scholarly journals ANALYSIS OF FACTORS AFFECTING THE EFFICIENCY OF HOUSEHOLDS LOANS USING FROM ECONOMIC DEVELOPMENT CAPITAL OF THE WOMEN’S UNION OF DUYEN HAI DISTRICT, TRA VINH PROVINCE

2021 ◽  
Vol 1 (42) ◽  
pp. 20-24
Author(s):  
Nguyen Thi Thanh Nguyen
Keyword(s):  
Economic Development ◽  
Regression Model ◽  
Education Level ◽  
Current Situation ◽  
Social Policies ◽  
Factors Affecting ◽  
Research Results ◽  
Multivariable Regression Model ◽  
Multivariable Regression ◽  
Loan Amount

Nowadays, women receive a lot of attention and assistance in production and business. They have been support with loans from  the Women’s Union, capital from Vietnam Bank for Social Policies to facilitate family economic development. This study aims to assess the current situation of demand and efficiency of loanusing in Duyen Hai District, Tra Vinh Province. In this study, the method of Multivariable Regression model was used to analyze the factors affecting the efficiency of using such loans. Research results shown that there are four factors that have positive correlation with loans using efficiency, including age, education level, landarea, loan amount. On the contrary, three factors including the number of employees, the main source of income, and the purpose of loan are negatively related to the efficiency of using loans. In addition, the study proposes some solutions to help households in using capital more efficiently and enhancing their standard of lives.

scholarly journals Short-Term Air Quality Prediction Based on Fractional Grey Linear Regression and Support Vector Machine

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Meng Dun ◽  
Zhicun Xu ◽  
Yan Chen ◽  
Lifeng Wu
Keyword(s):  
Air Quality ◽  
Regression Model ◽  
Hybrid Model ◽  
Air Pollutants ◽  
Support Vector ◽  
Support Vector Regression Model ◽  
Air Quality Prediction ◽  
Multivariable Regression Model ◽  
Multivariable Regression ◽  
The Mean

To predict the daily air pollutants, the fractional multivariable model is established. The hybrid model of the grey multivariable regression model with fractional order accumulation model (FGM(0, m)) and support vector regression model (SVR) is used to predict the air pollutants (PM10, PM2.5, and NO2) from December 31, 2018, to January 3, 2019, in Shijiazhuang and Chongqing. The absolute percentage errors (APEs) are used to determine the weights of the FGM(0, m) and SVR. Meanwhile, the Holt–Winters model is used to predict the air quality pollutants for the same location and period. When the mean absolute percent error (MAPE) is 0%–20%, it indicates that the model has good accuracy of fitting and prediction. The MAPE of the hybrid model is less than 20%. It is shown that except for the PM2.5 concentration prediction in Shijiazhuang (13.7%), the MAPE between the forecasting and actual values of the three air pollutants in Shijiazhuang and Chongqing was less than 10%.

scholarly journals Fatty Liver is Associated with Low N-terminal pro-B-type Natriuretic Peptide in a Healthy Population: From the Kangbuk Samsung Health Study

2021 ◽  
Author(s):  
Hyo-In Choi ◽  
Mi Yeon Lee ◽  
Byeong Kil Oh ◽  
Seung Jae Lee ◽  
Jeong Gyu Kang ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Regression Model ◽  
Natriuretic Peptide ◽  
Abdominal Ultrasound ◽  
Health Study ◽  
Large Set ◽  
Model Assessment ◽  
Multivariable Regression Model ◽  
Multivariable Regression ◽  
The Impact

Abstract BackgroundFatty liver (FL), insulin resistance (IR), and obesity often coexist, but data on the independent impacts of these factors on N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels in healthy populations are scarce. We therefore examined the impact of FL, IR and obesity on NT-proBNP levels using a large set of cross-sectional data.MethodsThe associations of FL, IR and obesity with NT-proBNP were analyzed in 39,923 healthy adult participants using Kangbuk Samsung Health Study data. IR was estimated using homeostasis model assessment-estimated insulin resistance (HOMA-IR) index. A multivariable regression model that adjusted for factors that influence NT-proBNP was conducted to identify associations between NT-proBNP and FL on abdominal ultrasound. ResultsA total of 11,704 (29.3%) individuals had FL on abdominal ultrasound. FL, IR and obesity showed independent inverse associations with NT-proBNP after multiple adjustments for baseline characteristics. In a multivariable regression model adjusting for IR and obesity, FL was independently associated with lower levels of NT-proBNP (odds ratio 0.864, 0.849 - 0.880). The combination of FL and IR was a powerful dual predictor, lowering NT-proBNP levels approximately 25% in the generally healthy study population.ConclusionIn this large sample of healthy individuals, FL was independently associated with lower NT-proBNP levels. FL and a high HOMA-IR index are a powerful predictor combination for lower NT-proBNP levels. Further research is needed to elucidate the mechanism underlying the association between FL and NT-proBNP.

scholarly journals Investigation of timing of surgery and other factors possibly influencing outcome in dogs with acute thoracolumbar disc extrusion: a retrospective study of 1501 cases

2021 ◽  
Vol 63 (1) ◽  
Author(s):  
Almut Immekeppel ◽  
Stefan Rupp ◽  
Stanislas Demierre ◽  
Kai Rentmeister ◽  
Andrea Meyer-Lindenberg ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Regression Model ◽  
Clinical Signs ◽  
Physical Rehabilitation ◽  
Timing Of Surgery ◽  
Time Span ◽  
Bivariate Analysis ◽  
Multivariable Regression Model ◽  
Thoracolumbar Region ◽  
Multivariable Regression

Abstract Background Intervertebral disc extrusions in the thoracolumbar region are a common spinal neurologic disorder in dogs and usually considered a neurological emergency. Several factors, like timing of surgery, have previously been analysed in order to determine the effect on outcome and time of recovery. Most studies have investigated one defined population of dogs and the influence of a single factor on the overall outcome. In this retrospective study, a large cohort of dogs and the influence of one or combinations of several factors on outcome and time of recovery were analysed. Results The bivariate analysis demonstrated a significant association between the following variables and the time of recovery: the time span between the onset of clinical signs and surgery (Cramers Phi $$\varphi^{\prime}$$ φ ′  = 0.14; P = 0.003), the grade of severity ($$\varphi^{\prime}$$ φ ′  = 0.23; P < 0.001) and the implementation of physical rehabilitation ($$\varphi^{\prime}$$ φ ′  = 0.2; P < 0.001). However, the analysis of a multivariable regression model demonstrated that a significant correlation only exists between the time span between the onset of clinical signs and surgery and the overall outcome (P = 0.007), as well as between the grade of severity and the time of recovery (P < 0.001). The percentage of dogs with lacking deep pain perception (DPP) that had to be euthanised due to their neurological condition, decreased from 20.0 to 2.9% when physical rehabilitation was implemented. Additionally, the proportion of dogs (same group) that improved to reach an ambulatory status increased from 80.0 to 91.4%. Conclusion The results of the bivariate analysis demonstrated several correlations between some variables and overall outcome or time of recovery, whereas the multivariable regression model demonstrated only two associations. The time span between the onset of clinical signs and surgery was significantly associated with the overall outcome. We therefore suggest that a surgical intervention should be performed without unreasonable delay. Due to the correlation between the grade of severity and time of recovery, owners of dogs with more severe neurological deficits prior to surgery should be informed about the presumably prolonged time of recovery.

scholarly journals Modeling and Analyzing the Factors Affecting the Mortality of Pedestrians in Urban Accidents

2018 ◽  
Vol 14 (4) ◽  
pp. 10-21
Author(s):  
Ahmet Tortum ◽  
Alireza Motamadnia
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Motor Vehicle ◽  
Binary Logistic Regression ◽  
Education Level ◽  
Road Surface ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Surface Conditions

Abstract The nature of urban and rural accidents has been different from each other in some of the factors and even the severity of damage rate, mayhem, and death. In this research, using statistical methods and binary logistic regression model, we have addressed to analyze important parameters such as age, gender, education level, the color of the pedestrian dress, season of accident, time of accident, the speed of the vehicle colliding with pedestrians and road surface conditions at the time of accident on the way of death (at the scene of the incident or in the hospital) pedestrians who have been traumatized. After the creation of the binary logistic regression model, it was determined that only the parameters of speed and the accident time have been significant in the level less than 5%. And other parameters such as age, gender, the season of accident occurrence, the color of the pedestrian dress, road surface conditions and education level had no significant effect in terms of statistical on the incidence of mortality arising from a pedestrian accident with the motor vehicle. The results revealed that by adopting decisions related to the traffic calming, attention to passages lighting and brightness the mortality rate of a pedestrian due to the urban accidents can be reduced.

scholarly journals Cognitive Factors Affecting AIDS Preventive Behaviors in Iranian Women with Addicted Spouses

2020 ◽  
Vol 17 (4) ◽  
Author(s):  
Fatemeh Khosravi Chahak ◽  
Elaheh Allahyari ◽  
Mohammad Reza Miri ◽  
Ensiyeh Norozi
Keyword(s):  
Regression Model ◽  
Self Efficacy ◽  
Addiction Treatment ◽  
Health Belief ◽  
Risk Groups ◽  
Study Data ◽  
Education Level ◽  
P Value ◽  
Preventive Behaviors ◽  
Factors Affecting

Background: Human immunodeficiency virus (HIV)/AIDS is one of the most substantial socioeconomic health issues in many countries all around the world. Objectives: This study aimed to address the factors affecting AIDS preventive behaviors in women who had addicted husbands using the health belief model (HBM) in Sarbishe and Birjand cities, Iran, in 2019. Methods: A descriptive-analytical study was conducted on 224 women who had addicted husbands. A convenience sampling method was used, and all women whose husbands were under the support of the public and private addiction treatment centers were entered into the study. Data collection tools included a questionnaire of demographic items, HBM constructs, knowledge, and AIDS preventive behaviors. The collected data were analyzed using a correlation test and a regression model. The p value was considered less than 0.05 to be significant. Results: The respondents' mean age was 37.77 ± 8.97 years. Most women (93.8%) were housekeepers, and 54% of them had self-employed husbands. Most women (61.6%) and their husbands (58.9%) had an education level of under-diploma. Based on the regression model, the most important predictors of AIDS preventive behaviors included perceived self-efficacy (B = 0.231), education level (B = 0.196), and income (B = -0.154). Conclusions: Research findings confirm the association between perceived self-efficacy, education level, income, and adopting AIDS preventive behaviors. The obtained results can be used to develop theory-based interventions to shape AIDS preventive behaviors in high-risk groups.

scholarly journals Characteristics of US Adults Delaying Dental Care Due to the COVID-19 Pandemic

2020 ◽  
Vol 6 (1) ◽  
pp. 8-14
Author(s):  
A.M. Kranz ◽  
G. Gahlon ◽  
A.W. Dick ◽  
B.D. Stein
Keyword(s):  
Regression Model ◽  
Dental Care ◽  
Health Care Services ◽  
Chi Square ◽  
Cross Sectional ◽  
Dental Visits ◽  
Care Services ◽  
Multivariable Regression Model ◽  
Multivariable Regression ◽  
Nationally Representative

Background: Coronavirus disease 2019 (COVID-19) has disrupted the delivery of health care services, including dental care. The objective of this study was to quantify and describe US adults who delayed dental care due to the COVID-19 pandemic. Methods: We analyzed cross-sectional responses collected from a nationally representative and long-running panel survey of US adults conducted in late May and early June 2020 (response rate = 70%). The survey included questions about dental care delayed due to the COVID-19 pandemic, purpose of the delayed dental visits, timing of future dental visits, and demographic information. Pearson’s chi-square tests were used to determine if rates of delayed dental care varied by subgroup. A multivariable regression model, adjusted for age, race, Hispanic ethnicity, census division, and rurality, was estimated to predict the odds of reporting delayed dental care. Results: Nearly half of respondents (46.7%) reported delaying going to the dentist or receiving dental care due to the COVID-19 pandemic. Among adults who reported delaying dental care due to the pandemic, 74.7% reported delaying a checkup, 12.4% reported delaying care to address something that was bothering them, and 10.5% reported delaying care to get planned treatment. About 44.4% of adults reported that they planned to visit the dentist within the next 3 mo. In the multivariable regression model, only living in an urban (vs. rural) area was associated with significantly higher odds of delayed dental care due to the pandemic (odds ratio: 1.5; 95% confidence interval: 1.1, 2.1). Conclusions: Nearly half of US adults reported delaying dental care due to the COVID-19 pandemic during the spring of 2020. Our results offer insight into the experiences of patients seeking dental care this spring and the economic challenges faced by dental providers due to the pandemic. Knowledge Transfer Statement: This article describes US adults who delayed dental care due to the COVID-19 pandemic. Results can be used by clinicians and policymakers to understand delayed care during the pandemic.

Uncertain multivariable regression model

2018 ◽  
Vol 22 (17) ◽  
pp. 5861-5866 ◽  
Author(s):  
Yuanlong Song ◽  
Zongfei Fu
Keyword(s):  
Regression Model ◽  
Multivariable Regression Model ◽  
Multivariable Regression
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