scholarly journals Area characteristics and admission rates of people with schizophrenia and affective disorders in a German rural catchment area

2012 ◽  
Vol 21 (4) ◽  
pp. 371-379 ◽  
Author(s):  
C. Losert ◽  
M. Schmauß ◽  
T. Becker ◽  
R. Kilian
Keyword(s):  
Income Inequality ◽  
Population Density ◽  
Population Growth ◽  
Unemployment Rate ◽  
Rural Areas ◽  
Affective Disorders ◽  
Catchment Area ◽  
Average Income ◽  
Admission Rates ◽  
Green Areas

Background.Studies in urban areas identified environmental risk factors for mental illness, but little research on this topic has been performed in rural areas.Methods.Hospital admission rates were computed for 174 rural municipalities in the catchment area of the state psychiatric hospital in Günzburg in years 2006 to 2009 and combined with structural and socio-economic data. Relationships of overall and diagnosis-specific admission rates with municipality characteristics were analysed by means of negative binomial regression models.Results.Admission rates of patients with a diagnosis of schizophrenia and affective disorder combined decrease with increasing population growth, population density, average income and green areas, while admission rates are positively correlated with commuter balance, income inequality, unemployment rates and traffic areas. Admission rates for schizophrenia are negatively related to population growth, average income and agricultural areas, but positively related to mobility index, income inequality and unemployment rate. Admission rates for affective disorders are negatively related to population growth, population density, average income and green areas, while higher admission rates are correlated with commuter balance, high income inequality, unemployment rate and traffic-related areas.Conclusions.Effects of wealth, economic inequality, population density and structural area characteristics influence psychiatric admission rates also in rural areas.

scholarly journals Urban-rural gradients of ecosystem services and the linkages with socioeconomics

2015 ◽  
Vol 39 ◽  
pp. 1-31 ◽  
Author(s):  
Yin Hou ◽  
Felix Müller ◽  
Bo Li ◽  
Franziska Kroll
Keyword(s):  
Ecosystem Services ◽  
Population Density ◽  
Habitat Quality ◽  
Unemployment Rate ◽  
Rural Areas ◽  
Road Density ◽  
Urban Fabric ◽  
Housing Area ◽  
Urban Rural

The principle of urban-rural gradients can reveal the spatial variations of ecosystem services and socioeconomic dimensions. The interrelations between ecosystem services and socioeconomics have scarcely been considered in the context of urban-rural areas. We investigated the spatial gradients and the mutual linkages of several ecosystem services and socioeconomic variables in the urban-rural areas of Leipzig, Germany, and Kunming, China. The results showed some regularities in the spatial patterns of ecosystem services and socioeconomic dimensions in both study areas. Habitat quality and f-evapotranspiration of Leipzig and habitat quality of Kunming demonstrated apparent increasing trends along all gradient patterns. However, the other ecosystem services presented divergent spatial variabilities in different gradient patterns. Road density, urban fabric and population density showed identical declining trends in both case study areas. Differently, household size, housing area as well as unemployment rate in Leipzig presented inconsistent spatial dynamics with considerable fluctuations. With regard to the gradient interrelations, road density, urban fabric and population density were strongly correlated with most ecosystem services in both case study areas. In contrast, the gradients of household size, housing area and unemployment rate of Leipzig showed inconsistent correlations with the ecosystem services gradients. Our study provides evidence to the argument that typical patterns of ecosystem service gradients do not exist in different urban-rural areas.

scholarly journals Population Change and Income Inequality in Rural America

2020 ◽  
Author(s):  
Jaclyn L.W. Butler ◽  
Grace Wildermuth ◽  
Brian C. Thiede ◽  
David L. Brown
Keyword(s):  
Income Inequality ◽  
Population Growth ◽  
Rural Areas ◽  
Fixed Effects ◽  
Population Change ◽  
Population Decline ◽  
The United States ◽  
County Level ◽  
Level Data ◽  
The Relationship

This paper examines the effects of population growth and decline on county-level income inequality in the United States from 1980 to 2016. Findings from previous research have shown that income inequality is positively associated with population change, but these studies have not explicitly tested for differences between the impacts of population growth and decline. Understanding the implications of population dynamics is particularly important given that many rural areas are characterized by population decline. We analyze county-level data (n=15,375 county-decades) from the Decennial Census and American Community Survey (ACS), applying fixed effects models to estimate the respective effects of population growth and decline on income inequality, to identify the processes that mediate the links between population change and inequality, and to assess whether these effects are moderated by county-level economic and demographic characteristics. We find evidence that population decline is associated with increased levels of income inequality relative to counties experiencing stable and high rates of population growth. This relationship remains robust across a variety of model specifications, including models that account for changes in counties’ employment, sociodemographic, and ethnoracial composition. We also find that the relationship between income inequality and population change varies by metropolitan status, baseline level of inequality, and region.

Integrated Assessment of Socio-Economic Development of Rural Areas, Taking into Account Differences in Population Density

2020 ◽  
pp. 76-83
Author(s):  
N.N. Balashova ◽  
◽  
D.A. Korobeynikov ◽  
S.A. Popova ◽  
◽  
...  
Keyword(s):  
Sustainable Development ◽  
Economic Development ◽  
Population Density ◽  
Rural Areas ◽  
Rural Population ◽  
Integrated Assessment ◽  
Russian Regions ◽  
Socio Economic Development

Typologization of rural areas, taking into account differences in population density and level of socio-economic development, is necessary to identify “growth points” and strategic sustainability benchmarks. The method of integrated assessment of the level of socio-economic development of rural territories is proposed, according to which the grouping of Russian regions is carried out. Applying data on rural population density to the results of calculations allowed us to identify 12 typological groups, in the context of which unified recommendations on sustainable development of territories should be formed.

scholarly journals Effectiveness of Government Policies in Controlling COVID-19 in India

2020 ◽  
pp. 002073142098374
Author(s):  
Ashutosh Pandey ◽  
Nitin Kishore Saxena
Keyword(s):  
Population Density ◽  
Rural Areas ◽  
Rural Population ◽  
Urban Areas ◽  
Urban Population ◽  
Demographic Factors ◽  
Poverty Rate ◽  
Government Policies ◽  
Cumulative Number ◽  
Population Number

The purpose of this study is to find the demographic factors associated with the spread of COVID-19 and to suggest a measure for identifying the effectiveness of government policies in controlling COVID-19. The study hypothesizes that the cumulative number of confirmed COVID-19 patients depends on the urban population, rural population, number of persons older than 50, population density, and poverty rate. A log-linear model is used to test the stated hypothesis, with the cumulative number of confirmed COVID-19 patients up to period [Formula: see text] as a dependent variable and demographic factors as an independent variable. The policy effectiveness indicator is calculated by taking the difference of the COVID rank of the [Formula: see text]th state based on the predicted model and the actual COVID rank of the [Formula: see text]th state[Formula: see text]Our study finds that the urban population significantly impacts the spread of COVID-19. On the other hand, demographic factors such as rural population, density, and age structure do not impact the spread of COVID-19 significantly. Thus, people residing in urban areas face a significant threat of COVID-19 as compared to people in rural areas.

Komparácia pro-poor rastu vo vidieckych a mestských oblastiach Indonézie

2021 ◽  
Author(s):  
Barbora Frličková
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Poor People ◽  
Average Income ◽  
Poor Growth ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
Poverty And Inequality ◽  
Partial Period ◽  
Urban And Rural Areas

The paper analyses construction and use of a selected indicator of pro-poor growth – the rate of pro-poor growth. It further explains the interpretation of this indicator in absolute and relative terms and indicates how economic growth affects poverty and inequality. The selected indicator is applied to the example of Indonesia and compares pro-poor growth in urban and rural areas of the country, examines regional disparities in terms of pro-poor growth for the period 1996–2019. From the absolute interpretation, pro-poor growth is observed in both urban and rural areas over the whole period. In relative terms, results of pro-poor growth for the first partial period (1996–2000) differ. While there was a relative pro-poor growth in the rural areas, there was a strong pro-poor growth in the cities with a significant decline in inequality observed (incomes of poor people increased while the average income of the whole population dropped). Indonesia achieved trickle-down growth in both rural and urban areas in two remaining periods (2000–2010 and 2010–2019).

scholarly journals On the Determinants of Unemployment Rate in Nigeria: Evidence from Fully Modified OLS and Error Correction Model

2018 ◽  
Author(s):  
Monday Osagie Adenomon ◽  
N. A. Okoro-Ugochukwu ◽  
C. A. Adenomon
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Population Growth ◽  
Error Correction ◽  
Unemployment Rate ◽  
Inflation Rate ◽  
Error Correction Model ◽  
Correction Model ◽  
Short Run ◽  
Determinants Of Unemployment

This study employed the Fully Modified Ordinary Least Squares (FMOLS) and the Error Correction Model (ECM) to investigate the long-run and short-run determinants of unemployment rate in Nigeria. To achieve this annual data on unemployment rate, inflation rate, interest rate, exchange rate and population growth from 1981 to 2016 was collected from Central Bank Statistical Bulletins and the World Bank website. The ADF test revealed that the macroeconomic variables are stationary at first difference while the Cointegration test revealed that the variables are cointegrated. Using unemployment rate as dependent variable, the FMOLS model revealed that exchange rate and population growth are positively significantly related to unemployment rate, interest rate and inflation rate were negatively related to unemployment rate but only interest rate was significant. The short run relationship revealed that the coefficient of the ecm(-1) is negative and statistically significant at 5% level indicating that the system corrects its previous period disequilibrium at the speed of 48.93% yearly. This study concludes that high exchange rate and population growth can lead to increase in unemployment rate in Nigeria while the government should develop the industrial sector and non-oil sector in order to generate employment and boost export in Nigeria.

scholarly journals Trends of forest area and population and the impact of population on forest area per hectare in Serbia without APS

2012 ◽  
pp. 183-196
Author(s):  
Nenad Rankovic
Keyword(s):  
Population Density ◽  
Population Growth ◽  
Forest Cover ◽  
Forest Policy ◽  
Forest Area ◽  
Economic Changes ◽  
Policy Measures ◽  
Per Capita ◽  
The Impact

Socio-economic changes throughout history have shaped the attitude towards the forest and most significant ones are changes in terms of population. Over the centuries population and population density have had a significant impact on deforestation and the reduction of forest areas. Therefore, it is important to check what kind of trends are concerned and how population growth affects forest areas, forest cover and forest area per capita. These elements are important for assessing the direction, intensity of activity and the degree of success in the implementation of all forest policy measures in Serbia.

scholarly journals The Impact of Debt Burden on the Number of Suicides in the Russian Regions

2021 ◽  
Vol 17 (4) ◽  
pp. 97-117
Author(s):  
Svetlana Doroshenko ◽  
◽  
Olga Sanaeva ◽  
◽  
Keyword(s):  
Mental Disorders ◽  
Unemployment Rate ◽  
Rural Areas ◽  
Negative Impact ◽  
Generalized Method Of Moments ◽  
Russian Regions ◽  
Debt Burden ◽  
Suicide Rates ◽  
Number Of Patients ◽  
The Impact

Population size is one of the most important parameters of national social and economic systems. This parameter is controlled by a variety of factors (components) that form ambiguous and complex feedback circuits. The most important issue is the study of the behavioral reactions of the population, which form certain parameters of the dynamics of the population. The authors consider only one behavioral reaction that seems to them to be important – the propensity for suicide, which ultimately leads to the formation of the suicide dynamics and which entails serious socio-economic and demographic losses. We put an emphasis on assessing the impact of financial parameters, namely households’ debt burden, on the suicide rates in the Russian regions. An econometric assessment of the influence of individual debt on the number of suicides among other socio-economic factors (unemployment rate, logarithm of GRP per capita, divorce rate, number of patients with mental disorders, average actual working week, number of alcoholics) was carried out for the regions among rural, urban populations and total. We use panel data for 80 Russian regions covering the period from 2005 to 2018. We apply the generalized method of moments (GMM) using Stata 14 statistical package. The empirical analysis demonstrates negative impact of the amount of individual debt on the number of suicides in the regions of Russia, which contradicts the results of similar studies conducted for developed economies. At the same time, some results obtained earlier in domestic and foreign studies have been confirmed, including an existence of a parabolic (U-shaped) dependence between the length of working hours and the suicide rates in the regions of the Russian Federation. In addition, there is a direct connection between an increase in the committed suicides and an increase in divorce rates and the number of patients with mental disorders. Moreover, we find out that the rise in unemployment rate and alcohol consumption leads to an increase in the number of committed suicides. This effect is especially perceptible among the people living in rural areas

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