Даваа–Баасан 08:30–20:00 · Бямба 09:00–16:00
library@mnums.edu.mn
/

Б.Мөнх-Эрдэнэ

Loading...
Thumbnail Image
Товч нэр
Б.Мөнх-Эрдэнэ
Бүтэн нэр
Баяртай Мөнх-Эрдэнэ
Латин нэр
Bayartai Munkh-Erdene
Эрдмийн цол
Дэд профессор
Харьяалал

Settings

Now showing 1 - 3 of 3
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Identifying Key Predictors of Sarcopenic Obesity in Italian Severely Obese Older Adults: Deep Learning Approach
    (2025-04)
    Cândido, Leticia Martins
    ;
    Bae, Jun-Hyun
    ;
    Kim, Dae Young
    ;
    Bayartai, Munkh-Erdene
    ;
    Abbruzzese, Laura
    Background/Objectives: Sarcopenic obesity (SO), the coexistence of sarcopenia and obesity, poses serious health risks, such as increased mortality. Despite its clinical significance, key predictors of SO remain unclear, especially in severe obesity. This study aimed to identify independent predictors of SO in Italian older adults with obesity using a deep learning neural network. Methods: A cross-sectional study was conducted with hospitalized older adults diagnosed with severe obesity. SO was defined according to the 2022 ESPEN/EASO Statement Criteria, based on skeletal muscle function assessed by the five-repetition sit-to-stand test (5-SST) and body composition parameters evaluated using Dual X-ray Absorptiometry. A total of 42 independent variables were analyzed. Data normalization was performed using MinMaxScaler, and an optimal neural network architecture was selected via grid search with stratified 5-fold cross-validation. Model performance was assessed using accuracy, precision, recall, F1-score, AUC-ROC, and AUPRC metrics. Results: The correlation analysis revealed strong negative associations between SO and handgrip strength (HGS) (r = -0.785) and appendicular lean mass (ALM) (r = -0.745), as well as moderate correlations with 5-SST (r = 0.603), 30-second chair stand test (r = -0.474), 6-minute walking test (6m-WT) (r = 0.289), and waist circumference (WC) (r = 0.127). The deep learning model achieved an average classification accuracy of 72%, with a precision of 83% and an AUC of 0.9333. Conclusions: The main key predictors of SO were HGS, ALM, 5-SST, 30s-SST, 6m-WT, and WC in the early detection of this condition. The findings highlight deep learning's potential to improve SO diagnosis, risk assessment, clinical decision-making, and prevention in severely obese older adults.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Association of Physical Performance with Mental and Physical Health-Related Quality of Life and Low Back Pain-Related Disabilities among Older Adults with Severe Obesity
    (2024-09)
    Bayartai, Munkh-Erdene
    ;
    Tringali, Gabriella
    ;
    De Micheli, Roberta
    ;
    Danielewicz, Ana Lúcia
    ;
    Sartorio, Alessandro
    Background: Low back pain is one of the most prevalent musculoskeletal problems and continues to be the leading cause of disabilities worldwide. The aim of this study was to cross-sectionally investigate the association of physical performance with mental and physical health-related quality of life and low back pain-related disabilities among older adults with severe obesity. Methods: A total of 96 hospitalized older adults with severe obesity (45 males, 51 females, age: 69.7 ± 5.4 years; BMI: 43.7 ± 5.7 kg/m2) were recruited into the study. Physical performance, health-related quality of life, and low back pain-related disability were measured through physical performance tests, the 12-item short-form survey (SF-12), and the Oswestry disability index, respectively. Results: LBP-related disabilities, as well as physical health-related quality of life, were associated with all the physiological parameters measured by physical performance tests, including muscular strength, aerobic capacity, balance, and lower body flexibility (p < 0.05). In contrast, mental health-related quality of life was associated with fewer physiological parameters, such as primarily muscular strength (p < 0.05). Conclusions: These findings could provide important insights for developing rehabilitation strategies designed to improve LBP-related disabilities, as well as the physical and mental health-related quality of life, in older adults with severe obesity.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Spinal Posture and Movement in Female Adolescents with Anorexia Nervosa
    (2026-04)
    Bayartai, Munkh-Erdene
    ;
    Tringali, Gabriella
    ;
    De Micheli, Roberta
    ;
    Grimoldi, Ilaria
    ;
    Abbruzzese, Laura
    Background: Profound musculoskeletal alterations encompassing bones and soft tissues are common in people with anorexia nervosa (AN). This study aims to examine spinal posture and mobility in adolescents with AN, and to compare these outcomes with those obtained from normal-weight female controls. Methods: Spinal posture and movements were measured in 37 adolescents with AN and 31 normal-weight controls using the Idiag M360 scan tool, and between-group differences were analyzed using analysis of covariance. Results: Spinal postures and the lumbar-to-hip ratio were not different between subgroups. By contrast, AN had reduced thoracic (-21.8 degrees, p < 0.0001) and lumbar (-18.2 degrees, p < 0.0001) mobility in the frontal plane, as well as decreased hip flexion (-14 degrees, p = 0.001) and extension (-18.6 degrees, p < 0.0001) compared to the CG. Conclusions: Thoracic and lumbar spinal mobility, mainly in the frontal plane, and also hip mobility in the sagittal plane, are decreased in AN. These findings provide clinically relevant insights into spinal characteristics in adolescents with AN.