scholarly journals Changes in Cognitive Function and Risk Factors for Cognitive Impairment of the Elderly in China: 2005–2014

2019 ◽  
Vol 16 (16) ◽  
pp. 2847 ◽  
Author(s):  
Qilin Zhang ◽  
Yanli Wu ◽  
Tiankuo Han ◽  
Erpeng Liu
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cognitive Impairment ◽  
Cognitive Function ◽  
Logistic Regression Analysis ◽  
Binary Logistic Regression ◽  
The Elderly ◽  
Binary Logistic Regression Analysis ◽  
Chinese Elderly

Background: The cognitive function of the elderly has become a focus of public health research. Little is known about the changes of cognitive function and the risk factors for cognitive impairment in the Chinese elderly; thus, the purposes of this study are as follows: (1) to describe changes in cognitive function in the Chinese elderly from 2005–2014 and (2) to explore risk factors for cognitive impairment of the Chinese elderly. Design and setting: A total of 2603 participants aged 64 years and above participated in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and were followed up from 2005 to 2014. Cognitive function and cognitive impairment were assessed using the Chinese version of the Mini-Mental State Examination (MMSE). Binary logistic regression analysis was used to estimate the odds ratio (OR) and 95% confidence intervals (CI) of cognitive impairment. Results: Results revealed that the cognitive function of the Chinese elderly shows diversified changes: deterioration (55.09%), unchanged (17.21%) and improvement (27.70%). In addition, there are significant demographic differences in gender, age, education, marriage and other aspects when it comes to the changes of cognitive function in Chinese elderly. In the binary logistic regression analysis, female, increased age, lower education level, no spouse, less income, worse PWB (psychological well-being), less fresh fruit and vegetable intake, more activities of daily living (ADL) limitations, lower social engagement were significantly associated with higher odds for cognitive impairment. Conclusions: Various interventions should be implemented to maintain cognitive function in Chinese elderly.

scholarly journals A Novel Game-Based Intelligent Test for Detecting Elderly Cognitive Function Impairment

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chih-Wei Lin ◽  
Tso-Yen Mao ◽  
Chun-Feng Huang
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Cognitive Impairment ◽  
Cognitive Function ◽  
Multiple Regression ◽  
Cognitive Dysfunction ◽  
Predictive Power ◽  
Binary Logistic Regression ◽  
The Elderly ◽  
Correct Number

Purposes. This research explores the game-based intelligent test (GBIT), predicts the possibilities of Mini-Mental State Examination (MMSE) scores and the risk of cognitive impairment, and then verifies GBIT as one of the reliable and valid cognitive assessment tools. Methods. This study recruited 117 elderly subjects in Taiwan (average age is 79.92 ± 8.68 , average height is 156.91 ± 8.01 , average weight is 59.14 ± 9.67 , and average MMSE score is 23.33 ± 6.16 ). A multiple regression model was used to analyze the GBIT parameters of the elderly’s reaction, attention, coordination, and memory to predict their MMSE performance. The binary logistic regression was then utilized to predict their risk of cognitive impairment. The statistical significance level was set as α = 0.05 . Results. Multiple regression analysis showed that gender, the correct number of reactions, and the correct number of memory have a significantly positive predictive power on MMSE of the elderly ( F = 37.60 , R 2 = 0.69 , and p < 0.05 ). Binary logistic regression analysis noted that the correct average number of reactions falls by one question, and the ratio of cognitive dysfunction risk increases 1.09 times ( p < 0.05 ); the correct average number of memory drops by one question, the ratio of cognitive dysfunction risk increases 3.76 times ( p < 0.05 ), and the overall model predictive power is 88.20% (sensitivity: 84.00%; specificity: 92.30%). Conclusions. This study verifies that GBIT is reliable and can effectively predict the cognitive function and risk of cognitive impairment in the elderly. Therefore, GBIT can be used as one of the feasible tools for evaluating older people’s cognitive function.

scholarly journals Long-Term Use of Metformin Is Associated With Reduced Risk of Cognitive Impairment With Alleviation of Cerebral Small Vessel Disease Burden in Patients With Type 2 Diabetes

2021 ◽  
Vol 13 ◽  
Author(s):  
Zhenjie Teng ◽  
Jing Feng ◽  
Qianqian Qi ◽  
Yanhong Dong ◽  
Yining Xiao ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Cognitive Impairment ◽  
Logistic Regression Analysis ◽  
Small Vessel Disease ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Ordinal Logistic Regression Analysis ◽  
History Of

Objective: Type 2 diabetes (T2D) is a risk factor for cognitive impairment and cerebral small vessel disease (CSVD). The relation of metformin use and cognitive impairment or CSVD is not clear. The objective of this study was to investigate the cross-sectional effects of long-term use of metformin on total CSVD burden and cognitive function in patients with T2D.Methods: A total of 234 participants with T2D from the memory clinic in Hebei General Hospital were enrolled in this retrospective study. Duration of metformin use and dosage were recorded. Along with cerebral magnetic resonance imaging (MRI) examination, Mini-Mental State Examination (MMSE) was also performed to assess their cognitive status. We determined the validated total CSVD score (ranging from 0–4) by combining four markers of CSVD that were visually rated. We used binary logistic regression analysis, ordinal logistic regression analysis and mediation analysis to assess the relation of long-term use of metformin with CSVD burden and cognitive function.Results: Binary logistic regression analysis showed long-term use of metformin was associated with reducing the risk of cognitive impairment (OR: 0.446; 95% Confidence Interval (CI): 0.249 to 0.800; P = 0.007), after adjustment of potential confounders, such as total CSVD burden score, age, HbA1c, hypertension, history of stroke, homocysteine, body mass index, TG and HDL-C. Ordinal logistic regression analysis suggested that long-term use of metformin was associated with alleviation of total CSVD burden score (OR: 0.583; 95% CI: 0.359 to 0.943; P = 0.027), after adjusting for age, HbA1c, hypertension, history of stroke, homocysteine, body mass index, TG and HDL-C. Mediation analysis showed significant mediation by the presence of severe CSVD burden score for long-term use of metformin in relation to cognitive impairment.Conclusion: Long-term use of metformin was associated with lower rates of cognitive impairment and lower total CSVD burden score in patients with T2D. A proportion of the relation between long-term use of metformin and cognitive impairment may be attributable to alleviation of CSVD burden.

Relationship Between the Accumulation of Metabolic Syndrome Components and Orthostatic Hypotension

2021 ◽  
Vol 34 (7) ◽  
pp. 775-776
Author(s):  
Xiao-qi Cai ◽  
Xin-lei Gao ◽  
Ting-jun Wang ◽  
Yi-hua Shen ◽  
Guo-yan Xu ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Orthostatic Hypotension ◽  
Logistic Regression Analysis ◽  
Middle Age ◽  
Binary Logistic Regression ◽  
The Elderly ◽  
Elderly Subjects ◽  
Binary Logistic Regression Analysis

Abstract Background To investigate the relationship between the accumulation of metabolic syndrome (MS) components and orthostatic hypotension (OH). Methods A total of 2,201 subjects were enrolled and divided into 0 component (n = 199), 1–2 components (n = 1,003), and 3–4 components (n = 999) groups based on the number of MS components according to the criteria of 2018 Chinese Guidelines for Prevention and Management of Hypertension. Stratified analyses and binary logistic regression analysis were performed. Results The incidence of OH was significantly increased with the number of MS components (5.0% in 0 component group, 13.5% in 1–2 components group, and 17.9% in 3–4 components group, P &lt; 0.05). Compared with subjects without OH, the incidence of MS in those with OH was significantly elevated (55.2% vs. 43.7%, P &lt; 0.05). The incidence of OH in the elderly subjects was significantly higher than that in the young and middle-aged subjects (22.3% vs. 10.9%, P &lt; 0.01). Binary logistic regression analysis showed that the number of MS components was associated with OH in all subjects, and the risk of OH was increased with the increment of MS components. Compared with the subjects without any MS component, the risk of OH increased by 2.3 times in the subjects with 4 MS components (odds ratio = 3.274, 95% confidence interval 1.626–6.594, P &lt; 0.05). Stratified analyses found that the number of MS components was independently associated with OH in young to middle-age, female and non-MS subjects. Conclusions The incidence of OH is elevated with accumulations of MS components, especially in young to middle-age, female and non-MS subjects.

scholarly journals Distal Adding On In Lenke 2AR Adolescent Idiopathic Scoliosis:risk Factors Analysis and Clinical Assessment

2020 ◽  
Author(s):  
Yulei Dong ◽  
Ning Tang ◽  
Shengru Wang ◽  
Jianguo Zhang ◽  
Hong Zhao
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Clinical Assessment ◽  
Lumbar Lordosis ◽  
Binary Logistic Regression ◽  
Thoracic Curve ◽  
Binary Logistic Regression Analysis

Abstract Background: Risk factors and clinical outcome associated with distal adding on in Lenke 2AR adolescent idiopathic scoliosis (AIS) are not fully elucidated.Methods: Radiographic data of Lenke 2AR AIS patients treated by posterior pedicle screws in a single institution were retrospectively analyzed. Patients who developed distal adding on were compared with patients who did not. Clinical assessment were carried out by SF-36 and SRS-22 questionnaire. Risk factors of distal adding on were explored by binary logistic regression analysis.Results: A total of 88 patients completed an average of 2.9 (2-12.9) years of follow-up were included. 18 (20.5%) patients met the criterion of distal adding on while the rest of 70 cases did not at follow up.Clinical parameters were comparable before surgery and became lower at follow up in adding on group in dimensions of vitality (63.1±11.4Vs.67.5±11.8,P=0.026), mental health (73.9±9.2Vs.77.8±10.2,P=0.039), self-image (3.9±0.3Vs.4.2±0.3,P=0.021) and satisfaction (4.0±0.3Vs.4.5±0.4,P=0.035). The proportion of selection lowest instrumented vertebra (LIV) higher than last touching vertebra(LTV) was significantly higher in adding on group. (6/18vs 4/70, P=0.004) Binary logistic regression analysis revealed that preoperative main thoracic curve magnitude (OR=1.118,P=0.041), preoperative lumbar lordosis (OR=1.091,P=0.029), and the gap between LIV and LTV(OR=6.123,P=0.043) were independent risk factors associated with adding on.Conclusions: In Lenke 2AR AIS cases, the selection of LIV higher than LTV is closely correlated with the development of adding-on. Patients with minor main thoracic curve and lumbar lordosis are more likely to develop distal adding on. Adding on may cause discontent of patients .

scholarly journals Predicting Burn Mortality Using a Simple Novel Prediction Model

2021 ◽  
Author(s):  
Sneha Sharma ◽  
Raman Tandon
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Prediction Model ◽  
Receiver Operating Characteristic ◽  
Logistic Regression Analysis ◽  
Operating Characteristic ◽  
Binary Logistic Regression ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Binary Logistic Regression Analysis

Abstract Background Prediction of outcome for burn patients allows appropriate allocation of resources and prognostication. There is a paucity of simple to use burn-specific mortality prediction models which consider both endogenous and exogenous factors. Our objective was to create such a model. Methods A prospective observational study was performed on consecutive eligible consenting burns patients. Demographic data, total burn surface area (TBSA), results of complete blood count, kidney function test, and arterial blood gas analysis were collected. The quantitative variables were compared using the unpaired student t-test/nonparametric Mann Whitney U-test. Qualitative variables were compared using the ⊠2-test/Fischer exact test. Binary logistic regression analysis was done and a logit score was derived and simplified. The discrimination of these models was tested using the receiver operating characteristic curve; calibration was checked using the Hosmer—Lemeshow goodness of fit statistic, and the probability of death calculated. Validation was done using the bootstrapping technique in 5,000 samples. A p-value of <0.05 was considered significant. Results On univariate analysis TBSA (p <0.001) and Acute Physiology and Chronic Health Evaluation II (APACHE II) score (p = 0.004) were found to be independent predictors of mortality. TBSA (odds ratio [OR] 1.094, 95% confidence interval [CI] 1.037–1.155, p = 0.001) and APACHE II (OR 1.166, 95% CI 1.034–1.313, p = 0.012) retained significance on binary logistic regression analysis. The prediction model devised performed well (area under the receiver operating characteristic 0.778, 95% CI 0.681–0.875). Conclusion The prediction of mortality can be done accurately at the bedside using TBSA and APACHE II score.

Cross-Sectional Examination of Homocysteine Levels with Sarcopenia and Its Components in Memory Clinic Outpatients

2021 ◽  
pp. 1-10
Author(s):  
Yosuke Yamada ◽  
Hiroyuki Umegaki ◽  
Fumie Kinoshita ◽  
Chi Hsien Huang ◽  
Taiki Sugimoto ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Cognitive Impairment ◽  
Cognitive Function ◽  
Linear Regression ◽  
Logistic Regression Analysis ◽  
Linear Regression Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Memory Clinic ◽  
Cross Sectional

Background: Homocysteine is a common risk factor for cognitive impairment and sarcopenia. However, very few studies have shown an association between sarcopenia and serum homocysteine levels after adjustment for cognitive function. Objective: The purpose of this study was to investigate the relationship between homocysteine and sarcopenia in memory clinic patients. Methods: This cross-sectional study investigated outpatients in a memory clinic. We enrolled 1,774 participants (≥65 years old) with measured skeletal muscle mass index (SMI), hand grip strength (HGS), and homocysteine. All participants had undergone cognitive assessments and were diagnosed with dementia, mild cognitive impairment, or normal cognition. Patient characteristics were compared according to sarcopenia presence, SMI level, or HGS. Multivariate logistic regression analysis was performed to determine the association of homocysteine with sarcopenia, low SMI, or low HGS. Next, linear regression analysis was performed using HGS as a continuous variable. Results: Logistic regression analysis showed that low HGS was significantly associated with homocysteine levels (p = 0.002), but sarcopenia and low SMI were not. In linear regression analysis, HGS was negatively associated with homocysteine levels after adjustment for Mini-Mental State Examination score (β= –2.790, p <  0.001) or clinical diagnosis of dementia (β= –3.145, p <  0.001). These results were similar for men and women. Conclusion: Our results showed a negative association between homocysteine and HGS after adjustment for cognitive function. Our findings strengthen the assumed association between homocysteine and HGS. Further research is needed to determine whether lower homocysteine levels lead to prevent muscle weakness.

scholarly journals Predicting organizational performance from motivation in Oromia Seed Enterprise Bale branch

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Askalech Feyisa Jobira ◽  
Abdulnasir Abdulmelike Mohammed
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Intrinsic Motivation ◽  
Organizational Performance ◽  
Logistic Regression Analysis ◽  
Extrinsic Motivation ◽  
Binary Logistic Regression ◽  
Moderate Level ◽  
Binary Logistic Regression Analysis ◽  
Study Results

AbstractMotivation is one of the most researched yet crucial topics in academia from various perspectives. Despite this, researches show mixed results about the effect of extrinsic motivation on intrinsic motivation and organizational performance. Studies in Ethiopia also lack causal analysis and theoretical underpinning that made contributions from academia very little. Hence, this research is important to assess the effect of extrinsic motivation on intrinsic motivation and organizational performance from a cognitive evaluation theory perspective. The researchers adopted an explanatory research design with a quantitative approach. The entire 119 employees of the Oromia Seed Enterprise, Bale branch were included in the study to collect primary data through a close-ended questionnaire. The collected data was processed by SPSS software version 20. The relationship analysis was addressed by correlation and binary logistic regression analysis. Seen from extrinsic and intrinsic motivation aspects, the findings of the study showed that Oromia Seed Enterprise had a moderate level of organizational performance and a moderate level of employees’ motivation. The correlation analysis result indicated that employees’ extrinsic and intrinsic motivation had a positive relationship with organizational performance. The binary logistic regression analysis also indicated that extrinsic and intrinsic motivation had a positive and significant influence on organizational performance. However, the interaction effect of intrinsic and extrinsic motivation on organizational performance was not significant, implying the absence of influence when both intrinsic and extrinsic motivations happen at the same time. Finally, the study results have a theoretical contribution for compensating the lack of actual experience in the Ethiopian organization’s context. Equally, the understanding of the moderated relationship among the study variables may encourage Oromia Seed Enterprise and its managers to develop a practical motivation system, which entertains the complex interaction of motivation variables to improve organizational performance. In addition, studies of this nature can inform policymakers to strengthen an incentive system as well as other motivation veins in the Ethiopian public organizations.

scholarly journals Binary Logistic Regression Analysis of Variables That Influence Poverty in Central Java

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Sendi Nugraha Nurdiansah ◽  
Laelatul Khikmah
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Binary Logistic Regression ◽  
Equation Model ◽  
Binary Logistic Regression Analysis ◽  
Poor People ◽  
Regional Government ◽  
Central Java ◽  
The Government

The phenomenon of poverty is a serious problem faced by almost every country in the world. This is because poverty can affect various aspects of people's lives. One of the causes of poverty is due to lack of income and assets to meet basic needs such as food, clothing, housing, health level and acceptable education. In addition, poverty occurs because of the powerlessness of society to get out of the problems it faces. The Central Java regional government incorporated poverty issues into the Regional Medium-Term Development Plan (RPJMD) because Central Java has a high number of poor people. This was done as an effort by the Central Java government to reduce poverty. Therefore, research is needed to find out the variables that most influence poverty in order to assist the government in developing the RPJMD. To find out what factors influence poverty in Central Java with the dichotomous categorical response variable, binary logistic regression analysis was used. The results showed that based on the analysis conducted did not obtain a logistic regression equation model because there were no significant parameters because there were no variables that had a sig value <0.05. Existing variables are Number of Population, Female Head of Household, Number of Children not in School, Number of Disabled Individuals, Number of Chronic Disease Individuals, Unemployment, Non-Electricity Lighting Sources, Unprotected Drinking Water Sources, Kerosene and Wood Cooking Fuels, Location Facilities Defecation (BAB) Not Available, so there are no variables that affect the level of poverty in Central Java Province.

scholarly journals Factors affecting internet use among university students in Sarawak, Malaysia: an empirical study

2020 ◽  
Vol 7 (3) ◽  
pp. 848
Author(s):  
M. Mizanur Rahman ◽  
M. Taha Arif ◽  
Fready Luke ◽  
Santha Letchumi ◽  
Fatin Nabila ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
University Students ◽  
Logistic Regression Analysis ◽  
Internet Use ◽  
Binary Logistic Regression ◽  
Problematic Internet Use ◽  
The Internet ◽  
Binary Logistic Regression Analysis ◽  
Factors Affecting

Background: The internet has become an indispensable tool for communication, academic research, information and entertainment. However, heavy users of the internet lead to less confidence in social skills and the tendency to be isolated. The study aimed to assess the pattern of internet use and factors affecting problematic internet use among university students.Methods: This cross-sectional study conducted among the students of a university in Sarawak, Malaysia. A multistage cluster sampling technique was adapted to select the participants. Data were collected from 463 students by self-administered questionnaire. Hierarchical binary logistic regression analysis was done to determine the potential factors for problematic internet use.Results: The mean age of the students was 22 years, with a standard deviation of 1.6 years. Two-fifths (61.8%) of the students had no problematic internet use. However, 35.4% had moderate and 2.8% had severe problematic internet use. Hierarchical binary logistic regression analysis found that age of the students, year of study, duration of daily internet use and use of social networking like Skype appeared to be potential predictors of problematic internet use (p<0.05).Conclusions: This study was conducted in only one university, thus did not depict the overall scenarios of the country. The implications of the findings are still worth noting in the process of designing internet addiction studies among university students. Overall, this study has unearthed some useful insights which can serve as a guide to more elaborate studies.

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