How Does the Rohingya Influx Influence the Residential Satisfaction and Mobility Intentions of the Host Communities in Bangladesh?

This study investigates the residential satisfaction and future relocation intention of the host communities neighbouring Rohingya migrants in Bangladesh. An empirical study of 151 households was conducted in Ukhiya and Ramu Upazila of Cox’s Bazar district in late 2019. The residential satisfaction component includes the social environment (SE), neighbourhood environment (NE), and public services and facilities (PS&F). It shows that, due to the Rohingya influx, the residential satisfaction level of the Ukhiya host communities declined by 30.17%. Besides, to determine factors that impact on the intention to migrate, the ordinal logistic regression model has been run. A larger distance between the household and the Rohingya camps, longer duration of residence in the community, and a higher number of children in the family negatively influence the mobility intention of the host communities. Furthermore, the Hindu residents in the host communities have higher propensity to relocate. These findings demand that policies and programmes should be planned in a way that enables the host communities to stay in place despite the Rohingya influx.

Total Cerebral Small Vessel Disease Score and Anthropometric Indices: A Population-Based Study in Older Adults of Amerindian Ancestry

A total of 590 older adults of Amerindian ancestry living in rural Ecuador received anthropometric measurements and a brain magnetic resonance imaging to estimate the total cerebral small vessel disease (cSVD) score. A fully adjusted ordinal logistic regression model, with categories of the total cSVD score as the dependent variable, disclosed significant associations between the waist circumference, the waist-to-hip, and the waist-to-height ratios – but not the body mass index (BMI) – and the cSVD burden. Indices of abdominal obesity may better correlate with severity of cSVD than the BMI in Amerindians. Phenotypic characteristics of this population may account for these results.

Severe stunting and its associated factors among children aged 6–59 months in Ethiopia; multilevel ordinal logistic regression model

Background In Ethiopia, stunting is the most common form of undernutriton. Identifying the determinants of severe stunting among children is crucial for public health interventions to improve child health. Therefore, this study aimed to identify the determinants of severe stunting among under-five children in Ethiopia. Methods A community-based cross-sectional study design was employed. A two stage stratified cluster sampling technique was used. A multilevel ordinal logistic regression model was fitted to identify independent determinants. Adjusted odds ratio (AOR) and median odds ratio (MOR) with its 95% confidence interval at p-value< 0.05 were used to declare statistical significance. Results The result of this study showed that about 18% of the children were severely stunted. Being male increased the severity of stunting in children by 26% adjusted odds ratio (AOR): 1.26 (95% CI: 1.09–1.46), compared to female sex; over-weight mothers increased the severity of stunting in their children AOR: 3.43 (95% CI: 2.21–5.33) compared to normal BMI mothers; and children from middle, poorer, and poorest wealth index households were 1.84 (95% CI:1.27–2.67), 2.13 (95% CI, CI:1.45–3.14) and 2.52 (95% CI,1.72–3.68). In contrast, severe stunting was reduced by 62% (AOR: 0.38, 95% CI: 0.20–0.74) and 48% (AOR = 0.52, 95% CI: 0.37–0.72) in children of educated mothers compared to children of uneducated mothers and children of underweight mothers compared with those children of normal BMI mothers respectively. For each one-unit increase in maternal height, there is a 5% significant reduction in the child’s odds of being severely stunted. After controlling for other factors, the effect of predictors on the likelihood of stunting in high risk clusters increased by a median odds ratio (MOR) of 1.83 (95% CI: 1.69–2.00). Conclusions The magnitude of severe childhood stunting was still high with regional variation in Ethiopia. Child age, sex, maternal height, age, education and household wealth index as well as administrative regions were significantly associated factors with severe stunting. Significant interventions shall be implemented at the individual, household and community levels in order to reduce the problem.

Factors impacting on adoption of international education standards: an empirical study using factor analysis

The aim of this study is to determine the factors affecting International Education Standards (IESs) adoption, by using an econometric approach based on a sample of 64 Countries. To do that, data about legal, political, economic and cultural environment of each country was summarized using factorial analysis model. This model extracts four common factors from original data that’s likely to affect IESs adoption, those factors are legal, political and economic governance, opening of accounting profession to the outside world, initiative degree of the society, and accepting change and differences. The study concludes, using an ordinal logistic regression model (logit model), that legal, political and economic governance, opening of accounting profession to the outside world, initiative degree of the society has a significant effect on IESs adoption, while accepting change and differences have no effect.

Acetazolamide-Associated Acute Kidney Injury in Critically Ill Pediatric Patients

OBJECTIVE Our objective was to determine the incidence and risk factors for intravenous acetazolamide-associated acute kidney injury (AKI). METHODS We utilized a retrospective cohort study including patients &lt;19 years of age initiated on intravenous acetazolamide while admitted to an ICU. Data collection included patient demographics, clinical variables, acetazolamide dosing, and serum creatinine (SCr) values. Incidence of AKI was assessed per Kidney Disease Improving Global Outcomes criteria. Descriptive statistical analysis and ordinal logistic regression analysis were performed to determine the incidence of AKI and variables associated with AKI. RESULTS A total of 868 patients met study criteria (male 55.8%, median age 0.66 years [IQR 0.19, 3.0 years]). Intravenous acetazolamide was administered at 5.1 ± 2.8 mg/kg/dose for a median of 4 doses (IQR 2, 6). Median baseline SCr was 0.28 mg/dL (IQR 0.22, 0.37), corresponding to a creatinine clearance of 115 ± 55 mL/min/1.73 m2. Acute kidney injury occurred in 26.8% (n = 233) of patients (stage I = 20.1%, stage II = 3.7%, stage III 3.1%), and no patients received renal replacement therapy. An ordinal logistic regression model identified an increased odds of AKI with cyclosporine, ethacrynic acid, and piperacillin-tazobactam administration. CONCLUSIONS Acute kidney injury occurs frequently in critically ill pediatric patients receiving intravenous acetazolamide.

Financial Factors and Corporate Governance Affecting the Sukuk Rating

The development of corporate Sukuk in recent years has continued to show a significant increase in both the number of Sukuk issuers and investors of Sukuk instruments. This study aims to identify the determinants of financial factors and corporate governance factors on the Sukuk rating. The type of data used in this research is quantitative data from secondary sources. The purposive sampling method is used with criteria specifically non-financial companies issuing Sukuk circulating on the IDX and Sukuk ratings were issued by PT Pefindo. The data consist of 93 Sukuk issuances from 2010 to 2019. Ordinal logistic regression model with SPSS version 26 is then used to ascertain the significant determinants of Sukuk rating. This study found that financial factors such as liquidity, leverage, profitability, and firm size affect the Sukuk rating. However, company growth does not affect the Sukuk rating because the growth of company assets is not followed by the growth of intangible assets such as the quality of human resources. Corporate governance factors that affect the Sukuk rating are managerial ownership and independent commissioners. Meanwhile, the audit committee does not affect the Sukuk rating because the number of audit committee members does not increase the company's performance.

Citizens-based Assessment of a Renovation Facilitating Policy in Urban Deteriorated Areas: An Ordinal Logistic Regression Model

Este estudio probó qué factores latentes existen que podrían afectar significativamente la evaluación de desempeño basada en los ciudadanos de la Oficina de Servicios de Renovación de Vecindarios (NRSO), que es una política que facilita la renovación urbana. Doscientos residentes de áreas urbanas deterioradas (UDA) en los vecindarios de Fallah y Yaftabad fueronentrevistados mediante cuestionarios. Para analizar los resultados de los cuestionarios, primero se empleó un Análisis Factorial Exploratorio (EFA) para identificar los factores subyacentes para la evaluación de la política mencionada y, posteriormente, la Regresión Logística Ordinal (OLR) para modelar los factores relacionados con la evaluación del desempeño.Los residentes que estaban más familiarizados con los planes y políticas evaluaron el desempeño de la oficina de renovación de manera más positiva. Además, si las NRSO quieren ser evaluadas como más efectivas en su intervención, necesitan potenciar el factor socioeconómico de su comunidad interactiva. El modelo OLR mostró que el sentido de lugar esotro factor subyacente significativo en este sentido. Sin embargo, la duración de la residencia a pesar de converger como factor en la EFA no mostró ningún impacto significativo según el modelo OLR.

Predicting the Safety Climate in Construction Sites of Saudi Arabia: A Bootstrapped Multiple Ordinal Logistic Regression Modeling Approach

Construction site accidents can be reduced through proactive steps using prediction models developed based on factors that influence the safety climate. In this study, a prediction model of the safety climate observed by construction site personnel in Saudi Arabia was developed, identifying a set of significant safety climate predictors. The model was built with data collected from 401 active construction site personnel using a bootstrapped multiple ordinal logistic regression model. The model revealed five significant predictors: supervision, guidance, and inspection; social security and health insurance; management’s commitment to safety; management’s safety justice; and coworker influence. The model can correctly predict 67% of the safety evaluations. The identified predictors present proof of the importance of safety support, commitment, and interaction in construction sites and their influence on the perceived evaluations of the safety climate by personnel. Moreover, the prediction model can help construction industry decision makers, safety policy designers, government agencies, and stakeholders to estimate the safety climate and assess the current situation. Furthermore, the model can help form a better understanding and determine areas of improvement, which can translate into higher safety performance levels.