Socio-Economic Status of Coachmen according to Population Census Data of 1721-1722 (by the Example of Nizhny Novgorod Province)

ABSTRACTResearch has shown that the level of activity of the residents of a city's neighbourhood is related to the availability of activity-related resources. This study aimed to characterise the housing environment in which many older adults live by exploring what activity-related resources were available in senior apartment buildings in one Canadian city, Winnipeg. Of 195 senior apartment buildings in the city, 190 were surveyed to examine whether variation in the buildings' activity resources was related to neighbourhood characteristics, particularly socio-economic status. Resources were classified as those for physical activities (e.g. exercise classes), social activities (e.g. card games), and services (e.g. a grocery-store shuttle). The neighbourhood characteristics were taken from census data and included socio-economic and socio-demographic measures. The apartment buildings varied considerably in the resources available, and a positive relationship was found between neighbourhood income and physical and social activity programmes and services. Lower residential stability and a higher percentage of residents living alone were also related to the buildings' resource-richness, and senior apartment buildings with limited activity-related resources clustered in disadvantaged neighbourhoods. How senior apartments are resourced should be examined in relation to the neighbourhood in which they are located.

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The socio-economic status of communities predicts variation in brain serotonergic responsivity

Psychological Medicine ◽

10.1017/s0033291704003757 ◽

2004 ◽

Vol 35 (4) ◽

pp. 519-528 ◽

Cited By ~ 44

Author(s):

STEPHEN B. MANUCK ◽

MARIA E. BLEIL ◽

KAREN L. PETERSEN ◽

JANINE D. FLORY ◽

J. JOHN MANN ◽

...

Keyword(s):

Census Data ◽

Allelic Variation ◽

Peak Plasma ◽

Economic Status ◽

Community Sample ◽

Economic Disadvantage ◽

Acute Administration ◽

Plasma Prolactin ◽

Census Tracts ◽

Socio Economic Status

Background. We reported previously that the socio-economic status (SES) of individuals predicts variation in brain serotonergic responsivity, as assessed by neuropharmacological challenge in an adult community sample, and that this association is qualified by allelic variation in the serotonin transporter gene-linked polymorphic region (5-HTTLPR). Here we examine whether serotonergic responsivity covaries similarly with the SES of communities, as indexed by US Census data in the same study sample.Method. Community SES was defined by levels of income, economic disadvantage, housing costs, and educational attainment of census tracts in which 249 locally recruited study participants (54% male) resided. Serotonergic responsivity was assessed as the baseline-adjusted, peak plasma prolactin (Prl) concentration following acute administration of the serotonin-releasing agent, fenfluramine; tissue for DNA extraction and 5-HTTLPR genotyping was available on 131 participants.Results. Subjects residing in census tracts of lower SES showed a blunted Prl response to fenfluramine (diminished serotonergic responsivity) relative to individuals living in more affluent neighborhoods. When adjusted for personal income and education, SES at the community level continued to predict fenfluramine-stimulated Prl responses and did so independently of 5-HTTLPR genotype.Conclusions. Area-level indices of relative social and economic disadvantage covary with individual differences in brain serotonergic responsivity, and this association is, in part, independent of individually defined SES. These findings may be relevant to reported effects of low community SES on the prevalence of psychiatric disorders or behaviors associated with dysregulation of central serotonergic function, such as depression, impulsive aggression, and suicide.

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Minorities and Diversity in Scotland: Evidence from the 2011 Census

Scottish Affairs ◽

10.3366/scot.2017.0162 ◽

2017 ◽

Vol 26 (1) ◽

pp. 23-47 ◽

Cited By ~ 1

Author(s):

Ross Bond

Keyword(s):

Large Scale ◽

Minority Groups ◽

Census Data ◽

Social Research ◽

Economic Status ◽

National Minority ◽

Socio Economic Status ◽

Large Scale Data ◽

Majority Population ◽

Scale Data

The relatively low proportion of people in ethnic and national minority groups in Scotland has been an obstacle for social research concerning these minorities, especially in characterising and comparing these populations using large scale data. The 2011 census offers an invaluable resource in this regard, especially at a time when minorities are growing to represent a more prominent and significant element in Scotland's population. This paper uses standard aggregate census data and data derived from a 5% sample of census returns to provide an overview and comparison of the six largest minority groups in Scotland, focusing on the origins, identities and socio-economic status of people within these groups. It not only highlights how different minorities contrast with each other and the majority population, but also illuminates the diversity that exists within these groups.

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A Re-Examination Of The Property Tax Burden

Journal of Business & Economics Research (JBER) ◽

10.19030/jber.v14i2.9627 ◽

2016 ◽

Vol 14 (2) ◽

pp. 51-60

Author(s):

Mary Beal-Hodges ◽

Mary O. Borg ◽

Harriet A. Stranahan

Keyword(s):

Census Data ◽

Economic Status ◽

Property Tax ◽

Demographic Variables ◽

Single Family ◽

County Governments ◽

Tax Rate ◽

Current Income ◽

Fine Grained ◽

Socio Economic Status

The property tax is the major source of own revenues for most city and county governments, yet economists have had very little definitive information to share with policymakers about the burden that it imposes on local citizens. This is because most previous studies of property taxes have used a Suits index analysis which does not allow for any independent variables other than income. We estimate a regression model using current income and various socio-demographic variables in order to take a more fine grained approach. We use data obtained from the Florida Department of Revenue from 326,976 single family homeowners in four northeast Florida counties geo-coded with the 2010 block group census data. We find that the property tax is regressive with respect to current income. With respect to demographic variables, we find that homeowners over the age of 65 pay a higher average tax rate based on their current incomes. African Americans pay a lower tax rate than other races based on their current income. When we combine income and demographic variables to predict the tax rate paid by a hypothetical low socio-economic status household versus a high socio-economic status household, we find that the high SES household pays a higher average tax rate. Thus, the demographic variables temper the regressivity of the property tax based on current income alone.

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Evaluation of Neighborhood Socio-Economic Status, as Measured by the Delphi Method, on Dengue Fever Distribution in Jeddah City, Saudi Arabia

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18126407 ◽

2021 ◽

Vol 18 (12) ◽

pp. 6407

Author(s):

Ibrahim Alkhaldy ◽

Pauline Barnett

Keyword(s):

Saudi Arabia ◽

Dengue Fever ◽

Delphi Method ◽

Census Data ◽

Economic Status ◽

High Status ◽

Additional Tool ◽

Jeddah City ◽

Socio Economic Status ◽

Delphi Approach

Dengue fever, a mosquito-transmitted viral disease, is present in many neighborhoods in Jeddah City, Saudi Arabia. One factor likely to affect its distribution is the socio-economic status of local neighborhoods; however, the absence of socio-economic census data in Saudi Arabia has precluded detailed investigation. This study aims to develop a proxy measure of socio-economic status in Jeddah City in order to assess its relationship with the occurrence of dengue fever. The Delphi method was used to assess the socio-economic status (high, medium or low) of local neighborhoods in Jeddah City. A Geographic Information System (GIS) was applied to understand the distribution of dengue fever according to the socio-economic status of Jeddah City neighborhoods. Low-socio-economic status neighborhoods in south Jeddah City, with poor environmental conditions and high levels of poverty and population density, reported most cases of dengue fever. Nevertheless, dengue continues to increase in high socio-economic status neighborhoods in the northern part of the city, possibly due to ideal breeding conditions caused by the presence of standing water associated with high levels of construction. Moreover, the low-socioeconomic-status neighborhoods had the highest average number of cases, being 3.95 times that of high-status neighborhoods for the period 2006–2009. The Delphi approach can produce a useful and robust measure of socio-economic status for use in the analysis of patterns of dengue fever. Results suggest that there are nuances in the relationship between socio-economic status and dengue that indicate that higher status areas are also at risk. A useful additional tool for researchers in Saudi Arabia would be the development of census data or other systematic measures that allow socio-economic status to be included in spatial analyses of dengue fever and other diseases.

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Socio-Economical Status of India using Machine Learning Algorithms

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.e6610.018520 ◽

2020 ◽

Vol 8 (5) ◽

pp. 3804-3813

Keyword(s):

Machine Learning ◽

Census Data ◽

Economic Status ◽

Confusion Matrix ◽

Machine Learning Algorithms ◽

Machine Learning Techniques ◽

Clustering Methods ◽

Socio Economic Status ◽

The People ◽

Indian Census

Data is everywhere and lots of data is openly available to people. We can analyze this data to find the hidden and unnoticed information to use it purposefully. One important source of information is census data and it provides data related to the people living in a country. Analyzing such data is useful for knowing the socio economic status of the country. Data mining and machine learning techniques can be used to analyze such large volumes of data. In this work Indian census 2011 is analyzed and identified the socio economic status of different states of India. To identify the social status of each state we studied literacy rate, categories of workers in different fields, gender wise working population. To identify economical status like people living below poverty and above poverty we used clustering techniques of machine learning. At first we pre-processed the data and later correlation based feature selection was applied, and on that result k-means and k-mediods clustering methods were implemented independently. Finally the clusters are evaluated to see the performance using confusion matrix. The final results show that k-mediod has better performance than K-means.

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Advances in mapping population and demographic characteristics at small-area levels

International Journal of Epidemiology ◽

10.1093/ije/dyz179 ◽

2020 ◽

Vol 49 (Supplement_1) ◽

pp. i15-i25

Author(s):

Daniela Fecht ◽

Samantha Cockings ◽

Susan Hodgson ◽

Frédéric B Piel ◽

David Martin ◽

...

Keyword(s):

Big Data ◽

Small Area ◽

Census Data ◽

Economic Status ◽

Demographic Data ◽

Population Data ◽

Demographic Characteristics ◽

Population Characteristics ◽

Population Census ◽

The Us

Abstract Temporally and spatially highly resolved information on population characteristics, including demographic profile (e.g. age and sex), ethnicity and socio-economic status (e.g. income, occupation, education), are essential for observational health studies at the small-area level. Time-relevant population data are critical as denominators for health statistics, analytics and epidemiology, to calculate rates or risks of disease. Demographic and socio-economic characteristics are key determinants of health and important confounders in the relationship between environmental contaminants and health. In many countries, census data have long been the source of small-area population denominators and confounder information. A strength of the traditional census model has been its careful design and high level of population coverage, allowing high-quality detailed data to be released for small areas periodically, e.g. every 10 years. The timeliness of data, however, becomes a challenge when temporally and spatially highly accurate annual (or even more frequent) data at high spatial resolution are needed, for example, for health surveillance and epidemiological studies. Additionally, the approach to collecting demographic population information is changing in the era of open and big data and may eventually evolve to using combinations of administrative and other data, supplemented by surveys. We discuss different approaches to address these challenges including (i) the US American Community Survey, a rolling sample of the US population census, (ii) the use of spatial analysis techniques to compile temporally and spatially high-resolution demographic data and (iii) the use of administrative and big data sources as proxies for demographic characteristics.

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Reproductive Behaviour of Female Entrepreneurs in Russia

Economic Strategies ◽

10.33917/es-5.171.2020.90-97 ◽

2020 ◽

Vol 144 ◽

pp. 90-97

Author(s):

Aisylu A. Ilimbetova ◽

Keyword(s):

Women Entrepreneurs ◽

Economic Status ◽

Reproductive Behaviour ◽

Russian Population ◽

Sample Survey ◽

Population Census ◽

Female Entrepreneurs ◽

Demographic Profile ◽

Socio Economic Status

Research in the field of fertility often focuses on peculiarities of reproductive behaviour of various groups of population different in socio-economic status, material and moral needs and reproductive attitudes. Comprehension of these features is important when shaping a pro-birth policy, since different groups of the population may respond differently to the proposed measures. In the article women entrepreneurs are presented as one of the groups of the Russian population with specific reproductive behaviour. The features of demographic profile and reproductive behaviour are analyzed on the basis of results of the All-Russian population census of 2002 and 2010 and a sample survey of the population reproductive plans of 2017.

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Socio-economic status of youth non-participation in Yala province: Population-based study using Thailand 2000 census data

Kasetsart Journal of Social Sciences ◽

10.1016/j.kjss.2018.01.004 ◽

2018 ◽

Vol 39 (1) ◽

pp. 129-134

Author(s):

Sunaree Suwanro ◽

Phattrawan Tongkumchum ◽

Chamnein Choonpradub ◽

Arinda Ma-a-lee ◽

Nurin Dureh

Keyword(s):

Census Data ◽

Economic Status ◽

Population Based ◽

Population Based Study ◽

Socio Economic Status

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Oral Language Behavior of Older Cerebral Palsied Children

Journal of Speech and Hearing Research ◽

10.1044/jshr.0704.349 ◽

1964 ◽

Vol 7 (4) ◽

pp. 349-359 ◽

Cited By ~ 3

Author(s):

Russell J. Love

Keyword(s):

Oral Language ◽

Economic Status ◽

Educational Background ◽

Socio Economic Status ◽

Language Behavior ◽

Hearing Acuity

A battery of six tests assessing various aspects of receptive and expressive oral language was administered to 27 cerebral palsied children and controls matched on the variables of age, intelligence, sex, race, hearing acuity, socio-economic status, and similarity of educational background. Results indicated only minimal differences between groups. Signs of deviancy in language behavior often attributed to the cerebral palsied were not observed. Although previous investigators have suggested consistent language disturbances in the cerebral palsied, evidence for a disorder of comprehension and formulation of oral symobls was not found.

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