Geographic Differences in Social Determinants of Health Among US-Born and Non–US-Born Hispanic/Latino Adults With Diagnosed HIV Infection, United States and Puerto Rico, 2017

2021 ◽  
pp. 003335492097053
Author(s):  
Zanetta Gant ◽  
Shacara Johnson Lyons ◽  
Chan Jin ◽  
André Dailey ◽  
Ndidi Nwangwu-Ike ◽  
...  
Keyword(s):  
United States ◽  
Puerto Rico ◽  
Household Income ◽  
The United States ◽  
Median Household Income ◽  
Federal Poverty Level ◽  
Poverty Level ◽  
Hiv Diagnosis ◽  
Latino Adults ◽  
Us Census

Objective HIV disproportionately affects Hispanic/Latino people in the United States, and factors other than individual attributes may be contributing to these differences. We examined differences in the distribution of HIV diagnosis and social determinants of health (SDH) among US-born and non–US-born Hispanic/Latino adults in the United States and Puerto Rico. Methods We used data reported to the Centers for Disease Control and Prevention’s National HIV Surveillance System (NHSS) to determine US census tract–level HIV diagnosis rates and percentages among US-born and non–US-born Hispanic/Latino adults aged ≥18 for 2017. We merged data from the US Census Bureau’s American Community Survey with NHSS data to examine regional differences in federal poverty level, education, median household income, employment, and health insurance coverage among 8648 US-born (n = 3328) and non–US-born (n = 5320) Hispanic/Latino adults. Results A comparison of US-born and non–US-born men by region showed similar distributions of HIV diagnoses. The largest percentages occurred in census tracts where ≥19% of residents lived below the federal poverty level, ≥18% did not finish high school, the median household income was <$40 000 per year, ≥6% were unemployed, and ≥16% did not have health insurance. A comparison of US-born and non–US-born women by region showed similar distributions. Conclusion The findings of higher numbers of HIV diagnoses among non–US-born Hispanic/Latino adults than among US-born Hispanic/Latino adults, regional similarities in patterns of SDH and HIV percentages and rates, and Hispanic/Latino adults faring poorly in each SDH category are important for understanding SDH barriers that may be affecting Hispanic/Latino adults with HIV in the United States.

scholarly journals Mass Deportations Would Impoverish US Families and Create Immense Social Costs

2017 ◽  
Vol 5 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Robert Warren ◽  
Donald Kerwin
Keyword(s):  
United States ◽  
Household Income ◽  
The United States ◽  
Median Household Income ◽  
Poverty Level ◽  
Executive Summary ◽  
College Degrees ◽  
The Us ◽  
Us Census ◽  
Mixed Status

Executive Summary1 This paper provides a statistical portrait of the US undocumented population, with an emphasis on the social and economic condition of mixed-status households - that is, households that contain a US citizen and an undocumented resident. It is based primarily on data compiled by the Center for Migration Studies (CMS). Major findings include the following: • There were 3.3 million mixed-status households in the United States in 2014. • 6.6 million US-born citizens share 3 million households with undocumented residents (mostly their parents). Of these US-born citizens, 5.7 million are children (under age 18). • 2.9 million undocumented residents were 14 years old or younger when they were brought to the United States. • Three-quarters of a million undocumented residents are self-employed, having created their own jobs and in the process, creating jobs for many others. • A total of 1.3 million, or 13 percent of the undocumented over age 18, have college degrees. • Of those with college degrees, two-thirds, or 855,000, have degrees in four fields: engineering, business, communications, and social sciences. • Six million undocumented residents, or 55 percent of the total, speak English well, very well, or only English. • The unemployment rate for the undocumented was 6.6 percent, the same as the national rate in January 2014.2 • Seventy-three percent had incomes at or above the poverty level. • Sixty-two percent have lived in the United States for 10 years or more. • Their median household income was $41,000, about $12,700 lower than the national figure of $53,700 in 2014 (US Census Bureau 2015). Based on this profile, a massive deportation program can be expected to have the following major consequences: • Removing undocumented residents from mixed-status households would reduce median household income from $41,300 to $22,000, a drop of $19,300, or 47 percent, which would plunge millions of US families into poverty. • If just one-third of the US-born children of undocumented residents remained in the United States following a mass deportation program, which is a very low estimate, the cost of raising those children through their minority would total $118 billion. • The nation's housing market would be jeopardized because a high percentage of the 1.2 million mortgages held by households with undocumented immigrants would be in peril. • Gross domestic product (GDP) would be reduced by 1.4 percent in the first year, and cumulative GDP would be reduced by $4.7 trillion over 10 years. CMS derived its population estimates for 2014 using a series of statistical procedures that involved the analysis of data collected by the US Census Bureau's American Community Survey (ACS). The privacy of all respondents in the survey is legally mandated, and, for the reasons listed in the Appendix, the identity of undocumented residents cannot be derived from the data. A detailed description of the methodology used to develop the estimates is available at the CMS website.3

scholarly journals County-Level Social Distancing and Policy Impact in the United States: A Dynamical Systems Model

10.2196/23902 ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. e23902
Author(s):  
Kevin L McKee ◽  
Ian C Crandell ◽  
Alexandra L Hanlon
Keyword(s):  
United States ◽  
Differential Equation ◽  
Population Density ◽  
Household Income ◽  
The United States ◽  
Policy Impact ◽  
County Level ◽  
Median Household Income ◽  
Social Distancing

Background Social distancing and public policy have been crucial for minimizing the spread of SARS-CoV-2 in the United States. Publicly available, county-level time series data on mobility are derived from individual devices with global positioning systems, providing a variety of indices of social distancing behavior per day. Such indices allow a fine-grained approach to modeling public behavior during the pandemic. Previous studies of social distancing and policy have not accounted for the occurrence of pre-policy social distancing and other dynamics reflected in the long-term trajectories of public mobility data. Objective We propose a differential equation state-space model of county-level social distancing that accounts for distancing behavior leading up to the first official policies, equilibrium dynamics reflected in the long-term trajectories of mobility, and the specific impacts of four kinds of policy. The model is fit to each US county individually, producing a nationwide data set of novel estimated mobility indices. Methods A differential equation model was fit to three indicators of mobility for each of 3054 counties, with T=100 occasions per county of the following: distance traveled, visitations to key sites, and the log number of interpersonal encounters. The indicators were highly correlated and assumed to share common underlying latent trajectory, dynamics, and responses to policy. Maximum likelihood estimation with the Kalman-Bucy filter was used to estimate the model parameters. Bivariate distributional plots and descriptive statistics were used to examine the resulting county-level parameter estimates. The association of chronology with policy impact was also considered. Results Mobility dynamics show moderate correlations with two census covariates: population density (Spearman r ranging from 0.11 to 0.31) and median household income (Spearman r ranging from –0.03 to 0.39). Stay-at-home order effects were negatively correlated with both (r=–0.37 and r=–0.38, respectively), while the effects of the ban on all gatherings were positively correlated with both (r=0.51, r=0.39). Chronological ordering of policies was a moderate to strong determinant of their effect per county (Spearman r ranging from –0.12 to –0.56), with earlier policies accounting for most of the change in mobility, and later policies having little or no additional effect. Conclusions Chronological ordering, population density, and median household income were all associated with policy impact. The stay-at-home order and the ban on gatherings had the largest impacts on mobility on average. The model is implemented in a graphical online app for exploring county-level statistics and running counterfactual simulations. Future studies can incorporate the model-derived indices of social distancing and policy impacts as important social determinants of COVID-19 health outcomes.

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

A Potential Role of the Widespread Use of Microwave Ovens in the Obesity Epidemic

2018 ◽  
Vol 7 (2) ◽  
pp. 340-348 ◽  
Author(s):  
Satoshi Kanazawa ◽  
Marie-Therese von Buttlar
Keyword(s):  
United States ◽  
Household Income ◽  
The United States ◽  
Dietary Habit ◽  
Median Household Income ◽  
Extreme Obesity ◽  
Obesity Epidemic ◽  
British Cohort Study ◽  
Highly Correlated

Organisms acquire more calories from eating hot food than eating the identical food cold; thus, the widespread use of microwave ovens might have played a small role in the current obesity epidemic, just as the widespread use of refrigerators might have retarded the historic increase in obesity a century ago. Analysis of the British Cohort Study showed that, net of dietary habit, physical activities, genetic predisposition, and other demographic factors, the ownership of a microwave was associated with an increase of .781 in body mass index (BMI) and 2.1 kg in weight (when the ownership of other kitchen appliances was not associated with increased BMI or weight), and it more than doubled the odds of being overweight. In the United States from 1960 to 2015, the adult overweight, obesity, and extreme obesity rates were very highly correlated ( r = .94–.98) with the proportion of households with microwaves, and it was not because both were consequences of increasing wealth. Net of median household income, the proportion of households with microwaves was very strongly ( ds > 1.0) associated with adult overweight, obesity, and extreme obesity rates, while median household income was not at all associated with them. Individual data from the United Kingdom and historical data from the United States highlighted the possible role of the widespread use of microwave ovens in the obesity epidemic.

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 Visualizing Variation in Majority-Black Suburbs in the United States

2021 ◽  
Vol 7 ◽  
pp. 237802312110655
Author(s):  
Kiara Wyndham Douds ◽  
R. L’Heureux Lewis-McCoy ◽  
Kimberley Johnson
Keyword(s):  
United States ◽  
Middle Class ◽  
Household Income ◽  
Black Population ◽  
The United States ◽  
Median Household Income ◽  
Socioeconomically Disadvantaged ◽  
Metropolitan Statistical Areas ◽  
Housing Age

The aim of this visualization is to highlight sociodemographic variation among Black suburbs and spur further research on them. The authors provide a sociodemographic portrait of Black suburbs, defined as those that are more than 50 percent Black, to highlight their prevalence and variety. The 100 largest metropolitan statistical areas in 2018 contained 413 Black suburbs, representing 5 percent of all suburbs. The authors examine distributions of Black suburbs on two characteristics, median household income and housing age, to make two points. First, Black suburbs feature substantial sociodemographic variation in terms of both income and housing age. Second, this variation is not primarily a function of suburbs’ Black population share. Contrary to common assumptions, Black suburbs are not all older suburbs populated by the socioeconomically disadvantaged but include newer, middle-class, and affluent places as well.

The Question of Racial Mixing in the American Possessions

2017 ◽  
Author(s):  
Paul Schor
Keyword(s):  
United States ◽  
Puerto Rico ◽  
The United States ◽  
Virgin Islands ◽  
Racial Classification ◽  
National History ◽  
Us Virgin Islands ◽  
Black And White ◽  
The Us ◽  
Us Census

This chapter discusses the imposition of the US system of racial classification in the US Virgin Islands, Puerto Rico, and Hawaii. The original use in certain US territories of a “mixed” racial category highlights the national norm that made mulattoes into “lighter-skinned” blacks. In the various territories acquired by the United States after 1898, a rigid imposition of the categories of the US census was difficult because they were the product of a national history that had not been shared. Whether in the US Virgin Islands, Puerto Rico, or Hawaii the perception of what made a person black, white, or mulatto was very different from North American usage, showing that binary black and white mainland tradition was not working there.

scholarly journals An Examination of Geographic Differences in Social Determinants of Health Among Women with Diagnosed HIV in the United States and Puerto Rico, 2017

2021 ◽  
Vol 15 (1) ◽  
pp. 10-20
Author(s):  
Ndidi Nwangwu-Ike ◽  
Chan Jin ◽  
Zanetta Gant ◽  
Shacara Johnson ◽  
Alexandra B. Balaji
Keyword(s):  
United States ◽  
Puerto Rico ◽  
Health Insurance ◽  
Social Determinants ◽  
Census Tract ◽  
The United States ◽  
Adult Women ◽  
Hiv Diagnosis ◽  
Census Tracts ◽  
Census Tract Level

Objective: To examine differences, at the census tract level, in the distribution of human immunodeficiency virus (HIV) diagnoses and social determinants of health (SDH) among women with diagnosed HIV in 2017 in the United States and Puerto Rico. Background: In the United States, HIV continues to disproportionately affect women, especially minority women and women in the South. Methods: Data reported in the National HIV Surveillance System (NHSS) of the Centers for Disease Control and Prevention were used to determine census tract-level HIV diagnosis rates and percentages among adult women (aged ≥18 years) in 2017. Data from the American Community Survey were combined with NHSS data to examine regional differences in federal poverty status, education level, income level, employment status, and health insurance coverage among adult women with diagnosed HIV infection in the United States and Puerto Rico. Results: In the United States and Puerto Rico, among 6,054 women who received an HIV diagnosis in 2017, the highest rates of HIV diagnoses generally were among those who lived in census tracts where the median household income was less than $40,000; at least 19% lived below the federal poverty level, at least 18% had less than a high school diploma, and at least 16% were without health insurance. Conclusion: This study is the first of its kind and gives insight into how subpopulations of women are affected differently by the likelihood of an HIV diagnosis. The findings show that rates of HIV diagnosis were highest among women who lived in census tracts having the lowest income and least health coverage.

Educational Attainment and Suicide Rates in the United States

2005 ◽  
Vol 97 (1) ◽  
pp. 25-28 ◽  
Author(s):  
Ernest L. Abel ◽  
Michael L. Kruger
Keyword(s):  
Higher Education ◽  
United States ◽  
Educational Attainment ◽  
Suicide Rate ◽  
Household Income ◽  
College Graduates ◽  
The United States ◽  
Median Household Income ◽  
Suicide Rates ◽  
The Relationship

We examined the relationship between educational attainment and suicide rate in the United States for 2001. Suicide rates, adjusted for age, were compared with percentage of college graduates, median household income, and poverty in 50 states in 2001. The correlations of suicide rates with educational attainment and median household income were both negative and statistically significant. Poverty was not significantly related to suicide rates. We concluded that higher education and income were associated with a decrease in suicide rates in 2001. Data from other years require examination for this conclusion to be generalizable.

scholarly journals County-Level Social Distancing and Policy Impact in the United States: A Dynamical Systems Model (Preprint)

2020 ◽  
Author(s):  
Kevin L McKee ◽  
Ian C Crandell ◽  
Alexandra L Hanlon
Keyword(s):  
United States ◽  
Differential Equation ◽  
Population Density ◽  
Household Income ◽  
The United States ◽  
Policy Impact ◽  
County Level ◽  
Median Household Income ◽  
Social Distancing

BACKGROUND Social distancing and public policy have been crucial for minimizing the spread of SARS-CoV-2 in the United States. Publicly available, county-level time series data on mobility are derived from individual devices with global positioning systems, providing a variety of indices of social distancing behavior per day. Such indices allow a fine-grained approach to modeling public behavior during the pandemic. Previous studies of social distancing and policy have not accounted for the occurrence of pre-policy social distancing and other dynamics reflected in the long-term trajectories of public mobility data. OBJECTIVE We propose a differential equation state-space model of county-level social distancing that accounts for distancing behavior leading up to the first official policies, equilibrium dynamics reflected in the long-term trajectories of mobility, and the specific impacts of four kinds of policy. The model is fit to each US county individually, producing a nationwide data set of novel estimated mobility indices. METHODS A differential equation model was fit to three indicators of mobility for each of 3054 counties, with T=100 occasions per county of the following: distance traveled, visitations to key sites, and the log number of interpersonal encounters. The indicators were highly correlated and assumed to share common underlying latent trajectory, dynamics, and responses to policy. Maximum likelihood estimation with the Kalman-Bucy filter was used to estimate the model parameters. Bivariate distributional plots and descriptive statistics were used to examine the resulting county-level parameter estimates. The association of chronology with policy impact was also considered. RESULTS Mobility dynamics show moderate correlations with two census covariates: population density (Spearman <i>r</i> ranging from 0.11 to 0.31) and median household income (Spearman <i>r</i> ranging from –0.03 to 0.39). Stay-at-home order effects were negatively correlated with both (<i>r</i>=–0.37 and <i>r</i>=–0.38, respectively), while the effects of the ban on all gatherings were positively correlated with both (<i>r</i>=0.51, <i>r</i>=0.39). Chronological ordering of policies was a moderate to strong determinant of their effect per county (Spearman r ranging from –0.12 to –0.56), with earlier policies accounting for most of the change in mobility, and later policies having little or no additional effect. CONCLUSIONS Chronological ordering, population density, and median household income were all associated with policy impact. The stay-at-home order and the ban on gatherings had the largest impacts on mobility on average. The model is implemented in a graphical online app for exploring county-level statistics and running counterfactual simulations. Future studies can incorporate the model-derived indices of social distancing and policy impacts as important social determinants of COVID-19 health outcomes.

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