scholarly journals Defining Poverty as an Eligibility Requirement for Supportive Services

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 428-429
Author(s):  
Lauren Ring ◽  
Allen Glicksman
Keyword(s):  
The United States ◽  
Economic Security ◽  
Health Study ◽  
Service Needs ◽  
Federal Poverty Level ◽  
Supportive Services ◽  
Poverty Level ◽  
Poor Health Status ◽  
Using Data ◽  
Eligibility Requirement

Abstract Deciding which individuals qualify as “poor” often depends on how each country or municipality defines the term ‘poverty’. In the United States, program eligibility is often tied to the Federal Poverty Level (FPL), using 100% of the FPL as a cut-off for receipt of services. However, research has shown that incomes of 200% of the FPL and higher are often needed to establish even minimum levels of economic security. Using data from an omnibus health study conducted in 2018 that included 1,581 persons ages 60+ who were asked about their health and service needs, we compared persons making 100% of the FPL or less to persons making 101%-199% and 200%+, respectively. Results show that poor health status and need for services among persons in the 101%-199% are similar to those with incomes less than 100% FPL, and significantly higher than persons with incomes at 200%+ of the FPL.

scholarly journals Inequality in Context: Neighborhood Environments and the Association Among Education and Health

2018 ◽  
Author(s):  
Michael H Esposito
Keyword(s):  
Depressive Symptomatology ◽  
Well Being ◽  
The United States ◽  
Health Study ◽  
Adult Health ◽  
College Degree ◽  
Multilevel Regression ◽  
Tightly Coupled ◽  
Neighborhood Environments ◽  
Using Data

The association among a college degree and health is know to vary, in strength, across subsections of the United States population. Recent literature suggests that educational gradients in health are particularly dependent on contextual environments; higher-level social features, such as state of residence, have indeed been shown to modify how advanced educational credentials matters to well-being. To add resolution to this emerging insight, this study examines how \neighborhood environments, an especially salient level of geographic organization, impact educational gradients in the US. Using data from the Chicago Community Adult Health Study (n = 3,105) and Bayesian multilevel regression models, I examine how educational disparities in self-rated health and depressive symptomatology, between college and non-college degree holders, grow/shrink in response to a neighborhood-provided resource and with exposure to a neighborhood-level health challenge. Findings suggest that how tightly coupled a college degree is with well-being is strongly contingent upon one's immediate external risks, but less so on one's access to neighborhood social resources.

Effects of Medicaid Expansion on Poverty Disparities in Health Insurance Coverage

2021 ◽  
Author(s):  
Yilu Lin ◽  
Alisha Monnette ◽  
Lizheng Shi
Keyword(s):  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
The United States ◽  
Community Survey ◽  
Medicaid Expansion ◽  
Market Exchange ◽  
Federal Poverty Level ◽  
Poverty Level ◽  
The Impact ◽  
Poverty Levels

Abstract Background: More than 30 States have either expanded Medicaid or considering expansion. The coverage gains from this policy is well documented, however, the impacts of its increasing coverage on poverty disparity are unclear at national level.Method: American Community Survey (2012-2018) was used to examine the effects of Medicaid expansion (ME) on poverty disparity in insurance coverage for nonelderly adults in the United States. Differences-in-differences-in-differences design was used to analyze the trends in uninsured rates (UR) by different poverty levels: <138%, 138–400% and >400% federal poverty level (FPL).Results: Compared with UR in 2012, UR in 2018 decreased by 10.75%, 6.42%, and 1.11% for <138%, 138-400%, and >400% FPL. From 2012-2018, >400% FPL group continuously had the lowest UR and <138% FPL group had the highest UR. Compared with ≥ 138% FPL groups, there was a 2.54% reduction in uninsured risk after ME among <138% FPL group in ME states versus control states. After eliminating the impact of the ACA market exchange premium subsidy, 3.18% decrease was estimated. Conclusion: Poverty disparity in UR improved with ME. However, <138% FPL population are still at a higher risk for being uninsured.

Identifying Risk Factors for Acute Asthma Attacks: Application of Machine Learning in a Country-Wide Mobile Health Study (Preprint)

2021 ◽  
Author(s):  
Kevin Cheuk Him Tsang ◽  
Hilary Pinnock ◽  
Andrew M. Wilson ◽  
Syed Ahmar Shah
Keyword(s):  
Risk Factors ◽  
Mobile Health ◽  
The United States ◽  
Data Driven ◽  
Health Study ◽  
Future Research ◽  
Activity Levels ◽  
Factors Associated ◽  
Asthma Patients ◽  
Using Data

BACKGROUND Asthma is a variable long-term condition that affects 339 million people worldwide who are at risk of acute deteriorations or attacks. Because triggers, patterns, and risk of attacks vary from person to person, asthma can be difficult to study in small cohorts, but recent mobile-based studies like the Asthma Mobile Health Study (AMHS) provide an important opportunity to collect data from large populations. The AMHS is a publicly available dataset collected using a smartphone app from 10,010 asthma patients across the United States. OBJECTIVE Using data-driven methods, we aimed to identify different clusters of asthma patients based on patterns of clinical deterioration that may lead to loss of productivity, and determine key factors associated with each patient cluster. METHODS Based on existing asthma knowledge, 27 variables about the patient’s history, demographics, behaviour, and self-reported symptoms were extracted to generate 63 features. Of the 63 features, 10 were markers of attacks that were used to cluster patients with the k-means algorithm. We subsequently used a supervised learning approach, least absolute shrinkage and selection operator (LASSO), to rank the remaining 53 features and identify key risk factors associated with each patient cluster. The models were validated with 10-fold cross-validation. RESULTS Using data from 827 participants of AMHS with sufficient data, k-means clustering formed four patient clusters based on unscheduled healthcare usage and missed work. The most important factors contributing to the clustering were nocturnal symptoms, activity limitation, and sex. Being female, and having asthma that affects sleep and activity levels, were the key risk factors associated with having an asthma attack that necessitates the need for unscheduled medical care and time off work. Our internal validation resulted in an area under the curve (AUC) of up to 0.80. CONCLUSIONS The data-driven approach found risk factors associated with increased levels of asthma attacks that reflected those recognised in clinical practice. Future research about asthma risk factors should include these measures and also consider including work and school absence as markers of asthma attacks.

scholarly journals 974. The Effects of Changes in State-Level Policies Affecting Eligibility for the Supplemental Nutrition Assistance Program (SNAP) on Annual HIV Diagnoses in the United States

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S516-S516
Author(s):  
Aaron Richterman ◽  
Louise Ivers ◽  
Alexander Tsai ◽  
Jason Block
Keyword(s):  
United States ◽  
Food Insecurity ◽  
The United States ◽  
Inverse Association ◽  
Federal Poverty Level ◽  
Poverty Level ◽  
Assistance Program ◽  
State Income ◽  
Nutrition Assistance ◽  
Time Varying Covariates

Abstract Background The connection between food insecurity and HIV outcomes is well-established. The Supplementary Nutrition Assistance Program (SNAP), the primary program in the United States that addresses food insecurity, may have collateral impacts on HIV incidence, but the extent to which it does is unknown. “Broad-based categorical eligibility” for SNAP is a federal policy that provides a mechanism for states to increase the income or asset limits for SNAP eligibility. The Department of Agriculture under the Trump Administration has proposed eliminating this policy. Methods We estimated the association between the number of new HIV diagnoses from 2010 to 2014 for each state and (1) state income limits for SNAP eligibility as a percentage of the federal poverty level and (2) state asset limits for SNAP eligibility (increased/eliminated vs. unchanged). We fitted multivariable negative binomial regression models with annual incidence of HIV diagnoses specified as the outcome; SNAP policies as the primary explanatory variable of interest; state and year fixed effects; and time-varying covariates related to the costs of food, health care, housing, employment, SNAP outreach, and total spending on Temporary Assistance for Needy Families (TANF) programs. Results From 2010 to 2014, 204,034 new HIV diagnoses occurred in the United States. HIV diagnoses within states had a statistically significant inverse association with state income limits for SNAP eligibility (IRR 0.94 per increase in the income limit by 35% of federal poverty level, 95% CI 0.91-0.98), but no statistically significant association with state asset limits (increased asset limit vs. no change, IRR 1.02, 95% CI 0.94-1.10; eliminated asset limit vs. no change, IRR 1.04, 95% CI 0.99-1.10) (Table). Table Conclusion State income limits for SNAP eligibility were inversely associated with the number of new HIV diagnoses for states between 2010-2014. Proposals to eliminate the use of broad-based categorical eligibility to increase the income limit for SNAP may undercut efforts to end the HIV epidemic in the United States. Disclosures All Authors: No reported disclosures

scholarly journals US Foreign-Born Workers in the Global Pandemic: Essential and Marginalized

2020 ◽  
pp. 231150242095275
Author(s):  
Donald Kerwin* ◽  
Robert Warren*
Keyword(s):  
New York ◽  
Labor Force ◽  
Homeland Security ◽  
New York State ◽  
National Level ◽  
The United States ◽  
Economic Security ◽  
Foreign Born ◽  
Poverty Level ◽  
The Us

This article provides detailed estimates of foreign-born (immigrant) workers in the United States who are employed in “essential critical infrastructure” sectors, as defined by the Cybersecurity and Infrastructure Security Agency (CISA) of the US Department of Homeland Security (DHS) (DHS 2020). Building on earlier work by the Center for Migration Studies (CMS), the article offers exhaustive estimates on essential workers on a national level, by state, for large metropolitan statistical areas (MSAs), and for smaller communities that heavily rely on immigrant labor. It also reports on these workers by job sector; immigration status; eligibility for tax rebates under the Coronavirus Aid, Relief, and Economic Security Act (CARES Act); and other characteristics. It finds that: Sixty-nine percent of all immigrants in the US labor force and 74 percent of undocumented workers are essential workers, compared to 65 percent of the native-born labor force. Seventy percent of refugees and 78 percent of Black refugees are essential workers. In all but eight US states, the foreign-born share of the essential workforce equals or exceeds that of all foreign-born workers, indicating that immigrant essential workers are disproportionately represented in the labor force. The percentage of undocumented essential workers exceeds that of native-born essential workers by nine percentage points in the 15 states with the largest labor force. In the ten largest MSAs, the percentages of undocumented and naturalized essential workers exceed the percentage of native-born essential workers by 12 and 6 percent, respectively. A total of 6.2 million essential workers are not eligible for relief payments under the CARES Act, as well as large numbers of their 3.8 million US citizen children (younger than age 17), including 1.2 million US citizen children living in households below the poverty level. The foreign-born comprise 33 percent of health care workers in New York State, 32 percent in California, 31 percent in New Jersey, 28 percent in Florida, 25 percent in Nevada and Maryland, 24 percent in Hawaii, 23 percent in Massachusetts, and 19 percent in Texas. Section I of the article describes the central policy paradox for foreign-born workers during the COVID-19 pandemic: that they are “essential” at very high rates, but many lack status and they have been marginalized by US immigration and COVID-19-related policies. Section II sets forth the article’s main findings. Section III outlines major policy recommendations.

scholarly journals Neighborhood Inequities in Tobacco Retailer Density and the Presence of Tobacco-Selling Pharmacies and Tobacco Shops

2021 ◽  
pp. 109019812110083
Author(s):  
Amanda Y. Kong ◽  
Paul L. Delamater ◽  
Nisha C. Gottfredson ◽  
Kurt M. Ribisl ◽  
Chris D. Baggett ◽  
...  
Keyword(s):  
Regression Models ◽  
The United States ◽  
Federal Poverty Level ◽  
Poverty Level ◽  
Logistic Regression Models ◽  
Black Residents ◽  
Multivariable Regression ◽  
Density Measure ◽  
Multivariable Regression Models ◽  
Vacant Housing

Studies document inequitable tobacco retailer density by neighborhood sociodemographics, but these findings may not be robust to different density measures. Policies to reduce density may be less equitable depending on how the presence of store types differs by neighborhood characteristics. We built a 2018 list of probable tobacco retailers in the United States and calculated four measures of density for all census tracts ( N = 71,495), including total count, and number of retailers per 1,000 people, square mile, and kilometers of roadway. We fit multivariable regression models testing associations between each density measure and tract-level sociodemographics. We fit logistic regression models testing associations between sociodemographics and the presence of a tobacco-selling pharmacy or tobacco shop. Across all measures, tracts with a greater percentage of residents living below 150% of the federal poverty level (FPL) had higher density. A higher percentage of Black residents, Hispanic or Latino residents, and vacant housing was inconsistently associated with density across measures. Neighborhoods with a greater percentage of Black residents had a lower odds of having a pharmacy (adjusted odds ratio [a OR] = 0.96, 95% confidence interval [CI; 0.95, 0.97]) and tobacco shop (a OR = 0.87, CI [0.86, 0.89]), while those with a greater percentage of residents living below 150% FPL had greater odds of having a tobacco shop (a OR = 1.18, CI [1.16, 1.20]). Researchers and policymakers should consider how various measures of retailer density may capture different aspects of the environment. Furthermore, there may be an inequitable impact of retailer-specific policies on tobacco availability.

scholarly journals Association of Breastfeeding and the Federal Poverty Level: National Survey of Family Growth, 2011–2013

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
R. Constance Wiener ◽  
Usha Sambamoorthi ◽  
Sarah E. Hayes ◽  
Ilana R. Azulay Chertok
Keyword(s):  
National Survey ◽  
Household Income ◽  
The United States ◽  
Federal Poverty Level ◽  
Poverty Level ◽  
Statistical Adjustment ◽  
Family Growth ◽  
Healthy People 2020 ◽  
Logistic Regressions ◽  
Race Ethnicity

Breastfeeding is strongly endorsed in the Healthy People 2020 goals; however, there remain many disparities in breastfeeding prevalence. The purpose of this study was to examine the association between breastfeeding and the Federal Poverty Level in the United States. Data from 5,397 women in the National Survey of Family Growth 2011–2013 survey were included in this study. The data were analyzed for descriptive features and logistic regressions of the Federal Poverty Level on breastfeeding. There were 64.1% of women who reported breastfeeding. Over one-third (35.2%) of women reported having a household income of 0–99% of the Federal Poverty Level. There were 15.2% of women who reported an income of 400% and above the Federal Poverty Level. With statistical adjustment for maternal age, race/ethnicity, education, marital status, parity, preterm birth, birth weight, insurance, and dwelling, the Federal Poverty Level was not significantly associated with breastfeeding. In this recent survey of mothers, Federal Poverty Level was not shown to be a significant factor in breastfeeding.

scholarly journals Gender Differences in Pain: Examining Explanations for the Association

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 894-895
Author(s):  
Cherish Michael ◽  
Anne Barrett
Keyword(s):  
Mental Health ◽  
Gender Differences ◽  
Social Relationships ◽  
Later Life ◽  
The United States ◽  
Economic Security ◽  
The Body ◽  
Physical And Mental Health ◽  
Mediating Role ◽  
Using Data

Abstract Physical pain is a gendered experience: Women report higher levels of it than do men. This pattern may stem from differences in experiences of the body. Women are socialized to be attentive to its functioning, appearance, and sensations, while men are discouraged from paying much attention to their bodies. Little is known, however, about the precise social and economic pathways leading to gender differences in pain, especially in middle and later life when pain is most prevalent. We examine this issue using data from Wave 3 of Midlife in the United States (2013-2014). We consider four possible explanations for women’s more frequent reports of pain: economic security, physical and mental health, social relationships, and discrimination. Results indicate that women are more likely than men to report experiencing chronic pain, as well as greater effects of it on their everyday lives. However, only two of the explanations contributed to explaining this association. Economic security and physical and mental health accounted for substantial portions of the association between gender and pain – 57 and 73 percent, respectively. In contrast, no mediating role was observed for either women’s social relationships, in particular the greater strain they experience in them, or their more frequent reports of everyday and lifetime discrimination. The final model including all the possible explanations revealed that gender was no longer significant, suggesting that middle-aged and older women’s greater pain is explained by their worse health and economic circumstances.

Predicting and Modeling Superintendent Turnover

2003 ◽  
Vol 13 (3) ◽  
pp. 328-346 ◽  
Author(s):  
Gerald L. Natkin ◽  
Bruce S. Cooper ◽  
James A. Alborano ◽  
Art Padilla ◽  
Sujit K. Ghosh
Keyword(s):  
North Carolina ◽  
School Districts ◽  
Postgraduate Education ◽  
The United States ◽  
Management Support ◽  
Poverty Level ◽  
Superintendent Turnover ◽  
Superintendent Tenure ◽  
Random Samples ◽  
Using Data

This study examines the longevity in office of superintendents in 292 school districts, using data from the period 1975-99. Random samples of districts from across the United States, as well as all school districts from North Carolina, were studied. Data were analyzed by survival analysis techniques, using information on superintendents, districts, and school boards as predictors. Superintendent tenure has not changed significantly since 1975-79, averaging 6–7 years over the whole period. Significantly related to survival in office were level of school board involvement in management, support for needed construction, merger of school systems, district poverty level, and superintendent postgraduate education.

scholarly journals US Foreign-Born Workers in the Global Pandemic: Essential and Marginalized

2020 ◽  
Vol 8 (3) ◽  
pp. 282-300
Author(s):  
Donald Kerwin* ◽  
Robert Warren*
Keyword(s):  
Labor Force ◽  
Homeland Security ◽  
New York State ◽  
National Level ◽  
The United States ◽  
Economic Security ◽  
Foreign Born ◽  
Poverty Level ◽  
Executive Summary ◽  
The Us

Executive Summary This article provides detailed estimates of foreign-born (immigrant) workers in the United States who are employed in “essential critical infrastructure” sectors, as defined by the Cybersecurity and Infrastructure Security Agency (CISA) of the US Department of Homeland Security (DHS) (DHS 2020). Building on earlier work by the Center for Migration Studies (CMS), the article offers exhaustive estimates on essential workers on a national level, by state, for large metropolitan statistical areas (MSAs), and for smaller communities that heavily rely on immigrant labor. It also reports on these workers by job sector; immigration status; eligibility for tax rebates under the Coronavirus Aid, Relief, and Economic Security Act (CARES Act); and other characteristics. It finds that: Sixty-nine percent of all immigrants in the US labor force and 74 percent of undocumented workers are essential workers, compared to 65 percent of the native-born labor force. Seventy percent of refugees and 78 percent of Black refugees are essential workers. In all but eight US states, the foreign-born share of the essential workforce equals or exceeds that of all foreign-born workers, indicating that immigrant essential workers are disproportionately represented in the labor force. The percentage of undocumented essential workers exceeds that of native-born essential workers by nine percentage points in the 15 states with the largest labor force. In the ten largest MSAs, the percentages of undocumented and naturalized essential workers exceed the percentage of native-born essential workers by 12 and 6 percent, respectively. A total of 6.2 million essential workers are not eligible for relief payments under the CARES Act, as well as large numbers of their 3.8 million US citizen children (younger than age 17), including 1.2 million US citizen children living in households below the poverty level. The foreign-born comprise 33 percent of health care workers in New York State, 32 percent in California, 31 percent in New Jersey, 28 percent in Florida, 25 percent in Nevada and Maryland, 24 percent in Hawaii, 23 percent in Massachusetts, and 19 percent in Texas. Section I of the article describes the central policy paradox for foreign-born workers during the COVID-19 pandemic: that they are “essential” at very high rates, but many lack status and they have been marginalized by US immigration and COVID-19-related policies. Section II sets forth the article’s main findings. Section III outlines major policy recommendations.

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