The Prevalence of Sarcopenia among Hunan Province Community-Dwelling Adults Aged 60 Years and Older and Its Relationship with Lifestyle: Diagnostic Criteria from the Asian Working Group for Sarcopenia 2019 Update

The causal relationships between iron status and sarcopenia in Europeans: a bidirectional two-sample Mendelian randomization study

BACKGROUND

Previous studies have indicated potential associations between metals, lifestyle factors, and sarcopenia. However, the specific causal relationships between iron status, lifestyle factors, and sarcopenia remain unclear. Therefore, we conducted a bidirectional two-sample Mendelian Randomization (MR) approach to investigate these relationships.

METHODS

The exposure variables included iron status, living alone, coffee intake, alcohol taken with meals, and moderate physical activity, while the outcome variable was sarcopenia, assessed by grip strength in both hands and usual walking pace. We employed the Weighted Median (WM), the Inverse Variance-Weighted (IVW), and other MR methods to explore these problems for analysis. Simultaneously, we conducted a bidirectional MR analysis to assess whether sarcopenia has a reverse causal relationship with internal iron status.

RESULTS

In our present research, we found serum iron (P = 0.033), ferritin (P = 0.001), transferrin saturation (P = 0.029) and coffee intake (P = 0.002) revealed a negative trend for sarcopenia, living alone (P = 0.022) and alcohol taken with meal (P = 0.006) showed a opposite trend for sarcopenia. Whereas sarcopenia showed negative trend for ferritin (P = 0.041) and transferrin saturation (P = 0.043), showed the opposite trend for transferrin (P = 0.021).

CONCLUSION

Our study suggested that higher serum iron levels might reduce the risk of sarcopenia. Moreover, living alone and alcohol consumption might increase the sarcopenia risk, while coffee intake and moderate physical activity could reduce the sarcopenia risk.

Sarcopenia risk in U.S. younger adults: the impact of physical activity intensity and occupational engagement-insights from a cross-sectional NHANES study

OBJECTIVE

This study aimed to investigate the associations between physical activity (PA) intensity, occupational PA engagement, and sarcopenia in younger adults.

METHODS

Data from the National Health and Nutrition Examination Survey (NHANES) (from 2011 to 2018) were used for the study. PA data were extracted for the Global Physical Activity Questionnaire, and the ratio of limb muscle mass (ALM) to body mass index (BMI) was used to determine sarcopenia. Multiple logistic regression was performed, and dose-response curves were drawn to evaluate the associations.

RESULTS

Of the 8802 adults aged 20 to 59 years, 770 (8.7%) were identified as having sarcopenia. Compared to those in the reference group, the participants in the "low", "moderate", and "high" total METs groups had lower risks of sarcopenia (low: OR = 0.730, 95% CI = 0.583; 0.915; moderate: OR = 0.643, 95% CI = 0.485; 0.853; high: OR = 0.560, 95% CI = 0.457; 0.687). The risk of sarcopenia decreased in the high-intensity recreational PA group; however, such a significant association was observed only in the high-intensity occupational PA group. The relationship between total METs and sarcopenia showed a nonlinear U-shaped trend.

CONCLUSIONS

A greater intensity of PA is associated with a lower risk of sarcopenia among younger adults, regardless of whether moderate or vigorous PA is performed. Moreover, recreational PA may particularly advantageously contrast with occupational PA in lowering the risk of sarcopenia.

The prevalence of sarcopenia and risk factors in the older adult in China: a systematic review and meta-analysis

Background

Understanding the epidemiological information of a certain disease is the first step in related prevention and control work. This article aims to understand the prevalence and associated risk factors of sarcopenia among the older adult (≥60 years old) in China and to provide an evidence-based basis for early identification, management, and prevention of sarcopenia patients.

Methods

We searched seven databases: CNKI, Wanfang, VIP, PubMed, Web of Science, Embase, and Cochrane Library databases from the establishment of the database until January 31, 2024. The Quality evaluation criteria of cross-sectional studies recommended by the Agency for Healthcare Research and Quality (AHRQ) were used for literature quality evaluation. Stata 18.0 software was used for statistical analysis.

Results

We finally included 45 studies, involving a total of 37,571 cases. After statistical analysis, we found that the prevalence of sarcopenia among the older adult in China was 20.7% [95% CI (18.3, 23.0%)]. The results of subgroup analysis suggest that: ① According to gender, the prevalence rate of sarcopenia in women (21.6%) is higher than that in men (19.2%); ② According to age, the prevalence rate of older adult people aged ≥80 (45.4%) was the highest, followed by 70-79 (27.2%) and 60-69 (15.7%). ③ According to region, the prevalence rate of the older adult in the south (21.7%) is higher than that in the north (19.0%); ④ According to the time of publication, the prevalence of sarcopenia among the older adult in China has increased (from 19.2% in 2014-2018 to 21.4% in 2019-2024); ⑤ According to the diagnostic criteria, the detection rate of AWGS (2019) is higher than that of AWGS (2014) (24.5% vs. 19.3%). Finally, aging, low BMI, low leg circumference, smoking, depression, osteoporosis, malnutrition and malnutrition risk are all risk factors for sarcopenia among the older adult in China.

Conclusion

The prevalence of sarcopenia in the older adult in China was higher (20.7%), which should be paid attention to by relevant health authorities. In addition, aging, low BMI, low calf circumference, smoking, depression, osteoporosis, malnutrition and malnutrition risk are risk factors for the development of sarcopenia in the older adult in China. For these high-risk populations, early identification, prevention, and intervention can be carried out to delay the occurrence and progression of sarcopenia.

A Computed Tomography-Based Fracture Prediction Model With Images of Vertebral Bones and Muscles by Employing Deep Learning: Development and Validation Study

BACKGROUND

With the progressive increase in aging populations, the use of opportunistic computed tomography (CT) scanning is increasing, which could be a valuable method for acquiring information on both muscles and bones of aging populations.

OBJECTIVE

The aim of this study was to develop and externally validate opportunistic CT-based fracture prediction models by using images of vertebral bones and paravertebral muscles.

METHODS

The models were developed based on a retrospective longitudinal cohort study of 1214 patients with abdominal CT images between 2010 and 2019. The models were externally validated in 495 patients. The primary outcome of this study was defined as the predictive accuracy for identifying vertebral fracture events within a 5-year follow-up. The image models were developed using an attention convolutional neural network-recurrent neural network model from images of the vertebral bone and paravertebral muscles.

RESULTS

The mean ages of the patients in the development and validation sets were 73 years and 68 years, and 69.1% (839/1214) and 78.8% (390/495) of them were females, respectively. The areas under the receiver operator curve (AUROCs) for predicting vertebral fractures were superior in images of the vertebral bone and paravertebral muscles than those in the bone-only images in the external validation cohort (0.827, 95% CI 0.821-0.833 vs 0.815, 95% CI 0.806-0.824, respectively; P<.001). The AUROCs of these image models were higher than those of the fracture risk assessment models (0.810 for major osteoporotic risk, 0.780 for hip fracture risk). For the clinical model using age, sex, BMI, use of steroids, smoking, possible secondary osteoporosis, type 2 diabetes mellitus, HIV, hepatitis C, and renal failure, the AUROC value in the external validation cohort was 0.749 (95% CI 0.736-0.762), which was lower than that of the image model using vertebral bones and muscles (P<.001).

CONCLUSIONS

The model using the images of the vertebral bone and paravertebral muscle showed better performance than that using the images of the bone-only or clinical variables. Opportunistic CT screening may contribute to identifying patients with a high fracture risk in the future.

Different Diagnostic Criteria for Determining the Prevalence of Sarcopenia in Older Adults: A Systematic Review

Background: Sarcopenia is defined as a loss of muscle mass, strength, and physical function associated with aging. It is due to a combination of genetic, environmental, and physiological factors. It is also associated with an increased risk of health problems. Since there are many different researchers in the field, with their own algorithms and cut-off points, there is no single criterion for diagnosis. This review aims to compare the prevalence of sarcopenia according to these different diagnostic criteria in older adult populations by age group and sex. Methods: Different databases were searched: Web of Science, Pubmed, Dialnet, Scopus, and Cochrane. The keywords used were "sarcopenia", "diagnosis", "prevalence", "assessment", "aged", "aging" and "older". Studies conducted in a population aged ≥65 assessing the prevalence of sarcopenia were selected. Results: Nineteen articles met the inclusion criteria, with a total of 33,515 subjects, 38.08% female and 61.42% male, at a mean age of 74.52. The diagnostic algorithms used were 52.63% AWGS2, 21.05% EWGSOP2, 10.53% AWGS1 and EWGS1, and 5.26% FNIH. Prevalence ranged from 1.7% to 37.47%, but was higher in males and increased with age. Conclusions: The prevalence of sarcopenia varies depending on the diagnostic algorithm used, but it increases with age and is higher in men. The EWGSOP2 and AWGS2 are the most used diagnostic criteria and measure the same variables but have different cut-off points. Of these two diagnostic algorithms, the one with the highest prevalence of sarcopenia and severe sarcopenia is the AWGS2. These differences may be due to the use of different tools and cut-off points. Therefore, a universal diagnostic criterion should be developed to allow early diagnosis of sarcopenia.

Causal Roles of Lifestyle, Psychosocial Characteristics, and Sleep Status in Sarcopenia: A Mendelian Randomization Study

BACKGROUND

Many studies reported that lifestyle, psychosocial characteristics, and sleep status related to sarcopenia, although few studies provided evidence of causal relationships between them.

METHODS

The data used in our study were from UK Biobank, FinnGen Release 8, and large genome-wide association study meta-analyses. Two-sample Mendelian randomization was conducted to identify the causal associations of 21 traits of lifestyle, psychosocial characteristics, and sleep status with 6 traits of sarcopenia. Benjamini-Hochberg correction was performed to reduce the bias caused by multiple tests. Risk factor analyses were performed to explore the potential mechanism behind the exposures.

RESULTS

Mendelian randomization analyses after adjustment proved the causal roles of coffee intake, education years, smoking, leisure screen time, and moderate-to-vigorous intensity physical activity during leisure time in sarcopenia was proven although providing no significant evidence for causal roles for carbohydrates intake, protein intake, alcohol, and sleep status in sarcopenia.

CONCLUSIONS

Our results strongly support that coffee intake, education years, smoking, leisure screen time, and moderate-to-vigorous intensity physical activity during leisure time played significantly causal roles in sarcopenia, which may provide new intervention strategies for preventing the development of sarcopenia.