Journal article
Prevalence of low muscle mass according to body mass index in older adults.
- Graf CE Medical Rehabilitation, Department of Rehabilitation and Palliative Medicine, Geneva University Hospitals and University of Geneva, Geneva, Switzerland.
- Pichard C Clinical Nutrition, Geneva University Hospitals and University of Geneva, Geneva, Switzerland.
- Herrmann FR Geriatrics, Department of Internal Medicine, Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland.
- Sieber CC Friedrich-Alexander-University Erlangen-Nürnberg, Nürnberg, Germany.
- Zekry D Geriatrics, Department of Internal Medicine, Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland.
- Genton L Clinical Nutrition, Geneva University Hospitals and University of Geneva, Geneva, Switzerland. Electronic address: Laurence.genton@hcuge.ch.
- 2017-01-09
Published in:
- Nutrition (Burbank, Los Angeles County, Calif.). - 2017
Body composition
Elderly
Fat-free mass
Presarcopenia
Skeletal muscle mass
Aged
Body Composition
Body Mass Index
Body Weight
Electric Impedance
Female
Humans
Logistic Models
Male
Multivariate Analysis
Muscle, Skeletal
Prevalence
Retrospective Studies
Sarcopenia
English
OBJECTIVE
Low muscle mass has been associated with increased morbi-mortality and should be identified for optimizing preventive and therapeutic strategies. This study evaluates the prevalence of bioelectrical impedance analysis (BIA)-derived low muscle mass in older persons using definitions found through a systematic literature search and determines the link between body mass index (BMI) and low muscle mass.
METHODS
We performed a systematic search of trials involving ≥100 persons that derived low muscle mass from BIA and reported cut-offs for low muscle mass normalized for body height or weight. These cut-offs were applied to all adults ≥65 y who underwent a BIA measurement at Geneva University Hospital between 1990 and 2011 (N = 3181). The association between BMI and low muscle mass was evaluated through multivariate logistic regressions.
RESULTS
We identified 15 cut-offs based on the fat-free mass index (FFMI), skeletal muscle index (SMI), or skeletal muscle percentage (SMP). Depending on the definition, the prevalence of low muscle mass was 17% to 68% in women and 17% to 85% in men. The risk of low muscle mass increased with a BMI <18.5 kg/m2 when using cut-offs based on FFMI (odds ratio [OR] ♀ 14.28-24.04/♂ 25.42-50.64) or SMI (OR ♀ 3.56-4.56/♂ 7.07-8.87) and decreased with a BMI ≥25 kg/m2 (FFMI: OR ♀ 0.03-0.04/♂ 0.01-0.04; SMI: OR ♀ 0.18-0.25/♂ 0.14-0.18). The opposite association appeared between BMI and cut-offs based on SMP.
CONCLUSION
The prevalence of low muscle mass varies widely depending on the definition, especially in persons with BMI <18.5 or ≥25 kg/m2.
Low muscle mass has been associated with increased morbi-mortality and should be identified for optimizing preventive and therapeutic strategies. This study evaluates the prevalence of bioelectrical impedance analysis (BIA)-derived low muscle mass in older persons using definitions found through a systematic literature search and determines the link between body mass index (BMI) and low muscle mass.
METHODS
We performed a systematic search of trials involving ≥100 persons that derived low muscle mass from BIA and reported cut-offs for low muscle mass normalized for body height or weight. These cut-offs were applied to all adults ≥65 y who underwent a BIA measurement at Geneva University Hospital between 1990 and 2011 (N = 3181). The association between BMI and low muscle mass was evaluated through multivariate logistic regressions.
RESULTS
We identified 15 cut-offs based on the fat-free mass index (FFMI), skeletal muscle index (SMI), or skeletal muscle percentage (SMP). Depending on the definition, the prevalence of low muscle mass was 17% to 68% in women and 17% to 85% in men. The risk of low muscle mass increased with a BMI <18.5 kg/m2 when using cut-offs based on FFMI (odds ratio [OR] ♀ 14.28-24.04/♂ 25.42-50.64) or SMI (OR ♀ 3.56-4.56/♂ 7.07-8.87) and decreased with a BMI ≥25 kg/m2 (FFMI: OR ♀ 0.03-0.04/♂ 0.01-0.04; SMI: OR ♀ 0.18-0.25/♂ 0.14-0.18). The opposite association appeared between BMI and cut-offs based on SMP.
CONCLUSION
The prevalence of low muscle mass varies widely depending on the definition, especially in persons with BMI <18.5 or ≥25 kg/m2.
- Language
-
- English
- Open access status
- closed
- Identifiers
-
- DOI 10.1016/j.nut.2016.10.002
- PMID 28063507
- Persistent URL
- https://sonar.ch/global/documents/169403
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