scholarly journals Effects of Different Socio-economic Characteristics of Rural Households on Their Saving Decision in Pabna District of Bangladesh: A Binary Logistic Regression Analysis

2020 ◽  
pp. 14-20
Author(s):  
Md. Al-Amin
Keyword(s):  
Logistic Regression ◽  
Random Sampling ◽  
Rural Households ◽  
Binary Logistic Regression ◽  
Sampling Technique ◽  
Binary Logistic Regression Analysis ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
Household Saving ◽  
Private Savings

Household saving ensures a smooth future by softening the potential insecurities arise from uncertainty at the cost of present consumption. Moreover, the volume of national investment determines the actual health of an economy which is intensively associated with national savings. This study aimed at determining the effects of different socio-economic characteristics of rural households on their saving decision in Pabna district of Bangladesh. This research used a set of cross-sectional data from 250 households from three upazilas in Pabna district namely Pabna Sadar, Iswardi and Sujanagar on the relevant variables for the empirical analysis. A multistage random sampling technique involving simple, purposive and stratified random sampling was used to draw the sample. The study employed a binary logistic regression model to assess the influences of different socio-economic and demographic characteristics of rural household on their saving decision. The findings of the current study asserted that gender, family size and dependency ratio of household have significant and negative effects on their decision to start saving or not to start saving. Contrarily, the effects of the variables age, education level, marital status, income, secondary earner and liabilities on the decision of households to participate in saving were positive and significant. Moreover, the results revealed that social status has a strong but insignificant effect, but the variables access to bank and credit facilities have almost no significant effect on the household saving decisions. Since, private savings is essential for both the micro and macro level of an economy, therefore the study tried to suggest some recommendations with a view to increase private savings.

scholarly journals Socioeconomic determinants of micro and small enterprise growth in North Wollo and Waghimira Zone selected towns

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Erstu Tarko Kassa
Keyword(s):  
Research Design ◽  
Binary Logistic Regression ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Small Enterprise ◽  
Binary Logistic Regression Analysis ◽  
Cross Sectional ◽  
Tax Rate ◽  
Socioeconomic Determinant ◽  
North Wollo

AbstractThis study aims to investigate the socioeconomic determinant factors that affect the growth of micro and small enterprises (MSEs) in North Wollo and Waghimira Zone selected towns. In this study, a cross-sectional research design with both descriptive and explanatory research design has been employed, and 303 owners of enterprises have participated. The towns were selected purposely, and the respondents were also selected by using a simple random sampling technique. The data were analyzed by using STATA v-14 and applied descriptive and binary logistic regression analysis (odds ratio). The finding of the study revealed that age of the owner, access to finance, family business background, and interest rate most likely affect the growth of the enterprises with the statistically significant level. On the contrary, entrepreneurship training, the experience of the owner, the inflation rate, and competition less likely affect the growth of the enterprises with a statistical significant level. The remaining factors such as gender of the owners, education background, business age, business type, business location, social responsibility, tax rate, and social attitude were not statistically significant to determine the growth of MSEs.

MO376CLINICAL OUTCOMES OF ACUTE KIDNEY INJURY FOLLOWING SNAKE BITE INJURIES

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Weerakit Naweera ◽  
Thapat Wannarong
Keyword(s):  
Acute Kidney Injury ◽  
Logistic Regression ◽  
Kidney Injury ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Renal Recovery ◽  
Binary Logistic Regression Analysis ◽  
Cross Sectional ◽  
Hospital Arrival ◽  
Russell’S Viper

Abstract Background and Aims Snakebite is a common animal bite injury in tropical countries. Acute kidney injury (AKI) is an important complication in snakebite patients. This study aimed to comprehensively investigate the clinical profiles and outcomes of patients following hematotoxin-related snakebite associated with kidney impairment. Method We conducted a hospital-based, cross-sectional study of 238 patients with hematotoxin-related snakebite injuries. Data were retrieved from the King Narai Hospital Registry from October 2014 to August 2020. The prevalence of complications associated with snakebite injuries, including acute kidney injury (AKI) and its severity, was determined. Univariate and Multivariate predictors of AKI diagnosis were evaluated using binary logistic regression analysis Results A total of 238 patients, with 63.4% men, median (IQR) age 49.8 (39-61) years and median duration from injury to a hospital arrival of 1 hour (0.5-2) hours, were injured by Green pit viper (85.7%), Russell’s viper (12.6%) and Malayan pit viper (1.7%). AKI mostly occurred in Russell’s viper group 66.7%. An AKI was reported in thirty (12.6%, 95% CI: 8.7 % - 17.5%) patients, with the severity of 66.7% stage one, 6.7% stage two, 26.6% stage three by KDIGO classifications, and 13.3% requiring hemodialysis. Complete renal recovery was seen in twenty-two patients (73.3%), while partial renal recovery was 23.3%. Other complications included 84.4 % limb cellulitis, 4.6% significantly bleeding, 2.5% hypotension, 25.6% prolonged venous clotting time (VCT), 46.7% prolonged prothrombin time (PT), and 14.3% prolonged partial thromboplastin time (PTT). Of total patients, 60.1% were treated with anti-venom. Mortality was relatively low (0.4%). In multivariable logistic regression analyses, AKI was significantly associated with time to hospital arrival more than 3 hours (p = 0.04), Russell’s viper bitten (p = 0.01), clinical bleeding (p = 0.01), and prolonged PT (p < 0.01). Conclusion The prevalence of AKI in patients bitten by hematotoxin snakes was 12.6%, mostly from Russell’s viper. Factors associated with AKI outcomes were time to hospital arrival more than 3 hours, Russell’s viper bitten, clinical bleeding, and prolonged PT. Besides, one-fourth of AKI patients turned to chronic kidney disease.

scholarly journals A predictive model for early diagnosis of keratoconus

2020 ◽  
Author(s):  
GRACIA CASTRO-LUNA ◽  
ANTONIO PÉREZ-RUEDA
Keyword(s):  
Logistic Regression ◽  
Predictive Model ◽  
Early Stage ◽  
Corneal Thickness ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Bivariate Analysis ◽  
Diagnostic Model ◽  
Binary Logistic Regression Model ◽  
Cross Sectional

Abstract Background: The diagnosis of keratoconus in the early stages of the disease is necessary to initiate an early treatment of keratoconus. Furthermore, to avoid possible refractive surgery that could produce ectasias. This study aims to describe the topographic, pachymetric and aberrometry characteristics in patients with keratoconus, subclinical keratoconus and normal corneas. Additionally to propose a diagnostic model of subclinical keratoconus based in binary logistic regression models Methods: The design was a cross-sectional study. It included 205 eyes from 205 patients distributed in 82 normal corneas, 40 early-stage keratoconus and 83 established keratoconus. The rotary Scheimpflug camera (Pentacam® type) analyzed the topographic, pachymetric and aberrometry variables. It performed a descriptive and bivariate analysis of the recorded data. A diagnostic and predictive model of early-stage keratoconus was calculated with the statistically significant variables Results: Statistically significant differences were observed when comparing normal corneas with early-stage keratoconus/ in variables of the vertical asymmetry to 90º and the central corneal thickness. The binary logistic regression model included the minimal corneal thickness, the anterior coma to 90º and posterior coma to 90º. The model properly diagnosed 92% of cases with a sensitivity of 97.59%, specificity 98.78%, accuracy 98.18% and precision 98.78%Conclusions: The differential diagnosis between normal cases and subclinical keratoconus depends on the mínimum corneal thickness, the anterior coma to 90º and the posterior coma to 90º.

scholarly journals Association between the non-HDL-cholesterol to HDL-cholesterol ratio and non-alcoholic fatty liver disease in Chinese children and adolescents: a large single-center cross-sectional study

2020 ◽  
Author(s):  
Shouxing Yang ◽  
Jinwei Zhong ◽  
Mengsi Ye ◽  
Lei Miao ◽  
Guangrong Lu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Children And Adolescents ◽  
Binary Logistic Regression ◽  
Hdl Cholesterol ◽  
Chinese Children ◽  
Binary Logistic Regression Analysis ◽  
Cross Sectional ◽  
Alcoholic Fatty Liver ◽  
Chinese Children And Adolescents

Abstract Background: The non-HDL-cholesterol to HDL-cholesterol (NHDLC/HDLC) ratio is closely related to a variety of dyslipidemia-related diseases. This study aimed to inspect the relationship between the NHDLC/HDLC ratio and non-alcoholic fatty liver (NAFLD) in children and adolescents.Methods: In this cross-sectional survey, a total of 7,759 eligible Chinese children and adolescents (5,692 boys and 2,067 girls) received routine medical examinations. The anthropometric and laboratory data of the subjects were collected. NAFLD was diagnosed by liver ultrasonography. Binary logistic regression analysis was performed on the NHDLC/HDLC ratio, NHDLC, HDLC and NAFLD. Receiver operating characteristic (ROC) curve analysis was exploited to compare the diagnostic significance of the above parameters for NAFLD.Results: The total prevalence of NAFLD was 4.36%, and the prevalence in boys was higher than that in girls (5.61% vs. 1.9%, P < 0.001). The prevalence of NAFLD was positively correlated with the NHDLC/HDLC ratio (P < 0.001). The binary logistic regression analysis demonstrated that the OR was 8.61 (95% CI, 5.90-12.57, P < 0.001) in tertile 3 (highest NHDLC/HDLC ratio) compared with tertile 1 (lowest NHDLC/HDLC ratio). After adjustment for age, sex, body mass index (BMI), alanine aminotransferase (ALT), uric acid (UA), total bilirubin (TB), fasting plasma glucose (FPG) and Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), the OR for tertile 3 (OR=1.83, 95% CI, 1.04-3.22, P = 0.035) was still significantly higher than that of tertile 1. The area under the curve (AUC) of the NHDLC/HDLC ratio of boys was 0.787, which was significantly greater than that of NHDLC and HDLC (0.719 and 0.726, P < 0.001). For girls, the AUC of the NHDLC/HDLC ratio was 0.763, which was also significantly greater than that of NHDLC (0.661, P < 0.001). Furthermore, the cutoff point of the NHDLC/HDLC ratio was 2.475 in boys and 2.695 in girls. In addition, the AUC of the NHDLC/HDLC ratio was 0.761 in subjects with normal ALT levels (ALT ≤ 40 U/L), which was significantly higher than that of NHDLC (0.680, P < 0.001) and HDLC (0.724, P = 0.007). For subjects with elevated ALT levels (ALT > 40 U/L), the AUC of the NHDLC/HDLC ratio (0.746) was also significantly greater than that of NHDLC (0.646, P < 0.001)Conclusions: The NHDLC/HDLC ratio was positively correlated with NAFLD in Chinese children and adolescents. It may serve as an effective indicator to help identify NAFLD in children and adolescents.

scholarly journals A model of visual limitation in patients with keratoconus

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Antonio Pérez-Rueda ◽  
Gracia Castro-Luna
Keyword(s):  
Visual Acuity ◽  
Logistic Regression ◽  
Operating Characteristic ◽  
Spherical Aberration ◽  
Area Under The Curve ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
Corrected Visual Acuity

Abstract This paper aims to calculate a relevance model of visual limitation (V.L.) in keratoconus patients based on refractive and topographic parameters. A cross-sectional study was carried out in Torrecárdenas Hospital, Almería, Spain, between February 2018 and July 2019. It included 250 keratoconus patients. Two groups were created according to a grading system of V.L. based on RETICS (Red Temática de Investigación Cooperativa en Salud) classification: keratoconus patients with no V.L. (best spectacle-corrected visual acuity (BSCVA) ≤ 0.05 logMAR) and keratoconus patients with V.L. (BSCVA > 0.05 logMAR). Correlations and a binary logistic regression were established. V.L. was correlated with maximum curvature (r = 0.649, p < 0.001) and root mean square higher-order aberrations (HOARMS) (r = 0.625, p < 0.001). Binary logistic regression included V.L. as the dependent variable and spherical equivalent, HOARMS, spherical aberration and interaction between the anterior and posterior vertical coma as independent variables. The model was a good fit. Area under the curve (A.U.C.) of receiver operating characteristic (R.O.C.) curve was 0.924, sensitivity 91.90%, specificity 83.60%, accuracy 88.94%; and precision 91.17%. Binary logistic regression model of V.L. is a good fit model to predict the early loss of visual acuity in keratoconus patients.

Procurement planning as a strategic tool for public procurement effectiveness: Experience from selected public procuring entities in Dodoma city, Tanzania

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ismail Abdi Changalima ◽  
Gift Onesmo Mushi ◽  
Shadrack Samwel Mwaiseje
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Public Procurement ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
Content Type ◽  
Survival And Development ◽  
Procurement Planning

Purpose The significance of the public procurement function is on the survival and development of procuring entities and that of a nation at large. This study aims to focus on examining the influence of procurement planning on the effectiveness of public procurement, experience from selected public procuring entities in Dodoma city, Tanzania. Design/methodology/approach A cross-sectional design was adopted from which data were collected from 146 respondents who were purposively chosen from several public procuring entities located at Dodoma city in the United Republic of Tanzania by using a survey structured questionnaire and analysed through a binary logistic regression model. Findings Findings revealed that procurement planning as a strategic function significantly influences the effectiveness of public procurement. The binary logistic regression model included the implementation of prepared procurement plans (p = 0.039), the involvement of users as stakeholders and important institutional actors in public procurement (p = 0.033), compliance to procurement laws and regulations when planning (p = 0.016) and adequacy of budget (p = 0.042) as predictors of procurement planning were tested to be significantly related to the effectiveness of public procurement. It was concluded that public procuring entities can achieve public procurement effectiveness through procurement planning. Social implications The implications and policy recommendations of the findings of this study would be useful to procurement practitioners mostly in public procuring entities. Originality/value This study contributes to adding knowledge to the existing body of knowledge on procurement planning as an imperative activity in public procurement in Tanzania.

scholarly journals A predictive model for early diagnosis of keratoconus

2020 ◽  
Author(s):  
GRACIA CASTRO-LUNA ◽  
ANTONIO PÉREZ-RUEDA
Keyword(s):  
Logistic Regression ◽  
Predictive Model ◽  
Corneal Thickness ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Bivariate Analysis ◽  
Diagnostic Model ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
Logistic Regression Models

Abstract Background: The diagnosis of keratoconus in the early stages of the disease is necessary to initiate an early treatment of keratoconus. Furthermore to avoid possible refractive surgery that could produce ectasias. This study aims to describe the topographic, pachymetric and aberrometry characteristics in patients with keratoconus, subclinical keratoconus and normal corneas. Additionally to propose a diagnostic model of subclinical keratoconus based in binary logistic regression models Methods: The design was a cross-sectional study. It included 205 eyes from 205 patients distributed in 82 normal corneas, 40 subclinical keratoconus and 83 established keratoconus The rotary Scheimpflug camera (Pentacam® type) analyzed the topographic, pachymetric and aberrometry variables. It performed a descriptive and bivariate analysis of the recorded data. A diagnostic and predictive model of subclinical keratoconus was calculated with the statistically significant variables Results: Statistically significant differences were observed when comparing normal corneas with subclinical keratoconus/ in variables of the vertical asymmetry to 90º and the central corneal thickness. The binary logistic regression model included the minimal corneal thickness, the anterior coma to 90º and posterior coma to 90º. The model properly diagnosed 92% of cases Conclusions: The differential diagnosis between normal cases and subclinical keratoconus depends on the mínimum corneal thickness, the anterior coma to 90º and the posterior coma to 90º.

scholarly journals Nexus between Poverty and Child Labor: A Case Study in Narayanganj Area of Bangladesh Using Binary Logistic Regression

2021 ◽  
Vol 7 (11) ◽  
pp. 194
Author(s):  
Shamima Akter ◽  
Wasim Akram
Keyword(s):  
Logistic Regression ◽  
Child Labor ◽  
Odds Ratio ◽  
Group Discussion ◽  
Binary Logistic Regression ◽  
Sampling Technique ◽  
Drop Out ◽  
Poor People ◽  
Binary Logistic Regression Model ◽  
Household Heads

<p>The purpose of the study is to see how poverty influences child labor. To carry out the study, moderate poor people have been considered as respondents. Kalibazar and Langalband regions of Narayanganj district have been selected. Random sampling technique and Focused Group Discussion with children have been taken to conduct the study. Data has been collected from 50 Household Heads and 50 Children (male and female). For economic analysis, the Binary Logistic Regression model has been undertaken to see the relationship between poverty and child labor.  The analysis shows that the odds ratio indicates that drop-out children from school are 11.34 times more likely to go for taking the occupation of child labor due to poverty (major cause) than those children who have been dropped out due to other reasons (reference category). The study also shows that the families having no loan are 0.444 times less likely to go for child labor due to major causes (poverty) than that of the families having a loan. Moreover, the odds ratio corresponding to the children who use their income to help their families is 3.26. It means that the children who use their income for family purposes go 3.26 times more likely to take the occupation of child labor due to a major cause (poverty) than those children who do not use their income for family purposes. At the same time, the children who use their income for treatment purposes go 1.45 times more likely to take the occupation of child labor due to poverty (a major cause) than those children who do not use their income for treatment purposes.</p>

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHI PANGSA PENGELUARAN PANGAN RUMAH TANGGA PETANI PADI-SAPI DI KECAMATAN PANGKALAN KABUPATEN KARAWANG

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Ugih Sugiarto ◽  
Tuti Karyani ◽  
Dini Rochdiani
Keyword(s):  
Logistic Regression ◽  
Food Security ◽  
Random Sampling ◽  
Quantitative Research ◽  
Binary Logistic Regression ◽  
Sampling Technique ◽  
Household Food Security ◽  
Stratified Random Sampling ◽  
Rice Farmers ◽  
Food Expenditure

ABSTRAKPenelitian ini bertujuan untuk mengidentifikasi status ketahanan pangan rumah tangga petani padi serta faktor-faktor yang mempengaruhi pangsa pengeluaran pangan di Kecamatan Pangkalan Kabupaten Karawang. Penelitian ini merupakan penelitian kuantitatif dengan teknik survey. Teknik pengambilan sampling dalam penelitian ini dilakukan dengan cara stratified random sampling. Dengan mengidentifikasi daerah dan petani yang memiliki potensi pertanian padi dan usaha ternak sapi maka terpilihlah Desa Tamanmekar, Desa Tamansari, dan Desa Medalsari di Kecamatan Pangkalan yang memiliki jumlah petani padi-sapi terbanyak menurut data survei awal sebelum penelitian. Dari populasi 146 petani diambil sampel yang sebanyak 107 responden petani padi dan padi-sapi. Analisis data menggunakan analisis pangsa pengeluaran pangan dan regresi logistik biner untuk menganalisis faktor-faktor yang mempengaruhi ketahanan pangan rumah tangga petani. Hasil perhitungan pangsa pengeluaran pangan dengan status tahan pangan sebanyak 69 petani, sedangkan jumlah rumah tangga dengan status tidak tahan pangan sebanyak 38 petani. Hasil regresi logistik biner menunjukkan bahwa faktor jumlah anggota keluarga, usia kepala keluarga, dan jenis usahatani berpengaruh terhadap ketahanan pangan rumah tangga petani dengan nilai signifikansi α = 5% dan α = 10%.Kata kunci : pangsa pengeluaran pangan, regresi logistik binerABSTRACT This study aims to identify the status of food security of rice farmers' households and the factors that influence share of food expenditure in Pangkalan District, Karawang Regency. This research is a quantitative research with survey techniques. The sampling technique in this study was carried out by stratified random sampling. By identifying areas and farmers have potential rice farming and cattle then elected Tamanmekar village, Tamansari village, and Medalsari village has several rice-cattle farmers according to preliminary survey prior to the study. From the population of 146 farmers, sample of 107 respondents from rice farmers and rice-cattle farmers was taken.  Data analysis used an analysis of share of food expenditure and binary logistic regression to analyze the factors that influence farm household food security. The share of food expenditure calculation results with food secure status is 69 farmers, while the number of households with food insecure status is 38 farmers. The binary logistic regression results indicate that the number of family members, the age of the family head, and the type of farming affect the food security of farm households with a significance value of α = 5% and α = 10%.Keywords: share of food expenditure, binary logistic regression.

scholarly journals ANALISIS FAKTOR YANG MEMPENGARUHI STATUS PENERIMAAN BERAS KELUARGA MISKIN MENGGUNAKAN REGRESI LOGISTIK BINER DI KECAMATAN LANGSA BARAT

2020 ◽  
Vol 14 (2) ◽  
pp. 181-192
Author(s):  
Amelia Amelia ◽  
Fitra Mulyani ◽  
Ulya Nabilla
Keyword(s):  
Logistic Regression ◽  
Economic Status ◽  
Secondary Data ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Binary Logistic Regression Analysis ◽  
Binary Logistic Regression Model ◽  
The Status ◽  
Rice Consumption ◽  
The Government

Poverty is an inability to meet basic needs measured by expenditure, including rice consumption. Based on data from the Central Statistics Agency (BPS), as much as 95% of Indonesia's population consumes rice as the main food, with an average rice consumption of 102 kg/person/ year (BPS, 2013). Furthermore, BPS stated that almost 1/4 of them or around 25.95 million people were included in the category of the poor population as of March 2018. So the government made a policy to tackle the problem through the program of giving poor family rice (Raskin), namely subsidized rice assistance to households poor. However, in the implementation of the Raskin program, there was a deviation of around 40% of Indonesia's population with a middle-upper social-economic status receiving Raskin and 12.5% ​​of the population with a socio-economic status upon receiving Raskin. Therefore this study aims to analyze the significant factors that affect the status of rice in poor families using binary logistic regression analysis. The location of the study was conducted in the District of West Langsa because the district was one of the districts receiving the most Raskin in the City of Langsa. The data used in this study are primary data and secondary data. The results of the analysis show that the factors that influence Raskin's acceptance status are the level of education, type of floor, type of fuel, expenditure for food, and frequency of purchasing new clothes. The binary logistic regression model obtained is

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