American Community Survey Data Research Articles

Hospital-acquired Clostridioides difficile infection among patients at an urban safety-net hospital in Philadelphia: Demographics, neighborhood deprivation, and the transferability of national statistics.

To investigate associations between healthcare-associated Clostridioides difficile infection and patient demographics at an urban safety-net hospital and compare findings with national surveillance statistics. Study participants were selected using a case-control design using medical records collected between August 2014 and May 2018 at Hahnemann University Hospital in Philadelphia. Controls were frequency matched to cases by age and length of stay. Final sample included 170 cases and 324 controls. Neighborhood-level factors were measured using American Community Survey data. Multilevel models were used to examine infection by census tract, deprivation index, race/ethnicity, insurance type, referral location, antibiotic use, and proton-pump inhibitor use. Patients on Medicare compared to private insurance had 2.04 times (95% CI, 1.31-3.20) the odds of infection after adjusting for all covariables. Prior antibiotic use (2.70; 95% CI, 1.64-4.46) was also associated with infection, but race or ethnicity and referral location were not. A smaller proportion of hospital cases occurred among white patients (25% vs 44%) and patients over the age of 65 (39% vs 56%) than expected based on national surveillance statistics. Medicare and antibiotics were associated with Clostridioides difficile infection, but evidence did not indicate association with race or ethnicity. This finding diverges from national data in that infection is higher among white people compared to nonwhite people. Furthermore, a greater proportion of hospital cases were aged <65 years than expected based on national data. National surveillance statistics on CDI may not be transportable to safety-net hospitals, which often disproportionately serve low-income, nonwhite patients.

Geographic disparities in COVID-19 infections and deaths: The role of transportation

The US government imposed two travel restriction policies to prevent the spread of the COVID-19 but may have funneled asymptomatic air travelers to selected major airports and transportation hubs. Using the most recent JHU COVID-19 database, American Community Survey, Airport and Amtrak data form Bureau of Transportation Statistics from 3132 US counties we ran negative binomial regressions and Cox regression models to explore the associations between COVID-19 cases and death rates and proximity to airports, train stations, and public transportation. Counties within 25 miles of an airport had 1.392 times the rate of COVID-19 cases and 1.545 times the rate of COVID-19 deaths in comparison to counties that are more than 50 miles from an airport. More effective policies to detect and isolate infected travelers are needed. Policymakers and officials in transportation and public health should collaborate to promulgate policies and procedures to protect travelers and transportation workers from COVID-19.

Gentrifying Neighborhoods, Gentrifying Schools? An Emerging Typology of School Changes in a Gentrifying Urban School District

An increasing number of central cities across the U.S. are experiencing a growth in white middle-class population, which is associated with gentrification in historically disinvested and racially segregated urban neighborhoods. These changing neighborhood dynamics are starting to shift the context of urban schooling in some districts across the nation. While we know that racial and socioeconomic demographic shifts are associated with neighborhood and school gentrification, there is little conceptual clarity about how school gentrification unfolds over time and the varying conditions of schools in gentrified neighborhoods. To advance scholarship on the topic, researchers need an organizing framework. This study addresses this gap by drawing on existing research, 16 years of Census and American Community Survey data, and 6 years of district data in Austin, Texas. Highlighting Austin, an urban city with growing neighborhood gentrification, we put forth a typology to explain the experiences of schools in the district. We conclude with implications for future research.

Prevalence of intellectual disability among eight-year-old children from selected communities in the United States, 2014

BackgroundChildren with intellectual disability (ID), characterized by impairments in intellectual functioning and adaptive behavior, benefit from early identification and access to services. Previous U.S. estimates used administrative data or parent report with limited information for demographic subgroups. ObjectiveUsing empiric measures we examined ID characteristics among 8-year-old children and estimated prevalence by sex, race/ethnicity, geographic area and socioeconomic status (SES) area indicators. MethodsWe analyzed data for 8-year-old children in 9 geographic areas participating in the 2014 Autism and Developmental Disabilities Monitoring Network. Children with ID were identified through record review of IQ test data. Census and American Community Survey data were used to estimate the denominator. ResultsOverall, 11.8 per 1,000 (1.2%) had ID (IQ ≤ 70), of whom 39% (n = 998) also had autism spectrum disorder. Among children with ID, 1,823 had adaptive behavior test scores for which 64% were characterized as impaired. ID prevalence per 1,000 was 15.8 (95% confidence interval [95% CI], 15.0–16.5) among males and 7.7 (95% CI, 7.2–8.2) among females. ID prevalence was 17.7 (95% CI, 16.6–18.9) among children who were non-Hispanic black; 12.0 (95% CI, 11.1–13.0), among Hispanic; 8.6 (95% CI, 7.1–10.4), among non-Hispanic Asian; and 8.0 (95% CI, 7.5–8.6), among non-Hispanic white. Prevalence varied across geographic areas and was inversely associated with SES. ConclusionsID prevalence varied substantively among racial, ethnic, geographic, and SES groups. Results can inform strategies to enhance identification and improve access to services particularly for children who are minorities or living in areas with lower SES.

Association of Medicaid Expansion With Access to Abortion Services for Women With Low Incomes in Oregon.

The Affordable Care Act allowed states to expand Medicaid eligibility for women with low incomes before pregnancy. Women who experience an unintended pregnancy may encounter fewer delays in accessing abortion services if they are already enrolled in Medicaid. In states where the Medicaid program includes coverage for abortion services, Medicaid expansion may increase timely access to abortion services. Oregon has expanded Medicaid and is 1 of 16 states in which the Medicaid program covers abortion services. We explored how Medicaid expansion in Oregon was associated with Medicaid-financed abortion rates and receipt of medication abortion relative to surgical abortion. Using Medicaid claims and eligibility data we identified women ages 19 to 43 (n=30,367) who had abortions before the expansion period (2008-2013) and after the expansion period (2014-2016). We used American Community Survey data to estimate the annual number of Oregon women aged 19 to 43 with incomes below 185% of the federal poverty level who would be eligible for a Medicaid-financed abortion. We conducted interrupted time series analyses using negative binomial and logistic regression models. Incidence of Medicaid-financed abortion increased from 13.4 in 1,000 women in 2008 to 16.3 in 2016. Medication abortion receipt increased from 11.5% of abortions in 2008 to 31.7% in 2016. For both outcomes, we identified an increasing time trend after Medicaid expansion, followed by a subsequent leveling off of the trend. By the end of 2016, incidence of Medicaid-financed abortion was 4.5 abortions per 1,000 women-years (95% confidence interval, 3.3-5.7) higher than it would have been without expansion and medication abortions comprised a 7.4 percentage point (95% confidence interval, 4.4-10.4) greater share of all abortions. Medicaid expansion was associated with increased receipt of Medicaid-financed abortions and may have reduced out-of-pocket payment among women with low incomes. Increased receipt of medication abortion may indicate that expansion enhanced earlier access to services, possibly as a result of increased prepregnancy Medicaid enrollment, and this earlier access may increase reproductive autonomy and safety.

Relationships between density, transit, and household expenditures in small urban areas

This study developed three models to estimate the relationships between density, transit ridership, and household expenditures, with a focus on small urban areas. First, a regression model was developed that estimated transit ridership in small urban areas as a function of service quantity, service characteristics, the unemployment rate, demographic characteristics, and population density. A three-stage least squares estimation model was used to account for the simultaneity between ridership and service quantity. A second model, using American Community Survey data at the Census block group level, estimated the relationships between density and use of transit for commuting, as well as the impacts of living or working in the metro area’s principal city on commuting behavior. Lastly, data from the U.S. Consumer Expenditure Survey were used to model relationships between dwelling type and age with household transportation expenditures. Density was shown to be positively associated with transit ridership. The estimated elasticity is 0.09. The use of transit for commuting was found to increase with block group density, total metro population, if the area is within the principal city, and if a large percentage of workers commute to the principal city. Household transportation expenditures were found to be greater for those living in single-family detached structures and lowest for those living in high rises. Among households living in single-family detached structures, those in older homes were found to spend less on transportation. Older homes tend to be in neighborhoods that are more accessible by walking, biking, and transit.

Measuring Gentrification’s Association With Perceived Housing Unaffordability: A Philadelphia Case Study

ABSTRACT Gentrification, the growing presence of middle- and upper-income residents in previously low-income communities, is associated with unaffordable housing. However, there is a lack of research examining gentrification’s relationship to perceived housing unaffordability across all city neighborhoods. This study addresses this limitation by pooling three waves of the Philadelphia Health Management Corporation’s Southeastern Pennsylvania Household Health Survey—2010, 2012, 2014/15—and nesting them within census tracts measuring gentrification with U.S. Census 2000 and 2010/14 American Community Survey data. Using hierarchical linear models, we find that gentrification overall has a negative relation with residents’ sense of their housing unaffordability. This association is likely driven by gentrification accompanied by increases in non-Whites. Gentrification marked by increases in Whites but decreases in non-Whites has no measurable relationship with perceived housing unaffordability, although these places have the most expensive housing among gentrifying neighborhoods.

Arts majors as entrepreneurs and innovators.

This study examines the role of college graduates with degrees in the arts, STEM, and other creative fields as entrepreneurs and innovators in the US economy. As creativity is a trait of art students and is important for those acting as entrepreneurs and innovators in an economy, arts majors have the potential to play an important role in these areas. Using American Community Survey data, we look to identify arts, STEM, and other creative majors who are working in entrepreneurial occupations, those where self-employment is common, and innovative industries, those that are copyright intensive. As it is possible that the nature of arts occupations may be inherently more entrepreneurial and innovative, we compare arts majors to STEM and other creative majors also likely to work in such occupations. Using logistic regression, we find that majoring in a core arts field more than doubles an individual’s likelihood of working in an entrepreneurial occupation or an innovative industry relative to non-creative majors. Other creative majors, like communications and STEM majors, are also associated with an increased likelihood of working as entrepreneurs or innovators. Relative to STEM and other creative majors, majoring in a core arts field is associated with the greatest increase in the likelihood of working in an entrepreneurial occupation and third greatest increase in the likelihood of working in an innovative industry. While arts graduates play an important role in artistic creation, this paper highlights a role for these graduates as entrepreneurs and innovators in the US economy.Electronic supplementary materialThe online version of this article (10.1007/s11187-020-00416-x) contains supplementary material, which is available to authorized users.

Characterizing the Relationship between Social Determinants of Health and Air Quality

Background: Much of health is determined by peoples’ social determinants of health (SDH) and environments. Understanding them gives a more realistic model for risk stratification and the true complexity of patient populations, which may lead to more effective patient, family, and community engagement. For example, in the current COVID-19 pandemic African Americans are experiencing worse outcomes due to existing medical issues, less access to healthcare, and a higher likelihood to work unstable jobs. At the same time, there is likely an increased severity in COVID-19 cases following long-term exposure to air pollution. The objective of this study was to find relationships between SDH and environmental factors independent of a particular disease.Methods: Using the Factors Affecting Communities and Enabling Targeted Services model, we compiled SDH data for Utah census tracts from the American Community Survey data for the years 2012-2016. We assigned daily air quality measurements (AQ) for each of these census tracts based on the closest Environmental Protection Agency monitoring station. We performed clustering on the cleaned dataset using the Python package scikit-learn and visualized the obtained clusters with Tableau. We used the elbow method to obtain an optimum number of clusters and used the values for each variable in the clusters’ centroid to discover relationships between SDH and environment.Results: We obtained 10 distinct clusters of SDH and AQ. Clusters of census tracts with bad air tended to have higher proportions of individuals who were non-white, non-college educated, lower income, and lacking insurance.Conclusion: This analysis suggests a tangible relationship between poor AQ and SDH. Next steps include using modeled AQ data for finer spatial granularity and expanding timeframe and locations. The relationship between SDH and AQ irrespective of the disease is worth exploring further. The whole is more than the sum of its parts.

Public electric vehicle charger access disparities across race and income in California

Widespread electric vehicle (EV) adoption is crucial for achieving California's climate goals. The inclusion of marginalized populations in this process is important and will require that they have access to charging infrastructure. Public EV charging stations may help reduce the EV adoption barriers affecting these populations. This study combines public charging station location data with American Community Survey data at the census block group level in California, finding that public charger access is lower in block groups with below-median household incomes and in those with a Black and Hispanic majority populations. These public charger access disparities are more pronounced in areas with a higher proportion of multi-unit housing, where they are critical for EV operation due to a lower likelihood of residential charger access. Controlling for distance to the nearest highway or freeway, multi-unit housing unit rate, and median household income, we find that Black and Hispanic majority block groups are the only race and ethnicity group that is significantly less likely to have access to any public charger in their block groups compared to the rest of the state. The odds of having public charger access for the group is 0.7-times that of the no majority reference group. The access gap is even larger for the publicly-funded charging stations where Black and Hispanic majority block groups are approximately half as likely as the no-majority reference group to have access. Hence directing a larger portion of the funding to underserved communities and further government involvement in filling the public charger access gap can be crucial in achieving widespread and equitable EV adoption.

The Local Labor Market Effects of Korean Automotive Investments in the United States

This study investigates the local labor market effects of automotive foreign direct investment (FDI) in Alabama in the wake of the North American Free Trade Agreement (NAFTA). Of particular interest is the effect of FDI originating from a nontraditional source country in comparison to investments by European and Japanese firms. Using 2005–2011 American Community Survey (ACS) data, we compare changes in employment rates and median weekly wages in three area types: areas with Korean FDI, areas with German and Japanese FDI and areas without FDI. Results show that Korean FDI leads to increased employment rates but decreased median weekly wages. We attribute these findings to price competitive strategies of Korean firms.

Using estimates of undocumented immigrants to study the immigration-crime relationship

ABSTRACT The debate about undocumented immigration and its potential relation to crime continues to boil in the United States. We study this relationship by using two sets of estimates for the 2014 undocumented foreign-born population in U.S. metropolitan areas acquired from the Pew Research Center and the Migration Population Institute, 2013-2015 FBI Uniform Crime Report data, and 2011-2015 American Community Survey data from the U.S. Census Bureau, to model the association between undocumented immigration and violent and property crime. Findings are consistent across all estimates of metropolitan undocumented populations. Net of relevant covariates, we find negative effects of undocumented immigration on the overall property crime rate, larceny, and burglary; effects in models using violent crime measures as the outcomes are statistically non-significant. Although the results are based on cross-sectional data, they mirror other research findings that immigration either reduces or has no impact on crime, on average, and contribute to a growing literature on the relationship between immigration and crime.

S0335 Colorectal Cancer Screening Gender and Race Disparities in Western PA … Is There Really a Difference?

INTRODUCTION: The American College of Gastroenterology advocates that colorectal cancer screening should start earlier in African Americans because of the higher incidence and more aggressive nature in this population. We aimed to address colonoscopy screening disparities among the different races and genders investigating valuable significant contributors. METHODS: We reviewed GIQuIC data from 3 hospitals and 5 endoscopy outpatient surgical centers from October 2018 to December 2019. An analysis was created utilizing Highmark Health claims and the US Census Bureau American Community Survey data showing the strongest correlation for a lack of colorectal cancer screening by race and lower socioeconomic status (Figure 1). Through utilization of this data and GIQuIC data, we analyzed race and age of colorectal cancer screenings among African American and Caucasians. RESULTS: Among all screening colonoscopies available in the GIQuIC data, 84.1% constituted whites and 11.5% constituted African Americans (P < 0.0001) which is consistent with the low rate of African American screenings in the census data. Of all screenings, 54.7% were females and 45.3% males (P < 0.0001). We further looked at the data by race and gender (Table 1) and screening rates by age group (Table 2). Whites had screenings at age 50 more often than age appropriate screening for African Americans (age 45). Interestingly, colonoscopy prep quality was the lowest in black males, while it was the highest for white females. CONCLUSION: We found that African Americans are less likely than Caucasians to have screening tests for colorectal cancer in our region. This is consistent with previous studies. This may be due to lower socioeconomic status, lack of access in underserved areas, and lack of awareness/education. Better resources are required to educate the African American population regarding timely colonoscopy screening at age 45, colonoscopy prep instruction, and identifying barriers to access as key indicators to improve screening overall. We plan to target the underserved areas in the near future to improve CRC screening in the African American population. There was also an overwhelmingly higher number of females screened when compared to males. Is it because males are more apprehensive about colonoscopy? Further studies are needed to investigate such findings.Figure 1.: US Census Bureau American Community Survey data.Table 1.: Race and Gender.Table 2.: Screening Rates by Age Range.

Transit use for single-parent households: Evidence from Maryland

Single parents face unique transportation barriers in their lives. Although helping single parents obtain private vehicles (e.g., car donation programs) would be a potential solution, we cannot ignore the high expense of maintaining and operating a vehicle, which may impose a heavy financial burden on single-parent families and constrain their ability to access opportunities and services. In contrast, public transit could be a more accessible and affordable transportation mode that benefits single-parent families. This study examined the association between public transit use and single parents using 2017 National Household Travel Survey and American Community Survey data for Maryland, United States. Using zero-inflated negative binomial (ZINB) regression, we found that single parents used transit more than the average resident, and census block groups with more single-parent families had more transit commuters, holding other demographic and socioeconomic variables constant. This association was more significant in large metropolitan and urban areas than the state average. The findings highlight the vital role of public transit in single parents' daily travel. We discussed policy implications related to helping single parents access opportunities and services.

Welcome Mats and On-Ramps for Older Adults: The Impact of the Affordable Care Act's Medicaid Expansions on Dual Enrollment in Medicare and Medicaid.

For many low-income Medicare beneficiaries, Medicaid provides important supplemental insurance that covers out-of-pocket costs and additional benefits. We examine whether Medicaid participation by low-income adults age 65 and up increased as a result of Medicaid expansions to working-age adults under the Affordable Care Act (ACA). Previous literature documents so-called "welcome mat" effects in other populations but has not explicitly studied older persons dually eligible for Medicare and Medicaid. We extend this literature by estimating models of Medicaid participation among persons age 65 and up using American Community Survey data from 2010 to 2017 and state variation in ACA Medicaid expansions. We find that Medicaid expansions to working-age adults increased Medicaid participation among low-income older adults by 1.8 percentage points (4.4 percent). We also find evidence of an "on-ramp" effect; that is, low-income Medicare beneficiaries residing in expansion states who were young enough to gain coverage under the 2014 ACA Medicaid expansions before aging into Medicare were 4 percentage points (9.5 percent) more likely to have dual Medicaid coverage relative to similar individuals who either turned 65 before the 2014 expansions or resided in non-expansion states. This on-ramp effect is an important mechanism behind welcome mat effects among some older adults.

Military service and STEM employment: Do veterans have an advantage?

We use five years of American Community Survey data to examine how military service provides a non-degree-based pathway into STEM occupations. Military service is associated with STEM occupations in positive and surprising ways. Veterans are more likely than their civilian counterparts to work in STEM, an effect particularly strong for women and among workers without a STEM bachelor's degree. Among workers lacking STEM BAs, veterans were more likely to hold STEM occupations. Indeed, veterans lacking a college degree at all are more likely than their nonveteran counterparts to hold STEM employment. We conclude that military service in itself provides a rarely-discussed route to diversifying STEM and consider the policy implications.

Involuntary migration, context of reception, and social mobility: the case of Vietnamese refugee resettlement in the United States

ABSTRACT In this study, we examine the Vietnamese population of the United States as a case study in the integration of a refugee group. We first offer a brief review of Vietnamese refugee resettlement in the US and the making of a new ethnic community. We then provide a quantitative analysis of socioeconomic mobility among Vietnamese refugees using American Community Survey data from 1980 to 2015 and other national-level data. We examine how this ethnic population has changed over time by focusing on key socioeconomic indicators, such as levels of education, occupation, and income, as well as poverty rates. Third, we seek to explain what enables Vietnamese refugees and their children to overcome initial disadvantage and move up in society based on our own work over the span of 20 years with qualitative data. We consider how policies, institutions (government, civil society, and ethnic), and patterns of social relations in the Vietnamese American community have interacted with individual agency to shape mobility.

Evaluating MTurk as a recruitment tool for rural people with disabilities

BackgroundRecruitment of people with disabilities often occurs through disability organizations, advocacy groups, service providers, and patient registries. Recruitment that relies exclusively on established relationships can produce samples that may miss important information. The MTurk online marketplace offers a convenient option for recruitment. ObjectiveThe paper compares samples recruited through (1) conventional and (2) MTurk methods to better understand how these samples contrast with one another and with national estimates of people with disabilities. MethodsIn 2019, researchers recruited 1374 participants through conventional methods and 758 through MTurk to complete the National Survey on Health and Disability (NSHD). We analyzed sample differences between recruitment groups with t-tests, Chi-square, and logistic regression. ResultsWith the exception of race/ethnicity, the conventional and MTurk samples were significantly different on several dimensions including age, gender, education level, marital status, children living at home, and sexual orientation. The MTurk sample was overrepresented in lower income brackets. A significantly higher percentage of the conventional sample received SSI, SSDI, or both, compared to the MTurk sample (36.2% vs 12.8%) and had significantly higher rates of insurance coverage. Comparisons with American Community Survey data show that the conventional and MTurk samples aligned more closely with the general population of people with disabilities on different characteristics. ConclusionsMTurk is a viable complement to conventional recruitment methods, but it should not be a replacement. A combination of strategies builds a more robust dataset that allows for more varied examination of issues relevant to people with disabilities.

Challenges to the economic integration of Afghan refugees in the U.S.

ABSTRACT Informed by a modified segmented assimilation theory, we use 5% Census and American Community Survey data to examine the economic integration of Afghan refugees resettled in the U.S. First-wave Afghan refugees have made significant gains in income and employment, while their poverty rates and reliance on government assistance decreased dramatically. However, the most recent wave of Afghan refugees is not doing as well as the first at comparable points in time. Analysis of ACS data from 2006–2015 finds that, with controls, Afghan refugees’ earned incomes are the lowest of seven refugee/immigrant comparison groups. Given the robust set of controls, we hypothesise that anti-Muslim discrimination is an important unmeasured explanatory factor and suggest where to focus future research on this topic. Afghans’ lower incomes are substantially explained by lower employment levels, especially among less educated Afghan women and highly educated Afghan women and men. Evidence suggests that these patterns are influenced by distance between Afghan and U.S. gender orders, greater physical and mental disability from exposure to traumas, and the limited internal social capital of this small refugee group from a poor country.

Estimation of Average Annual Daily Bicycle Counts using Crowdsourced Strava Data

Traffic volumes are fundamental for evaluating transportation systems, regardless of travel mode. A lack of counts for non-motorized modes poses a challenge for practitioners developing and managing multimodal transportation facilities, whether they want to evaluate transportation safety or the potential need for infrastructure changes, or to answer other questions about how and where people bicycle and walk. In recent years, researchers and practitioners alike have been using crowdsourced data to supplement the non-motorized counts. As such, several methods and tools have been developed. The objective of this paper is to take advantage of new data sources that provide a limited and biased sample of trips and combine them with traditional counts to develop a practical tool for estimating annual average daily bicycle (AADB) counts. This study developed a direct-demand model for estimating AADB in Texas. Data from 100 stations, installed in 12 cities across the state, was used together with the crowdsourced Strava, roadway inventory, and American Community Survey data to develop the count model for estimating AADB. The results indicate that crowdsourced Strava data is an acceptable predictor of bicycle counts, and when used with the roadway functional class and number of high-income households in a block group, can provide quite an accurate AADB estimate (29% prediction error).