Multilevel Analysis of Determinants of Stunting Prevalence among Children under Age Five in Ethiopia

Background: Stunting is a well-established child health indicator of chronic malnutrition related to environmental and socio-economic circumstances. In Ethiopia, childhood stunting is the most widely prevalent among children under the age of five years. Objective: To estimate the prevalence of stunting and model the determinants of stunting prevalence among children under age five in Ethiopia. Methods: Data were extracted from 2016 EDHS, and samples of 8487 children under age five were used in this study. The sample was selected using a two-stage stratified sampling process, and a multilevel logistic regression model was used to determine the factors associated with childhood stunting in Ethiopia. Results: This study revealed that the prevalence of stunting among children under age five years in Ethiopia was around 39.39%. The multilevel binary logistic regression analysis was performed to investigate the variation of predictor variables of stunting prevalence among children under age five. Accordingly, it has been identified that the ages of the child above 12 months, male gender, children from poor households, and no mother education significantly affect the prevalence of stunting in Ethiopia. It is found that variances related to the random term were statistically significant, implying a variation in the prevalence of stunting across Ethiopia's regional states. Conclusion: The current study confirmed that the prevalence of stunting among children under aged five years in Ethiopia was a severe public health problem. Therefore, governmental or stakeholders should pay attention to all the significant factors mentioned in this study's analysis.

Download Full-text

Unplanned pregnancy among married women: an exploratory study in a rural area of Bengal

International Journal of Community Medicine and Public Health ◽

10.18203/2394-6040.ijcmph20174484 ◽

2017 ◽

Vol 4 (11) ◽

pp. 4101

Author(s):

Manika Pal ◽

Lina Bandyopadhyay ◽

Aparajita Dasgupta

Keyword(s):

Logistic Regression ◽

Rural Area ◽

Unplanned Pregnancy ◽

Public Health Problem ◽

Binary Logistic Regression ◽

Cross Sectional Study ◽

Married Women ◽

Binary Logistic Regression Analysis ◽

Major Public Health Problem ◽

Cross Sectional

Background: Globally unplanned pregnancy has emerged as a major public health problem with its impact on demography and economy. Despite being the first country to initiate a nationwide family planning program, contraceptives access and utilization are low in India. As per a study conducted in 35 low- and middle-income countries, India contributed the largest number of undesired pregnancy. Our current study was aimed at determining the proportion of unplanned pregnancy and examining its predictors among currently married women aged 15-35 years, residing in a rural area. Methods: A facility based, observational, cross-sectional study was conducted in a rural area of Bengal. 158 participants were selected by purposive sampling and face to face interviews were conducted using structured schedule ensuring confidentiality. Statistically data were summarized with descriptive statistics and adjusted with binary logistic regression analysis in SPSS (version 16). Results: The proportion of unplanned pregnancy was found to be 28.5%. On multivariable logistic regression, it was observed that there was significant association between unplanned pregnancy and low SE status AOR (CI) 2.523 (1.074-5.926), lack of women’s empowerment AOR (CI) 2.971 (1.198-7.367), husbands’ lower level of education AOR (CI) 2.673 (1.041-6.866), and no contraception or traditional method of contraception AOR (CI) 2.391 (1.104-5.180). Conclusions: The study revealed alarmingly high proportion of unplanned pregnancy. In addition to the existing strategies of the national program, emphasis should be on IEC activities. All efforts should be made to educate women on hazards of unsafe abortion and unplanned pregnancy.

Download Full-text

Predicting Burn Mortality Using a Simple Novel Prediction Model

Indian Journal of Plastic Surgery ◽

10.1055/s-0040-1721867 ◽

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.

Download Full-text

MO376CLINICAL OUTCOMES OF ACUTE KIDNEY INJURY FOLLOWING SNAKE BITE INJURIES

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfab082.0030 ◽

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.

Download Full-text

Abstract 3734: Presurgical fMRI and Morbidity Outcomes in Patients with Vascular Lesions

Stroke ◽

10.1161/str.43.suppl_1.a3734 ◽

2012 ◽

Vol 43 (suppl_1) ◽

Author(s):

Andrew C Radtke ◽

Joshua Pankratz ◽

Ryan Holdsworth ◽

Dovile Baniulis ◽

Nicole Kornder ◽

...

Keyword(s):

Logistic Regression ◽

Preoperative Planning ◽

Binary Logistic Regression ◽

Vascular Lesion ◽

Vascular Lesions ◽

Motor Deficits ◽

Binary Logistic Regression Analysis ◽

Language Mapping ◽

Motor Mapping ◽

The Relationship

Background fMRI is being increasingly used as an adjunct imaging technique for preoperative planning for patients with various brain lesions. The proximity of the lesion to eloquent cortex is a major factor in guiding surgical planning. Our group has previously reported significant association between the distance between brain tumor periphery and area of fMRI activation (Lesion-Activation Distance; LAD) and morbidity and mortality outcomes. This study investigated the relationship between vascular lesion LAD and morbidity. Methods This study was a retrospective analysis of data from patients with vascular lesions [arteriovenous malformations (AVMs) (n=49), and cavernomas (n=57)], who had received fMRI as part of their preoperative planning. The preoperative fMRI included motor mapping (n=87) and/or language mapping (n=102). The fMRI paradigms were chosen based on observed preoperative weakness (aphasia, paresis) and anticipated functional areas of the brain that may be affected by treatment. Results Multiple logistic regression analyses showed that a model that combines Age and Language LAD was a significant predictor of postoperative deficits (p= 0.04). Broca’s LAD(1-2 cm) X Age was a significant predictor of postoperative deficits (change in odds ratio (OR) =0.82, CI:0.68-0.98). The relationship between Brocas’s LAD and postoperative aphasia and Broca’s LAD and pre and postoperative aphasia trended towards significance (p = .08 and p =.07 respectively). Wernicke’s LAD, independently or combined with Age, was not a significant predictor of postoperative deficits. Binary logistic regression analysis for SMC LAD and postop deficits did not reach significance (p =.10). There were no significant differences in postoperative language or motor deficits as a function of gender or handedness. Conclusions These results suggest that both age and the proximity of a vascular lesion to language LAD are factors that can help predict postoperative outcomes, especially for Broca’s LAD. The lack of similar results when investigating the relationship between Wernicke’s LAD and postoperative deficits suggests potential brain reorganization and/or robustness of this brain region. These results have implications for the potential use of fMRI as a presurgical tool for language mapping in patients with vascular lesions.

Download Full-text

Predicting organizational performance from motivation in Oromia Seed Enterprise Bale branch

Humanities and Social Sciences Communications ◽

10.1057/s41599-021-00742-9 ◽

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.

Download Full-text

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

10.21203/rs.3.rs-63438/v3 ◽

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.

Download Full-text

PENGARUH KEBUTUHAN BERPRESTASI DAN KARAKTERISTIK PERSONAL TERHADAP KINERJA USAHA WIRAUSAHA WANITA (Survey pada Petani Tanaman Obat Keluarga (TOGA) di Kecamatan Jumantono Kabupaten Karanganyar)

RESEARCH FAIR UNISRI ◽

10.33061/rsfu.v4i1.3396 ◽

2020 ◽

Vol 4 (1) ◽

Author(s):

Setyaningsih SU ◽

Edi Wibowo

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Women Entrepreneurs ◽

Business Performance ◽

Binary Logistic Regression ◽

Personal Characteristics ◽

Binary Logistic Regression Analysis ◽

Entrepreneurship Training ◽

Analysis Technique ◽

Business Experience

This study aims to analyze the effect of the needs of achievement and personal characteristics (education, age, experience, training) on business performance. This research is census research, using 63 respondents of women entrepreneurs to Toga farmers in Jumantono District, Karanganyar Regency. Data analysis technique using binary logistic regression analysis. The conclusions from the results of this study indicate that the needs of achievement and personal characteristics of business experience have a significant effect on business performance, while the variables of education, age, and entrepreneurship training have no significant effect on business performance. Based on the results of this study, the odds/probabilities of the performance of women's entrepreneurial business in Toga farmers in Jumantono District, Karanganyar Regency can be predicted by the needs of achievement and business experience. The implication of this finding is that to achieve high business performance, Toga farmers in Jumantono District, Karanganyar Regency need to increase their needs for achievement and business experience.Keywords: needs of achievement, education, age, experience, training, business performance

Download Full-text

Determining factors in MSMEs success: An empirical study in Mexico

Small Business International Review ◽

10.26784/sbir.v6i1.384 ◽

2022 ◽

Vol 6 (1) ◽

pp. e384

Author(s):

Rubén Molina-Sánchez ◽

Domingo García-Pérez-de-Lema ◽

Alejandra López-Salazar ◽

Roberto Godínez-López

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Empirical Study ◽

Small And Medium Enterprises ◽

Binary Logistic Regression ◽

Binary Logistic Regression Analysis ◽

Technology And Innovation ◽

Determining Factors ◽

Quality Technology ◽

Medium Enterprises

This work empirically analyzes the competitive factors that help make micro, small, and medium enterprises (MSMEs) successful. To do this, an empirical study with a sample of 614 companies in Guanajuato, Mexico, has been carried out. The results of the binary logistic regression analysis show that quality, technology, and innovation are the main variables that determine a company’s success. These findings could provide guidelines to help MSMEs improve their competitiveness, and they could help public administrations better support MSME growth.

Download Full-text

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

Journal of Intelligent Computing & Health Informatics ◽

10.26714/jichi.v1i1.5381 ◽

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.

Download Full-text

Does Physical Fitness Predict Future Karate Success? A Study in Young Female Karatekas

International Journal of Sports Physiology and Performance ◽

10.1123/ijspp.2019-0435 ◽

2020 ◽

Vol 15 (6) ◽

pp. 868-873

Author(s):

Óscar Martínez de Quel ◽

Ignacio Ara ◽

Mikel Izquierdo ◽

Carlos Ayán

Keyword(s):

Logistic Regression ◽

Physical Fitness ◽

Muscle Power ◽

Binary Logistic Regression ◽

Young Female ◽

Binary Logistic Regression Analysis ◽

Discriminative Ability ◽

Logistic Regression Models ◽

Elite Group ◽

Competitive Success

Objective: To assess the discriminative ability of several fitness dimensions and anthropometric attributes for forecasting competitive success in female karate athletes. Methods: Fitness and anthropometric data from 98 female junior karatekas obtained during the training camps of the Spanish National Karate Federation between 1999 and 2012 were used. Binary logistic-regression models were built to ascertain whether the set of fitness and anthropometric variables could predict future sporting-performance levels. For this purpose, participants were classified as elite (medalist in World or European Championships in the senior category) or subelite (at least a medalist in Spanish National Championships in cadet or junior but not included in the elite group), according to the results achieved up to 2019. Results: Participants who were subsequently classified as elite karatekas showed significant differences in agility, upper- and lower-body muscle power, and general fitness in comparison with those who were classified as subelite in the senior category. A total of 57 junior female karatekas who were subsequently classified as elite (7) or subelite (50) were included in the binary logistic-regression analysis. Resultant models showed significant capacity to predict karate performance. Conclusions: Assessing physical fitness in junior categories can be a useful resource to determine future karate success. Coaches in this sport should pay special attention to the levels of muscle power and agility shown by their athletes, as both fitness dimensions could be indicators of future sportive success.

Download Full-text