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

2004 ◽  
Vol 35 (4) ◽  
pp. 519-528 ◽  
Author(s):  
STEPHEN B. MANUCK ◽  
MARIA E. BLEIL ◽  
KAREN L. PETERSEN ◽  
JANINE D. FLORY ◽  
J. JOHN MANN ◽  
...  

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.

2009 ◽  
Vol 29 (3) ◽  
pp. 397-411 ◽  
Author(s):  
VERENA H. MENEC ◽  
DAWN M. VESELYUK ◽  
AUDREY A. BLANDFORD ◽  
SCOTT NOWICKI

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.


2017 ◽  
Vol 26 (1) ◽  
pp. 23-47 ◽  
Author(s):  
Ross Bond

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.


2016 ◽  
Vol 14 (2) ◽  
pp. 51-60
Author(s):  
Mary Beal-Hodges ◽  
Mary O. Borg ◽  
Harriet A. Stranahan

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.


2015 ◽  
Vol 35 (4) ◽  
pp. 450-459 ◽  
Author(s):  
Wen Tang ◽  
Blair Grace ◽  
Stephen P. McDonald ◽  
Carmel M. Hawley ◽  
Sunil V. Badve ◽  
...  

♦BackgroundThe aim of the present study was to investigate the relationship between socio-economic status (SES) and peritoneal dialysis (PD)-related peritonitis.♦MethodsAssociations between area SES and peritonitis risk and outcomes were examined in all non-indigenous patients who received PD in Australia between 1 October 2003 and 31 December 2010 (peritonitis outcomes). SES was assessed by deciles of postcode-based Australian Socio-Economic Indexes for Areas (SEIFA), including Index of Relative Socio-economic Disadvantage (IRSD), Index of Relative Socio-economic Advantage and Disadvantage (IRSAD), Index of Economic Resources (IER) and Index of Education and Occupation (IEO).♦Results7,417 patients were included in the present study. Mixed-effects Poisson regression demonstrated that incident rate ratios for peritonitis were generally lower in the higher SEIFA-based deciles compared with the reference (decile 1), although the reductions were only statistically significant in some deciles (IRSAD deciles 2 and 4 – 9; IRSD deciles 4 – 6; IER deciles 4 and 6; IEO deciles 3 and 6). Mixed-effects logistic regression showed that lower probabilities of hospitalization were predicted by relatively higher SES, and lower probabilities of peritonitis-associated death were predicted by less SES disadvantage status and greater access to economic resources. No association was observed between SES and the risks of peritonitis cure, catheter removal and permanent hemodialysis (HD) transfer.♦ConclusionsIn Australia, where there is universal free healthcare, higher SES was associated with lower risks of peritonitis-associated hospitalization and death, and a lower risk of peritonitis in some categories.


Author(s):  
Ibrahim Alkhaldy ◽  
Pauline Barnett

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.


2020 ◽  
Vol 8 (5) ◽  
pp. 3804-3813

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.


2015 ◽  
Vol 21 (1) ◽  
pp. 27-37 ◽  
Author(s):  
Juliet Ruth Helen Wakefield ◽  
Fabio Sani ◽  
Vishnu Madhok ◽  
Michael Norbury ◽  
Pat Dugard

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