scholarly journals Perceived spatial stigma, body mass index and blood pressure: a global positioning system study among low-income housing residents in New York City

2016 ◽  
Vol 11 (2) ◽  
Author(s):  
Dustin T. Duncan ◽  
Ryan R. Ruff ◽  
Basile Chaix ◽  
Seann D. Regan ◽  
James H. Williams ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Body Mass Index ◽  
New York ◽  
New York City ◽  
Low Income ◽  
York City ◽  
Household Income ◽  
Cardiovascular Health ◽  
Global Positioning ◽  
Low Income Housing

Previous research has highlighted the salience of spatial stigma on the lives of low-income residents, but has been theoretical in nature and/or has predominantly utilised qualitative methods with limited generalisability and ability to draw associations between spatial stigma and measured cardiovascular health outcomes. The primary objective of this study was to evaluate relationships between perceived spatial stigma, body mass index (BMI), and blood pressure among a sample of low-income housing residents in New York City (NYC). Data come from the community-based NYC Low-income Housing, Neighborhoods and Health Study. We completed a crosssectional analysis with survey data, which included the four items on spatial stigma, as well objectively measured BMI and blood pressure data (analytic n=116; 96.7% of the total sample). Global positioning systems (GPS) tracking of the sample was conducted for a week. In multivariable models (controlling for individual-level age, gender, race/ethnicity, education level, employment status, total household income, neighborhood percent non-Hispanic Black and neighborhood median household income) we found that participants who reported living in an area with a bad neighborhood reputation had higher BMI (B=4.2, 95%CI: -0.01, 8.3, P=0.051), as well as higher systolic blood pressure (B=13.2, 95%CI: 3.2, 23.1, P=0.01) and diastolic blood pressure (B=8.5, 95%CI: 2.8, 14.3, P=0.004). In addition, participants who reported living in an area with a bad neighborhood reputation had increased risk of obesity/overweight [relative risk (RR)=1.32, 95%CI: 1.1, 1.4, P=0.02) and hypertension/pre-hypertension (RR=1.66, 95%CI: 1.2, 2.4, P=0.007). However, we found no differences in spatial mobility (based GPS data) among participants who reported living in neighborhoods with and without spatial stigma (P>0.05). Further research is needed to investigate how placebased stigma may be associated with impaired cardiovascular health among individuals in stigmatised neighborhoods to inform effective cardiovascular risk reduction interventions.

scholarly journals Residential and GPS-Defined Activity Space Neighborhood Noise Complaints, Body Mass Index and Blood Pressure Among Low-Income Housing Residents in New York City

2017 ◽  
Vol 42 (5) ◽  
pp. 974-982 ◽  
Author(s):  
Kosuke Tamura ◽  
Brian Elbel ◽  
Basile Chaix ◽  
Seann D. Regan ◽  
Yazan A. Al-Ajlouni ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Body Mass Index ◽  
New York ◽  
New York City ◽  
Body Mass ◽  
Low Income ◽  
York City ◽  
Activity Space ◽  
Low Income Housing

Neighborhood Stigma and Sleep: Findings from a Pilot Study of Low-Income Housing Residents in New York City

2016 ◽  
Vol 44 (1) ◽  
pp. 48-53 ◽  
Author(s):  
Ryan Richard Ruff ◽  
Jeannie Ng ◽  
Girardin Jean-Louis ◽  
Brian Elbel ◽  
Basile Chaix ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Pilot Study ◽  
Low Income ◽  
York City ◽  
Low Income Housing

scholarly journals An ecological study of socioeconomic predictors in detection of COVID-19 cases across neighborhoods in New York City

2020 ◽  
Author(s):  
Richard S. Whittle ◽  
Ana Diaz-Artiles
Keyword(s):  
New York ◽  
New York City ◽  
Low Income ◽  
York City ◽  
Household Income ◽  
Health Management ◽  
Median Household Income ◽  
Female Ratio ◽  
Aging Populations ◽  
The Usa

AbstractBackgroundNew York City was the first major urban center of the COVID-19 pandemic in the USA. Cases are clustered in the city, with certain neighborhoods experiencing more cases than others. We investigate whether potential socioeconomic factors can explain between-neighborhood variation in the number of detected COVID-19 cases.MethodsData were collected from 177 Zip Code Tabulation Areas (ZCTA) in New York City (99.9% of the population). We fit multiple Bayesian Besag-York-Mollié (BYM) mixed models using positive COVID-19 tests as the outcome and a set of 10 representative economic, demographic, and health-care associated ZCTA-level parameters as potential predictors. The BYM model includes both spatial and nonspatial random effects to account for clustering and overdispersion.ResultsMultiple different regression approaches indicated a consistent, statistically significant association between detected COVID-19 cases and dependent (under 18 or 65+ years old) population, male to female ratio, and median household income. In the final model, we found that an increase of only 1% in dependent population is associated with a 2.5% increase in detected COVID-19 cases (95% confidence interval (CI): 1.6% to 3.4%, p < 0.0005). An increase of 1 male per 100 females is associated with a 1.0% (95% CI: 0.6% to 1.5%, p < 0.0005) increases in detected cases. A decrease of $10,000 median household income is associated with a 2.5% (95% CI: 1.0% to 4.1% p = 0.002) increase in detected COVID-19 cases.ConclusionsOur findings indicate associations between neighborhoods with a large dependent population, those with a high proportion of males, and low-income neighborhoods and detected COVID-19 cases. Given the elevated mortality in aging populations, the study highlights the importance of public health management during and after the current COVID-19 pandemic. Further work is warranted to fully understand the mechanisms by which these factors may have affected the number of detected cases, either in terms of the true number of cases or access to testing.

scholarly journals Long-term Recovery From Hurricane Sandy: Evidence From a Survey in New York City

2017 ◽  
Vol 12 (2) ◽  
pp. 172-175 ◽  
Author(s):  
Elisaveta P. Petkova ◽  
Jaishree Beedasy ◽  
Eun Jeong Oh ◽  
Jonathan J. Sury ◽  
Erin M. Sehnert ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Low Income ◽  
York City ◽  
Household Income ◽  
Hurricane Sandy ◽  
Middle Income ◽  
Assistance Programs ◽  
Federal Assistance

AbstractObjectivesThis study aimed to examine a range of factors influencing the long-term recovery of New York City residents affected by Hurricane Sandy.MethodsIn a series of logistic regressions, we analyzed data from a survey of New York City residents to assess self-reported recovery status from Hurricane Sandy.ResultsGeneral health, displacement from home, and household income had substantial influences on recovery. Individuals with excellent or fair health were more likely to have recovered than were individuals with poor health. Those with high and middle income were more likely to have recovered than were those with low income. Also, individuals who had not experienced a decrease in household income following Hurricane Sandy had higher odds of recovery than the odds for those with decreased income. Additionally, displacement from the home decreased the odds of recovery. Individuals who applied for assistance from the Build it Back program and the Federal Emergency Management Agency had lower odds of recovering than did those who did not apply.ConclusionsThe study outlines the critical importance of health and socioeconomic factors in long-term disaster recovery and highlights the need for increased consideration of those factors in post-disaster interventions and recovery monitoring. More research is needed to assess the effectiveness of state and federal assistance programs, particularly among disadvantaged populations. (Disaster Med Public Health Preparedness. 2018;12:172–175)

Practical Philanthropy: The Phelps-Stokes Fund and Housing

Prospects ◽  
1990 ◽  
Vol 15 ◽  
pp. 359-411
Author(s):  
Deborah S. Gardner
Keyword(s):  
New York ◽  
New York City ◽  
African Americans ◽  
Native Americans ◽  
Low Income ◽  
White Students ◽  
York City ◽  
Educational Opportunities ◽  
The Other ◽  
Low Income Housing

Improving low-income housing in New York City was one of two objectives for the Phelps-Stokes Fund when it was incorporated in 1911. Enhancing educational opportunities for African-Americans, Native Americans, Africans, and needy white students was the other. Both represented lifelong concerns of Caroline Phelps Stokes (1854–1909), whose bequest financed the fund.

‘Homelessness’, Contagious Destruction of Housing, and Municipal Service Cuts in New York City: 1. Demographics of a Housing Deficit

1989 ◽  
Vol 21 (12) ◽  
pp. 1585-1602 ◽  
Author(s):  
R Wallace
Keyword(s):  
New York ◽  
New York City ◽  
Low Income ◽  
York City ◽  
Forced Migration ◽  
Emergency Shelter ◽  
Time Dynamics ◽  
Urban Decay ◽  
Economic Forces ◽  
Low Income Housing

Approaches from community and population ecology are adapted to study ‘homelessness’ in New York City, where long-standing and continued reductions of critical housing-related municipal services, particularly fire extinguishment, to levels below those needed for maintaining urban population densities have triggered waves of coupled contagious destruction of low-income housing and forced migration of population. Massive destruction of housing, after a delay occasioned by the outmigration of some 1.3 million non-Hispanic whites from the city between 1970 and 1980 has contributed significantly to a serious housing deficit, by direct loss of low-income housing and possibly by creating economic forces which encourage the conversion of remaining low-income units to high-income units. This deficit, which by some analyses approaches a quarter million housing units affecting perhaps a million people, has created a large ‘precariously housed’ population which, after a delay, is becoming overtly homeless as the decline of low-income housing supply collides with increasing numbers of the poor. Elementary mathematical analysis suggests the demographics of those precariously housed, but not yet homeless, strongly determines the dynamics of demand for emergency shelter, implying, for example, that under some circumstances the probability of avoiding homelessness may decline exponentially with time spent precariously housed, and that the number requiring emergency shelter may increase as rapidly as the square of the number precariously housed, depending on exact mechanisms. This paper provides prerequisites to a subsequent fuller exploration of the complex time dynamics of synergistic couplings between contagious urban decay, population migration, precariously housed population, homelessness, and public health deterioration in New York City.

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