Effects Of Socioeconomic Variables Research Articles

Influence of Sociodemographic Profile on Interactions Between Human Populations and Fauna in the Semi-Arid Region of Northeast Brazil and Its Relationship with Conservation

Background: The relationship between human populations and wild animals dates back across centuries of interactions, enabling the construction of belief systems in communities. The socioecological perspective allows us to understand the interactions between the social and ecological dimensions of a population and nature. Methods: In this context, 133 residents of a rural community were interviewed to assess their knowledge and use of animals. We sought to evaluate the following: (i) animal species used by community residents, (ii) types of use and (iii) the effects of socioeconomic variables on different uses of vertebrate animal taxa. Results: The fauna cited were represented by 82 ethnospecies distributed in 48 families; it was not possible to identify nine ethnospecies and two were identified only at the genus level (Columbina sp. and Turdus sp.). Among the identified species, birds presented the greatest taxonomic richness (n = 34/41.0%), followed by mammals (n = 22/27.0%) and reptiles (n = 15/18.0%). Through generalized linear models, we identified which socioeconomic variables influenced the knowledge and use of wildlife resources. Furthermore, the influence of socioeconomic variables varied between taxa and use categories. Conclusions: The influence of socioeconomic variables may vary according to the taxonomic group, as well as the type of cultural domain, favoring the increase or decrease in the use of a resource.

Effect of socio-economic variables on unemployment in South Africa: A Vector Error Correction Model

Effect of socio-economic variables on unemployment in South Africa: A Vector Error Correction Model

Research on social and economic factors influencing regional mortality patterns in China

Regional population mortality correlates with regional socioeconomic development. This study aimed to identify the key socioeconomic factors influencing mortality patterns in Chinese provinces. Using data from the Seventh Population Census, we analyzed mortality patterns by gender and urban‒rural division in 31 provinces. Using a functional regression model, we assessed the influence of fourteen indicators on mortality patterns. Main findings: (1) China shows notable gender and urban‒rural mortality variations across age groups. Males generally have higher mortality than females, and rural areas experience elevated mortality rates compared to urban areas. Mortality in individuals younger than 40 years is influenced mainly by urban‒rural factors, with gender becoming more noticeable in the 40–84 age group. (2) The substantial marginal impact of socioeconomic factors on mortality patterns generally becomes evident after the age of 45, with less pronounced differences in their impact on early-life mortality patterns. (3) Various factors have age-specific impacts on mortality. Education has a negative effect on mortality in individuals aged 0–29, extending to those aged 30–59 and diminishing in older age groups. Urbanization positively influences the probability of death in individuals aged 45–54 years, while the impact of traffic accidents increases with age. Among elderly people, the effect of socioeconomic variables is smaller, highlighting the intricate and heterogeneous nature of these influences and acknowledging certain limitations.

Regional variations in the management of primary hyperparathyroidism in Sweden: population-based case-control study.

Substantial disparities in the utilization of parathyroidectomy for primary hyperparathyroidism have been reported. This study aimed to analyse regional variations in parathyroidectomy incidence with respect to the patient's disease burden and socioeconomic status. A population-based case-control study included all patients with primary hyperparathyroidism who underwent parathyroidectomy in Sweden between 2008 and 2017 and 10 matched controls. Data on demographic and socioeconomic variables, co-morbidities and drug prescriptions were collected from relevant national registers. Conditional logistic regression was used to analyse predictors of parathyroidectomy. A total of 8626 patients with primary hyperparathyroidism (77% women) underwent parathyroidectomy during the study interval. The annual incidence of parathyroidectomy was 9.0 per 100 000 persons. The annual age-adjusted regional incidences of parathyroidectomy varied between 3.3 and 16.9 operations per 100 000 inhabitants. Except for a small underrepresentation of patients with lower education, no effect of socioeconomic variables was observed. Compared with matched controls, the parathyroidectomy group had increased odds ratios of having developed classical symptoms of primary hyperparathyroidism and being prescribed medication against cardiovascular disorders and psychiatric illness at the time of parathyroidectomy. Increased risks of kidney stones and osteoporosis were observed 5 years before parathyroidectomy. Patients with primary hyperparathyroidism selected for parathyroidectomy from regions with a low incidence of operations had a higher prevalence of kidney stones, osteoporosis and hypertension, as well as larger adenomas and higher calcium levels at the time of parathyroidectomy compared with patients in high-incidence regions. The considerable variation in parathyroidectomy seems more likely associated with different clinical thresholds for detection of primary hyperparathyroidism and referral to surgery than socioeconomic disparities.

Effect of Socioeconomic Variables in Predicting Global Fire Ignition Occurrence

Fires are a pervasive feature of the terrestrial biosphere and contribute large carbon emissions within the earth system. Humans are responsible for the majority of fire ignitions. Physical and empirical models are used to estimate the future effects of fires on vegetation dynamics and the Earth’s system. However, there is no consensus on how human-caused fire ignitions should be represented in such models. This study aimed to identify which globally available predictors of human activity explain global fire ignitions as observed by satellites. We applied a random forest machine learning framework to state-of-the-art global climate, vegetation, and land cover datasets to establish a baseline against which influences of socioeconomic data (cropland fraction, gross domestic product (GDP), road density, livestock density, grazed lands) on fire ignition occurrence were evaluated. Our results showed that a baseline random forest without human predictors captured the spatial patterns of fire ignitions globally, with hotspots over Sub-Saharan Africa and South East Asia. Adding single human predictors to the baseline model revealed that human variables vary in their effects on fire ignitions and that of the variables considered GDP is the most vital driver of fire ignitions. A combined model with all human predictors showed that the human variables improve the ignition predictions in most regions of the world, with some regions exhibiting worse predictions than the baseline model. We concluded that an ensemble of human predictors can add value to physical and empirical models. There are complex relationships between the variables, as evidenced by the improvement in bias in the combined model compared to the individual models. Furthermore, the variables tested have complex relationships that random forests may struggle to disentangle. Further work is required to detangle the complex regional relationships between these variables. These variables, e.g., population density, are well documented to have substantial effects on fire at local and regional scales; we determined that these variables may provide more insight at more continental scales.

Pathways to Environmental Inequality: How Urban Traffic Noise Annoyance Varies across Socioeconomic Subgroups.

The article investigates how socioeconomic background affects noise annoyance caused by residential road traffic in urban areas. It is argued that the effects of socioeconomic variables (migration background, education, and income) on noise annoyance tend to be underestimated because these effects are mainly indirect. We specify three indirect pathways. (1) A "noise exposure path" assumes that less privileged households are exposed to a higher level of noise and therefore experience stronger annoyance. (2) A "housing attributes path" argues that less privileged households can shield themselves less effectively from noise due to unfavorable housing conditions and that this contributes to annoyance. (3) Conversely, an "environmental susceptibility path" proposes that less privileged people are less concerned about the environment and have a lower noise sensitivity, and that this reduces their noise annoyance. Our analyses rest on a study carried out in four European cities (Mainz and Hanover in Germany, Bern and Zurich in Switzerland), and the results support the empirical validity of the three indirect pathways.

Maternal exposure to intimate partner violence and uptake of maternal healthcare services in Ethiopia: Evidence from a national survey.

BackgroundWomen exposed to Intimate Partner Violence (IPV) often do not utilize maternal health care optimally both because of stigma and other social problems. The current study aims to explore an association between maternal healthcare seeking and violence exposure among Ethiopian women and to assess if educational attainment and wealth status moderate this association.MethodsThe analyses included 2836 (weighted) currently married women with one live birth. We focus on the five years preceding the 2016 Ethiopian Demographic and Health Survey (EDHS) who participate, in the domestic violence sub-study. Exposure was determined by maternal reports of physical, emotional, sexual IPV or any form of IPV. The utilization of antenatal care (ANC) and place of delivery were used as proxy outcome variables for uptake of skilled maternal healthcare utilization. Women’s education attainment and wealth status were selected as potential moderators, as they can enable women with psychological and financial resources to counteract impact of IPV. Multilevel logistic regression analyses were used to explore the association between spousal IPV and maternal health outcomes. Moderation effects by education and wealth status were tested, and the data stratified. Using statistical software Stata MP 16.1, the restricted maximum likelihood method, we obtained the model estimates.ResultsAbout 27.5% of the women who reported exposure to any form of IPV had a health facility delivery. While 23.4% and 22.4% visited four or more antenatal care services among mothers exposed to emotional IPV and sexual IPV, respectively. After adjusting for potential confounding factors, only the association between maternal exposure to emotional IPV and adequate use of ANC was statistically significant (OR = 0.73, (95% CI:0.56–0.95)). But we found no significant association between IPV and utilization of health facility delivery. Some moderation effects of education and wealth in the association between IPV and maternal healthcare service utilization outcome were found.ConclusionExposure to emotional IPV was associated with poor uptake of maternal health care service utilization for married Ethiopian women. While developing interventions to improve women’s maternal healthcare service use, it is crucial to consider the effects of socio-economic variables that moderate the association especially with the intersection of IPV.

Economics of catfish hatchery farmers and its contribution to household poverty alleviation in Nigeria

Abstract Fish and fisheries products are considered as one of the most substantial parts of Nigeria economy. Demand for these products is on the high side due to the rapid growth of human population, changes in lifestyle and eating habits. Fishery is thus serving as a source of employment, income generation and food security. This paper made use of the data gathered from the farm and household levels to analyse the economics of catfish hatchery farming and its contribution to household poverty alleviation in Oyo and Osun States, Southwest Nigeria, using profitability analyses, Foster-Greer-Thorbecke index and Tobit regression models. The findings indicate that fish hatchery farming is profitable, altough 43.1% of fish hatchery farmers interviewed were above the poverty line. Thus, the enterprise significantly (p < 0.05) reduced poverty in the study area. Furthermore, the effects of socioeconomic variables, gender, education level, and framing experience (p < 0.01); marital status and household size (p < 0.1); labour employed, hatchery units, quality of fish seed produced and membership of cooperative society (p < 0.05) indicating several interactions between poverty and the variables analysed. In conclusion, policy makers, government and non-governmental organisation should give the enterprise adequate attention and support as this could be adopted in lifting the country from poverty.

Paying for Sustainable Coffee in a Developing Country: Consumers’ Profile in Costa Rica

This article analyzes the willingness to pay of Costa Rican consumers for three environmental certifications in the coffee market, namely, Carbon Neutral, Fairtrade, and ISO 14001. A face-to-face survey was applied to 1191 Costa Rican inhabitants. The results show that Costa Rican consumers are willing to pay price premiums around 30% for all the considered environmental certifications. In addition, a Cragg’s hurdle model shows that household income, the level of education, and environmental or community activism increase the likelihood of consumers paying price premiums for environmental certifications, while men are less likely to pay than women. It was also found that the size of the price premiums that respondents are willing to pay are positively related to income, gender (female), and education, and negatively related to age. Once the effect of socioeconomic variables has been controlled for, we conclude that consumers are more willing to pay for the CN certification than for the other two. The results can be useful for participants in the coffee value chain; coffee producers can use environmental certifications both to enhance their participation in green markets, particularly in developing countries, and to improve their environmental performance.

A Re-Look at Poverty through the Lens of the Sustainable Development Goals in Ghana: Drivers and Policy Implications

ABSTRACT The study aims a re-examination of the poverty situation in Ghana using the Alkire-Foster multidimensional poverty framework. Using cross-sectional data from the Ghana Living Standards Survey (GLSS7) collected on 14,009 households, the results revealed that multidimensional poverty was higher for the Northern belt followed by the Middle belt and then the Coastal belt. The results further indicated that different socioeconomic and supply-side factors significantly affect multidimensional poverty in different locations of the country. The heterogeneous effect of socio-economic variables on multidimensional poverty across belts implies that designing “best-fits” policy strategy may be more effective than “one size fits all” policy strategy.

Relationship Analysis between Socio-Economic Variables and Job Performance of Accredited Social Health Activists in Maharashtra

National Rural Health Mission (NRHM) was launched in India in 2005. It brought a new concept of Accredited Social Health Activist (ASHA) in to the arena of health sector of India. Since it is a new concept it is imperative to study the effect of socio economic variables on the job performance of ASHAs. Coefficient of correlation was applied to carry out the relational analysis between socio-economic variables and job performance of ASHAs. It was seen that age was positively related with job performance whereas all other independent variables were negatively and significantly related with job performance.

Assessment of Regional Inequality in Female Work Participation: Measurement of Disparity and Determinants

The regional difference of complex Indian social structure and customs have a different impact on the nature of women’s work participation. The present study aims at unravelling the influence of social, cultural and economic forces in differentiating the level of women work participation in different eco-regions of West Bengal. The study is based purely on secondary sources and data have been collected from the Census of India. It is in the rural areas that the female work participation is directly linked to agriculture and allied activities and the study confines itself to an understanding of work participation of women only in the rural areas. The modern technological implication as a result of green revolution has a worse impact on women work participation particularly in the South Bengal plain and some parts of East Rarh Plain region. The high gender gap is noticed in Nadia district located in the middle part of South Bengal Plain causes very high withdrawn of female from there. Effect of socioeconomic variables, work participation of Scheduled component in main economic activity is also varied from the non-scheduled component. Non-scheduled worker participated more in non-agricultural sector rather than the scheduled counter parts. Subsequently, the low growth rate of female work participation represents a distress picture in work force structure which is a cause of worried also.

ANALISIS PENAWARAN BERAS PROVINSI SUMATERA UTARA

Financial inclusion programs in Asia began to intensify with focus on improving public access, especially those who have not yet enjoyed banking services. This makes financial inclusion one of the focuses of development in the financial sector in various countries, especially ASEAN, as a sound financial system can promote economic growth. This study aims to see the comparison of financial inclusion rates and see the effect of socio-economic variables on financial inclusion in ASEAN countries 2010-2015. In order to see the comparison of inclusion level of finance in each ASEAN country, the Index of Financial Inclusion (IFI) method was developed by Sarma (2008), while to examine the relationship between socio-economic variables to financial inclusion, the Ordinary Least Square (OLS) method was used estimation techniques in the Random Effects Model approach. The results show that in general, financial inclusion in ASEAN countries is mainly influenced by the dimension of a disorder. In addition, only per-capita GDP variables are not significant partially. While other variables, namely population over 15 years, unemployment rate, and the number of people in rural areas have a significant influence on index of financial inclusion

STUDI KOMPARASI TINGKAT INKLUSI KEUANGAN DI NEGARA ASEAN

Financial inclusion programs in Asia began to intensify with focus on improving public access, especially those who have not yet enjoyed banking services. This makes financial inclusion one of the focuses of development in the financial sector in various countries, especially ASEAN, as a sound financial system can promote economic growth. This study aims to see the comparison of financial nclusion rates and see the effect of socio-economic variables on financial inclusion in ASEAN countries 2010-2015. In order to see the comparison of nclusion level of finance in each ASEAN country, the Index of Financial Inclusion (IFI) method was developed by Sarma (2008), while to examine the relationshipbetween socio-economic variables to financial inclusion, the Ordinary Least quare (OLS) method was used estimation techniques in the Random Effects Model approach. The results show that in general, financial inclusion in ASEAN countries is mainly influenced by the dimension of a disorder. In addition, only per-capita GDP variables are not significant partially. While other variables, namely population over 15 years, unemployment rate, and the number of people n rural areas have a significant influence on index of financial inclusion.

Testing the Slippery Slope Framework in the Scope of Fiscal Sociology: A Study on the Classification of Income Levels

The purpose of the study is testing the hypothesis of the slippery slope framework which is "power of authorities and trust in authorities explain tax compliance". Trust in authorities and power of authorities are the two main variables of the theory and in this study, other social, cultural and economic variables that affect tax compliance are included to measure the effects of socio economic variables on tax compliance. In the study, the countries are classified according to their income levels and the data for the period 2007-2017 are analyzed by panel data method. As a result, research suggests that power of authorities and trust in authorities have the most significant impact on tax compliance and additionally the study finds evidence for the assumptions of the slippery slope framework.

Post-adoption of the candlenut agroforestry in Central Sulawesi, Indonesia

This research examined the contribution and effect of socio-economic variables toward the post-adoption of the candlenut agroforestry by using Path Analysis to provide the magnitude and significance of the hypothesized causal connection between the variables. The target population in this research includes all farmers of the agroforestry in Sigimpu and Bakubakulu villages, Palolo sub-district, Sigi District, Central Sulawesi Province of Indonesia (315 farmers) out of which a number of 164 farmers were selected by using Isaac and Michael Table. The path model shows the magnitude of the direct effects to post-adoption was 48.8% and the total effect was 66.5%. The variable of satisfaction on agroforestry inheritance was greater than the variable of satisfaction on income from the agroforestry, while the variable of a number of candlenut trees was the biggest contributor to the exogenous variables. The statistical evidence indicates not only the satisfaction variables affected the post-adoption, but also they sign an important of land tenure security for along term of the management.

Analysis of the main service quality dimensions that affect the satisfaction of users of the metropolitan rail public transit services in Algiers

The improvement in public transit is one of the basic and essential pillars to promote sustainable urban and metropolitan mobility everywhere. Algeria´s transportation system primarily relies on private vehicle, which causes innumerable problems such as congestion, emissions, traffic accidents, social inequalities, gender inequalities, and deterioration of the environment. Given that, the Algerian Government has recently carried out some transportation projects such as the Algiers metro and tramway service to promote collective public transportation in the country. Therefore, it becomes essential to provide public administrations and technicians with relevant information and efficient analytical tools to help enhance and develop this mass transit. In this line, the first Customer Satisfaction Survey was designed and implemented in November 2014 at the three railways transit services of Algiers: the light rail, the underground heavy rail (both started into operation in 2011) and the commuter rail. Thanks to this survey instrument, users’ profiles and travel patterns were found out. Moreover, an analytical framework based on a principal component analysis and an ordered probit model identified service quality dimensions and their impact on users’ overall satisfaction. In addition, the effect of socio-economic variables and travel patterns on the previously identified quality dimensions was obtained through multiple linear regression models. The results presented in this paper could help Algerian transport authorities towards elaborate specific proposals to increase transit ridership.

Spillovers Espaciais no desenvolvimento educacional dos municípios da Amazônia Clássica Brasileira

As políticas públicas educacionais aplicadas na Amazônia Clássica brasileira permitiram mudanças nas cidades da região de forma geral. Com isso, esse trabalho buscou verificar a existência de spillovers educacionais2 nos municípios da Amazônia Clássica do Brasil. Traçou como objetivos: identificar padrões espaciais de desenvolvimento educacional entre os municípios; b) detectar a existência de relacionamento espacial entre variáveis socioeconômicas e o crescimento do nível educacional e; c) evidenciar os efeitos diretos e indiretos de variáveis socioeconômicas sobre o crescimento do nível educacional dos municípios do norte brasileiro. Para isso, foi utilizada a metodologia de análise exploratória de dados espaciais e estimação de modelos espaciais, por meio da qual verificou-se que a taxa de pobreza, a taxa de analfabetismo e a taxa de trabalho infantil dos municípios impactam diretamente, mas de forma negativa no desenvolvimento das próprias cidades. Esses efeitos também transbordam para cidades vizinhas, confirmando a presença de spillovers educacionais e a necessidade de se pensar em políticas públicas educacionais de forma regionalizada visando à diminuição da pobreza, do trabalho infantil e a promoção da educação aos analfabetos.

Socioeconomic Driving Forces of International Migration

Abstract This paper makes a contribution to the literature on the driving forces of international migration. In contrast to the existing literature we consider the effect of socioeconomic variables (population dynamics, education and health, and openness) on migration flows. Especially the effects of openness of a society have not received much attention in the scientific debate.We use a panel data set of bilateral migration flows between 16 destination and 198 origin countries over the time span from 1980 to 2015. Most importantly, we find that our socioeconomic variables significantly affect the migration decision. Including socioeconomic variables does affect the size of the effects of the commonly used variables in the literature.Further, we find robust evidence that the socioeconomic variables at hand have non-linear effects on migration. For example, we find that the effect of human capital on migration follows an inverted U-shaped pattern.

Evolving Patterns of Child Sex Ratio in India

The article focuses on the geographical dimension of child sex ratio (CSR) and its evolving pattern for the last 40 years (1981–2011). Using a spatial statistical approach, it has been possible to identify homogeneous groups of objects in the study area. The study considered the role of spatial proximity of cultural diffusion which spreads rapidly regardless of the position of groups within a social structure. In doing so, the article tried to conceptualise the role of region in shaping its gender. The study explained declining CSR through the process of two mechanisms: one, the regional pull, that is, a region exerts a force so as to cause a movement towards itself and the other, diffusion of knowledge and ideational changes. Finally, the study has tried to measure the effect of socio-economic variables on CSR through a regression model.