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Sarcopenic obesity is defined as the presence of high fat mass and low muscle mass combined with low physical function, and it is closely related with the onset of cardiovasular diseases (CVD). The existing anthropometric indices, which are being utilised in clinical practice as predictors of CVD, may also be used to screen sarcopenic obesity, but their feasibility remained unknown. Using cross-sectional data of 2031 participants aged 70–84 years (mean age, 75·9 ± 3·9 years; 49·2 % women) from the Korean Frailty and Aging Cohort Study, we analysed the association of anthropometric indices, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and weight-adjusted waist index (WWI) with sarcopenic obesity. Body composition was measured using dual-energy X-ray absorptiometry. Higher WWI, WHtR and WC quartiles were associated with higher risk of sarcopenic obesity; the odds ratio (OR) of sarcopenic obesity were highest in the fourth quartile of the WWI (OR: 10·99, 95 % CI: 4·92–24·85, P for trend < 0·001). WWI provided the best diagnostic power for sarcopenic obesity in men (area under the receiver operating characteristic curve: 0·781, 95 % CI: 0·751–0·837). No anthropometric indices were significantly associated with sarcopenic obesity in women. WWI was the only index that was negatively correlated with physical function in both men and women. WWI showed the strongest association with sarcopenic obesity, defined by high fat mass and low muscle mass combined with low physical function only in older men. No anthropometric indices were associated with sarcopenic obesity in older women.

Muscle weakness is linked to a range of adverse health outcomes across the lifespan including mortality, morbidity, and disability. Because lifestyles and body composition are quite different between Western and Asian countries, there is an urgent need to establish normative grip strength values for individuals of Asian descent. This study presents normative data for hand grip strength in a Korean population-representative sample. A sample of 11,073 individuals (age 10-80 years) was included from the Sixth Korea National Health and Nutrition Examination Survey, 2014-2015. Isometric grip strength was assessed using a handheld dynamometer. Relative grip strength was calculated as the maximum absolute grip strength divided by body mass index. Means, standard error, and quintiles for grip strength and relative grip strength were analyzed per 5-year age group for each sex. To create growth charts for grip strength and relative grip strength, parametric quantile regression was used. In males, absolute grip strength increased quickly starting from 10 years of age until approximately 20 years of age. In females, there was gradual growth until approximately 15 years of age. Grip strength continued to increase until a peak between ages 30 and 39 years, and then declined from midlife onwards in both sexes. Our data showed that the prevalence of weak grip strength increased rapidly in late adult life based on a T-score of -2 standard deviations below the sex-specific peak mean (equivalent to 33 kg in males and 20 kg in females). Approximately 20% of subjects had weak grip strength at age 65-69 years. This was the first study to establish normative reference values for grip strength across the lifespan in a Korean population aged 10-80 years. Percentiles of grip strength will inform clinical assessments and will help identify thresholds for the identification of muscle weakness.

Cognitive frailty (CF), a clinical syndrome involving both physical frailty (PF) and impaired cognition (IC), is associated with adverse health outcomes in older adults. This study aimed to identify key predictors of CF and develop a machine learning-based model for CF risk assessment using data from 2404 community-dwelling older adults in the Korean Frailty and Aging Cohort Study (2016–2017). PF was evaluated using Fried frailty phenotype, while IC was assessed using Mini-Mental State Examination (MMSE). Participants exhibiting at least one frailty phenotype and MMSE score ≤ 24 were classified as having CF. A comprehensive analysis encompassing sociodemographic, clinical, and health status characteristics was conducted. A machine learning approach incorporating recursive feature elimination and bootstrapping was employed to develop the prediction model. Among the diverse CF-associated characteristics, the machine learning-based model identified six optimal features (key predictors): motor capacity, education level, physical function limitation, nutritional status, balance confidence, and activities of daily living. The model demonstrated robust predictive performance, achieving an area under the curve of 84.34%, with high sensitivity, specificity, and accuracy. These findings underscore the importance of comprehensive health assessments for early CF detection and demonstrate the potential of predictive modeling in facilitating personalized interventions for at-risk older adults.

To investigate the combined and separate effects of exercise and milk fat globule membrane (MFGM) supplementation on frailty, physical function, physical activity level, and hematological parameters in community-dwelling elderly Japanese women. A total of 131 frail, elderly women over 75 years were randomly assigned to one of four groups: exercise and MFGM supplementation (Ex+MFGM), exercise and placebo (Ex+Plac), MFGM supplementation, or the placebo group. The exercise group attended a 60-minute training program twice a week for three months, and the MFGM group ingested 1g of the MFGM supplement in pill form, daily for 3 months. The primary outcome measure was change in frailty status based on Fried's frailty phenotype. Secondary outcome measures included body composition, physical function and hematological parameters, and interview survey components assessing lifestyle factors. Participants were followed for 4 months post-intervention. Significant group × time interactions were observed for usual walking speed (P = 0.005), timed up & go (P<0.001), and insulin-like growth factor-binding protein 3/insulin-like growth factor 1 ratio (P = 0.013). The frailty components revealed that weight loss, exhaustion, low physical activity, and slow walking speed were reversed, but low muscle strength did not significantly changed. Frailty reversal rate was significantly higher in the Ex+MFGM (57.6%) than in the MFGM (28.1%) or placebo (30.3%) groups at post-intervention (χ2 = 8.827, P = 0.032), and at the follow-up was also significantly greater in the Ex+MFGM (45.5%) and Ex+Plac (39.4%) groups compared with the placebo (15.2%) group (χ2 = 8.607, P = 0.035). The exercise+MFGM group had the highest odds ratio (OR) for frailty reversal at post-intervention and follow-up (OR = 3.12, 95% confidence interval (CI) = 1.13-8.60; and OR = 4.67, 95% CI = 1.45-15.08, respectively). This study suggests that interventions including exercise and nutrition can improve frailty status. Statistically significant additive effects of MFGM with exercise could not be confirmed in this population, and further investigation in larger samples is necessary. The Japan Medical Association Clinical Trial Registry (JMACCT)JMA-IIA00069.

Falls are a critical concern in older adults with cognitive frailty (CF). However, previous studies have not fully examined whether machine learning models can predict falls in older individuals with CF. The 2-year longitudinal data set from the Korean Frailty and Aging Cohort Study and machine learning approach were utilized to predict fall risk. We analyzed multidimensional health data, including demographics, clinical conditions, as well as the physical and psychological health factors of 443 older adults with CF identified out of 2,404 older adults. For fall risk prediction, we developed a machine learning framework incorporating logistic regression, bootstrapping, and recursive feature elimination. Statistical analysis revealed significant differences between the non-faller and faller groups for nine clinical conditions as well as physical and psychological variables. Using nine significant variables, our machine-learning-based model demonstrated good predictive performance with an area under the curve (AUC) exceeding 80%. Furthermore, our machine learning framework identified four optimal variables: the number of Fried physical frailty (PF) phenotypes, PF-Mobility scores, scores from the Korean version of the Short Geriatric Depression Scale, and scores from SARC-F (consisting of five components: strength, assistance with walking, rising from a chair, climbing stairs, and experiencing falls). It demonstrated excellent predictive performance, with an AUC, sensitivity, specificity, and accuracy exceeding 95%. These variables reflect the critical association between physical and psychological health and fall risk. These findings underscore the importance of integrating multidimensional health data with machine learning methodologies to accurately predict fall risk in older adults with CF, design targeted interventions, and enable healthcare professionals to implement strategies to reduce and prevent such falls.

Background and Objectives: Sarcopenic obesity, characterized by sarcopenia and obesity, is associated with adverse outcomes. The recent consensus from the European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the Study of Obesity (EASO) proposed a diagnostic algorithm (screening, diagnosis, and staging) for sarcopenic obesity. However, the effectiveness of recommended screening tools for sarcopenic obesity remains unclear. This study aimed to assess the performance of SARC-F questionnaire (Strength, walking Assistance, Rise, Climb, and Falls), calf circumference (CC), and SARC-CalF (SARC-F combined with CC), combined with obesity indicators, as screening tools for sarcopenic obesity. Materials and Methods: This cross-sectional study analyzed 2020 community-dwelling older adults from the Korean Frailty and Aging Cohort Study. Sarcopenic obesity was defined according to ESPEN and EASO criteria. Screening tools included SARC-F, CC, and SARC-CalF in combination with high body mass index (BMI; ≥25 kg/m2) or high waist circumference (WC; men, ≥90 cm; women, ≥85 cm). The diagnostic performance was evaluated using sensitivity, specificity, and predictive value. Results: SARC-F (≥4) with high BMI or WC demonstrated low sensitivity (men, 5.68%; women, 17.82%) but high specificity (men, 99.03%; women, 94.35%) and negative predictive value (NPV) (men, 91.68%; women, 91.09%). Lowering the SARC-F cutoff improved sensitivity but reduced specificity. CC combined with a high BMI or WC showed modest sensitivity (men, 34.09%; women, 34.65%) but moderate specificity (men, 59.48%; women, 59.91%). SARC-CalF (≥11) combined with high BMI or WC showed slightly higher sensitivity (men, 13.64%; women, 19.80%) but lower specificity (men, 95.04%; women, 86.93%) than SARC-F. Conclusions: SARC-F combined with obesity indicators may serve as a case-finding tool with high specificity and NPV, supporting its usefulness in ruling out sarcopenic obesity in the clinical setting. Meanwhile, CC was not an effective screening tool, and SARC-CalF did not substantially improve sensitivity or accuracy compared with SARC-F.

(1) Background: The effect of Juingong meditation on brainwave patterns has not been explored yet. This study aimed to study the changes in brainwave patterns produced by Juingong meditation, through electroencephalography (EEG) measurements. (2) Methods: The study included 23 participants from the Hanmaum Seon Center in Korea. EEG measurements were performed using InteraXon’s four-channel EEG measurement equipment, Muse. It measures EEG patterns in the temporoparietal and anterior frontal lobes. Brainwaves were measured in two different states: when Juingong meditation was practiced and when instructed mind wandering (IMW) was practiced. The EEG recordings were analyzed using the theta/alpha index. (3) Results: In the Juingong meditation state, the power of alpha was relatively higher than that of theta and these results were valid in the temporal parietal lobe channel. This indicates that relatively more alpha waves were induced in the temporal parietal lobe when Juingong meditation was practiced. (4) Conclusions: When Juingong meditation is practiced, the theta/alpha ratio changes without delay, which means that the practical effect of Juingong meditation on brainwave patterns is immediately apparent.

Frailty is defined as a state of increased vulnerability to stressors, and it predicts disability and mortality in the older population. This study aimed to investigate the standardized prevalence and multidimensional risk factors associated with frailty among Korean community-dwelling older adults. We analyzed the baseline data of 2907 adults aged 70–84 years (mean age 75.8 ± 3.9 years, 57.8% women) in the Korean Frailty and Aging Cohort Study. The Fried frailty phenotype was used to define frailty. Analyzed data included sociodemographic, physical, physical function, biological, lifestyle, health condition, medical condition, psychological, and social domains. Data were standardized using the national standard population composition ratio based on the Korean Population and Housing Census. The standardized prevalence of frailty and prefrailty was 7.9% (95% confidence interval (CI) 6.8–8.9%) and 47.0% (95% CI, 45.1–48.8%), respectively. The following 14 risk factors were significantly associated with frailty: at risk of malnutrition, sarcopenia, severe mobility limitation, poor social capital, rural dwellers, depressive symptoms, poor self-perceived health, polypharmacy, elevated high-sensitivity C-reactive protein, elevated glycosylated hemoglobin, low 25-hydroxy vitamin D level, longer Timed Up and Go, and low Short Physical Performance Battery score (p < 0.05). Physiconutritional, psychological, sociodemographic, and medical factors are strongly associated with frailty.

PurposeThe purpose of the Korean Frailty and Aging Cohort Study (KFACS) is to initiate a nationwide, population-based prospective cohort study of older adults living in the community to assess their frailty status and explore transitions between frailty states over time in Korea.ParticipantsThe KFACS is a multicentre longitudinal study with the baseline survey conducted from May 2016 to November 2017. Each centre recruited participants using quota sampling stratified by age and sex. The number of participants recruited through 2 years of baseline study from 10 centres was 3014, with each site accounting for approximately 300 participants. The inclusion criteria were: having an age of 70–84 years, currently living in the community, having no plans to move out in the next 2 years, having no problems with communication and no prior dementia diagnosis.Findings to dateTo define physical frailty, the KFACS used a modified version of the Fried Frailty Phenotype (FFP) consisting of five components of frailty: unintended weight loss, weakness, self-reported exhaustion, slowness and low physical activity. In the baseline study of 2016–2017, 2907 of 3014 individuals fulfilled all five components of FFP. The results indicated that 7.8% of the participants (n=228) were frail, 47.0% (n=1366) were prefrail and 45.2% (n=1313) were robust. The prevalence of frailty increased with age in both sexes; in the group aged 70–74 years, 1.8% of men and 3.7% of women were frail, whereas in the 80–84 years age group, 14.9% of men and 16.7% of women were frail. Women tended to exhibit a higher prevalence of frailty than men in all age groups.Future plansThe KFACS plans to identify outcomes and risk factors associated with frailty by conducting a 10-year cohort study, with a follow-up every 2 years, using 3014 baseline participants.

This cross-sectional study investigated the association between sarcopenia components and depressed mood in community-dwelling adults aged 70–84 years from the Korean Frailty and Aging Cohort Study. Depressed mood was assessed using the Geriatric Depression Scale short form. Logistic regression was used to examine sex-specific associations between sarcopenia components and depressed mood. Among 1,913 participants (mean age: 75.9 years, 49.0% women), 12.2% and 23.6% had depressed mood and sarcopenia, respectively. Sarcopenia prevalence increased among individuals with depressed mood in both sexes (men: P  < 0.001; women: P  = 0.016). Severe sarcopenia (men: OR, 3.620; 95% CI, 1.634−8.022; women OR, 3.332; 95% CI, 1.689−6.574) and concurrent low muscle strength and physical performance (men: OR, 3.660; 95% CI, 1.541−8.691; women: OR, 2.333; 95% CI, 1.294−4.206) correlated with depressed mood across sexes. The co-occurrence of low muscle mass and muscle strength (OR, 2.451; 95% CI, 1.007−5.964) was associated with depressed mood in men, whereas low physical performance (OR, 2.007; 95% CI, 1.275−3.160) and the coexistence of low muscle mass and physical performance (OR, 1.804; 95% CI, 1.003–3.248) correlated with depressed mood in women. Sarcopenia and depressed mood were significantly associated among older adults, underscoring the need to account for sex-specific differences in sarcopenia components when evaluating mental health outcomes to tailor interventions targeting sarcopenia and improve the mental well-being of aging populations.