scholarly journals Effects of the Contents of Mineral Elements on Gummosis in Prunus salicina Lindl.

HortScience ◽  
2021 ◽  
pp. 1-4
Author(s):  
Xiaoli Ma ◽  
Xuefeng Liu ◽  
Pingwei Xiang ◽  
Shichun Qiu ◽  
Xiangcheng Yuan ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Prevention And Control ◽  
Mineral Elements ◽  
Binary Logistic Regression Analysis ◽  
Fertilization Experiment ◽  
Prunus Salicina ◽  
Ordinal Logistic Regression Analysis ◽  
And Control

To investigate the relationship between mineral elements and plum gummosis disease, Prunus salicina Lindl. trees with four grades of gummosis were used as the experimental materials. The contents of N, P, K, Ca, Mg, B, Fe, Mn, Zn and Cu in the branches and leaves were measured, and the correlation between mineral elements and gummosis was systemically analyzed through multiple comparisons, binary logistic regression analysis, and ordinal logistic regression analysis. In addition, the effects of prevention and control of the necessary mineral elements on the gummosis disease of P. salicina were verified after a fertilization experiment. The results indicate that the contents of nitrogen and manganese positively correlate with the occurrence of gummosis. In contrast, the contents of calcium and boron significantly negatively correlate with the occurrence of gummosis. A fertilization experiment facilitated the discovery that the control of nitrogen, as well as the increased application of boron and calcium fertilizers, contributed to the prevention and control on gummosis disease in P. salicina

scholarly journals Knowledge, Attitude, and Practice of Pediculus Capitis Prevention and Control and Their Predictors among Schoolchildren in Woreta Town, Northwest Ethiopia, 2018: A School-Based Cross-Sectional Study

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Henok Dagne ◽  
Awel Aba Biya ◽  
Amanuel Tirfie ◽  
Walelegn Worku Yallew ◽  
Zewudu Andualem ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Prevention And Control ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Attitude And Practice ◽  
Pediculus Capitis ◽  
And Control ◽  
Knowledge Attitude And Practice

Background. Pediculus capitis is a human head lice infestation, a major public health issue that is most prevalent in resource-limited countries globally. The current study aimed to assess the knowledge, attitude, and practice of pediculus capitis prevention and control and their predictors among schoolchildren in North West Ethiopia. Methods. About 402 randomly selected schoolchildren from three schools in Woreta town participated in the study from April to June 2018. The outcomes of this study were knowledge, attitude, and self-reported practice of schoolchildren about pediculus capitis prevention and control. We used EPI Info 7.1 and SPSS 21 software for data entry and analysis, respectively. Binary logistic regression was employed to test the association of covariates with the outcome/response variables. Variables with a p value <0.2 during the bivariable binary logistic regression analysis were included in the multivariable binary logistic regression analysis. Variables with p value <0.05 were declared as significantly associated with outcomes. Results. The mean age of the study participants was 10.19 (±1.62) years. About 58.8%, 45.8%, and 78.6% of the schoolchildren had better self-reported pediculus capitis prevention knowledge, attitude, and practice, respectively. Age of children [9 to 11 years (AOR=2.24, 95% C.I (1.10, 4.55)) and>12 years (AOR=3.84, 95% C.I (1.56, 9.46))], better practice (AOR=2.93, 95% C.I (1.39, 6.18)), and those who were not infested (AOR=2.25, 95% C.I (1.14, 4.44)) were predictors of knowledge regarding pediculus capitis prevention. Better practice (AOR=4.33, 95% C.I (1.69, 11.09)) and absence of infestation (AOR=2.97, 95% C.I (1.64, 5.36)) were predictors of attitude of schoolchildren about pediculus capitis prevention. Number of students in a class [51 to 56 students per classroom, AOR=4.61, 95% C.I (1.83, 11.67); 57 to 58 students per classroom, AOR=8.18, 95% C.I (2.73, 24.46)], less than five family size (AOR=2.37, 95% C.I (1.24, 4.54)), better knowledge (AOR=2.93, 95% C.I (1.32, 6.50)), desirable attitude (AOR=4.24, 95% C.I (1.60, 11.23)), and absence of infestation (AOR=3.52, 95% C.I (1.22, 10.15)) were predictors of self-reported pediculus capitis prevention practice. Conclusion. The knowledge, attitude, and practice of schoolchildren regarding pediculus capitis prevention and control were not satisfactory. To bring change, intensive efforts on factors associated with the knowledge, attitude, and practice should be encouraged.

Decline of gustatory sensitivity with the progression of Alzheimer's disease

2015 ◽  
Vol 28 (3) ◽  
pp. 511-517 ◽  
Author(s):  
Mariko Sakai ◽  
Manabu Ikeda ◽  
Hiroaki Kazui ◽  
Kazue Shigenobu ◽  
Takashi Nishikawa
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Ordinal Logistic Regression ◽  
Threshold Values ◽  
Ordinal Logistic Regression Analysis ◽  
And Control ◽  
Detection And Recognition

ABSTRACTBackground:Patients with Alzheimer's disease (AD) manifest various impairments in eating behavior. However, few previous studies have directly investigated the gustatory function of AD patients, and results have been inconsistent.Methods:Thirty-two AD patients (Clinical Dementia Rating (CDR) 0.5/1/2, respectively 11/15/6 patients) and 22 normal control participants were examined to measure detection and recognition thresholds of the four elemental tastes (sweet, salty, sour, and bitter), and their ability to discriminate between tastes. Effects of demographic and clinical factors (age, sex, histories of alcohol and tobacco consumption, and CDR grade) on gustatory threshold were examined using ordinal logistic regression analysis. Performance was compared between AD and control groups.Results:Total threshold values (the sum of threshold grades for the four tastes) for detection and recognition of tastes were significantly higher in the AD group. Detection thresholds for sweet, salty, and bitter, and recognition thresholds for sweet and sour, were also significantly higher in the AD group. Ordinal logistic regression analysis revealed that CDR grade was the only factor that significantly affected both total threshold values. Regarding taste discrimination, there were no significant differences between the AD group and control group.Conclusions:These findings suggest that progression of dementia severity accompanies gustatory decline. Although it seemingly paradoxical, weight loss and preference for sweet tastes are frequently, often simultaneously, observed in AD. Gustatory dysfunction may be partially involved in these symptoms. Thus, the nutritional care of patients with AD could be improved by making the taste of meals stronger, while controlling calorie and mineral intake.

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.

scholarly journals Cross-Sectional Association between Hypercholesterolemia and Knee Pain in the Elderly with Radiographic Knee Osteoarthritis: Data from the Korean National Health and Nutritional Examination Survey

2021 ◽  
Vol 10 (5) ◽  
pp. 933
Author(s):  
Byung Woo Cho ◽  
Du Seong Kim ◽  
Hyuck Min Kwon ◽  
Ick Hwan Yang ◽  
Woo-Suk Lee ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Knee Pain ◽  
Logistic Regression Analysis ◽  
National Health ◽  
Large Scale ◽  
Metabolic Diseases ◽  
The Elderly ◽  
Cross Sectional ◽  
Ordinal Logistic Regression Analysis

Few studies have reported the relationship between knee pain and hypercholesterolemia in the elderly population with osteoarthritis (OA), independent of other variables. The aim of this study was to reveal the association between knee pain and metabolic diseases including hypercholesterolemia using a large-scale cohort. A cross-sectional study was conducted using data from the Korea National Health and the Nutrition Examination Survey (KNHANES-V, VI-1; 2010–2013). Among the subjects aged ≥60 years, 7438 subjects (weighted number estimate = 35,524,307) who replied knee pain item and performed the simple radiographs of knee were enrolled. Using multivariable ordinal logistic regression analysis, variables affecting knee pain were identified, and the odds ratio (OR) was calculated. Of the 35,524,307 subjects, 10,630,836 (29.9%) subjects experienced knee pain. Overall, 20,290,421 subjects (56.3%) had radiographic OA, and 8,119,372 (40.0%) of them complained of knee pain. Multivariable ordinal logistic regression analysis showed that among the metabolic diseases, only hypercholesterolemia was positively correlated with knee pain in the OA group (OR 1.24; 95% Confidence Interval 1.02–1.52, p = 0.033). There were no metabolic diseases correlated with knee pain in the non-OA group. This large-scale study revealed that in the elderly, hypercholesterolemia was positively associated with knee pain independent of body mass index and other metabolic diseases in the OA group, but not in the non-OA group. These results will help in understanding the nature of arthritic pain, and may support the need for exploring the longitudinal associations.

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.

scholarly journals PELUANG ALUMNI PENDIDIKAN MATEMATIKA FKIP UMB DALAM MENDAPATKAN PEKERJAAN DENGAN MENGGUNAKAN ANALISIS REGRESI LOGISTIK

2017 ◽  
Vol 10 (2) ◽  
pp. 85
Author(s):  
Mahyudi Mahyudi
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Mathematics Education ◽  
Survey Data ◽  
Logistic Regression Analysis ◽  
Work Experience ◽  
National Origin ◽  
College Graduation ◽  
The Road ◽  
Ordinal Logistic Regression Analysis

Graduation or college graduation become the most exciting moment for a student. In addition to successfully get a degree, they are also eager to enter the workforce. But sometimes the spirit was lost in the middle of the road. Many fresh graduates complain of difficult to get a job at this time. Every year the number of graduates to grow while jobs are not directly proportional to the increase in the number of graduates. The study analyzed what are the chances of graduates Mathematics Education FKIP Muhammadiyah University of Bengkulu in getting a job. Samples taken as many as 78 graduates between September 2015 to April 2016. The factors considered were gender, age, GPA, national origin, jobs for college and the work areas as desired. Analysis of survey data using ordinal logistic regression analysis. The results showed that the dominant factors that affect the length of the graduates in getting a job is GPA, work experience in college and the desired field of work.

scholarly journals An Investigation of the Variables Predicting Faculty of Education Students’ Speaking Anxiety through Ordinal Logistic Regression Analysis

2016 ◽  
Vol 6 (1) ◽  
pp. 27
Author(s):  
Ebru Bozpolat
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Self Efficacy ◽  
Public Speaking ◽  
Education Students ◽  
Speaking Anxiety ◽  
Ordinal Logistic Regression Analysis ◽  
Faculty Of Education ◽  
Speech Content

The purpose of this study is to determine whether Cumhuriyet University Faculty of Education students’ levels of speaking anxiety are predicted by the variables of gender, department, grade, such sub-dimensions of “Speaking Self-Efficacy Scale for Pre-Service Teachers” as “public speaking”, “effective speaking”, “applying the speaking rules”, “organizing the speech content”, and “evaluating the speech”. Correlational survey model is employed in the study. While the dependent variable of the study is students’ “speaking anxiety”, its independent variables are gender, department, grade, and such sub-dimensions of “Speaking Self-Efficacy Scale for Pre-Service Teachers” as “public speaking”, “effective speaking”, “applying the speaking rules”, “organizing the speech content”, and “evaluating the speech”. The research population consists of 2983 students studying at seven departments of Faculty of Education of Cumhuriyet University in the 2015-2016 academic year. The research sample, on the other hand, is composed of 1057 students from seven departments of Faculty of Education of Cumhuriyet University. Data were collected via “Scale of Speaking Anxiety for Prospective Teachers”, which was developed by Kınay and Özkan (2014) to determine pre-service teachers’ speaking anxiety, and “Speaking Self-Efficacy Scale for Pre-Service Teachers”, which was developed by Katrancı and Melanlıoğlu (2013) to determine pre-service teachers’ speaking self-efficacy. Data were collected through ordinal logistic regression analysis as the dependent variable was made three-category and ordinal through cluster analysis. According to the logistic regression analysis results, gender, department, such sub-dimensions of “Speaking Self-Efficacy Scale for Pre-Service Teachers” as “public speaking” and “applying the speaking rules” have a significant influence on speaking anxiety.

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.

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