Associations between Sarcopenic Obesity and Cognitive Impairment in Elderly Chinese Community-Dwelling Individuals

2018 ◽  
Vol 23 (1) ◽  
pp. 14-20 ◽  
Author(s):  
H. Wang ◽  
S. Hai ◽  
Y. X. Liu ◽  
L. Cao ◽  
Y. Liu ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Community Dwelling ◽  
Sarcopenic Obesity ◽  
Chinese Community ◽  
Elderly Chinese

scholarly journals A Risk Prediction Model Based on Machine Learning for Cognitive Impairment Among Chinese Community-Dwelling Elderly People With Normal Cognition: Development and Validation Study

10.2196/20298 ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. e20298
Author(s):  
Mingyue Hu ◽  
Xinhui Shu ◽  
Gang Yu ◽  
Xinyin Wu ◽  
Maritta Välimäki ◽  
...  
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Cognitive Impairment ◽  
Older People ◽  
Prediction Model ◽  
Elderly People ◽  
Community Dwelling ◽  
Chinese Community ◽  
Model Based ◽  
Normal Cognition

Background Identifying cognitive impairment early enough could support timely intervention that may hinder or delay the trajectory of cognitive impairment, thus increasing the chances for successful cognitive aging. Objective We aimed to build a prediction model based on machine learning for cognitive impairment among Chinese community-dwelling elderly people with normal cognition. Methods A prospective cohort of 6718 older people from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) register, followed between 2008 and 2011, was used to develop and validate the prediction model. Participants were included if they were aged 60 years or above, were community-dwelling elderly people, and had a cognitive Mini-Mental State Examination (MMSE) score ≥18. They were excluded if they were diagnosed with a severe disease (eg, cancer and dementia) or were living in institutions. Cognitive impairment was identified using the Chinese version of the MMSE. Several machine learning algorithms (random forest, XGBoost, naïve Bayes, and logistic regression) were used to assess the 3-year risk of developing cognitive impairment. Optimal cutoffs and adjusted parameters were explored in validation data, and the model was further evaluated in test data. A nomogram was established to vividly present the prediction model. Results The mean age of the participants was 80.4 years (SD 10.3 years), and 50.85% (3416/6718) were female. During a 3-year follow-up, 991 (14.8%) participants were identified with cognitive impairment. Among 45 features, the following four features were finally selected to develop the model: age, instrumental activities of daily living, marital status, and baseline cognitive function. The concordance index of the model constructed by logistic regression was 0.814 (95% CI 0.781-0.846). Older people with normal cognitive functioning having a nomogram score of less than 170 were considered to have a low 3-year risk of cognitive impairment, and those with a score of 170 or greater were considered to have a high 3-year risk of cognitive impairment. Conclusions This simple and feasible cognitive impairment prediction model could identify community-dwelling elderly people at the greatest 3-year risk for cognitive impairment, which could help community nurses in the early identification of dementia.

scholarly journals Associations of fat mass and muscle function but not lean mass with cognitive impairment: The Yishun Study

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256702
Author(s):  
Nien Xiang Tou ◽  
Shiou-Liang Wee ◽  
Benedict Wei Jun Pang ◽  
Lay Khoon Lau ◽  
Khalid Abdul Jabbar ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Fat Mass ◽  
Lean Mass ◽  
Handgrip Strength ◽  
Community Dwelling ◽  
Sarcopenic Obesity ◽  
Immediate Memory ◽  
Domain Specific ◽  
Neuropsychological Status ◽  
Impaired Attention

Background Sarcopenia and obesity are reportedly associated with risk of cognitive decline, and sarcopenic obesity (SO) heightens the risk, but the evidence is sparse and inconclusive. This study aimed to examine the association between SO and cognitive impairment. Methods A total of 542 community-dwelling adults aged between 21 and 90 years were recruited. All participants were assessed for body composition (dual X-ray absorptiometry), handgrip strength (HGS), gait speed (GS), and cognitive function (Repeatable Battery for the Assessment of Neuropsychological Status). Sarcopenia was defined by the presence of low appendicular lean mass index (ALMI) and low HGS or low GS according to the 2019 Asian Working Group for Sarcopenia criteria, and obesity was defined based on the upper two quintiles of fat mass index (FMI). Results Sarcopenia alone or in combination with obesity were not significantly associated with cognitive impairment after controlling for confounding variables. Obesity on its own was significantly associated with greater odds of impaired attention (OR: 2.05, 95%CI 1.12–3.82). Low ALMI was not associated, but low HGS, slow GS, and high FMI were individually associated with cognitive impairment: low HGS and immediate memory (OR: 1.91, 95% CI 1.04–3.49); low GS and immediate memory (OR: 2.17, 95% CI 1.26–3.72); high FMI and attention (OR: 2.06, 95% CI 1.22–3.51). Co-occurring high FMI with either low HGS or slow GS exacerbated the observed odds of global and domain-specific (attention, visuospatial) cognitive impairment. Conclusions Lean mass is not relevant, whereas muscle strength and physical performance or adiposity are relevant in defining sarcopenia or sarcopenic obesity in terms of their cognitive impacts.

Association of Neutrophil-Lymphocyte Ratio with Mild Cognitive Impairment in Elderly Chinese Adults: A Case-control Study

2020 ◽  
Vol 16 (14) ◽  
pp. 1309-1315
Author(s):  
Peilin An ◽  
Xuan Zhou ◽  
Yue Du ◽  
Jiangang Zhao ◽  
Aili Song ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Function ◽  
Predictive Values ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Elderly Chinese ◽  
Normal Cognitive Function ◽  
The Absolute

Background: Inflammation plays a significant role in the pathophysiology of cognitive impairment in previous studies. Neutrophil-lymphocyte ratio (NLR) is a reliable measure of systemic inflammation. Objective: The aim of this study was to investigate the association between NLR and mild cognitive impairment (MCI), and further to explore the diagnostic potential of the inflammatory markers NLR for the diagnosis of MCI in elderly Chinese individuals. Methods: 186 MCI subjects and 153 subjects with normal cognitive function were evaluated consecutively in this study. Neutrophil (NEUT) count and Lymphocyte (LYM) count were measured in fasting blood samples. The NLR was calculated by dividing the absolute NEUT count by the absolute LYM count. Multivariable logistic regression was used to evaluate the potential association between NLR and MCI. NLR for predicting MCI was analyzed using Receiver Operating Characteristic (ROC) curve analysis. Results: The NLR of MCI group was significantly higher than that of subjects with normal cognitive function (2.39 ± 0.55 vs. 1.94 ± 0.51, P < 0.001). Logistic regression analysis showed that higher NLR was an independent risk factor for MCI (OR: 4.549, 95% CI: 2.623-7.889, P < 0.001). ROC analysis suggested that the optimum NLR cut-off point for MCI was 2.07 with 73.66% sensitivity, 69.28% specificity, 74.48% Positive Predictive Values (PPV) and 68.36% negative predictive values (NPV). Subjects with NLR ≥ 2.07 showed higher risk relative to NLR < 2.07 (OR: 5.933, 95% CI: 3.467-10.155, P < 0.001). Conclusion: The elevated NLR is significantly associated with increased risk of MCI. In particular, NLR level higher than the threshold of 2.07 was significantly associated with the probability of MCI.

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