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.

Abstract P636: Social Determinants of Stroke Hospitalization and Mortality in the United States

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Randhir Sagar Yadav ◽  
Durgesh Chaudhary ◽  
Shima Shahjouei ◽  
Jiang Li ◽  
Vida Abedi ◽  
...  
Keyword(s):  
United States ◽  
Income Inequality ◽  
Social Determinants ◽  
Hemorrhagic Stroke ◽  
The United States ◽  
Care Physician ◽  
County Level ◽  
Medicare Beneficiaries ◽  
Level Data ◽  
Control And Prevention

Introduction: Stroke hospitalization and mortality are influenced by various social determinants. This ecological study aimed to determine the associations between social determinants and stroke hospitalization and outcome at county-level in the United States. Methods: County-level data were recorded from the Centers for Disease Control and Prevention as of January 7, 2020. We considered four outcomes: all-age (1) Ischemic and (2) Hemorrhagic stroke Death rates per 100,000 individuals (ID and HD respectively), and (3) Ischemic and (4) Hemorrhagic stroke Hospitalization rate per 1,000 Medicare beneficiaries (IH and HH respectively). Results: Data of 3,225 counties showed IH (12.5 ± 3.4) and ID (22.2 ± 5.1) were more frequent than HH (2.0 ± 0.4) and HD (9.8 ± 2.1). Income inequality as expressed by Gini Index was found to be 44.6% ± 3.6% and unemployment rate was 4.3% ± 1.5%. Only 29.8% of the counties had at least one hospital with neurological services. The uninsured rate was 11.0% ± 4.7% and people living within half a mile of a park was only 18.7% ± 17.6%. Age-adjusted obesity rate was 32.0% ± 4.5%. In regression models, age-adjusted obesity (OR for IH: 1.11; HH: 1.04) and number of hospitals with neurological services (IH: 1.40; HH: 1.50) showed an association with IH and HH. Age-adjusted obesity (ID: 1.16; HD: 1.11), unemployment (ID: 1.21; HD: 1.18) and income inequality (ID: 1.09; HD: 1.11) showed an association with ID and HD. Park access showed inverse associations with all four outcomes. Additionally, population per primary-care physician was associated with HH while number of pharmacy and uninsured rate were associated with ID. All associations and OR had p ≤0.04. Conclusion: Unemployment and income inequality are significantly associated with increased stroke mortality rates.

scholarly journals The evolution of infant mortality inequality in the United States, 1960–2016

2020 ◽  
Vol 6 (29) ◽  
pp. eaba5908
Author(s):  
Nick Turner ◽  
Kaveh Danesh ◽  
Kelsey Moran
Keyword(s):  
United States ◽  
Infant Mortality ◽  
The United States ◽  
Mortality Rates ◽  
County Level ◽  
Level Data ◽  
Antipoverty Programs ◽  
The Relationship ◽  
Over Time ◽  
Mortality Inequality

What is the relationship between infant mortality and poverty in the United States and how has it changed over time? We address this question by analyzing county-level data between 1960 and 2016. Our estimates suggest that level differences in mortality rates between the poorest and least poor counties decreased meaningfully between 1960 and 2000. Nearly three-quarters of the decrease occurred between 1960 and 1980, coincident with the introduction of antipoverty programs and improvements in medical care for infants. We estimate that declining inequality accounts for 18% of the national reduction in infant mortality between 1960 and 2000. However, we also find that level differences between the poorest and least poor counties remained constant between 2000 and 2016, suggesting an important role for policies that improve the health of infants in poor areas.

scholarly journals A County-Level Examination of the Relationship Between HIV and Social Determinants of Health: 40 States, 2006-2008

2012 ◽  
Vol 6 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Gant Z ◽  
Lomotey M ◽  
Hall H.I ◽  
Hu X ◽  
Guo X ◽  
...  
Keyword(s):  
Income Inequality ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
The United States ◽  
Determinants Of Health ◽  
Physical Factors ◽  
County Level ◽  
Hiv Diagnosis ◽  
Hiv Surveillance ◽  
The Relationship

Background: Social determinants of health (SDH) are the social and physical factors that can influence unhealthy or risky behavior. Social determinants of health can affect the chances of acquiring an infectious disease – such as HIV – through behavioral influences and limited preventative and healthcare access. We analyzed the relationship between social determinants of health and HIV diagnosis rates to better understand the disparity in rates between different populations in the United States. Methods: Using National HIV Surveillance data and American Community Survey data at the county level, we examined the relationships between social determinants of health variables (e.g., proportion of whites, income inequality) and HIV diagnosis rates (averaged for 2006-2008) among adults and adolescents from 40 states with mature name-based HIV surveillance. Results: Analysis of data from 1,560 counties showed a significant, positive correlation between HIV diagnosis rates and income inequality (Pearson correlation coefficient ρ = 0.40) and proportion unmarried – ages >15 (ρ = 0.52). There was a significant, negative correlation between proportion of whites and rates (ρ = -0.67). Correlations were low between racespecific social determinants of health indicators and rates. Conclusions/Implications: Overall, HIV diagnosis rates increased as income inequality and the proportion unmarried increased, and rates decreased as proportion of whites increased. The data reflect the higher HIV prevalence among non-whites. Although statistical correlations were moderate, identifying and understanding these social determinants of health variables can help target prevention efforts to aid in reducing HIV diagnosis rates. Future analyses need to determine whether the higher proportion of singles reflects higher populations of gay and bisexual men.

scholarly journals Quantifying the mortality impact of the 1935 old-age assistance

2021 ◽  
Author(s):  
Gregori Galofré-Vilà ◽  
Martin McKee ◽  
David Stuckler
Keyword(s):  
United States ◽  
Old Age ◽  
Event Study ◽  
Fixed Effects ◽  
Older Persons ◽  
The Elderly ◽  
The United States ◽  
County Level ◽  
Level Data ◽  
Old Age Assistance

Abstract In 1935, the United States introduced the old-age assistance (OAA) program, a means-tested program to help the elderly poor. The OAA improved retirement conditions and aimed to enable older persons to live independently. We use the transition from early elderly plans to OAA and the large differences in payments and eligibility across states to show that OAA reduced mortality by between 30 and 39 percent among those older than 65 years. This finding, based on an event study design, is robust to a range of specifications, a range of fixed effects, placebo tests, and a border-pair policy discontinuity design using county-level data. The largest mortality reductions came from drops in communicable and infectious diseases, such as influenza and nephritis, and mostly affected white citizens.

scholarly journals Are All Politics National? County-Level Social Contexts and Inequality Remediation Attitudes, 2006 to 2012

2021 ◽  
Vol 7 ◽  
pp. 237802312110099
Author(s):  
Andrew M. Lindner ◽  
Jason N. Houle
Keyword(s):  
Income Inequality ◽  
Fixed Effects ◽  
Government Intervention ◽  
Local Level ◽  
General Social Survey ◽  
The United States ◽  
Social Contexts ◽  
County Level ◽  
Social Survey ◽  
Individual Level

Despite growing economic inequality in recent decades, public support for government intervention to address it has been stable. A substantial literature has documented the individual-level demographic, social, and political characteristics that are associated with the extent to which individuals favor government intervention to reduce inequality. However, less work has examined how the local social environments that individuals are embedded in shape attitudes regarding inequality remediation. Using data from the General Social Survey (2006–2012) and other data sources, the authors examine whether local economic and social characteristics are associated with individuals’ support for government intervention to address income inequality in the United States during the Great Recession. Specifically, the authors link restricted General Social Survey data with place-level identifiers to county-level data on local income inequality, racial segregation, and partisan leanings. Broadly, the authors find that although individual-level conditions and year fixed effects are strongly correlated with perceptions about inequality remediation, most local-level characteristics were not strongly nor significantly associated with individual attitudes regarding government intervention to address inequality. These findings suggest that individuals formulate policy stances regarding inequality on the basis of national messaging rather than on observations within their own communities.

Recent Migration Patterns in the Developed World: A Clarification of Some Differences between our and NASA's Findings

1981 ◽  
Vol 13 (2) ◽  
pp. 243-250 ◽  
Author(s):  
D Vining ◽  
R Pallone ◽  
D Plane
Keyword(s):  
Population Growth ◽  
Internal Migration ◽  
Growth Rates ◽  
Rural Areas ◽  
Population Change ◽  
Metropolitan Areas ◽  
The United States ◽  
Migration Patterns ◽  
Regional Population ◽  
Developed World

This paper is a reply to two recently published critiques of our finding of a discontinuity in the recent internal migration patterns of Europe, Japan, and North America. Using data from the HAS A Human Settlements Systems Task, Hall–Hay and Gordon both fail to detect any significant narrowing in the differential between the growth rates of metropolitan areas and the growth rates of rural areas in Europe and Japan over the period 1950–1970 (they concede that this difference has disappeared, and has even been reversed in the United States). Our rejoinder here consists simply of a clarification of our own independent research on regional population change in these same countries. Unlike the IIASA project, this research has been confined, in the case of Europe and Japan, to a study of the trends in net internal migration to their politically and economically dominant core regions, for which data are available for the post-1970 period as well. Most of the disagreement over the presence or absence of a discontinuity in the regional population trends in the countries of western Europe and Japan can be explained by this simple difference in the principal orientations of the two studies, the first towards all metropolitan areas in these countries for the period 1950–1970, and emphasizing the total population growth of these areas, the other towards their densest, richest, and generally most important regions for the longer period 1950–1980, and emphasizing net internal migration to these regions rather than their overall population growth. For there is little doubt, as we demonstrate here, that there has been an abrupt and precipitous reduction in net internal migration towards the core regions of many countries in the developed world in the 1970s, though a comparable reduction may not have taken place to all metropolitan areas in the aggregate. Gordon's and Hall–Hay's claim to have rebutted our thesis is thus seen to be based on a misconception of the subject of our study.

scholarly journals Timing of social distancing policies and COVID-19 mortality: county-level evidence from the U.S.

2021 ◽  
Author(s):  
Catalina Amuedo-Dorantes ◽  
Neeraj Kaushal ◽  
Ashley N. Muchow
Keyword(s):  
New York ◽  
Political Ideology ◽  
Death Rate ◽  
The United States ◽  
County Level ◽  
Level Data ◽  
Level Information ◽  
Alternative Measures ◽  
The U.S ◽  
Pharmaceutical Interventions

AbstractUsing county-level data on COVID-19 mortality and infections, along with county-level information on the adoption of non-pharmaceutical interventions (NPIs), we examine how the speed of NPI adoption affected COVID-19 mortality in the United States. Our estimates suggest that adopting safer-at-home orders or non-essential business closures 1 day before infections double can curtail the COVID-19 death rate by 1.9%. This finding proves robust to alternative measures of NPI adoption speed, model specifications that control for testing, other NPIs, and mobility and across various samples (national, the Northeast, excluding New York, and excluding the Northeast). We also find that the adoption speed of NPIs is associated with lower infections and is unrelated to non-COVID deaths, suggesting these measures slowed contagion. Finally, NPI adoption speed appears to have been less effective in Republican counties, suggesting that political ideology might have compromised their efficacy.

Trust in Government and the American Public’s Responsiveness to Rising Inequality

2019 ◽  
Vol 73 (4) ◽  
pp. 790-804 ◽  
Author(s):  
David Macdonald
Keyword(s):  
United States ◽  
Public Opinion ◽  
Income Inequality ◽  
State Level ◽  
Political Trust ◽  
The United States ◽  
Trust In Government ◽  
Combine Data ◽  
Election Studies ◽  
The Relationship

The United States has become increasingly unequal. Income inequality has risen dramatically since the 1970s, yet public opinion toward redistribution has remained largely unchanged. This is puzzling, given Americans’ professed concern regarding, and knowledge of, rising inequality. I argue that trust in government can help to reconcile this. I combine data on state-level income inequality with survey data from the Cumulative American National Election Studies (CANES) from 1984 to 2016. I find that trust in government conditions the relationship between inequality and redistribution, with higher inequality prompting demand for government redistribution, but only among politically trustful individuals. This holds among conservatives and non-conservatives and among the affluent and non-affluent. These findings underscore the relevance of political trust in shaping attitudes toward inequality and economic redistribution and contribute to our understanding of why American public opinion has not turned in favor of redistribution during an era of rising income inequality.

scholarly journals 694 Insufficient sleep linked with higher COVID-19 infection cases and deaths in the United States

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A271-A271
Author(s):  
Azizi Seixas ◽  
Nicholas Pantaleo ◽  
Samrachana Adhikari ◽  
Michael Grandner ◽  
Giardin Jean-Louis
Keyword(s):  
Regression Models ◽  
Negative Binomial ◽  
The United States ◽  
Poor Sleep ◽  
County Level ◽  
Infection Rates ◽  
Insufficient Sleep ◽  
Death Rates ◽  
Rural Counties ◽  
The Relationship

Abstract Introduction Causes of COVID-19 burden in urban, suburban, and rural counties are unclear, as early studies provide mixed results implicating high prevalence of pre-existing health risks and chronic diseases. However, poor sleep health that has been linked to infection-based pandemics may provide additional insight for place-based burden. To address this gap, we investigated the relationship between habitual insufficient sleep (sleep <7 hrs./24 hr. period) and COVID-19 cases and deaths across urban, suburban, and rural counties in the US. Methods County-level variables were obtained from the 2014–2018 American community survey five-year estimates and the Center for Disease Control and Prevention. These included percent with insufficient sleep, percent uninsured, percent obese, and social vulnerability index. County level COVID-19 infection and death data through September 12, 2020 were obtained from USA Facts. Cumulative COVID-19 infections and deaths for urban (n=68), suburban (n=740), and rural (n=2331) counties were modeled using separate negative binomial mixed effects regression models with logarithmic link and random state-level intercepts. Zero-inflated models were considered for deaths among suburban and rural counties to account for excess zeros. Results Multivariate regression models indicated positive associations between cumulative COVID-19 infection rates and insufficient sleep in urban, suburban and rural counties. The incidence rate ratio (IRR) for urban counties was 1.03 (95% CI: 1.01 – 1.05), 1.04 (95% CI: 1.02 – 1.05) for suburban, and 1.02 (95% CI: 1.00 – 1.03) rural counties.. Similar positive associations were observed with county-level COVID-19 death rates, IRR = 1.11 (95% CI: 1.07 – 1.16) for urban counties, IRR = 1.04 (95% CI: 1.01 – 1.06) for suburban counties, and IRR = 1.03 (95% CI: 1.01 – 1.05) for rural counties. Level of urbanicity moderated the association between insufficient sleep and COVID deaths, but not for the association between insufficient sleep and COVID infection rates. Conclusion Insufficient sleep was associated with COVID-19 infection cases and mortality rates in urban, suburban and rural counties. Level of urbanicity only moderated the relationship between insufficient sleep and COVID death rates. Future studies should investigate individual-level analysis to understand the role of sleep mitigating COVID-19 infection and death rates. Support (if any) NIH (K07AG052685, R01MD007716, R01HL142066, K01HL135452, R01HL152453

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