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

2021 ◽  
Author(s):  
Bangkim Biswas ◽  
Bishawjit Mallick ◽  
Nasif Ahsan ◽  
Rupkatha Priodarshini
Keyword(s):  
Logistic Regression ◽  
Empirical Study ◽  
Logistic Regression Model ◽  
Residential Satisfaction ◽  
Satisfaction Level ◽  
Neighbourhood Environment ◽  
Number Of Children ◽  
The Social ◽  
The Family ◽  
Ordinal Logistic Regression Model

AbstractThis 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.

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

2021 ◽  
Vol 47 (1) ◽  
Author(s):  
Amare Muche ◽  
Reta Dewau
Keyword(s):  
Logistic Regression ◽  
Odds Ratio ◽  
Associated Factors ◽  
Logistic Regression Model ◽  
Adjusted Odds Ratio ◽  
Wealth Index ◽  
Maternal Height ◽  
Severe Stunting ◽  
Mothers And Children ◽  
Ordinal Logistic Regression Model

Abstract 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.

scholarly journals Portrait of a Russian Homeschooler’s Family: Results of an Online Poll

Discourse ◽  
2021 ◽  
Vol 6 (6) ◽  
pp. 87-98
Author(s):  
M. N. Yashina
Keyword(s):  
Online Survey ◽  
Primary School Children ◽  
Family Education ◽  
Data Set ◽  
Number Of Children ◽  
Random Samples ◽  
The Social ◽  
The Family ◽  
Total Data ◽  
High Level

Introduction. The practice of obtaining family education has become a fashionable trend in our country in recent years. Despite the growing popularity among the population, we have not yet received enough scientific understanding of this form of training. The purpose of the article is to describe the social portrait of families who have chosen a family form of education for a child. The scientific novelty of the work is due to the empirical data presented in it, which have a dynamic nature of observing the studied object.Methodology and sources. The methodological basis for the study was the conflict approach and the principles of a radical humanistic approach to education in the interpretation of I. Illich. The empirical basis of the study is the results of three surveys of parents o f c hildren f rom 6 t o 1 8 y ears o ld w ho are o n f amily e ducation. S urveys w ere implemented from 2016 to 2020, according to the same methodology and tools. To collect data, a questionnaire for an online survey was developed, which was distributed on social networks, mainly in VKontakte communities dedicated to family education. The total data set includes 443 respondents.Results and discussion. According to surveys, children in family education grow up in full families, where the parent's ode has a high level of education, the mother, as a rule, does not work or has the possibility of a free schedule and is a teacher for the child. The main source of income in the family is the father. The total income of the family, which averages from 40 to 60 thousand rubles per month. In the family, most often two children, one of whom is in family education. Family education is mainly provided with primary school children.Conclusion. The peculiarity of studying family education not only in our country, but also in the world is the lack of accurate statistics on the number of children of homeschoolers. In this regard, only non-random samples are possible in the implementation. The portrait of Russian homeschoolers differs from American ones, in particular in the level at which family education is implemented, the place of residence of families, and their income.

scholarly journals Exploring Medical Expenditure Clustering and the Determinants of High-Cost Populations from the Family Perspective: A Population-Based Retrospective Study from Rural China

2018 ◽  
Vol 15 (12) ◽  
pp. 2673
Author(s):  
Shan Lu ◽  
Yan Zhang ◽  
Yadong Niu ◽  
Liang Zhang
Keyword(s):  
Logistic Regression ◽  
Health Insurance ◽  
Gini Coefficient ◽  
Logistic Regression Model ◽  
Rural China ◽  
Healthcare Spending ◽  
Medical Expenditure ◽  
Traffic Conditions ◽  
Family Perspective ◽  
The Family

The costliest 5% of the population (identified as the “high-cost” population) accounts for 50% of healthcare spending. Understanding the high-cost population in rural China from the family perspective is essential for health insurers, governments, and families. Using the health insurance database, we tallied 202,482 families that generated medical expenditure in 2014. The Lorentz curve and the Gini coefficient were adopted to describe the medical expenditure clustering, and a logistic regression model was used to identify the determinants of high-cost families. Household medical expenditure showed an extremely uneven distribution, with a Gini coefficient of 0.76. High-cost families spent 54.0% of the total expenditure. The values for family size, average age, and distance from and arrival time to the county hospital of high-cost families were 4.05, 43.18 years, 29.67 km, and 45.09 min, respectively, which differed from the values of the remaining families (3.68, 42.46 years, 30.47 km, and 46.29 min, respectively). More high-cost families live in towns with low-capacity township hospitals and better traffic conditions than the remaining families (28.98% vs. 12.99%, and 71.19% vs. 69.6%, respectively). The logistic regression model indicated that family size, average age, children, time to county hospital, capacity of township hospital, traffic conditions, economic status, healthcare utilizations, and the utilization level were associated with high household medical expenditure. Primary care and health insurance policy should be improved to guide the behaviors of rural residents, reduce their economic burden, and minimize healthcare spending.

Quality Classification Model of Material Products Based on Ordinal Logistic Regression

2012 ◽  
Vol 460 ◽  
pp. 393-397 ◽  
Author(s):  
Peng Fei Mu ◽  
Dong Ling Zhang ◽  
Xiao Mei Xu ◽  
Yang Liu
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Quality Evaluation ◽  
Ordinal Logistic Regression ◽  
Processing Method ◽  
Classification Model ◽  
Classification Result ◽  
Quality Classification ◽  
Ordinal Logistic Regression Model

It presents a proposed method for the development of quality evaluation and classification for material products, and shows the application of the ordinal logistic regression model and its advantages. It involved several steps: applying the linguistic information processing method, building the ordinal logistic regression model, differentiating and analyzing the quality evaluation to reach the quality classification result

An Empirical Study on Identification of False Accounting Information of Listed Companies -Based on the Comparison between Logistic Regression Model and Multiple Eigenvalues Detection Model

2011 ◽  
Vol 268-270 ◽  
pp. 753-758
Author(s):  
Ai Hao Guan
Keyword(s):  
Logistic Regression ◽  
Empirical Study ◽  
Regression Model ◽  
Empirical Analysis ◽  
Logistic Regression Model ◽  
Accounting Information ◽  
Listed Companies ◽  
Detection Model ◽  
Multiple Eigenvalues

In this study, multiple eigenvalues detection model has been put forward and empirical analysis and comparison between logistic regression model and multiple eigenvalues detection model has been conducted in the same sample on the basis of overall data. The results have showed the characteristics of accuracy, stability or extensive adaptability of multiple eigenvalues detection model in detecting false accounting information.

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