INTRODUCTION: The diagnosis of sarcopenia relies on key indicators such as handgrip strength, walking speed and muscle mass. Developing a composite index that integrates these measures could enhance clinical evaluation in older adults. This study aimed to standardise and combine these metrics to establish a z score for the sarcopenia composite index (ZoSCI) tailored for the ageing population. Additionally, we explore the risk factors associated with ZoSCI to provide insights into early prevention and intervention strategies. METHOD: This retrospective study analysed data between January 2017 and December 2021 from an elderly health programme in Taiwan, applying the Asian Working Group for Sarcopenia criteria to assess sarcopenia. ZoSCI was developed by standardising handgrip strength, walking speed and muscle mass into z scores and integrating them into a composite index. Receiver operating characteristic (ROC) curve analysis was used to determine optimal cut-off values, and multiple regression analysis identified factors influencing ZoSCI. RESULTS: Among the 5047 participants, the prevalence of sarcopenia was 3.7%, lower than the reported global prevalence of 3.9-15.4%. ROC curve analysis established optimal cut-off points for distinguishing sarcopenia in ZoSCI: -1.85 (sensitivity 0.91, specificity 0.88) for males and -1.97 (sensitivity 0.93, specificity 0.88) for females. Factors associated with lower ZoSCI included advanced age, lower education levels, reduced exercise frequency, lower body mass index and creatinine levels. CONCLUSION This study introduces ZoSCI, a new compo-site quantitative indicator for identifying sarcopenia in older adults. The findings highlight specific risk factors that can inform early intervention. Future studies should validate ZoSCI globally, with international collaborations to ensure broader applicability.
Humans ; Sarcopenia/physiopathology* ; Male ; Aged ; Female ; Retrospective Studies ; Hand Strength ; Taiwan/epidemiology* ; ROC Curve ; Aged, 80 and over ; Risk Factors ; Walking Speed ; Geriatric Assessment/methods* ; Prevalence ; Muscle, Skeletal ; Middle Aged

An in-depth understanding of the mechanism of lower extremity muscle coordination during walking is the key to improving the efficacy of gait rehabilitation in patients with neuromuscular dysfunction. This paper investigates the effect of changes in walking speed on lower extremity muscle synergy patterns and muscle functional networks. Eight healthy subjects were recruited to perform walking tasks on a treadmill at three different speeds, and the surface electromyographic signals (sEMG) of eight muscles of the right lower limb were collected synchronously. The non-negative matrix factorization (NNMF) method was used to extract muscle synergy patterns, the mutual information (MI) method was used to construct the alpha frequency band (8-13 Hz), beta frequency band (14-30 Hz) and gamma frequency band (31-60 Hz) muscle functional network, and complex network analysis methods were introduced to quantify the differences between different networks. Muscle synergy analysis extracted 5 muscle synergy patterns, and changes in walking speed did not change the number of muscle synergy, but resulted in changes in muscle weights. Muscle network analysis found that at the same speed, high-frequency bands have lower global efficiency and clustering coefficients. As walking speed increased, the strength of connections between local muscles also increased. The results show that there are different muscle synergy patterns and muscle function networks in different walking speeds. This study provides a new perspective for exploring the mechanism of muscle coordination at different walking speeds, and is expected to provide theoretical support for the evaluation of gait function in patients with neuromuscular dysfunction.
Humans ; Walking Speed ; Muscle, Skeletal/physiology* ; Electromyography ; Gait/physiology* ; Walking/physiology*

BACKGROUND: The number of adults aged over 65 years is rapidly increasing in several Southeast Asian countries. Muscle mass decreases with age, leading to sarcopenia. The primary objective of this study was to determine whether differences exist in the body composition and physical strength, according to ethnicity, among community-dwelling Japanese and Thai older adults living in Chiang Mai Province, Thailand. METHODS: A survey was conducted in February and March 2019. Japanese and Thai adults aged ≥ 60 years living in Chiang Mai Province were recruited through community clubs. Participants completed a self-administered questionnaire that enabled collection of data on age, sex, educational background, marital status, annual income, current medical conditions, smoking and alcohol consumption, and exercise habits. Measurements were collected on height, weight, body composition, blood pressure, hand grip, and walking speed for 6 m. Body composition was measured using a standing-posture 8-electrode multifrequency bioimpedance analysis analyzer. Hand grip of each hand was measured with the patient in the standing position using a digital grip dynamometer. Multivariable logistic regression was used to determine factors associated with skeletal muscle mass index (SMI). RESULTS: Of the total 119 participants, 47 were Japanese (26 men, 21 women) and 72 were Thai (16 men, 56 women). The prevalence of a low SMI was 3/26 (12%), 1/21 (5%), 6/16 (38%), and 5/56 (9%) among Japanese men, Japanese women, Thai men, and Thai women, respectively. The prevalence of low muscle strength was 2/26 (8%), 2/21 (10%), 3/16 (19%), and 13/56 (23%) among Japanese men, Japanese women, Thai men, and Thai women, respectively. There were significant differences between ethnic groups in body mass index for both sexes, percentage body fat in women, SMI in men, and average grip strength in men. Ethnic group, sex, age, and body mass index were independent predictors of SMI. CONCLUSIONS Ethnicity had a clinically important effect on body composition and physical strength among older Japanese and Thai adults living in a similar environment.
Aged ; Aging/physiology* ; Asians/ethnology* ; Body Composition ; Body Mass Index ; Cross-Sectional Studies ; Electric Impedance ; Ethnicity ; Female ; Hand Strength ; Humans ; Independent Living ; Male ; Middle Aged ; Muscle Strength ; Thailand/ethnology* ; Walking Speed