Sarcopenic obesity and overall mortality: Results from the application of novel models of body composition phenotypes to the National Health and Nutrition Examination Survey 1999–2004

Carla Van Aller, Jose Lara, Blossom C.M. Stephan, Lorenzo Maria Donini, Steven Heymsfield, Peter T. Katzmarzyk, Jonathan C.K. Wells, Carla M. Prado, Mario Siervo*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Background/Objectives: There is no consensus on the definition of sarcopenic obesity (SO), resulting in inconsistent associations of SO with mortality risk. We aim to evaluate association of dual energy x-ray absorptiometry (DXA) SO models with mortality risk in a US adult population (≥50 years). Subjects/Methods: The study population consisted of 3577 participants aged 50 years and older from the 1999–2004 National Health and Nutrition and Examination Survey with mortality follow-up data through December 31, 2011. Difference in survival time in people with and without SO defined by three body composition DXA models (Model 1: body composition phenotype model; Model 2: Truncal Fat Mass (TrFM)/Appendicular Skeletal Muscle Mass (ASM) ratio model; Model 3: Fat Mass (FM)/Fat Free Mass (FFM) ratio). The differences between the models were assessed by the acceleration failure time model, and expressed as time ratios (TR). Results: Participants age 50–70 years with SO had a significantly decreased survival time, according to the body composition phenotype model (TR: 0.92; 95% CI: 0.87–0.97), and TrFM/ASM ratio model (TR: 0.88; 95% CI: 0.81–0.95). The FM/FFM ratio model did not detect significant differences in survival time. Participants with SO aged 70 years and older did not have a significantly decreased survival time, according to all three models. Conclusions: A SO phenotype increases mortality risk in people of age 50–70 years, but not in people aged 70 years and older. The application of the body composition phenotype and the TrFM/ASM ratio models may represent useful diagnostic approaches to improve the prediction of disease and mortality risk.

Original languageEnglish
Pages (from-to)264-270
Number of pages7
JournalClinical Nutrition
Volume38
Issue number1
Early online date15 Feb 2018
DOIs
Publication statusPublished - 1 Feb 2019

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