BF 37.8 ± 9.3%, and BIA %BF 27.6 ± 8.6%. A regression equation using age, sex, weight, and ABDSF provided R2 correlation of 0.57 with 4C %BF (p < .0001). Metabolic syndrome was identified in 59.4% of the sample. Conclusion: Body composition techniques to determine body fat are labor intensive and expensive for persons with SCI, and the regression equation developed against the criterion standard 4C model may allow clinicians to quickly estimate %BF and more accurately demonstrate obesity-induced cardiometabolic syndrome in this population.
Keywords: adipose tissue; body composition; metabolic syndrome; obesity; spinal cord injury.
© 2021 American Spinal Injury Association.
Conflict of interest statement
Conflicts of Interest The authors declare no conflicts of interest.
Similar articles
-
Correlations between percent body fat measured by dual-energy X-ray absorptiometry and anthropometric measurements in Thai persons with chronic traumatic spinal cord injury.Spinal Cord. 2022 Dec;60(12):1094-1099. doi: 10.1038/s41393-022-00828-4. Epub 2022 Jun 30. Spinal Cord. 2022. PMID: 35773356
-
Assessing body composition among 3- to 8-year-old children: anthropometry, BIA, and DXA.Obes Res. 2004 Oct;12(10):1633-40. doi: 10.1038/oby.2004.203. Obes Res. 2004. PMID: 15536227
-
Validation of DXA body composition estimates in obese men and women.Obesity (Silver Spring). 2009 Apr;17(4):821-6. doi: 10.1038/oby.2008.595. Epub 2009 Jan 8. Obesity (Silver Spring). 2009. PMID: 19131939
-
Anthropometric Prediction of Visceral Adiposity in Persons With Spinal Cord Injury.Top Spinal Cord Inj Rehabil. 2021;27(1):23-35. doi: 10.46292/sci20-00055. Top Spinal Cord Inj Rehabil. 2021. PMID: 33814881 Free PMC article. Review.
-
Comparison of body composition methods: a literature analysis.Eur J Clin Nutr. 1997 Aug;51(8):495-503. doi: 10.1038/sj.ejcn.1600448. Eur J Clin Nutr. 1997. PMID: 11248873 Review.
Cited by
-
Predictors of muscle hypertrophy responsiveness to electrically evoked resistance training after spinal cord injury.Eur J Appl Physiol. 2023 Mar;123(3):479-493. doi: 10.1007/s00421-022-05069-0. Epub 2022 Oct 28. Eur J Appl Physiol. 2023. PMID: 36305973
-
The comparison of total energy and protein intake relative to estimated requirements in chronic spinal cord injury.Br J Nutr. 2024 Feb 14;131(3):489-499. doi: 10.1017/S0007114523002088. Epub 2023 Sep 20. Br J Nutr. 2024. PMID: 37726106 Free PMC article.
-
A longitudinal analysis of resting energy expenditure and body composition in people with spinal cord injury undergoing surgical repair of pressure injuries: a pilot study.Eur J Clin Nutr. 2023 Mar;77(3):386-392. doi: 10.1038/s41430-022-01248-6. Epub 2022 Dec 7. Eur J Clin Nutr. 2023. PMID: 36477671
-
Predicting resting energy expenditure in people with chronic spinal cord injury.Spinal Cord. 2022 Dec;60(12):1100-1107. doi: 10.1038/s41393-022-00827-5. Epub 2022 Jul 2. Spinal Cord. 2022. PMID: 35780202
-
A Literature Review of Nutrition Knowledge Measurement Items Used in Persons Living with Spinal Cord Injuries and Disorders.Top Spinal Cord Inj Rehabil. 2024 Fall;30(4):66-79. doi: 10.46292/sci23-00066. Epub 2024 Nov 28. Top Spinal Cord Inj Rehabil. 2024. PMID: 39619820 Review.
References
-
- Gater D, Farkas G. Alterations in body composition after SCI and the mitigating role of exercise. In: Taylor JA, editor. The Physiology of Exercise in Spinal Cord Injury. New York: Springer Nature; 2016. pp. 175–198.
-
- Heyward VH, Wagner DR. Applied Body Composition Assessment. Champaign, IL: Human Kinetics; 2004.
-
- Nash MS, Gater DR. Cardiometabolic disease and dysfunction following spinal cord injury: origins and guideline-based countermeasures. Phys Med Rehabil Clin North Am. 2020;31(3):415–436. - PubMed
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
Miscellaneous