FRI0323 The association of fat mass and skeletal muscle mass with knee OA: The neo study

2013 ◽  
Vol 71 (Suppl 3) ◽  
pp. 423.1-423
Author(s):  
W. Visser ◽  
M. den Heijer ◽  
M. Reijnierse ◽  
R. de Mutsert ◽  
F. Rosendaal ◽  
...  
2020 ◽  
Author(s):  
Lazuardhi Dwipa ◽  
Rini Widiastuti ◽  
Alif Bagus Rakhimullah ◽  
Marcellinus Maharsidi ◽  
Yuni Susanti Pratiwi ◽  
...  

Abstract Background The relationship between obesity and low bone mineral density (BMD) in older adults is still unclear. Most of the previous study did not account the factor of sarcopenia which is the progressive loss of skeletal muscle mass due to aging, and distribution of fat in obesity. Thus, this study was aimed to explore the correlation between appendicular skeletal muscle mass (ASMM), total fat mass (FM), and truncal fat mass (TrFM) as well as indexes (ASMM/FM and ASMM/TrFM ratio) with BMD in older adults.Methods This was an analytic cross-sectional study. Dual x-ray absorptiometry (DXA) and bioelectric impedance analysis (BIA) were used to assess BMD and body composition, respectively. Appendicular Skeletal Muscle Mass (ASMM) were used in the analysis to reflect sarcopenia, Fat Mass (FM) and Trunkal Fat Mass (TrFM) were used to reflect general and central obesity, respectively. All data were obtained from medical records of Geriatric Clinic of Hasan Sadikin General Hospital Bandung Indonesia from January 2014 to December 2018. The correlation between body compositions variable with BMD were analyzed using Spearman’s test. We also conducted a comparison analysis of body composition variables between low and normal BMD using Mann-Whitney test. Results A total of 112 subjects were enrolled in the study. ASMM and TrFM were positive (rs=0.517, p<0.001) and negative (rS=-0.22, p=0.02) correlated with BMD, respectively. FM were not correlated with BMD, rS=-0.113 (p=0.234). As indexes, ASMM/FM and ASMM/TrFM had positive correlation with BMD, rS=0.277 (p<0.001), and rS=0.391 (p<0.001), respectively. The ASMM, TrFM, and ASMM/TrFM ratio between normal and low BMD also significantly different (p<0.001), meanwhile FM were not (p=0.204).Conclusion ASMM and TrFM have a positive and negative correlation with BMD, respectively. ASMM/TrFM ratio as new sarcopenia-central obesity index has a positive correlation with BMD.


2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Hiroshi Ogawa ◽  
Toshimitsu Koga ◽  
Daisuke Fuwa ◽  
Hirofumi Tamaki ◽  
Takayuki Nanbu ◽  
...  

Abstract Background and Aims Patients on hemodialysis are prone to undernutrition, malnutrition-inflammation-atherosclerosis (MIA) syndrome, and protein-energy wasting (PEW). One of the major adipocytokines adiponectin (ADPN) is involved in anti-arteriosclerotic and anti-inflammatory processes. However, ADPN is implicated in muscle weakness and loss of muscle mass in the elderly in addition to sarcopenia. At the 2019 ERA-EDTA Congress, we announced that total plasma ADPN levels in patients on hemodialysis (HD) showed a significant inverse correlation with BMI, body fat in percentage, mass and estimated skeletal muscle mass, and ADPN may be involved in sarcopenia in patients on HD. Herein, we investigated the association of ADPN level with sarcopenia in patients on HD using a method different from the one used in our previous study. We examined the relationship between total plasma ADPN level and the rate of change in estimated skeletal muscle mass, bone mineral content, and body fat mass over 5 years after the plasma ADPN measurement. Furthermore, we analyzed whether an elevated ADPN level was predictive of a subsequent decline in these parameters. Method Total plasma ADPN levels were measured using ELISA (Bio Vendor-Laboratorni Medicina a.s., Czech Republic) in 42 male patients on HD (age: 51.1 ± 9.0 years, dialysis vintage: 144.8 ± 99.2 months, BMI: 21.8 ± 3.2, dry BW: 62.0 ± 10.9 kg, dialysis time: 15.6 ± 3.1 hours/week). The estimates of skeletal muscle mass, bone mineral content, and body fat mass were made using multi-frequency bioelectrical impedance analysis (MFBIA) within the same year when total plasma ADPN level were first measured in 2011 as well as in 2016. We then calculated the rates of change in the estimated skeletal muscle mass, bone mineral content, and body fat mass over the 5 years and correlated these parameters with the total plasma ADPN measurements. Results Conclusion Total plasma ADPN levels inversely correlate with larger rates of decrease in estimated skeletal muscle mass and bone mineral content in patients on HD. This suggests that ADPN may play a role in the decline in skeletal muscle mass and bone mineral content over time in patients on HD.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Chi-Hsien Chen ◽  
Li-Ying Huang ◽  
Kang-Yun Lee ◽  
Chih-Da Wu ◽  
Hung-Che Chiang ◽  
...  

Maturitas ◽  
2007 ◽  
Vol 56 (4) ◽  
pp. 404-410 ◽  
Author(s):  
Marco Di Monaco ◽  
Fulvia Vallero ◽  
Roberto Di Monaco ◽  
Rosa Tappero ◽  
Alberto Cavanna

2021 ◽  
Author(s):  
Pablo Cresta Morgado ◽  
Alfredo Navigante ◽  
Adriana Pérez

Abstract BACKGROUND:Body composition and its changes affect cancer patient outcomes. Its determination requires specific and expensive devices. We designed a study to evaluate machine learning approaches to predict fat and skeletal muscle mass using daily practice clinical variables.METHODS:We designed a cross-sectional study in advanced gastrointestinal cancer patients. Response variables were skeletal muscle mass and body fat mass, measured by bioimpedance analysis. Predictors were laboratory and anthropometric variables. Imputation methods were applied. Six approaches were analyzed: (1) multicollinearity analysis, best subset selection (BSS) and multiple linear regression; (2) multicollinearity, BSS and generalized additive models (GAM); (3) multicollinearity, lasso to perform variable selection and GAM; (4) ridge regression; (5) lasso regression; (6) random forest. Model selection was performed evaluating the Mean Squared Error calculated by leave-one-out cross-validation.RESULTS:We included 101 patients under chemotherapy treatment. For skeletal muscle mass, the best approach was the combination of multicollinearity analysis followed by BSS and GAM using smoothing splines with 6 variables (albumin, Hb, height, weight, sex, lymphocytes). The adjusted R2 was 0.895. The best approach for fat mass was multicollinearity analysis, variable selection by lasso, and GAM using smoothing splines with 3 variables (waist-hip ratio, weight, sex). The adjusted R2 was 0.917.CONCLUSION:We developed the first accurate predictive models for body composition in cancer patients applying daily practice clinical variables. This study shows that machine learning is a useful tool to apply in body composition. This is a starting point to evaluate these approaches in research and clinical practice.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 789.1-790 ◽  
Author(s):  
M. Wieczorek ◽  
C. Rotonda ◽  
J. Sellam ◽  
F. Guillemin ◽  
A. C. Rat

Background:Many trials investigated the beneficial effect of physical activity (PA) on physical function (PF) in people with osteoarthritis (OA), but factors involved in this relationship are poorly understood. Considering the link between OA and obesity and obesity-related disorders, body composition (BC) could be one of these factors.Objectives:To examine the relationships between baseline components of PA and 5-year PF scores, considering BC variables measured at 3 years as potential mediators in theses associations (Figure).Methods:We used data from the KHOALA cohort, a French population-based multicenter cohort of 878 patients with symptomatic knee and/or hip OA, aged between 40 and 75 years old. Baseline PA intensity (Metabolic Equivalent of Task, MET), frequency (times/week), duration (hours/week) and type (weight-bearing or not) were assessed by the Modifiable Activity Questionnaire. PF was measured with the WOMAC questionnaire at 5 years (higher scores = greater functional limitations).Skeletal muscle mass (grams) and fat mass (grams) were measured by dual X-ray absorptiometry (DXA) in 358 patients at 3 years. Fat mass index (kg/m2), appendicular fat mass (kg), % of fat mass, lean mass index (kg/m2), appendicular muscle mass (kg), skeletal muscle mass index (kg/m2or %) were calculated based on DXA data. Sarcopenia was defined according to the FNIH Sarcopenia Project recommendations.A causal mediation analysis was used to highlight the mediating role of BC variables. Bivariate analyses (multiple linear and logistic regressions) were performed to select the variables of interest. Separate generalized linear models were used to describe the relationships between PA components, PF and selected BC variables. Unadjusted and adjusted for baseline confounders (age, gender, number of comorbidities, disease duration, mental health and vitality scores) models were ran.Results:A 1-MET increase in baseline PA intensity was significantly associated with an improvement in PF at 5 years (-3 points). Weight-bearing PA was also significantly associated with better PF scores (-5 points).A 1-MET-increase in PA intensity at baseline was associated with a subsequent decrease at 3 years in fat mass index (-0.86 k/m2), an increase in skeletal muscle mass index (≥ 6%), and a decrease in % of fat mass (-2%). Non-weight-bearing PA was significantly associated with a decrease in fat mass index (-2.5 kg/m2).A 1-point increase in PF score was associated with a reduction in skeletal muscle mass index (calculated from body mass index, -0.3%) and an increase in skeletal muscle mass index (calculated from height, +3 kg/m2). The presence of sarcopenia was significantly associated with a degradation of PF (+7 points).Crude analyses indicated that 20.4% of the effect of baseline PA intensity on PF scores at 5 years was mediated by skeletal muscle mass index (calculated from height), 23.2% by fat mass index and 26.6% by % of fat mass. Similarly, 19.3% of the effect of baseline PA type on PF scores at 5 years was mediated by fat mass index and 15.1% by % of fat mass. After adjustment, we found no longer evidence of a mediating role of BC variables in these associations.Conclusion:We found significant associations between a 1-MET increase in PA intensity, weight-bearing PA at baseline and improvement in PF at 5 years, without any mediating role of BC variables. Further studies are needed to better understand the factors involved in these associations, especially psychosocial variables.Disclosure of Interests:Maud Wieczorek: None declared, Christine Rotonda: None declared, Jérémie SELLAM: None declared, Francis Guillemin Grant/research support from: Francis Guillemin received a grant from Expanscience paid to his institution., Anne-Christine Rat: None declared


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Nana Takao ◽  
Satoshi Kurose ◽  
Takumi Miyauchi ◽  
Katsuko Onishi ◽  
Atsuko Tamanoi ◽  
...  

Abstract Background An effective strategy for weight loss in patients who are overweight or obese is to reduce body fat mass while maintaining skeletal muscle mass. Adiponectin and myostatin are affected through changes in body composition due to weight loss, and examining their dynamics may contribute to strategies for maintaining skeletal muscle mass through weight loss. We aimed to examine the relationships among myostatin, adiponectin, and body composition, depending on the extent of weight loss, in patients with obesity undergoing a weight loss program. Methods We examined 66 patients with obesity (age: 46.8 ± 14.0 years, body mass index: 34.3 [31.0–38.4] kg/m2) attending a hospital weight loss program. We categorized the patients into two groups, namely an L group (those with a weight reduction of < 5% from baseline) and an M group (those with a weight reduction of > 5% from baseline). All patients underwent blood tests and were assessed for body composition, insulin resistance, adipocytokine and myokine levels, exercise tolerance, and muscle strength at baseline and post-intervention. Results Serum myostatin and adiponectin levels increased post-intervention in both groups. Body weight and %fat decreased, and the rate of lean body mass (%LBM) increased in both groups. Exercise capacity and muscle strength improved in the M group only. Change in (⊿) myostatin correlated with ⊿%fat, ⊿%LBM, and ⊿adiponectin. ⊿adiponectin (β = − 0.262, p = 0.035) was an independent predictor of ⊿myostatin. Conclusions Myostatin and adiponectin might cross-talk and regulate changes in skeletal muscle and fat mass with or without successful weight loss. These findings indicate that evaluating serum myostatin and adiponectin levels in clinical practice could be used to predict the effects of weight loss and help prevent skeletal muscle mass loss.


2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Andrew O. Agbaje ◽  
Alan R. Barker ◽  
Tomi-Pekka Tuomainen

Abstract Background A temporal association where better arterial function and structure predicts adiponectin level and skeletal muscle mass during childhood remains uninvestigated. Methods We studied 5566 children and adolescents (51% girls) aged 9-11 years from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort, Bristol, UK. Brachial artery endothelial function was determined using flow-mediated dilation (FMD), expressed as the percentage change in diameter from baseline after reactive hyperemia; arterial elasticity as distensibility coefficient (DC) expressed in mean percentage change in cross-sectional area relative to blood pressure (BP); and arterial stiffness by carotid to radial pulse wave velocity (crPWV). Skeletal muscle mass and total fat mass were assessed by dual-energy Xray absorptiometry. We conducted multivariable linear regressions with Sidak correction and adjusted for age, sex, total fat mass, cardiorespiratory fitness, pubertal status, brachial artery diameter, systolic BP, low-density lipoprotein cholesterol, mother’s social-economic class, and time (years) between the measurement of predictors and outcomes. Results FMD (β [95% CI]) = (0.027 [0.007 to 0.047]; P = 0.009) and DC (0.229 [0.088 to 0.369]; P = 0.001) were directly associated with skeletal muscle mass. FMD had a borderline inverse association with adiponectin (-0.004 [-0.008 to &lt; 0.0001]; P = 0.056). crPWV was unrelated to adiponectin and skeletal muscle mass, while DC was not associated with adiponectin. Conclusions Better endothelial function and arterial elasticity were associated with higher skeletal muscle mass while arterial stiffness was unrelated to adiponectin and lean mass. Key message Healthy arterial function and structure may enhance muscle growth in children.


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