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Sarcopenic obesity and insulin resistance: application of novel body composition models

Published online by Cambridge University Press:  05 October 2018

I. Mendes ,
E. Poggiogalle ,
B. Lee ,
C.M. Prado ,
G. Mocciaro ,
G. Mariniello ,
J. Lara ,
C. Lubrano ,
A. Lenzi  and
L.M. Donini
...Show all authors
I. Mendes
Affiliation:
Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Medical School, Newcastle upon Tyne, NE2 4HH, UK
E. Poggiogalle
Affiliation:
Department of Experimental Medicine - Medical Pathophysiology, Food Science and Endocrinology Section, Sapienza University of Rome, 00185 Rome, Italy
B. Lee
Affiliation:
Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Medical School, Newcastle upon Tyne, NE2 4HH, UK
C.M. Prado
Affiliation:
Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
G. Mocciaro
Affiliation:
Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Medical School, Newcastle upon Tyne, NE2 4HH, UK
G. Mariniello
Affiliation:
University of Naples, Federico II, 80100, Naples, Italy
J. Lara
Affiliation:
Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, NE1 8ST, Newcastle upon Tyne, UK.
C. Lubrano
Affiliation:
Department of Experimental Medicine - Medical Pathophysiology, Food Science and Endocrinology Section, Sapienza University of Rome, 00185 Rome, Italy
A. Lenzi
Affiliation:
Department of Experimental Medicine - Medical Pathophysiology, Food Science and Endocrinology Section, Sapienza University of Rome, 00185 Rome, Italy
L.M. Donini
Affiliation:
Department of Experimental Medicine - Medical Pathophysiology, Food Science and Endocrinology Section, Sapienza University of Rome, 00185 Rome, Italy
M. Siervo
Affiliation:
Human Nutrition Research Centre, Institute of Cellular Medicine, Newcastle University, Medical School, Newcastle upon Tyne, NE2 4HH, UK
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Abstract

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Sarcopenic Obesity (SO) is characterized by the co-occurrence of high adiposity (HA) and low muscle mass (LM)(Reference St-Onge and Gallagher1) and it has been linked to insulin resistance, inflammation and increased cardio-metabolic risk(Reference Goodpaster, Krishnaswami and Resnick2, Reference George3). This cross-sectional study investigated the association between markers of insulin sensitivity and SO defined using three novel body composition definitions: 1) body composition phenotypes; 2) truncal fat mass/appendicular skeletal mass ratio (TrFM/ASM) load-capacity; 3) fat mass/fat free mass ratio (FM/FFM) load-capacity(Reference Prado, Siervo and Mire4, Reference Siervo, Prado and Mire5).

314 participants (18–65 years) were included. Body composition was assessed by dual-energy-X-ray absorptiometry and stratified into four body composition phenotypes: Low Adiposity- High Muscle mass (LA-HM), High Adiposity- High Muscle mass (HA-HM), Low Adiposity- Low Muscle mass (LA-LM) and High Adiposity- Low Muscle mass (HA-LM). Subjects were also stratified into three centile groups: <15th, 15th-84th and ⩾85th centile groups for TrFM/ASM and FM/FFM load capacity definitions(Reference Prado, Siervo and Mire4, Reference Siervo, Prado and Mire5). Glucose tolerance was assessed using a 2-hour oral glucose tolerance test (OGTT) and insulin sensitivity was calculated using the Matsuda Index(Reference Matsuda and DeFronzo6).

Lower insulin sensitivity was observed in the HA-LM (p < 0·001), as well as in the ⩾85th centile groups of the TrFM/ASM ratio (p < 0·001) and the FM/FFM ratio (p = 0·001). HA-LM and ⩾85th centile group of the TrFM/ASM ratio showed significantly higher (p < 0·001) HbA1c concentrations compared to the other phenotypes.

Fig. 1.

Differences in the Matsuda Index in subjects stratified by body composition phenotypes (a), FM/FFM ratio centile load capacity (b) and TrFM/ASM ratio centile load capacity models (c). The variable was log transformed as it was not normally distributed. Data were showed as mean ± standard error of mean. Post-hoc analysis (p < 0·05): a: HA-HM vs LA-HM; b: HA-HM vs LA-LM; c: HA-LM vs LA-HM; d: HA-LM vs LA-LM; e: <15th Centile vs 15th-84th Centile; f: <15th Centile vs ⩾85th Centile. Note: HA-HM: High Adiposity High Muscle; HA-LM: High Adiposity Low Muscle; LA-HM: Low Adiposity High Muscle; LA-LM: Low Adiposity Low Muscle; FM Fat Mass; FFM: Fat Free Mass; TrFM: Truncal Fat Mass; ASM: Appendicular Skeletal muscle Mass; AU: Arbitrary Units.

SO defined by both four body composition phenotypes and TrFM/ASM definitions showed a good association and a better prediction of insulin resistance.

References

1.St-Onge, M-P & Gallagher, D (2010) Nutrition (Burbank, Los Angeles County, Calif) 26(2), 152–5.Google Scholar
2.Goodpaster, BH, Krishnaswami, S, Resnick, H, et al. (2003) Diabetes Care 26(2), 372–9.Google Scholar
3.George, AB (2004) J Clin Endocrinol Metab 89(6), 2583–9.Google Scholar
4.Prado, CMM, Siervo, M, Mire, E, et al. (2014) Am J Clin NutrGoogle Scholar
5.Siervo, M, Prado, CM, Mire, E, et al. (2015) Public Health Nutr 18(7), 1245–54.Google Scholar
6.Matsuda, M & DeFronzo, RA (1999) Diabetes Care 22(9), 1462–70.Google Scholar
Figure 0

Fig. 1. Differences in the Matsuda Index in subjects stratified by body composition phenotypes (a), FM/FFM ratio centile load capacity (b) and TrFM/ASM ratio centile load capacity models (c). The variable was log transformed as it was not normally distributed. Data were showed as mean ± standard error of mean. Post-hoc analysis (p < 0·05): a: HA-HM vs LA-HM; b: HA-HM vs LA-LM; c: HA-LM vs LA-HM; d: HA-LM vs LA-LM; e: <15th Centile vs 15th-84th Centile; f: <15th Centile vs ⩾85th Centile. Note: HA-HM: High Adiposity High Muscle; HA-LM: High Adiposity Low Muscle; LA-HM: Low Adiposity High Muscle; LA-LM: Low Adiposity Low Muscle; FM Fat Mass; FFM: Fat Free Mass; TrFM: Truncal Fat Mass; ASM: Appendicular Skeletal muscle Mass; AU: Arbitrary Units.