Public Use Microdata Sample Research Articles

BLACK MALES IN NON-STEM AND STEM OCCUPATIONS

While many labor market studies have examined wage inequality by race, gender, and class, the research has seldom directly considered labor market outcomes of STEM college graduates within the context of non-STEM and STEM occupations. The current study investigates the determinants of wages among Black males in STEM and non-STEM occupations compared to their White male peers. Through this investigation, it explores the feasibility of broadening Black males' participation in STEM occupations but also how they might earn higher wages and thereby close the wage gap with White male peers. The Public Use Microdata Sample (PUMS) files for the 2018 American Community Survey (ACS) were the primary data source for the current study. Following the convention in labor economics, the author used Mincer's single-equation model to explain variations in earnings as a function of select wage determinants derived from the data. Three main insights emerged from the current study. The findings suggested that opportunities do exist for employers to hire qualified Black males seeking gainful employment in STEM occupations. The findings also indicated that within the Black male group, working in a STEM occupation with a college degree in a STEM field was the best route to attain maximum wages. The third insight from the current study cannot be avoided: the noticeable gaps in wages between White and Black males. Implications of the findings for employers seeking to diversify their STEM workforce and for Black males considering employment or employed in a STEM occupation are discussed.

A Sense of Place: African Americans, Ethnogenesis and the Search for a “Black Mecca”

Ethnogenesis is a powerful mechanism which outlines how ethnic groups are formed. It is a complex process which often involves factors such as migration, cultural exchanges, intermarriage as well as religion. Ethnogenesis is also described as the historical and contemporary emergence of a group of people who define themselves in relation to a common socio-cultural and historical heritage. Focusing on African American migration during the Great Migration and its subsequent reverse migration, this study uses the theme of ethnogenesis to describe how migration to northern cities were shaped by a desire for solidarity and opportunity in as much as an escape from racial violence in the South. In the current trend of reverse migration, this work contends that migration is built on a need for opportunity as well as a desire for connectedness to ancestral homelands in the South. Examining the emergence of the “New South” in the post Jim-Crow landscape, this work evaluates the cultural, social and economic appeal of current migration streams. Using data from the Census Bureau’s American Community Survey (ACS) Public Use Microdata Sample (PUMS) files, significant population declines are reported in former destinations like San Francisco, Chicago, and New York. Data also show southern resurgences in destinations like Lafayette, Louisiana and Charlotte, North Carolina. Likewise, there are also marked increases in new destinations like Las Vegas, Nevada and Phoenix-Mesa-Glendale, Arizona. Additionally, data show that the Black population is growing in its diversity as well as density. People who identify as single-race Black, Black Latinx, and Black multiracial are a large (and growing) part of the Black population.

The effects of casino proximity and time on poverty levels in New York City

The effect of casino proximity and time on poverty levels in New York City examines levels of poverty over a 5-year duration for urban casino communities under the theoretical dimensions of exposure and adaption. Links between casino proximity and problem gambling or other gambling-related problems that could adversely impact individuals in disadvantaged communities were reported before the influx of urban casinos in major metro areas. This analysis uses Public Use Microdata Samples (PUMS) from the American Community Survey (ACS) estimates. A two-way factorial ANOVA measured poverty-level outcomes at high and low casino proximity in year 1 and year 5 after an urban casino had been opened. No significant interaction was found between casino proximity and year for poverty-level outcomes. The hypothesis that levels of poverty defined as PUMS score in urban casino communities and two levels of casino proximity in the New York metro area for the first and fifth year after the casino had been opened would not report statistically significant changes was supported. Higher poverty-level outcome scores were reported at closer distances measured as high casino proximity with approximately the same reported scores for year 1 and year 5, suggesting that closer distances to a casino despite the lifespan of the casino could influence poverty levels and other potential socio-economic factors. Contextualizing the findings in the exposure and adaptation theory frameworks suggests that exposure to a casino can have adverse consequences based on the increase in poverty-level outcome scores. Conversely, adaptation, which could occur over time, typically at the 5-year mark of operation, was not indicated due to the negligibility of poverty-level scores between year 1 and year 5; thus, refuting adaptation theory. This research expands the literature on urban casino proximity in the context of exposure and adaptation theory. Implication of these results provide the broader community of legislators, community workers, scholar-practitioners, preventionists, and industry with a better understanding of the phenomenon, and any potential adverse consequences to host and neighboring communities so that policy, intervention, prevention, and treatment can be implemented well before a casino opens.

Vehicle ownership rates: The role of lifecycle, period, and cohort effects

Researchers and policymakers often attempt to forecast trends in automobile ownership. But to understand recent changes in demand for cars, researchers must account for behaviors specific to different generations, while simultaneously controlling for the influence of lifecycle and historical effects. To overcome the analytical challenges of cross-sectional data in Age-Period-Cohort (APC) analysis, we apply three different approaches largely used by biostatisticians to isolate how cohort effects influence the likelihood that a U.S. adult lives in a zero-vehicle household.Our analyses draw on data from the U.S. Census Public Use Microdata Samples (PUMS) from 1970 to 2019. To test for cohort effects, we use constraint-based binary logistic regression, a nonlinear parametric approach to log-linear models, and median polish analysis. We find that people born from 1935 to 1944 experienced the strongest negative cohort effect of all groups, and thus were least likely to live in zero-vehicle households (after accounting for age and period effects). Compared to this cohort, persons born before 1924 and after 1955 saw higher likelihoods of living in zero-vehicle households, all else equal.The peak cohort effect of people born in the 1930s to 1940s may please those interested in reducing automobile use. But because automobiles offer access benefits, more recent cohorts may experience transportation challenges. Negative effects may be especially salient for Millennials, a group faring worse economically than previous generations. Further, recent changes in the transportation landscape – including the growth of services like carshare and ride-hail and behavioral changes emerging from the COVID-19 pandemic – complicate efforts to forecast demand for automobiles.

Investigating the application of a commercial and residential energy consumption prediction model for urban Planning scenarios with Machine Learning and Shapley Additive explanation methods

Building energy forecasting methodologies utilized by municipal governments tend to be geared heavily towards depicting broader qualitative representations of regional change and are in need of complementary data-driven models that can produce quantitatively reliable depictions of future energy consumption at the neighborhood-level. The current research demonstrates an application of a Machine Learning (ML) model in the form of an Extreme Gradient Boosting (XGBoost) algorithm for forecasting the energy use of commercial and residential buildings. The methodology serves to improve on municipal scenario planning by providing a more spatially granular representation of future energy use. In this way, city government and urban planners can more accurately set carbon emission benchmarks and target specific locales for sustainability initiatives. The second major contribution of the study is to demonstrate how scenario planning approaches can utilize existing Machine Learning techniques to compensate for gaps in the data. This work is developed through a case study of Philadelphia. The study begins with the construction of residential and commercial energy models for the year 2015 and corresponding models for the year 2045. The forecast models integrate regional socioeconomic trends from the Delaware Valley Regional Planning Commission (DVRPC) scenario of Enduring Urbanism. The commercial energy use model is developed from the DVRPC’s open-source Geographic Information System (GIS) datasets, the Commercial Buildings Energy Consumption Survey (CBECS), and CoStar commercial real estate data. The residential model applies the Residential Energy Consumption Survey (RECS), the Public Use Microdata Sample (PUMS), and Census Bureau American Community Survey (ACS) estimates. A corresponding SHAP (SHapley Additive exPlanations) analysis is implemented to pinpoint feature contributions to the model’s energy estimates. By using the PopGen software, the model’s energy estimates could be analyzed at the household level, the smallest possible scale. To provide a useful resource for key stakeholders, the study aggregates model output by Traffic Analysis Zone (TAZ) and Public Use Microdata Area (PUMA) to display a detailed forecast of energy use. The results indicate that the DVRPC Enduring Urbanism trends in income and employment do not significantly affect energy consumption for the study area. However, features related to lower building intensity (e.g., lower square footage, fewer floors per building) were associated with reduced energy use in both models. Additionally, the study found residential buildings under the “single-family attached” zoning designation to correspond with higher energy estimates.

DIRECT CARE WORKFORCE IN THE US BEFORE AND DURING COVID-19

Abstract Purpose This study describes the changes in the direct care workforce between 2019 and 2020. Design and Methods Data were from the 1% Public Use Microdata Sample (PUMS) of the 2019 and 2020 American Community Survey (ACS). Logistic regression was used to compare demographic and employment characteristics of direct care workers (DCWs) in 2019 and 2020. Results While the total number of DCWs increased by 0.08% and the number employed in home care increased by 3.45%, the number of DCWs employed in hospitals decreased by 3.73% and the number employed in residential care facilities decreased by 4.01% from 2019 to 2020. Compared to 2019, DCWs in 2020 were more likely to be nonmedical aides, under 25, over 65, non-white, to purchase health insurance directly, and to receive health insurance from Medicaid. DCWs in 2020 were less likely to be widowed, to be recently married, to be non-English speaking, to work year-round and full-time, to have moved in the last year, and to be below poverty than they were in the previous year. Implications: By the end of 2020, the early effects of the COVID-19 pandemic on the direct care workforce could be seen. While the total number of DCWs increased slightly, this was due to the accelerated growth of DCWs in home care, as the decline in the number of DCWs in hospitals and residential care facilities also accelerated. The direct care workforce in 2020 was more nonmedical, part-time, entry-level or exit-level and non-white than in the previous year.

Disability and the household context: Findings for the United States from the public Use Microdata Sample of the American Community Survey.

IntroductionBased on questions about impairments and activity limitations, the American Community Survey shows that roughly 13% of the U.S. population is experiencing disability. As most people live in households with other persons, this study explores disability at the household level. Considering the literature on household decision-making, solidarity, and capabilities in disability, this analysis of the household context of disability takes into account residential settings, household composition, and urban–rural differences.MethodThe 2015–2019 ACS Public Use Microdata Sample (PUMS), which shows persons with disability (PwD) and persons without disability (PwoD), also indicates household membership, used here to separately identify PwoD as those living in households with persons with disability (PwoD_HHwD) and those in households without any household member with disability (PwoD_HHwoD). Relationship variables reveal the composition of households with and without disabilities. An adaption of Beale's rural–urban continuum code for counties is used to approximate rural–urban differences with ACS PUMS data.ResultsSolo living is two times as common among persons with disability than among persons without disability, and higher in rural than urban areas. In addition to 43 million PwD, there are another 42 million PwoD_HHwD. Two times as many persons are impacted by disability, either of their own or that of a household member, than shown by an analysis of individual-level disability. For family households, differences in the composition of households with and without disabilities are considerable with much greater complexities in the makeup of families with disability. The presence of multiple generations stands out. Adult sons or daughters without disability play an important role. Modest urban–rural differences exist in the composition of family households with disability, with a greater presence of multigenerational households in large cities.DiscussionThis research reveals the much wider scope of household-level disability than indicated by disability of individuals alone. The greater complexity and multigenerational makeup of households with disability imply intergenerational solidarity, reciprocity, and resource sharing. Household members without disability may add to the capabilities of persons with disabilities. For the sizeable share of PwD living solo, there is concern about their needs being met.

Couple Households and the Commuting Time–Gender Gap

Using the Public Use Microdata Sample (PUMS) 2014–2018, we examine whether the household responsibility hypothesis (HRH) remains in the United States, using commuting times. After dividing couple households into subgroups by relative income level and educational level, we find that couple members in a higher income quartile tend to spend more time commuting. This implies that the HRH only explains the situation of a couple in which the man earns more than the woman. Given that the share of this household type among couples has diminished over time, this suggests that gender inequality within households has improved. Nevertheless, couples in which men earn more than women still dominate. So, we find, overall, that women’s commuting times still tend to be shorter than men’s, regardless of their relative educational levels. Furthermore, we find that the commuting time–gender gap is generally somewhat larger for couple households with a minor child, because men’s commuting times tend only to be slightly greater than when no minor child is present. This implies that women are still taking on a larger burden of household responsibilities, while also providing some financial support for their families.

The Choice of Customer Relationship Management Approach in the Supply Chain: Examining Small Business Performance

This study examines supply chain management approaches to customer relationship management (CRM), and how they influence the performance of small businesses. Our motivation was to relate supply chain positioning to business performance. The data for the small businesses for our study were sourced from the US Census Bureau’s survey of business owners (SBO) Public Use Microdata Sample (PUMS). We categorized the CRM environment for small businesses by primary customer type and by size, and examined the performance differences across these categories. Specifically, the CRM categories were business-to-consumer (B2C), business-to-business (B2B), business-to-government/federal (B2Gf), or business-to-government/state and local (B2Gs); while the size categories were Micro (<10 employees), Mini (10–24 employees), Small-I (25–49 employees), and Small-II (50–99 employees). We found evidence of superior performance for B2B firms on several dimensions including sales, employment, as well as sales per employee and sales per payroll measures of efficiency. This study contributes to the literature by clarifying how the positioning of small businesses in the supply chain can influence their performance.

Representation and Wage Gaps in the Planning Profession

Problem, research strategy, and findings Although gender and racial/ethnic equity have been primary concerns in planning, little research has examined whether the planning profession has achieved such equity in its workforce. In this study, I investigated representation and wage gaps by gender and race/ethnicity in the U.S. planning profession. Using Public Use Microdata Sample (PUMS) data, I explored a) whether gender and racial/ethnic gaps exist in representation and wages among planners and b) the extent to which such gaps changed over the 2000–2018 period and how they varied by employment sector. The results showed a substantial increase in the proportion of female planners over the study period. Black and Hispanic planners remained severely underrepresented, especially in the private sector, although the temporal patterns of their representation differed. Despite a significant reduction in the unadjusted gender wage gap among planners over time, the adjusted gap remained constant. Notably, the gender wage gap was significant only among planners with children, likely driven by fatherhood wage premiums. Unlike other related professions, planning did not exhibit significant racial/ethnic wage gaps at the beginning of the study period. However, Black and Hispanic planners in the public sector experienced significant wage penalties later in the study period. Takeaway for practice Planning employers need to develop strategies to close the gender wage gap, which includes work–life benefits and workplace awareness campaigns to transform the masculine culture in the planning workplace. Results also highlight the need to improve Black and Hispanic planners’ representation, especially in the private sector. Particular focus should be directed toward supporting Black planners, given their decreasing representation in both sectors and their wage penalties in the public sector in recent years. My study further suggests that interventions that hold public sector employers more accountable for their pay decisions are needed to address the racial/ethnic wage gaps recently found among planners.

Direct Care Workers Employed as Medical Aides: Home Health Aides, Nursing Assistants, and Orderlies

Purpose: This study describes the differences among direct workers (DCWs) employed as medical aides in three occupations: home health aides, nursing assistants, and orderlies. Design and Methods: Data were from the 1% Public Use Microdata Sample (PUMS) of the 2019 American Community Survey (ACS). Logistic regression was used to compare demographic and employment characteristics of DCWs employed as medical aides in three occupations: home health aides, nursing assistants and orderlies. Results: Compared to orderlies and psychiatric aides, home health aides are more likely to be foreign born, more likely to be female, less likely to work in institutional settings, less likely to be under age 25, less likely to work year-round full-time, less likely to have more education, and less likely to receive insurance from their employers. Implications: Since 2018, the PUMS of the ACS separates nursing, psychiatric, and home health aides (previously one occupational category) into three: home health aides, nursing assistants, and orderlies. This affords researchers a more precise understanding of this part of the direct care workforce. Home health aides represented more than 2/3 of DCWs employed as medical aides in 2019. Further, these workers are distinct among medical aides. More than nursing assistants and orderlies, home health aides are older, female, underinsured, foreign-born, and with limited education. This reflects both the barriers home health aides face to other occupations and also the preferences of their employers (which include private households). These findings have implications for the recruitment and retention of medical aides across all three occupations.

Older Vietnamese Have the Highest Prevalence of Disability Compared to White and Other Asian Groups

Informal caregivers are critical stakeholders in nursing home (NH) care for individuals with dementia. Given racial and ethnic disparities in United States NHs, there is a need to understand informal caregivers’ perspectives, particularly among those that identify as members of a community of color. We conducted a scoping review of informal caregiver priorities of nursing home dementia care. Included studies exclusively examined priorities of informal caregivers identifying as Black, Indigenous, or people of color. The final sample (n=12) included two United States studies representing African American and Korean informal caregivers. The remaining studies were conducted in other countries. Informal caregivers expressed a desire for professional support during the nursing home transition, increased staff knowledge of dementia, and improved resident engagement. These findings highlight the paucity of informal caregivers identifying as Black, Indigenous, or people of color represented in US nursing home dementia research. Future efforts must include communities of color.

A Method for Measuring Coupled Individual and Social Vulnerability to Environmental Hazards

Although models of social vulnerability to environmental hazards are commonly developed to support policy interventions in emergencies and disasters, their utility is hindered by a lack of contextual information on individuals exposed to and affected by hazards. We develop a novel approach to model social vulnerability that couples individuals and their varying forms of protective capacity with the social fabric of the communities in which they reside. The backbone of our model is the Public-Use Microdata Sample (PUMS), a product of the U.S. Census Bureau that preserves a representative sample of completed responses to the American Community Survey (ACS). The PUMS enables us to understand the full range of individual protective capacities against a hazard in an exposed area, which we term individual vulnerability profiles (IVPs). In this case, we examine IVPs in the Coney Island–Brighton Beach section of New York City, which suffered severe impacts during Hurricane Sandy in 2012. To manage the large number of unique IVPs in Coney Island–Brighton Beach, we perform a segmentation analysis to generalize them into thematic cohort vulnerability profiles (CVPs) representing a typology of vulnerable people in Coney Island–Brighton Beach during Sandy. From synthetic populations of CVPs, we then estimate how individuals in varying housing types were coexposed to Sandy at the census tract level by classifying these areas into community social vulnerability profiles (SVPs). Our results provide a topology of social vulnerability that simultaneously links individual, community, and population-wide concerns, enabling a more holistic understanding of resources and interventions beneficial to human security during events like Sandy than is attainable with area-level metrics.

G.I. Jane Goes to College? Female Educational Attainment, Earnings, and the Servicemen’s Readjustment Act of 1944

The 1944 Servicemen’s Readjustment Act (the “G.I. Bill”) provided returning WWII veterans with educational benefits sufficient to cover tuition, fees, and living expenses at almost any U.S. university or college. While several studies examine subsequent educational attainment and earnings for male veterans, little is known about how the G.I. Bill affected the 330,000 American females who served in WWII. Using data from the 1980 5 percent Census Public-use Microdata Sample, I find that female WWII veteran status is associated with a 19 percentage point increase in the proportion who report any college attendance, a 7.8 percentage point increase in college completion, and earnings that are 19.8 percent greater relative to comparable females who are not veterans. Because service was entirely voluntary for females, I use service eligibility requirements, enlistment records, 1940 Census data, and the G.I. Bill’s retroactive nature to establish a causal relationship among veteran status, educational attainment via the G.I. Bill, and increased earnings. To help separate the effect of the G.I. Bill from the effect of military service itself, and because benefits increased with longer service, I instrument for female veterans’ educational attainment using age at the time of the G.I. Bill’s announcement. My instrumental variables estimates imply that female veterans’ earnings increase by $1,350 (11.6 percent) per year of G.I. Bill-induced education, explaining 73 percent of the overall difference between veteran and non-veteran females’ earnings in 1980.

Real wage growth in the U.S. health workforce and the narrowing of the gender pay gap

BackgroundHealthcare has been identified as a job engine during recent recessions in the U.S. Whether the healthcare sector provides better than average pay remains a question. This study investigates if wages grew with the expanding demand for healthcare workers between 2001 and 2017. Wage growth in the (1) physicians and surgeons, (2) nurse, (3) healthcare practitioner and technical, (4) healthcare support, and (5) direct patient care jobs are examined. The gender pay gap in each occupation is investigated.MethodsThe American Community Survey (ACS) public use microdata sample (PUMS) for 2001, 2004, 2008, 2013, and 2017 were used to derive hourly wages for full-time, full-year workers aged 18–75. The cumulative percent change in unadjusted, median hourly wages between 2001 and 2017 was calculated for each occupation. Quantile regression estimates predicted a median hourly wage for men and women by year and job after adjusting for differences in demographics, industry, and hours worked.ResultsUnadjusted median wage growth was 9.92% for nurses, 5.68% for healthcare practitioners, and 37.6% for physicians between 2001 and 2017. These rates are roughly above the estimated national rate of wage growth at the 50th wage percentile. In healthcare support and direct patient care occupations, workers experienced either stagnant or negative wage growth. Women had lower occupational wages than men.ConclusionThe slow or negative median wage growth in all but the physician occupation between 2004–2008 and 2008–2013 confirms that healthcare wages in the U.S. are not recession-proof, unlike healthcare employment. Generally, women's earnings grew at rates that were higher or less negative than rates for men. This trend contributed to narrowing the gender pay gap in every occupation except for nurse.

The value of climate amenities: A comparison of hedonic and discrete choice approaches

Amenities that vary across cities are typically valued using either a hedonic model, in which amenities are capitalized into wages and housing prices, or a discrete model of household location choice. In this paper, we use the 2000 Public Use Microdata Sample (PUMS) to value climate amenities using both methods. We compare estimates of marginal willingness to pay (MWTP), allowing preferences for climate amenities to vary by location. We find that mean MWTP for warmer winters is about twice as large using the discrete choice approach as with the hedonic approach; mean MWTP for cooler summers is approximately the same. The two approaches differ, however, in their estimates of MWTP by location. These disparities lead to significant differences in estimates of willingness to pay to avoid the A2 and B1 SRES scenarios in 2020–2050 using the two approaches.

Linguistic occupation segregation along the U.S.–Mexico border: using the index of dissimilarity to measure inequality in employment among monolingual speakers and Spanish–English bilinguals

Abstract The U.S.–Mexico border is a Latina/o concentrated region and Spanish–English bilingual society. While there are some indications of an economic advantage associated with Spanish–English bilingualism in regions with over-representations of Spanish-origin speakers, the degree of occupational linguistic segregation in such ethno-linguistic context is unknown. Based on data from the American Community Survey (ACS) Public Use Microdata Sample (PUMS) for 2018, this study calculates the occupational dissimilarity index (D) among monolingual-Spanish speakers, Spanish–English bilinguals, and monolingual-English speakers for cities located along the Texas–Mexico border and in the Houston metropolis. Findings show that the highest occupational segregation is found between monolingual-Spanish speakers and both monolingual-English and Spanish–English bilinguals. This indicates that the monolingual-Spanish workforce is occupationally segregated from those with fluent command of English. The lowest occupation dissimilarity indices are between Spanish–English bilinguals and monolingual-English speakers, indicating that these groups are approaching similar occupational placements. I conclude by highlighting an occupational advantage to Spanish–English bilingualism, but only in border cities characterised by concentrations of Spanish-origin speakers. In the non-border city of Houston, being Spanish–English bilingual is not enough to experience occupational upward mobility.

Senior Migration and Housing Consumption Findings from Metropolitan Baltimore

This study examines the intersection between residential mobility and housing consumption for seniors who migrate inward from the suburbs of the Baltimore metropolitan statistical area (MSA), with a particular focus on marital status. Using probit and multinomial logistic specifications that are developed with the dataset drawn from the 2013–2017 Public Use Microdata Sample (PUMS), the findings support the argument that preferences for tenure vary greatly with respect to the life-cycle phase. Throughout the Baltimore MSA, seniors show a strong tendency toward downsizing and becoming renters – specifically of apartments – regardless of location. Single status itself does not have a positive effect on the likelihood that a senior may migrate inward nor does it directly impact whether or not a senior adjusts their housing wealth. Nonetheless, recent widowhood significantly increases one’s propensity to move inward; but there is mixed evidence on one’s decision to dissave their housing wealth. This study seeks to provide a better understanding of the varied correlations between senior migration and housing consumption in the Baltimore MSA.

Direct Care Workforce: Where the Boys Really Are

Purpose: This study describes the continued growth of male direct care workers (DCWs) and identifies the occupations with the greatest concentrations of male DCWs by utilizing the expanded information available in the 2018 American Community Survey (ACS). Design and Methods: Data were taken from the 1% Public Use Microdata Sample (PUMS) from the 2018 ACS. Beginning in 2018, the ACS separated the single occupation category nursing, psychiatric, and home health aides into three categories: home health aides, nursing assistants, and orderlies and psychiatric aides. Results: Between 2000 and 2018, the total number of male DCWs in the U.S. increased 118% to 474,925, with more than half (52.6%) in 2018 employed as nursing, psychiatric, and home health aides. Among these 250,139 aides, 62% (154,557) were employed as nursing assistants, 23% (57,126) worked as home health aides, and 15% (38,456) were employed as orderlies and psychiatric aides. However, 60% of all orderlies and psychiatric aides were male; this was the only occupation in the direct care workforce in which men were in the majority. Implications: The majority of male DCWs work as nursing, psychiatric, and home health aides and the new occupation classifications in the ACS reveal that while most work as nursing assistants and home health aides, the one occupation with a majority male workforce was orderlies and psychiatric aides. These findings suggest that the greatest need for male DCWs may be as orderlies and psychiatric aides, occupations in which size and physical strength are important factors.

Cognitive Disability Among Arab Americans by Nativity Status: Lack of Evidence for the Healthy Migrant Effect

Limited research exists on cognitive disabilities among foreign-born adults, particularly non-Hispanic Arab Americans. We analyzed 10 years (2008-2017) of data from the American Community Survey (ACS) Public Use Microdata Samples (PUMS) (n=5,011,469; ages >45 years). In US-born adults, the age- and sex-adjusted prevalence of cognitive disability among non-Hispanic Arab Americans was 5.3%, which was lower than non-Hispanic whites (6.5%), blacks (10.8%), and Hispanics (10.0%). Among foreign-born adults, the prevalence of cognitive disability was highest, 7.3%, for non-Hispanic Arab Americans compared to all other racial and ethnic groups. Among foreign-born adults, non-Hispanic Arab Americans had 1.24 times greater odds (95% CI=1.12, 1.37) of having a cognitive disability compared to foreign-born non-Hispanic whites. This is the first study to examine cognitive disabilities among US- and foreign-born Arab Americans. More research is needed to better understand factors that may contribute to the increased prevalence of cognitive disabilities for foreign-born adults.