US Multidimensional Poverty by Race, Ethnicity and Motherhood: Evidence from Pennsylvania Census Data

2017 ◽  
pp. 223-254 ◽  
Author(s):  
Feridoon Koohi-Kamali ◽  
Ran Liu
Keyword(s):  
Census Data ◽  
Multidimensional Poverty ◽  
Race Ethnicity

Differences in overall survival for patients with cholangiocarcinoma: Racial/ethnic disparity or socioeconomic factors?

2019 ◽  
Vol 37 (4_suppl) ◽  
pp. 380-380 ◽  
Author(s):  
Rachel M Lee ◽  
Yuan Liu ◽  
Mohammad Yahya Zaidi ◽  
Adriana Carolina Gamboa ◽  
Maria C. Russell ◽  
...  
Keyword(s):  
Overall Survival ◽  
Socioeconomic Factors ◽  
Ethnic Groups ◽  
Racial Differences ◽  
Low Income ◽  
Census Data ◽  
Private Insurance ◽  
Cancer Data ◽  
Race Ethnicity ◽  
Racial Ethnic

380 Background: Inequities in cancer survival are well documented. Whether disparities in overall survival (OS) result from inherent racial differences in underlying disease biology or socioeconomic factors (SEF) is not known. Our aim was to define the association of race/ethnicity and SEF with OS in pts with cholangiocarcinoma (CCA). Methods: Pts with CCA of all sites and stages in the National Cancer Data Base (2004-14) were included. Racial/ethnic groups were defined as non-Hispanic White (NH-W), non-Hispanic Black (NH-B), Asian, and Hispanic. Income and education were based on census data for pts’ zip code. Income was defined as high (³$63,000) vs low ( < $63,000). Primary outcome was OS. Results: 27,151 pts were included with a mean age of 68 yrs; 51% were male. 78% were NH-W, 8% NH-B, 6% Asian, and 6% Hispanic. 56% had Medicare, 33% private insurance, 7% Medicaid, and 4% were uninsured. 67% had high income. 21% lived in an area where > 20% of adults did not finish high school. NH-B and Hispanic pts had more unfavorable SEF including uninsured status, low income, and less formal education than NH-W and Asian pts (all p < 0.001). They were also younger, more likely to be female and to have metastatic disease (all p < 0.001). Despite this, NH-B race and Hispanic ethnicity were not associated with decreased OS. Male sex, older age, non-private insurance, low income, lower education, non-academic facility, location outside the Northeast, higher Charlson-Deyo score, worse grade, larger tumor size, and higher stage were all associated with decreased OS (all p < 0.001). On MV analysis, along with adverse pathologic factors, type of insurance (p = 0.003), low income (p < 0.001), and facility type and location of treatment (p < 0.001) remained associated with decreased OS; non-white race/ethnicity was not. Conclusions: Disparities in survival exist in CCA, however they are not driven by race/ethnicity. Non-privately insured and low-income pts had decreased OS, as did pts treated at non-academic centers and outside the Northeast. This suggests that decreased ability to access and afford care results in worse outcomes, rather than biological differences amongst racial/ethnic groups.

scholarly journals 0360 Neighborhood Disadvantage is Associated with Lower Quality Sleep and More Variability in Weeknight Sleep Duration Among Urban Adolescents

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A137-A138
Author(s):  
N G Nahmod ◽  
L Master ◽  
H F McClintock ◽  
L Hale ◽  
O M Buxton
Keyword(s):  
Sleep Duration ◽  
Summer School ◽  
Multilevel Models ◽  
Census Data ◽  
National Level ◽  
Neighborhood Disadvantage ◽  
Disadvantaged Neighborhoods ◽  
Falling Asleep ◽  
Adolescent Sleep ◽  
Race Ethnicity

Abstract Introduction Differential social and contextual environments may contribute to adolescent sleep disparities. Yet, most prior studies are limited to self-reported sleep data, and the actigraphic studies of sleep are not conducted at a national level, thus limiting the variation in neighborhood contexts. This study examined the association between neighborhood disadvantage and actigraphic assessment of adolescent sleep. Methods Participants (682 adolescents, mean age 15.4 years) were racially/ethnically diverse (44% Black, 26% Hispanic, 17% White, 14% other race/ethnicity), sampled from 20 large US cities in the Fragile Families and Child Wellbeing Study. Neighborhood disadvantage was calculated from American Community Survey 2015 census data using the Standardized Neighborhood Deprivation Index (SNDI), consolidating five variables (proportion of female-headed households, public assistance recipients, households in poverty, adults without high school degrees, and unemployed) into an index. SNDI quartiles 1-3 fell below national averages of SNDI variables (“most disadvantaged”) and were compared to quartile 4 (“least disadvantaged”). Sleep indicators (duration, quality, and timing) were measured over ≥5 nights using wrist-worn accelerometers. Separate multilevel models estimated differences in sleep indicators, adjusting for weekday/weekend and summer/school year. General linear models used within-person standard deviations of sleep indicators (controlling for number of days) to test for associations between neighborhood disadvantage and consistency of weeknight sleep patterns. Models adjusted for individual-level sociodemographic covariates (age, sex, race/ethnicity, household income, caregiver education, and family structure). Results In fully adjusted models, adolescents living in more disadvantaged neighborhoods spent more time awake after falling asleep (4.0 minutes/night, p&lt;0.05), spent greater percentage of nighttime sleep intervals awake (1%, p&lt;.01), and had less consistent sleep duration (11.7% higher standard deviation, p&lt;.05). Sleep duration and timing did not differ across neighborhood groups. Conclusion Living in more disadvantaged neighborhoods is associated with lower quality adolescent sleep; more research is needed to identify causal mechanisms. Support Research was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) of the National Institutes of Health (NIH), award numbers R01HD073352 (PI: Hale), R01HD36916, R01HD39135, and R01 HD40421, and private foundations. The content is the responsibility of the authors and does not represent official NIH views.

The Odds of Transiting from One Level of Sports Participation to Another

1996 ◽  
Vol 13 (3) ◽  
pp. 288-299 ◽  
Author(s):  
Wilbert M. Leonard
Keyword(s):  
Social Mobility ◽  
Women Of Color ◽  
Census Data ◽  
Professional Sports ◽  
Sports Participation ◽  
Professional Athlete ◽  
Men And Women ◽  
Race Ethnicity ◽  
Upward Social Mobility ◽  
Operational Issues

The present study contributes to, updates, and extends the literature on sport and social mobility by reconceptualizing and reoperationalizing the odds of attaining college and professional athlete status. Using 1990 U.S. census data and team rosters, rates for achieving college and professional sports “careers” were computed for men and women of color in the most popular U.S. sports. A methodological contribution of this research is that the norming variables employed in the statistical calculations were refined, that is, they were age, race/ethnicity, sport, and sex specific. This inquiry contains the most systematic, extensive, and refined measures for assessing the likelihood of achieving the ultimate in sport upward social mobility—major league professional athlete status. A discussion of why the odds of obtaining professional athlete status vary is explored along with some of the conceptual and operational issues created by the concept Hispanic.

scholarly journals SPATIAL STATISTICAL ANALYSES TO ASSESS THE SPATIAL EXTENT AND CONCENTRATION OF MULTIDIMENSIONAL POVERTY IN GAUTENG USING THE SOUTH AFRICAN MULTIDIMENSIONAL POVERTY INDEX

2018 ◽  
Vol XLII-4/W8 ◽  
pp. 85-92 ◽  
Author(s):  
S. Katumba
Keyword(s):  
Urban Areas ◽  
Census Data ◽  
Multidimensional Poverty ◽  
Gauteng Province ◽  
Multidimensional Poverty Index ◽  
Fine Grained ◽  
Policy Interventions ◽  
Holistic Understanding ◽  
Comprehensive Picture ◽  
Core Areas

<p><strong>Abstract.</strong> Assessment of poverty has generally been carried out using “money-metric” measures. But since poverty is multidimensional, these measures fall short of generating a comprehensive picture of the poor. Contrastingly, multidimensional poverty analyses are capable of generating parameters that help in providing holistic understanding of poverty in its various forms. This study compares two indexes of multidimensional poverty computed from census data collected in 2001 and 2011 in Gauteng (South Africa) by performing a spatial autocorrelation analysis. The results reveal fine-grained detailed variations in the concentration of poverty across the Gauteng province. Overall, multidimensional poverty is concentrated at the periphery of the province while affluence is concentrated in the core urban areas. Pockets of grinding poverty can also be found in core areas juxtaposed with affluence. Such an analysis will lead to the formulation of spatially targeted policy interventions geared towards poverty alleviation.</p>

scholarly journals Race, Poverty, and U.S. Children’s Exposure to Neighborhood Incarceration

2021 ◽  
Vol 7 ◽  
pp. 237802312110678
Author(s):  
Alexander F. Roehrkasse
Keyword(s):  
Residential Segregation ◽  
Census Data ◽  
The United States ◽  
African American Child ◽  
American Child ◽  
Poverty Status ◽  
Working Age ◽  
Race Ethnicity ◽  
Children’S Exposure ◽  
Prison Admission

Recent research has documented negative associations between children’s welfare and mobility and their exposure to neighborhood incarceration. But inequality in such exposure among children in the United States is poorly understood. This study links tract-level census data to administrative data on prison admissions to measure 37.8 million children’s exposure to neighborhood incarceration in 2008, by race/ethnicity and poverty status. The average poor Black or African American child lived in a neighborhood where 1 in 174 working-age adults was admitted to prison annually, more than twice the rate of neighborhood prison admission experienced by the average U.S. child. Residential segregation and the spatial concentration of incarceration combine to create significant ethnoracial and economic inequality in the neighborhood experiences of U.S. children.

scholarly journals Is Working Longer the Solution to an Aging Society?

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 809-809
Author(s):  
Phyllis Moen
Keyword(s):  
Policy Development ◽  
Census Data ◽  
Population Aging ◽  
Later Life ◽  
Paid Work ◽  
Safety Nets ◽  
Adult Participation ◽  
Dual Earner ◽  
Race Ethnicity ◽  
Opening Up

Abstract Population aging, together with increases in life expectancy, women’s employment, dual-earner households, and unraveling safety nets, are transforming the demography of work and retirement in the later life course. A seemingly obvious policy solution is to encourage Boomers and those following to work longer, postponing retirementt. And yet there is insufficient understanding of factors that predict ongoing older adult participation in paid work. The simple work/retirement dichotomy no longer fits the experience of growing numbers of Americans. Drawing on census data, I show six such pathways differing by age, gender, and race/ethnicity. Needed is policy development recognizing the new realities of different and unequal pathways. The challenge is recognizing disparities in capacities and constraints among our aging population, along with the need to change the way we work, opening up flexible options in order to enable working longer.

scholarly journals The incidence of non-affective psychotic disorders in Chile between 2005 and 2018: results from a national register of over 30 000 cases

2020 ◽  
pp. 1-10
Author(s):  
Alfonso González-Valderrama ◽  
Hannah E. Jongsma ◽  
Cristián Mena ◽  
Carmen Paz Castañeda ◽  
Rubén Nachar ◽  
...  
Keyword(s):  
Population Density ◽  
Psychotic Disorders ◽  
Census Data ◽  
Multidimensional Poverty ◽  
International Classification Of Diseases ◽  
Global South ◽  
First Episode ◽  
National Register ◽  
National Register Data ◽  
Group Sex

Abstract Background Evidence suggests the incidence of non-affective psychotic disorders (NAPDs) varies across persons and places, but data from the Global South is scarce. We aimed to estimate the treated incidence of NAPD in Chile, and variance by person, place and time. Methods We used national register data from Chile including all people, 10–65 years, with the first episode of NAPD (International Classification of Diseases, Tenth Revision: F20–F29) between 1 January 2005 and 29 August 2018. Denominators were estimated from Chilean National Census data. Our main outcome was treated incidence of NAPD and age group, sex, calendar year and regional-level population density, multidimensional poverty and latitude were exposures of interest. Results We identified 32 358 NAPD cases [12 136 (39.5%) women; median age-at-first-contact: 24 years (interquartile range 18–39 years)] during 171.1 million person-years [crude incidence: 18.9 per 100 000 person-years; 95% confidence interval (CI) 18.7–19.1]. Multilevel Poisson regression identified a strong age–sex interaction in incidence, with rates peaking in men (57.6 per 100 000 person-years; 95% CI 56.0–59.2) and women (29.5 per 100 000 person-years; 95% CI 28.4–30.7) between 15 and 19 years old. Rates also decreased (non-linearly) over time for women, but not men. We observed a non-linear association with multidimensional poverty and latitude, with the highest rates in the poorest regions and those immediately south of Santiago; no association with regional population density was observed. Conclusion Our findings inform the aetiology of NAPDs, replicating typical associations with age, sex and multidimensional poverty in a Global South context. The absence of association with population density suggests this risk may be context-dependent.

The Effect of Neighborhood Diversity on Volunteering: Evidence From New Zealand

2012 ◽  
Vol 12 (1) ◽  
Author(s):  
Jeremy Clark ◽  
Bonggeun Kim
Keyword(s):  
New Zealand ◽  
Cross Section ◽  
Fixed Effects ◽  
Census Data ◽  
Empirical Literature ◽  
Neighborhood Size ◽  
Neighborhood Characteristics ◽  
Cross Sectional ◽  
Neighborhood Diversity ◽  
Race Ethnicity

Abstract A growing empirical literature has found that neighborhood heterogeneity lowers people’s likelihood of contributing to public goods. However, this literature has been mostly cross-sectional, and so struggled to address the effects of unobserved influences on contributions that may be correlated with heterogeneity. It has also paid little attention to how heterogeneity’s estimated effects are influenced by neighborhood size or the concavity of heterogeneity measures. With access to a panel of three waves of census data on volunteering rates in New Zealand, released at two fine levels of aggregation, we can control for stable unobserved neighborhood characteristics that may affect volunteering rates. We use pooled cross-section, between and fixed effects regressions to test whether volunteering rates are lowered by heterogeneity in race/ethnicity, language, birthplace, or income. We find that estimates are affected by neighborhood definition, and that ethnic and language heterogeneity are robustly associated with lower volunteering rates in New Zealand.

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