Association of sarcopenia and systolic blood pressure with mortality: A 5-year longitudinal study

Prevalence of sarcopenia in middle-aged and older adults with cognitive impairment: a meta-analysis

BACKGROUND

Cognitive impairment, dementia and sarcopenia significantly reduce the quality of life in middle-aged and older adults by impairing daily functioning, making cognitive decline a major concern for healthcare professionals.

OBJECTIVE

To estimate the prevalence of sarcopenia and probable sarcopenia in middle-aged and older adults with cognitive impairment.

METHODS

Six databases-Embase, Ovid MEDLINE, PubMed, CINAHL, Scopus and Web of Science was conducted through February 2025. Cohort and cross-sectional studies included, and a random-effects model was used for pooled prevalence analysis. Cognitive impairment is a decline in cognitive functions, including memory, attention and executive function, covering mild cognitive impairment and dementia. Sarcopenia is decreased skeletal muscle mass and function, assessed by muscle strength or physical performance.

RESULTS

A total of 67 studies involving 23 532 participants revealed a pooled sarcopenia prevalence of 30.1% and a probable sarcopenia prevalence of 40.5%. Additionally, amongst adults aged 65 and older, the prevalence of sarcopenia was 32.7%. The prevalence of sarcopenia varied by setting: 25.3% in community-dwelling populations, 35.5% in hospitals and 41.5% in institutional settings. Moderating factors included age, female, body mass index, comorbidities and risk factors such as depression, diabetes, hypertension, malnutrition, osteoarthritis, alcohol consumption and smoking.

CONCLUSIONS

Approximately one-third of middle-aged and older adults with cognitive impairment demonstrate to have sarcopenia. Early detection and tailored interventions by public health professionals are crucial, particularly for individuals with mild cognitive impairment and dementia. Enhanced preventive strategies are essential to improving outcomes and reducing healthcare costs.

Predictive model for sarcopenia in chronic kidney disease: a nomogram and machine learning approach using CHARLS data

Background

Sarcopenia frequently occurs as a complication among individuals with chronic kidney disease (CKD), contributing to poorer clinical outcomes. This research aimed to create and assess a predictive model for the risk of sarcopenia in CKD patients, utilizing data obtained from the China Health and Retirement Longitudinal Study (CHARLS).

Methods

Sarcopenia was diagnosed based on the Asian Working Group for Sarcopenia (AWGS 2019) criteria, including low muscle strength, reduced physical performance, and low muscle mass. The 2015 CHARLS data were split randomly into a training set (70%) and a testing set (30%). Forty-nine variables encompassing socio-demographic, behavioral, health status, and biochemical factors were analyzed. LASSO regression identified the most relevant predictors, and a logistic regression model was used to explore factors associated with sarcopenia. A nomogram was developed for risk prediction. Model accuracy was evaluated using calibration curves, while predictive performance was assessed through receiver operating characteristic (ROC) and decision curve analysis (DCA). Four machine learning algorithms were utilized, with the optimal model undergoing hyperparameter optimization to evaluate the significance of predictive factors.

Results

A total of 1,092 CKD patients were included, with 231 (21.2%) diagnosed with sarcopenia. Multivariate logistic regression revealed that age, waist circumference, LDL-C, HDL-C, triglycerides, and diastolic blood pressure are significant predictors. These factors were used to construct the nomogram. The predictive model achieved an AUC of 0.886 (95% CI: 0.858-0.912) in the training set and 0.859 (95% CI: 0.811-0.908) in the validation set. Calibration curves showed good agreement between predicted and actual outcomes. ROC and DCA analyses confirmed the model's strong predictive performance. The Gradient Boosting Machine (GBM) outperformed other machine learning models. Applying Bayesian optimization to the GBM achieved an AUC of 0.933 (95% CI: 0.913-0.953) on the training set and 0.932 (95% CI: 0.905-0.960) on the validation set. SHAP values identified age and waist circumference as the most influential factors.

Conclusion

The nomogram provides a reliable tool for predicting sarcopenia in CKD patients. The GBM model exhibits strong predictive accuracy, positioning it as a valuable tool for clinical risk assessment and management of sarcopenia in this population.

Physical inactivity, depressive symptoms, and progression to sarcopenia in older adults: a 4-year longitudinal study

OBJECTIVES

To examine the combined association of physical inactivity and depressive symptoms with the progression to sarcopenia in community-dwelling older adults.

DESIGN

A 4-year follow-up longitudinal study.

SETTING

Community-dwelling older adults living in Japan, who were not sarcopenic at baseline.

PARTICIPANTS

The participants were 2,538 community-dwelling older adults and with a mean age of 70.9 ± 4.6 years, of whom 1,327 (52.3%) were women.

MEASUREMENTS

Sarcopenia, defined according to the European Working Group on Sarcopenia in Older People 2, was assessed at baseline and at the 4-year follow-up. Participants were divided into four groups according to their inactivity and depressive symptoms. Physical inactivity was assessed using two face-to-face questions regarding the frequency of regular exercise, sports, and light exercise per week. Depressive symptoms were defined as a score of six or higher on the Geriatric Depression Scale 15-item version. Logistic regression analysis was used to determine whether inactivity and depressive symptoms were associated with progression to sarcopenia 4 years later. For participants who could not be followed and participants with missing data in the follow-up assessment, the data at the follow-up assessment were imputed using the multiple imputations.

RESULTS

After 4 years, 518 participants (20.4%) with complete data progressed to sarcopenia. The rate of progression to sarcopenia after multiple imputations was 23.4%. Logistic regression analysis after multiple imputations showed that the group with both factors was significantly associated with the progression to sarcopenia [Odds ratio, 1.64 (95% Confidence interval 1.11-2.44), p = 0.014]. By contrast, no significant association was found for either inactivity or depressive symptoms alone.

CONCLUSION

This study indicates that the coexistence of physical inactivity and depressive symptoms may contribute to the progression of sarcopenia. Addressing both physical and mental factors, rather than limiting the problem to a single factor, may be essential for preventing sarcopenia.

Sex differences in the association between chest computed tomography-defined sarcopenia and cardiovascular risk factors among inpatients

Background

While sarcopenia has been found to be associated with increased risks of cardiovascular diseases (CVDs), evidence exploring sex-related differences remains insufficient. This study aimed to investigate the differences in how often sarcopenia occurs in each sex, as determined by skeletal muscle area (SMA) in chest CT images, and its association with CVD common risk factors.

Methods

This cross-sectional study involved 1,340 inpatients from the Department of Geriatrics of Renji Hospital, affiliated to Shanghai Jiaotong University School of Medicine. Data on age, sex, body mass index (BMI), smoking status, disease history, and clinical parameters were collected. Sarcopenia was defined using chest CT images with a cut-off value of T12-SMA/height2 <25.75 cm2/m2 in male patients and <20.16 cm2/m2 in female patients. Cardiovascular risk was assessed using the Framingham risk score (FRS). The association between T12-SMA/height2-defined sarcopenia and CVD risk factors by sex was evaluated using a multivariate logistic regression analysis.

Results

The overall prevalence of T12-SMA/height2-defined sarcopenia (<25.75 cm2/m2 for male patients, <20.16 cm2/m2 for female patients) was 54.03%, with 48.09% in male patients and 63.19% in female patients. The proportion of male patients with high CVD risk was greater than that of female patients. The multivariate analysis revealed that T12-SMA/height2-defined sarcopenia was independently associated with age (in male patients only), systolic blood pressure (SBP), cholesterol, and high-density lipoprotein cholesterol (HDL-C) among the six FRS cardiovascular risk indices.

Conclusion

Our results suggest that T12-SMA/height2-defined sarcopenia was more prevalent in male patients than in female patients. Sarcopenia was associated with higher levels of SBP and HDL-C and lower levels of cholesterol. Increasing age had a more significant effect on CVD risk in male patients.

Associations between life's essential 8 and sarcopenia in US adults: a cross-sectional analysis

Cardiovascular disease (CVD) is closely associated with sarcopenia. We aimed to examine the relationship between Life's Essential 8 (LE8) and the incidence of sarcopenia among adults in the United States. In this study, a cross-sectional analysis was conducted using data from the National Health and Nutrition Examination Survey from 2013 to 2018 and included 5999 adult participants. LE8 score was categorized into low (< 49), moderate (49-79), and high CVH (≥ 79) groups and consisted of health behavior score and health factor score based on American Heart Association definitions. Sarcopenia was defined according to The Foundation for the National Institutes of Health Sarcopenia Project. Multivariate logistic regressions, restricted cubic spline regressions, and subgroup analyses were used to assess the association between LE8 and sarcopenia. LE8 and its subscales score were negatively associated with the incidence of sarcopenia in US adults.

Evaluation of health factors on artificial intelligence and the internet of things-based older adults healthcare programmes

Objective

This study evaluates Artificial intelligence and the Internet of Things-based older adults' healthcare programmes (AI·IoT-OAHPs), which offer non-face-to-face and face-to-face health management to older adults for health promotion.

Methods

The study involved 146 participants, adults over 60 who had registered in AI·IoT-OAHPs. This study assessed the health factors as the outcome of pre- and post-health screening and health management through AI·IoT-OAHPs for six months.

Results

Preand post-health screening and management through AI·IoT-OAHPs were evaluated as significant outcomes in 14 health factors. Notably, the benefits of post-cognitive function showed a twofold increase in older female adults through AI·IoT-OAHPs. Adults over 70 showed a fourfold increase in post-walking days, a threefold in post-dietary practice, and a twofold in post-cognitive function in the post-effects compared with pre via AI·IoT-OAHPs.

Conclusions

AI·IoT-OAHPs seem to be an effective program in the realm of face-to-face and non-face-to-face AI·IoT-based older adults' healthcare initiatives in the era of COVID-19. Consequently, the study suggests that AI·IoT-OAHPs contribute to the upgrade in health promotion of older adults. In future studies, the effectiveness of AI·IoT-OAHPs can be evaluated as a continuous project every year in the short term and every two years in the long term.

Low lean mass with obesity in older adults with hypertension: prevalence and association with mortality rate

BACKGROUND

The influence of sarcopenic obesity (SO) on overall survival in older adults with hypertension has not been addressed. The aim of this study was to investigate the prevalence and mortality predictive value of various body composition phenotypes, focusing mainly on SO, in older adults with hypertension.

METHODS

We included 1105 hypertensive patients aged ≥ 60 years from the National Health and Nutrition Examination Survey 1999-2004. Sarcopenia was broadly defined based on low lean mass (LLM; as measured by dual-energy X-ray absorptiometry), and was defined using appendicular lean mass (ALM) divided by height squared (ALM/height2), weight (ALM/weight), and body mass index (BMI; ALM/BMI), respectively. Obesity was defined as BMI ≥ 30 kg/m2, body fat percentage ≥ 30/42%, or waist circumference ≥ 102/88 cm. The prevalence of LLM with obesity was estimated according to each ALM index (ALMI). Multivariable Cox regression analysis and sensitivity analysis were used to examine the association between various body composition phenotypes and all-cause mortality.

RESULTS

In older adults with hypertension, the prevalence of LLM with obesity by the ALM/height2 index (9.8%) was lower relative to the ALM/weight (11.7%) and ALM/BMI indexes (19.6%). After a median follow-up of 15.4 years, 642 deaths occurred. In the fully adjusted models, LLM with obesity was significantly associated with a higher risk of all-cause mortality (hazard ratio [HR] 1.69, 95% confidence interval [CI] 1.14-2.49, P = 0.008; HR 1.48, 95% CI 1.04-2.10, P = 0.028; HR 1.30, 95% CI 1.02-1.66, P = 0.037; respectively) compared with the normal body phenotype, with no statistical differences found in individuals with LLM or obesity alone. Sensitivity analysis confirmed the robustness of the results.

CONCLUSIONS

The prevalence of LLM with obesity markedly differed in older adults with hypertension according to the 3 different ALMIs, varying from 9.8%, 11.7%, to 19.6%. Patients with both LLM and obesity had a higher risk of all-cause mortality. Further large, prospective, cohort studies are warranted to validate these findings and uncover underlying mechanisms.

The frequency of sarcopenia has increased in patients with glomerulonephritis

AIM

Sarcopenia is defined as the loss of muscle mass and muscle strength, and its frequency increases in kidney patients. However, sarcopenia frequency in patients with glomerulonephritis is unknown. The present study aimed to investigate the frequency of sarcopenia in patients with glomerulonephritis and compare the results with the healthy population for the first time in the literature.

PATIENTS AND METHODS

A total of 110 participants, including 70 patients previously diagnosed with glomerulonephritis and 40 healthy individuals, were included in the study. The diagnosis of sarcopenia was made based on the EWSGOP 2 Criteria.

RESULTS

The mean age of the glomerulonephritis patients group was 39.3 ± 1.5. In the anthropometric measurements of the patients, walking speed was low in 50 patients (71.4%), muscle strength was decreased in 44 patients (62.9%), and sarcopenia was detected in 10 patients (14.3%) according to the EWGSOP 2 Criteria. Considering the anthropometric measurements of the control group, sarcopenia was not detected in any of the subjects according to the EWGSOP 2 Criteria.

CONCLUSION

The result of the present study revealed that the rate of sarcopenia was significantly higher in glomerulonephritis patients compared to the healthy population and that sarcopenia can also be observed even in middle age in this population. We think it would be beneficial for clinicians treating glomerulonephritis to be more careful regarding sarcopenia and keep these parameters in mind during treatment.

Long-Term Mortality Risk in Older Adults with Sarcopenia: An 11-Year Prospective Cohort Study Comparing AWGS 2014 and AWGS 2019 Guidelines for Enhanced Clinical Utility and Accurate Risk Prediction

OBJECTIVES

To discern the diagnostic accuracy between the updated diagnostic consensus of the Asian Working Group for Sarcopenia (AWGS) in 2019 (AWGS 2019) and the previous AWGS 2014 guidelines.

DESIGN

A prospective population-based cohort study.

SETTING AND PARTICIPANTS

The study included 731 older community-dwelling adults aged ≥ 65 years who participated in face-to-face interviews and were followed up for 11-year mortality until 31 Mar 2022.

MEASUREMENTS

We utilized a handgrip strength dynamometer to measure participants' muscle strength, while their walking speed was determined by a timed 6-meter walk test at their usual pace. Additionally, muscle mass was measured using dual-energy X-ray absorptiometry scanning. Sarcopenia was defined as the presence of low muscle mass in combination with weakness and/or slowness both by AWGS 2014 and 2019 criteria.

RESULTS

The present study followed 731 participants (mean age 73.4 ± 5.4 years, men predominant 52.8%) over a period of 11 years, yielding 5927 person-years and 159 deaths. Prevalence of sarcopenia defined by AWGS 2019 and 2014 criteria were 8.5% and 6.8%, respectively. Sarcopenia defined by AWGS 2019 (HR 1.62, 95% CI 1.04-2.54, p=0.034) but not AWGS 2014 was significantly associated with mortality in community-living older adults after adjusting for potential confounders such as age, sex, education, drinking, disease burden and serum level of testosterone. The study also found that the AWGS 2019 criteria had a better model fitness than AWGS 2014 criteria in predicting mortality.

CONCLUSION

AWGS 2019 criteria outperformed AWGS 2014 in identifying sarcopenia risk and predicting mortality. Screening for sarcopenia in older adults may improve health outcomes by identifying those at increased mortality risk.