Sarcopenia Coexisting with High Adiposity Exacerbates Insulin Resistance and Dyslipidemia in Saudi Adult Men

Association between handgrip strength and metabolic syndrome in relation to gender and adiposity among middle aged and older Saudi populations

AIM

This cross-sectional study investigated the association between metabolic syndrome (MetS) and handgrip strength (HGS) with respect to sex and adiposity in Saudi men (n = 287) and women (n = 268).

MATERIAL AND METHODS

Anthropometry, body composition, HGS, and blood biochemistry were measured. The average age of the study population was 57.65 ± 9.3 years (men = 55.1 ± 9.3 years, women = 60.4 ± 9.3 years). We report that HGS/body mass index (BMI), HGS/weight, and HGS/fat (%) were significantly higher in controls than in patients with MetS in men but not in women. According to the ROC analysis, relative HGS (RHGS) was higher than HGS alone in the association with MetS, which was significant for men (p < 0.01). At lower quartiles of HGS, the probability of MetS was higher in women, and the same was found in men in the lower quartiles of HGS/%Fat. Multinomial regression revealed significant associations between age and adiposity and MetS in men and HGS in women. Additionally, the linear regression of age, HGS, and weight exhibited significant associations between HGS with WC in both sexes.

CONCLUSION

A higher risk of MetS in the lower quartiles of HGS was found in women, and adiposity moderated the relationship between HGS and MetS in men.

Unraveling the enigma of sarcopenia and sarcopenic obesity in Indian adults with type 2 diabetes - a comparative cross-sectional study

BACKGROUND

Sarcopenia and sarcopenic obesity are growing concerns associated with increasing diabetes incidence, but data from Indian diabetic cohorts are limited. This study examined the prevalence and clinical factors associated with sarcopenia and sarcopenic obesity.

METHODS

In this cross-sectional study, 750 participants aged 35-70 years were recruited by systematic stratification and a fixed quota sampling technique from medical camps and categorized into diabetic (n = 250), nondiabetic (n = 250), and obese nondiabetic (n = 250) groups. The assessments included questionnaires, muscle mass estimation by bioimpedance analysis, and blood tests. Sarcopenia was defined using the Asian Working Group consensus, and sarcopenic obesity was defined as sarcopenia with a BMI ≥ 25 kg/m2. Logistic regression was used to analyze risk factors.

RESULTS

Sarcopenia affected 60% of diabetic patients, 28% of nondiabetic patients, and 38% of nonobese nondiabetic patients (p < 0.001). The prevalence of sarcopenic obesity was 40%, 11%, and 30%, respectively (p < 0.001). Diabetes was associated with 2.3-fold greater odds (95% CI 1.1-4.7) of sarcopenia and 2.4-fold greater odds (1.1-5.0) of sarcopenic obesity after adjustment. A duration greater than 10 years, uncontrolled diabetes, age greater than 65 years, low physical activity, hypertension, and dyslipidemia also independently increased the odds.

CONCLUSION

Indian adults with type 2 diabetes have a high burden of sarcopenia and sarcopenic obesity. Early optimization of diabetes care and lifestyle changes are vital for preserving muscle health.

Prevalence of body composition phenotypes and their associations with glycemic, lipidic, and inflammatory biomarkers: a population-based study

We aimed to verify the prevalence of body composition phenotypes and the association of glycemic, lipidic, and inflammatory biomarkers with such phenotypes. This is a cross-sectional, population-based study, with 720 participants aged 20 to 59 years. Body composition was assessed by dual-energy X-ray absorptiometry. Obesity was defined as body fat percentage ≥ 25% in males and ≥ 32% in females and sarcopenia by appendicular muscle mass index < 7.0kg/m2 in males and < 5.5kg/m2 in females. Sarcopenic obesity (SO) was defined as the presence of both sarcopenia and obesity. The prevalence of obesity, sarcopenia, and SO were 62.5%, 4.5%, and 6.2%, respectively. The association between biomarkers and phenotypes was verified using multinomial logistic regression models adjusted for confounding factors. The models showed that increased glycemia (OR = 3.39; 95%CI: 1.83-6.27), total cholesterol (TC) (OR = 2.24; 95%CI: 1.35-3.70), LDL-c (OR = 1.01; 95%CI: 1.00-1.02), VLDL-c (OR = 1.04; 95%CI: 1.02-1.06), non-HDL-c (OR = 1.02; 95%CI: 1.01-1.03), triglycerides (Tg) (OR = 3.66; 95%CI: 2.20-6.06), and decreased HDL-c (OR = 0.97; 95%CI: 0.95-0.98) were significantly associated with the obesity phenotype. Increased HOMA-IR (OR = 3.94; 95%CI: 1.69-9.21), LDL-c (OR = 1.01; 95%CI: 1.00-1.02), non-HDL-c (OR = 1.01; 95%CI: 1.00-1.02), and hs-CRP (OR = 2.42; 95%CI: 1.04-5.66) were independently associated with SO phenotype. Our findings indicate that increased glycemia, TC, Tg, LDL-c, VLDL-c, non-HDL-c, and decreased HDL-c may be indicators of the obesity phenotype and that increased hs-CRP, HOMA-IR, LDL-c, and non-HDL-c appear to be indicators of the SO phenotype. Those parameters may be used as additional markers for screening.

Dyslipidemia is associated with sarcopenia of the elderly: a meta-analysis

PURPOSE

Sarcopenia is a pathological change characterized by muscle loss in older people. According to the reports, there is controversy on the relationship between dyslipidemia and sarcopenia. Therefore, this meta-analysis aimed to explore the association between sarcopenia and dyslipidemia.

METHODS

We searched the Cochrane Library, Web of Science, PubMed, China National Knowledge Infrastructure (CNKI), Wan Fang, China Science and Technology Journal Database (VIP Database) for case‒control studies to extract data on the odds ratio (OR) between sarcopenia and dyslipidemia and the MD(mean difference) of TC, LDL-C, HDL-C, TG, and TG/HDL-C between sarcopenia and nonsarcopenia. The JBI(Joanna Briggs) guidelines were used to evaluate the quality. Excel 2021, Review Manager 5.3 and Stata 16.0 were used for the statistical analysis.

RESULTS

Twenty studies were included in the meta-analysis, 19 of which were evaluated as good quality. The overall OR of the relationship between sarcopenia and dyslipidemia was 1.47, and the MD values of TC, LDL-C, HDL-C, TG, and TG/HDL-C were 1.10, 1.95, 1.27, 30.13, and 0.16 respectively. In female, compared with the non-sarcopnia, the MD of TC, LDL-C, HDL-C, TG of sarcopenia were - 1.67,2.21,1.02,-3.18 respectively. In male, the MD of TC, LDL-C, HDL-C, TG between sarcopenia and non-sarcopenia were - 0.51, 1.41, 5.77, -0.67. The OR between sarcopenia and dyslipidemia of the non-China region was 4.38, and it was 0.9 in China. In the group(> 60), MD of TC between sarcopenia and non-sarcopenia was 2.63, while it was 1.54 in the group(20-60).

CONCLUSION

Dyslipidemia was associated with sarcopenia in the elderly, which was affected by sex, region and age.

Causal relationship between lipid profile and muscle atrophy: A bi-directional Mendelian randomization study

BACKGROUND

The aim of this study was to analyze the bi-directional causal relationship between lipid profile and characteristics related to muscle atrophy by using a bi-directional Mendelian randomization (MR) analysis.

METHODS

The appendicular lean mass (ALM), whole body fat-free mass (WBFFM) and trunk fat-free mass (TFFM) were used as genome-wide association study (GWAS) data for evaluating muscle mass; the usual walking pace (UWP) and low grip strength (LGS) were used as GWAS data for evaluating muscle strength; and the triglycerides (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL), low density lipoprotein cholesterol (LDL), apolipoprotein A-1 (Apo A-1), and apolipoprotein B (Apo B) were used as GWAS data for evaluating lipid profile. For specific investigations, we mainly employed inverse variance weighting for causal estimation and MR-Egger for pleiotropy analysis.

RESULTS

MR results showed that the lipid profile predicted by genetic variants was negatively correlated with muscle mass, positively correlated with UWP, and was not causally correlated with LGS. On the other hand, the muscle mass predicted by genetic variants was negatively correlated with lipid profile, the UWP predicted by genetic variants was mainly positively correlated with lipid profile, while the LGS predicted by genetic variants had no relevant causal relationship with lipid profile.

CONCLUSIONS

Findings of this MR analysis suggest that hyperlipidemia may affect muscle mass and lead to muscle atrophy, but has no significant effect on muscle strength. On the other hand, increased muscle mass may reduce the incidence of dyslipidemia.

Anticipated correlation between lean body mass to visceral fat mass ratio and insulin resistance: NHANES 2011-2018

Objective

The relationship between body composition and insulin resistance (IR) is controversial. This study aimed to thoroughly examine the correlation between adipose tissue, lean body mass, and IR as evaluated by the Homeostatic Model Assessment (HOMA-IR).

Methods

In this cross-sectional study, we utilized data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2011 and 2018. Our study included 4981 subjects, and we employed multiple linear regression, smoothed curve fitting, threshold, and saturation effect analysis to investigate the relationship between lean body mass, visceral fat mass, and IR. Also, we used the lean body mass to visceral fat ratio (Log LM/VFM) as a proxy variable to analyze its association with IR alone.

Results

The study discovered a negative link between lean body mass and IR, but the visceral fat mass was positively correlated after correcting for covariates. A negative correlation was observed when the alternative variable Log LM/VFM was analyzed separately for its association with IR. This association was present regardless of whether the exposure variables were analyzed as continuous or categorical. The data analysis revealed a nonlinear relationship between Log LM/VFM and IR, as evidenced by the generalized additive model. In addition, a threshold effect with a critical value of 1.80 and a saturation effect with a critical point of 2.5 were also observed. Further subgroup analysis for sex, age, BMI, active levels, hypertension, and diabetes showed considerable robustness between the relationship of Log LM/VFM and IR.

Conclusion

Maintaining a proper ratio of lean body mass and visceral fat is beneficial for decreasing IR.

Azilsartan Ameliorates Skeletal Muscle Wasting in High Fat Diet (HFD)-induced Sarcopenic Obesity in Rats via Activating Akt Signalling Pathway

An association between the loss of skeletal muscle mass and obesity in the geriatric population has been identified as a disease known as sarcopenic obesity. Therefore, therapeutic/preventive interventions are needed to ameliorate sarcopenia. The present study investigates the effect of azilsartan (AZL) on skeletal muscle loss in High-Fat Diet (HFD)-induced sarcopenic obese (SO) rats. Four- and fourteen-months male Sprague Dawley rats were used and randomized in control and azilsartan treatment. 14 months animals were fed with HFD for four months and labeled as HFD-fed SO rats. Young & old rats received 0.5% carboxymethyl cellulose as a vehicle/AZL (8 mg/kg, per oral) treatment for six weeks. Grip strength and body composition analysis were performed after the last dose of AZL. Serum and gastrocnemius (GN)muscles were collected after animal sacrifice. AZL treatment significantly increased lean muscle mass, grip strength, myofibrillar protein, and antioxidant (superoxide dismutase & nitric oxide) levels in SO rats. AZL also restored the muscle biomarkers (creatine kinase, myostatin & testosterone), and insulin levels. AZL improves cellular, and ultracellular muscle structure and prevents type I to type II myofiber transitions in SO rats. Further, immunohistochemistry results showed increased expressions of pAkt and reduced expression of MuRF-1 and TNF-α exhibiting that AZL intervention could decrease protein degradation in SO rats. In conclusion, present results showed that AZL significantly increased lean mass, and restored muscle biomarkers, and muscle architecture. Taken together, the aforementioned findings suggest that azilsartan could be a possible therapeutic approach to reduce muscle wasting in sarcopenic obesity.

Prevalence and risk factors of sarcopenia without obesity and sarcopenic obesity among Chinese community older people in suburban area of Shanghai: A cross-sectional study

Objectives

The aim of the present study was to explore the prevalence and risk factors of sarcopenia without obesity (S) and sarcopenic obesity (SO) among community-dwelling older people in the Chongming District of Shanghai, China, according to the Asian Working Group for Sarcopenia (AWGS) 2019 Consensus as the diagnostic criteria of sarcopenia.

Methods

In this cross-sectional study, a total of 1,407 subjects aged ≥65 years were included, where the mean age of the subjects was 71.91 ± 5.59 years and their mean body mass index (BMI) was 24.65 ± 3.32 kg/m². According to the Asian Working Group for Sarcopenia (AWGS) 2019 Consensus, sarcopenia was defined as a low appendicular skeletal muscle mass index (≤7.0 kg/m² in males and ≤5.7 kg/m² in females), decreased handgrip strength (<28.0 kg in males and <18.0 kg in females), and/or low gait speed (<1.0 m/s) or poor 5-time chair stand test (5CST) (≥12s). The SO met both the diagnostic criteria for sarcopenia and obesity, meanwhile obesity was defined as an increased percentage of body fat (PBF) (≥25% in males and ≥35% in females). Univariate and multiple logistic regression analyses were performed to explore the risk factors of both S and SO.

Results

The prevalence of S and SO was 9.74% (M: 9.29%, F: 10.05%) and 9.95% (M: 13.94%, F: 7.14%). Lower BMI (OR = 0.136, 95% CI: 0.054-0.340, p < 0.001), lower hip circumference (OR = 0.858, 95% CI: 0.816-0.903, p < 0.001), farming (OR = 1.632, 95% CI: 1.053-2.530, p = 0.028), higher high-density lipoprotein cholesterol (HDL-C) level (OR = 2.235, 95% CI: 1.484-3.367, p < 0.001), and a sleep duration <7 h (OR = 0.561, 95% CI: 0.346-0.909, p = 0.019) were risk factors for S. While aging (70-74 y, OR = 1.923, 95% CI: 1.122-3.295, p = 0.017; 75-79 y, OR = 3.185, 95% CI: 1.816-5.585, p < 0.001; ≥80 y, OR = 7.192, 95% CI: 4.133-12.513, p < 0.001), male (OR = 1.981, 95% CI: 1.351-2.904, p < 0.001), higher BMI (OR = 4.865, 95% CI: 1.089-21.736, p = 0.038), higher monocyte level (OR = 4.203, 95% CI: 1.340-13.181, p = 0.014), and a sleep duration >9 h (OR = 1.881, 95% CI: 1.117-3.166, p = 0.017) were risk factors for SO.

Conclusion

Our study showed the high prevalence of S and SO among community-dwelling older people in the Chongming District. The SO was more prevalent in males. Behavioral factors and lifestyle (such as farming and sleep duration) were associated more with the development of S, while age and male gender were associated more with the development of SO.

Organokines, Sarcopenia, and Metabolic Repercussions: The Vicious Cycle and the Interplay with Exercise

Sarcopenia is a disease that becomes more prevalent as the population ages, since it is directly linked to the process of senility, which courses with muscle atrophy and loss of muscle strength. Over time, sarcopenia is linked to obesity, being known as sarcopenic obesity, and leads to other metabolic changes. At the molecular level, organokines act on different tissues and can improve or harm sarcopenia. It all depends on their production process, which is associated with factors such as physical exercise, the aging process, and metabolic diseases. Because of the seriousness of these repercussions, the aim of this literature review is to conduct a review on the relationship between organokines, sarcopenia, diabetes, and other metabolic repercussions, as well the role of physical exercise. To build this review, PubMed-Medline, Embase, and COCHRANE databases were searched, and only studies written in English were included. It was observed that myokines, adipokines, hepatokines, and osteokines had direct impacts on the pathophysiology of sarcopenia and its metabolic repercussions. Therefore, knowing how organokines act is very important to know their impacts on age, disease prevention, and how they can be related to the prevention of muscle loss.

Effects of three modes of physical activity on physical fitness and hematological parameters in older people with sarcopenic obesity: A systematic review and meta-analysis

Objective: This systematic review and meta-analysis assessed the effects of three modes of physical activity (PA) (aerobic training [AT], resistance training [RT], and aerobic combined with resistance training [MT]) on body composition (body weight [BW], body mass index [BMI] and percentage of body fat [BF%]), muscle mass (skeletal muscle mass [SM], appendicular skeletal muscle mass [ASM] and appendicular skeletal muscle mass index [ASMI]), muscle strength (handgrip strength [HG] and knee extension strength [KES]), physical performance (gait speed [GS]) and hematological parameters (inflammatory markers, insulin-like growth factor 1 [IGF-1] and lipid profiles) in older people with sarcopenic obesity (SO).

Methods: We searched all studies for PA effects in older people with SO from six databases published from January 2010 to November 2021. Two researchers independently screened studies, extracted data according to inclusion and exclusion criteria, and assessed the quality of included studies. Pooled analyses for pre-and post- outcome measures were performed by Review Manager 5.4. We calculated a meta-analysis with a 95% confidence interval (95% CI) and the standardized mean differences (SMD).

Results: 12 studies were analyzed. There were 614 older people (84.9% female) with SO, aged 58.4 to 88.4 years. Compared with a no-PA control group, AT decreased BW (SMD = −0.64, 95% CI: −1.13 to −0.16, p = 0.009, I² = 0%) and BMI (SMD = −0.69, 95% CI: −1.18 to −0.21, p = 0.005, I² = 0%); RT improved BF% (SMD = −0.43, 95% CI: −0.63 to −0.22, p < 0.0001, I² = 38%), ASMI (SMD = 0.72, 95% CI: 0.24 to 1.21, p = 0.004, I² = 0%), ASM (SMD = −0.94, 95% CI: −1.46 to −0.42, p = 0.0004), HG (SMD = 1.06, 95% CI: 0.22 to 1.91, p = 0.01, I² = 90%) and KES (SMD = 1.06, 95% CI: 0.73 to 1.39, p < 0.00001, I² = 14%); MT improved BMI (SMD = −0.77, 95% CI: −1.26 to −0.28, p = 0.002, I² = 0%), BF% (SMD = −0.54, 95% CI: −0.83 to −0.25, p = 0.0003, I² = 0%), ASMI (SMD = 0.70, 95% CI: 0.22 to 1.19, p = 0.005, I² = 0%) and GS (SMD = 0.71, 95% CI: 0.23 to 1.18, p = 0.004, I² = 37%). PA increased IGF-1 (SMD = 0.38, 95% CI: 0.11 to 0.66, p = 0.006, I² = 0%), but had no effect on inflammatory markers and lipid profiles.

Conclusion: PA is an effective treatment to improve body composition, muscle mass, muscle strength, physical performance, and IGF-1 in older people with SO.

Chair stand test as a proxy for physical performance and muscle strength in sarcopenia diagnosis: the Korean frailty and aging cohort study

BACKGROUND

The 5-times chair stand test (5CST) is a proxy tool for measuring physical performance and muscle strength in diagnosing sarcopenia. The Asian Working Group for Sarcopenia 2019 guidelines recommends the 5CST for evaluating gait speed, whereas the European Working Group on Sarcopenia in Older People guidelines recommend the chair stand test as a proxy for muscle strength.

AIMS

This study sought to determine whether the chair stand test correlates with handgrip strength and gait speed, and investigate sex differences in these relationships.

METHODS

We used data collected from 1416 participants (678 men and 738 women) in the 2017 Korean Frailty and Aging Cohort Study (KFACS).

RESULTS

The 5CST time had a higher correlation with gait speed (r =  - 0.470) than handgrip strength (r =  - 0.309). In addition, 5CST time predicted low gait speed (area under the curve [AUC] 0.727) better than low handgrip strength (AUC 0.641). The optimal cutoff values of the 5CST to estimate low gait speed were 10 s for men (sensitivity 62%, specificity 64%) and 11 s for women (sensitivity 68%, specificity 67%). The optimal cutoff values of the 5CST for low handgrip strength were the same as those for low gait speed (10 s for men and 11 s for women).

CONCLUSIONS

The 5-times chair stand test fits with gait speed and handgrip strength but seems to be a better proxy of gait speed than handgrip strength. The optimal cutoff values of the 5CST to estimate low gait speed and low handgrip strength were lower in men than women. Although none of the AWGS 2019 or EWGSOP guidelines present sex-specific cutoffs for the 5CST, it needs to be considered in the next guidelines.

Sarcopenic Obesity with Normal Body Size May Have Higher Insulin Resistance in Elderly Patients with Type 2 Diabetes Mellitus

OBJECTIVE

Data are limited regarding how body composition is linked to insulin resistance in elderly patients with type 2 diabetes mellitus (T2DM). We examined the association between body composition and insulin resistance in elderly T2DM patients.

METHODS

The cross-sectional study included 488 Chinese elderly patients wth T2DM. Subjects were classified into four groups based on body composition: normal body composition (NBC), low muscle mass alone (LMM), high body fat alone (HBF), both low muscle mass and high body fat (LMMHBF).

RESULTS

The percentage of subjects with LMMHBF was 14.5% (11.9% in men and 17.7% in women). Homeostasis model assessment of insulin resistance (HOMA2-IR) was higher in the LMMHBF group than in the HBF group (p = 0.045), and was also significantly higher in the LMMHBF or HBF group than in the NBC or LMM group. The HBF group showed the highest body mass index (BMI) of the four groups of different body compositions, and the LMMHBF group showed lower BMI than the HBF group; however, there was no significant difference in BMI or waist to hip ratio (WHR) between the LMMHBF group and the NBC group. The LMMHBF and HBF groups were significantly associated with increased risk of insulin resistance compared to the NBC group, with odds ratios (ORs) of 4.47 [95% confidence interval (CI) 2.06-9.68, p < 0.001] and 1.76 (95% CI 1.02-3.02, p = 0.041) respectively, even after the adjustment for covariates.

CONCLUSION

In China, though elderly T2DM patients with the body composition of sarcopenic obesity (as defined by coexistence of low muscle mass and high body fat) seemed to have normal body size, they exhibited the most severe degree and the highest risk of insulin resistance.

Waist-to-height ratio, an optimal anthropometric indicator for metabolic dysfunction associated fatty liver disease in the Western Chinese male population

Background

Non-alcoholic fatty liver disease (NAFLD) has been entitled as metabolic-dysfunction associated fatty liver disease (MAFLD). Therefore anthropometric indicators of adiposity may provide a non-invasive predictive and diagnostic tool for this disease. This study intended to validate and compare the MAFLD predictive and diagnostic capability of eight anthropometric indicators.

Methods

The study involved a population-based retrospective cross-sectional design. The Fangchenggang area male health and examination survey (FAMHES) was used to collect data of eight anthropometric indicators, involving body mass index (BMI), waist-to-height ratio (WHtR), waist-hip ratio (WHR), body adiposity index (BAI), cardiometabolic index (CMI), lipid accumulation product (LAP), visceral adiposity index (VAI), and abdominal volume index (AVI). Receiver operating characteristics (ROC) curves and the respective areas under the curves (AUCs) were utilized to compare the diagnostic capacity of each indicator for MAFLD and to determine the optimal cutoff points. Binary logistic regression analysis was applied to identify the odds ratios (OR) with 95% confidence intervals (95% CI) for all anthropometric indicators and MAFLD. The Spearman rank correlation coefficients of anthropometric indicators, sex hormones, and MAFLD were also calculated.

Results

All selected anthropometric indicators were significantly associated with MAFLD (P < 0.001), with an AUC above 0.79. LAP had the highest AUC [0.868 (95% CI, 0.853–0.883)], followed by WHtR [0.863 (95% CI, 0.848–0.879)] and AVI [0.859 (95% CI, 0.843–0.874)]. The cutoff values for WHtR, LAP and AVI were 0.49, 24.29, and 13.61, respectively. WHtR [OR 22.181 (95% CI, 16.216–30.340)] had the strongest association with MAFLD, regardless of potential confounders. Among all the anthropometric indicators, the strongest association was seen between LAP and sex hormones.

Conclusion

All anthropometric indicators were associated with MAFLD. WHtR was identified as the strongest predictor of MAFLD in young Chinese males, followed by LAP and AVI. The strongest association was found between LAP and sex hormones.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-021-01568-9.