Estimation of prevalence of sarcopenia by using a new bioelectrical impedance analysis in Chinese community-dwelling elderly people

Wang, Hui; Hai, Shan; Cao, Li; Zhou, Jianghua; Liu, Ping; Dong, Birong

doi:10.1186/s12877-016-0386-z

Cited by 99 publications

(84 citation statements)

References 42 publications

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“…For patients with a walking speed of ≤0.8 m/s, we used the bioelectrical impedance analysis (BIA) to assess muscle mass. The results of BIA are very similar to those of double-energy X-ray absorptiometry and magnetic resonance imaging; BIA also offers the advantages of safety, technical simplicity, low cost, and high patient compliance (Wang et al, 2016;Chien, Huang & Wu, 2008). All the results of BIA have been standardized by using cross-validated Sergi.…”

Section: Methods Of Assessmentmentioning

confidence: 56%

Predicting the risk of sarcopenia in elderly patients with patellar fracture: development and assessment of a new predictive nomogram

Chen

Cai

Kang

et al. 2020

PeerJ

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Purpose To develop a risk prediction model for postoperative sarcopenia in elderly patients with patellar fractures in China. Patients and methods We conducted a community survey of patients aged ≥55 years who underwent surgery for patellar fractures between January 2013 and October 2018, through telephone interviews, community visits, and outpatient follow-up. We established a predictive model for assessing the risk of sarcopenia after patellar fractures. We developed the prediction model by combining multivariate logistic regression analysis with the least absolute shrinkage model and selection operator regression (lasso analysis) as well as the Support Vector Machine (SVM) algorithm. The predictive quality and clinical utility of the predictive model were determined using C-index, calibration plots, and decision curve analysis. We also conducted internal sampling methods for qualitative assessment. Result We recruited 137 participants (53 male; mean age, 65.7 years). Various risk factors were assessed, and low body mass index and advanced age were identified as the most important risk factor (P < 0.05). The prediction rate of the model was good (C-index: 0.88; 95% CI [0.80552–0.95448]), with a satisfactory correction effect. The C index is 0.97 in the validation queue and 0.894 in the entire cohort. Decision curve analysis suggested good clinical practicability. Conclusion Our prediction model shows promise as a cost-effective tool for predicting the risk of postoperative sarcopenia in elderly patients based on the following: advanced age, low body mass index, diabetes, less outdoor exercise, no postoperative rehabilitation, different surgical methods, diabetes, open fracture, and removal of internal fixation.

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Section: Methods Of Assessmentmentioning

confidence: 56%

Predicting the risk of sarcopenia in elderly patients with patellar fracture: development and assessment of a new predictive nomogram

Chen

Cai

Kang

et al. 2020

PeerJ

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“…Skeletal muscle mass was quantified using Bioelectrical Impedance Analysis (BIA) (Model 1500; Bodystat, Isle of Man, UK). Although Dual-Energy X-ray Absorptiometry (DEXA) is commonly used for measuring appendicular lean mass index (ALMI) in sarcopenia studies 8,84 , BIA has been suggested as a valid and low-cost alternative for measuring Skeletal Muscle Mass Index (SMI) and is a common tool in larger population studies 27,85 . Indeed, a high correlation between muscle mass measured with BIA and DEXA has been reported 78,79 .…”

Section: Scientific Reports |mentioning

confidence: 99%

Prevalence and association of single nucleotide polymorphisms with sarcopenia in older women depends on definition

Khanal

Stebbings

et al. 2020

Sci Rep

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The prevalence of sarcopenia depends on the definition used. There are, however, consistent sarcopenic characteristics, including a low muscle mass and muscle strength. Few studies have investigated the relationship between sarcopenia and genotype. A cross-sectional study was conducted with 307 community-dwelling ≥60-year-old women in South Cheshire, UK. Handgrip strength was assessed with a handgrip dynamometer and skeletal muscle mass was estimated using bioelectrical impedance. DNA was extracted from saliva (∼38%) or blood (∼62%) and 24 single-nucleotide polymorphisms (SNPs) were genotyped. Three established sarcopenia definitions -%Skeletal Muscle Mass (%SMM), Skeletal Muscle Mass Index (SMI) and European Working Group on Sarcopenia in Older People (EWGSOP) -were used to assess sarcopenia prevalence. Binary logistic regression with age as covariate was used to identify SNPs associated with sarcopenia. The prevalence of sarcopenia was: %SMM 14.7%, SMI 60.6% and EWGSOP 1.3%. Four SNPs were associated with the %SMM and SMI definitions of sarcopenia; FTO rs9939609, ESR1 rs4870044, NOS3 rs1799983 and TRHR rs7832552. The first three were associated with the %SMM definition, and TRHR rs7832552 with the SMI definition, but none were common to both sarcopenia definitions. The gene variants associated with sarcopenia may help proper counselling and interventions to prevent individuals from developing sarcopenia.Sarcopenia is defined as an ageing-related loss of both muscle mass and strength below a threshold level 1 . It is an important predictor of adverse outcomes such as limited mobility, increased risk of falls, decreased quality of life (QoL), hospitalization and mortality, and contributes to tens of millions of pounds of health care costs in the UK 1-3 . Although muscle weakness and skeletal muscle atrophy are overt characteristics of this geriatric syndrome, there is ongoing debate on the operational definition, screening and diagnosis, and optimal management and treatment of the condition 1,4-6 . The considerable heterogeneity in the reported prevalence of sarcopenia is largely attributable to the different definitions or cut-offs used 7-9 .The fact that some elderly do not show sarcopenia, whilst others of the same age do 10,11 , suggests that some individuals are more susceptible to sarcopenia than others. The different susceptibility is likely due to a combination of factors including physical activity, diet, sedentary behaviour and genetics [12][13][14][15] . Several studies have reported an association of single nucleotide polymorphisms (SNPs) with lean mass, muscle volume and muscle strength [16][17][18] . It is thus possible that individuals carrying favourable gene variants are less susceptible to sarcopenia and hence can maintain independence until later life. To date, five studies have investigated the association of SNPs with sarcopenia; limited to VDR, IL6, ACTN3 and MSTN polymorphisms [19][20][21][22][23] . The studies identified an association of ACTN3 and VDR gene variants with sarcopenia, but di...

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“…[6], hand grip strength was considered to be under 26 kg for males and 18 kg for females. After informing about the patient's dynamometer, they were allowed to try 3 times.…”

Section: Introductionmentioning

confidence: 99%

Sarcopenia in diabetic nephropathy: a cross-sectional study

Çeliker

Selçuk

Olt

2018

Romanian Journal of Internal Medicine

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Objective: To investigate the relationship between sarcopenia and diabetic nephropathy. criteria which consist of hand grip strength, 6-meter walking test and muscle mass. Methods Results:The frequency of sarcopenia increased gradually from 15,1% in healthy control group to 21,4% in the diabetes group, and 34% in diabetic nephropathy group (X 2 for trend, p=0.029),. The frequency of sarcopenia was similar in diabetes and diabetic nephropathy group. However, the frequency of sarcopenia was higher in diabetic nephropathy than healthy controls (OR=2.89, CI [1.11-7.51] in logistic regression). Conclusion:In the present study, the prevalence of sarcopenia was higher in patients with diabetic nephropathy compared to healty controls.

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Estimation of prevalence of sarcopenia by using a new bioelectrical impedance analysis in Chinese community-dwelling elderly people

Cited by 99 publications

References 42 publications

Predicting the risk of sarcopenia in elderly patients with patellar fracture: development and assessment of a new predictive nomogram

Predicting the risk of sarcopenia in elderly patients with patellar fracture: development and assessment of a new predictive nomogram

Prevalence and association of single nucleotide polymorphisms with sarcopenia in older women depends on definition

Sarcopenia in diabetic nephropathy: a cross-sectional study

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