Engagement of health care workers has been shown to have a positive impact on job satisfaction and organizational performance, but this relationship is unclear for direct care workers in long-term care facilities. A survey of direct care workers in North Carolina nursing homes was conducted in 2020 to investigate the factors contributing to their job satisfaction using the Benjamin Rose Nurse Assistant Job Satisfaction Survey. Extrinsic factors affecting direct care worker job satisfaction such as compensation, workplace environment and support from management were examined, as well as intrinsic factors of job satisfaction such as communication, recognition at work and training. Survey results indicated that extrinsic factors such as pay and communication with administrators, followed by the intrinsic factor of worker recognition, are the most important factors affecting direct care worker job satisfaction. Management practices related to compensation, engaging and valuing direct care workers must be examined in order to have a lasting impact on direct care worker job satisfaction levels.

IMPORTANCE Calorie labels for prepared (ie, ready-to-eat) foods are required in large chain food establishments in the US. Large evaluations in restaurants suggest small declines in purchases of prepared foods after labeling, but to the authors’ knowledge, no studies have examined how this policy influences supermarket purchases. OBJECTIVE To estimate changes in calories purchased from prepared foods and potential packaged substitutes compared with control foods after calorie labeling of prepared foods in supermarkets. DESIGN, SETTING, AND PARTICIPANTS This controlled interrupted time series compared sales 2 years before labeling implementation (April 2015-April 2017) with sales 7 months after labeling implementation (May 2017-December 2017). Data from 173 supermarkets from a supermarket chain with locations in Maine, Massachusetts, New Hampshire, New York, and Vermont were analyzed from March 2020 to May 2022. INTERVENTION Implementation of calorie labeling of prepared foods in April 2017. MAIN OUTCOMES AND MEASURES Purchased items were classified as prepared foods, potential packaged substitutes for prepared foods, or all other (ie, control) foods. The primary outcome was mean weekly calories per transaction purchased from prepared foods, and the secondary outcome was mean weekly calories per transaction purchased from similar packaged items (for substitution analyses). Analyses of prepared and packaged foods were stratified by food category (bakery, entrées and sides, or deli meats and cheeses). RESULTS Among the included 173 supermarkets, calorie labeling was associated with a mean 5.1% decrease (95% CI, −5.8% to −4.4%) in calories per transaction purchased from prepared bakery items and an 11.0% decrease (95% CI, −11.9% to −10.1%) from prepared deli items, adjusted for changes in control foods; no changes were observed for prepared entrées and sides (change = 0.3%; 95% CI, −2.5% to 3.0%). Labeling was also associated with decreased calories per transaction purchased from packaged bakery items (change = −3.9%; 95% CI, −4.3% to −3.6%), packaged entrées and sides (change = −1.2%; 95% CI, −1.4% to −0.9%), and packaged deli items (change = −2.1%; 95% CI, −2.4% to −1.7%). CONCLUSIONS AND RELEVANCE In this longitudinal study of supermarkets, calorie labeling of prepared foods was associated with small to moderate decreases in calories purchased from prepared bakery and deli items without evidence of substitution to similar packaged foods.

This study describes how parental time investments in children in immigrant families vary according to children’s citizenship status. In families with multiple children, parents make allocation decisions about how to invest in each child. In immigrant households, a child’s citizenship status may shape parental time allocations because of how this status relates to a child’s prospects for socioeconomic mobility. It is unclear whether parents reinforce citizenship differences among siblings, compensate for these differences, or treat all siblings equally regardless of citizenship status. Moreover, past empirical research has not investigated differences in parental time investments in siblings with different citizenship statuses. To evaluate differential time investments in children based on citizenship, we conduct a quantitative analysis using data from the American Time Use Survey from 2003–2019 and focus on children in immigrant households with at least two children (N = 13,012). Our research shows that parents spend more time with children who have citizenship, but this result is primarily explained by a child’s age and birth order. Our study provides a basis for further inquiry on how legal contexts shaping socioeconomic mobility may influence micro-level family processes in immigrant households.

Infant sex ratios that differ from the biological norm provide a measure of gender status inequality that is not susceptible to social desirability bias. Ratios may become less biased with educational expansion through reduced preference for male children. Alternatively, bias could increase with education through more access to sex-selective medical technologies. Using National Vital Statistics data on the population of live births in the United States for 1969–2018, we examine trends in infant sex ratios by parental race/ethnicity, education, and birth parity over five decades. We find son-biased infant sex ratios among Chinese and Asian Indian births that have persisted in recent years, and regressions suggest son-biased ratios among births to Filipino and Japanese mothers with less than a high school education. Infant sex ratios are more balanced at higher levels of maternal education, particularly when both parents are college educated. Results suggest greater equality of gender status with higher education in the United States.

Over 32.1 million working people in the United States—more than one in five—worked part-time in 2021.1 Part-time workers were hit hard in the first year of the COVID-19 pandemic; there has been a net loss of over 1 million part-time jobs between 2019 and 2021, with women accounting for 100% of the jobs lost.2 Yet between February and April 2020, the number of people working part time for “economic reasons” (i.e., involuntarily) more than doubled.3 Although this number has since declined to below pre-pandemic levels, new variants of the coronavirus and ongoing economic uncertainty continue to create instability for the part-time workforce.

Background The present study examined racial/ethnic differences in US drug overdose mortality among US-born and foreign-born men and women. Methods In this cross-sectional analysis of 2010–2019 data from the National Center for Health Statistics, Bayesian hierarchical models predicted drug overdose mortality based on the interaction of race/ethnicity, nativity, and sex, adjusting for age, for 518,553 drug overdose deaths among individuals ages 15–74 identified as Non-Hispanic (NH) White, NH Black, Hispanic, or NH Asian/Pacific Islander (PI). Rate ratios with 95% Highest Posterior Density Intervals (HPDIs) were examined by race/ethnicity and nativity. Results In the US-born population, 2017–2019 estimated overdose mortality rates were higher for NH Black than NH White men (ratio 1.48 [95% HPDI 1.28–1.72]), similar between NH Black and NH White women (ratio 1.03 [95% HPDI 0.89–1.20]), similar between Hispanic and NH White men (ratio 0.96 [95% HPDI 0.82–1.10]), and lower for NH Asian/PI than NH White men and women. In the foreign-born population, both for men and women, estimated overdose mortality rates were lower in every racial/ethnic group relative to the NH White group. For men and women of all racial/ethnic groups examined, estimated overdose mortality rates were higher in US-born than foreign-born subpopulations, yet the extent of this nativity differential was least pronounced in the NH White group. Conclusions In the US-born population, NH Black men experienced the highest recent rates of overdose mortality; in the foreign-born population, the highest rates of overdose mortality were observed among NH White men and women.

Food insecurity is associated with poor clinical outcomes among adults with diabetes, but associations with nonclinical outcomes, such as missed work, have not been well characterized. Our objective was to assess the associations between food insecurity, health-related missed workdays, and overnight hospitalizations. We pooled National Health Interview Survey data from the period 2011–18 to analyze food insecurity among 13,116 US adults ages 18–65 who had diabetes. Experiencing food insecurity, compared with being food secure, was associated with increased odds of reporting any health-related missed workdays, more than twice the rate of health-related missed workdays, and increased odds of overnight hospitalization within the prior twelve months. There was no significant association between food insecurity and the number of nights spent hospitalized. These findings underscore the broad impacts of food insecurity on health and wellness for working-age adults with diabetes. When weighing the costs and benefits of proposed interventions to address food insecurity, policy makers should consider potential benefits related to productivity in addition to implications for health care use.

Black and low-income neighborhoods tend to have higher concentrations of fast-food restaurants and low produce supply stores. Limited access to and consumption of nutrient-rich foods is associated with poor health outcomes. Given the realities of food access, many members within the Black communities grow food as a strategy of resistance to food apartheid, and for the healing and self-determination that agriculture offers. In this paper, we unpack the history of Black people, agriculture, and land in the United States. In addition to our brief historical review, we conduct a descriptive epidemiologic study of community food-growing spaces, food access, and neighborhood racial composition in present day Philadelphia. We leverage one of the few existing datasets that systematically documents community food-growing locations throughout a major US city. By applying spatial regression techniques, we use conditional autoregressive models to determine if there are spatial associations between Black neighborhoods, poverty, food access, and urban agriculture in Philadelphia. Fully adjusted spatial models showed significant associations between Black neighborhoods and urban agriculture (RR: 1.28, 95% CI = 1.03, 1.59) and poverty and urban agriculture (RR: 1.27, 95% CI = 1.1, 1.46). The association between low food access and the presence of urban agriculture was generally increased across neighborhoods with a higher proportion of Black residents. These results show that Philadelphia neighborhoods with higher populations of Black people and neighborhoods with lower incomes, on average, tend to have more community gardens and urban farms. While the garden data is non-temporal and non-causal, one possible explanation for these findings, in alignment with what Philadelphia growers have claimed, is that urban agriculture may be a manifestation of collective agency and community resistance in Black and low-income communities, particularly in neighborhoods with low food access.

Learn how to create culturally responsive, socially just school–family partnerships that positively impact student learning outcomes. Responding to the current rise in White supremacy in America, a surge in hate crimes against BIPOC students and families, and the gaping digital divide exposed by the COVID-19 pandemic, this book addresses the need for educators and schools to develop competency in working with diverse families and their communities. Chapters address misconceptions of school personnel that often result in microaggressions and miscommunications that impede fully including families in the education of their children. Exploring a wide range of sociocultural issues present in today’s schools, readers will learn how to better work with military families during deployment, students with disabilities, families with various living arrangements, immigrant families, and religiously diverse students. The text features engaging, real-life scenarios and research-based practices designed to improve the academic success of all K–12 learners.

A large body of work suggests that trade affects workers unevenly. By shifting economic activity across occupations, industries, or regions, freer trade can generate gains for some workers and losses for others. For instance, in light of the increase in U.S. imports from China starting in the 1990s, Autor, Dorn and Hanson (2013) provide evidence that workers' labor market outcomes deteriorated more in regions exposed to tougher import competition from China. Relatedly, the recent work by Ferriere, Navarro and Reyes-Heroles (2021) shows that college enrollment by young individuals increased more in these exposed regions.1 In particular, they show that labor markets outcomes deteriorated more for workers with lower education levels, thus affecting incentives for young individuals to enroll into college. In this note, we provide evidence that trade openness has led to a greater increase in college enrollment by women than by men. We extend the work of Ferriere, Navarro and Reyes-Heroles (2021) by analyzing the gender-specific effects of import competition on labor market outcomes and college enrollment decisions. We first show that the adverse effect of import competition is strongest on the labor market outcomes of women without a college education. That is, after the increase in trade, the college premium increases more for women than for men. Second, we show that young women enrolled more into college than men in response to increased imports. Hence, college enrollment responded to the trade-induced increase in college premium.2 Section 2 of this note discusses our empirical strategy. Section 3 discusses the effects on labor market outcomes by gender and education levels, while Section 4 does the same for college enrollment. Section 5 concludes.

This cross-sectional study was approved by the LAC Department of Public Health (DPH) institutional review board and electronic informed consent was obtained. This study follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. We tested for RBD antibodies using an FDA emergency use authorized assay (Luminex xMAP SARS-CoV-2). We established 8 testing sites in LAC and residents who lived within a 15-mile radius (99% of LAC population) were eligible for participation. Testing was offered from April 9 to April 25, 2021. We used a proprietary database representing about a quarter of the LAC population maintained by a market research firm (LRW Group, a Material Company), to select participants. A random sample of these residents were invited, with quotas for enrollment for subgroups based on demographics of LAC residents. All participants were invited to participate in antibody testing and participants self-selected to consent for testing. Participants who had participated in a similar study conducted in April 2020 were oversampled.6 Weights were used to adjust results for LAC 2019 census estimates of demographics and LAC DPH data on confirmed COVID-19 cases and COVID-19 vaccination rates by race and ethnicity, age, and gender. Data on race and ethnicity were self reported by residents; race and ethnicity data were collected to document disparities in rate of potential protective immunity by race and ethnicity. We used these weighted data to estimate the fraction of LAC adults that had received at least 1 dose of vaccine or had RBD antibodies, as a whole, and by vaccination status, demographics, and area poverty level. Statistical analysis was performed using Stata version 15 (StataCorp) from April to November 2021.

Poverty scholarship in the United States is increasingly reliant upon the Supplemental Poverty Measure (SPM) as opposed to the Official Poverty Measure of the United States for research and policy analysis. However, the SPM still faces several critiques from scholars focused on poverty in nonmetropolitan areas. Key among these critiques is the geographic adjustment for cost of living employed in the SPM, which is based solely upon median rental costs and pools together all nonmetropolitan counties within each state. Here, we evaluate the current geographic adjustment of the SPM using both microdata and aggregate data from the American Community Survey for 2014-2018. By comparing housing costs, tenure, and commuting, we determine median rent is likely an appropriate basis for geographic adjustment. However, by demonstrating the wide variability between median rents of nonmetropolitan counties within the same state, we show that the current operationalization of this geographic adjustment could be improved through the use of more-specific categories such as metropolitan adjacency or Rural Urban Continuum Codes.

The share of adults who live alone is on the rise (Vespa, Lewis & Kreider, 2013), in part due to changes in marriage and divorce in the United States (FP-21-24). This Family Profile examines sociodemographic variation among single adults living alone in midlife (ages 30-59) in 2021 using data from the 2021 ASEC Current Population Survey from IPUMS-CPS. We begin with single adults who are not married or cohabiting and focus on those who are living alone (excluding those living with other adults such as parents, siblings, roommates, etc.). We begin by showing the share of adults 30-59 who are single and their living arrangements by age group, and then present marital status and home ownership variation by age group and gender among single adults living alone.

Very few labor-based pathways for regular migration are available for people in Northern Central America, often called the "Northern Triangle" of Guatemala, Honduras, and El Salvador. This paper briefly summarizes the state of labor-based migration channels in the region. It then argues that extending those channels is a necessary complement to asylum reform even for the goal of humanitarian protection. It concludes by arguing that five recommendations for long-term reform, though difficult, are needed to unleash the maximum shared benefit of these pathways.

One of the largest population displacement episodes in the U.S. took place in 1942, when over 110,000 persons of Japanese origin living in the West Coast were forcibly sent to ten internment camps throughout the country. Those affected lost jobs and assets and lived in camps between one and three years. After internment they had to reassess labor market and location choices. Using Census data, camp records, and survey data I study the long-run career consequences of this episode for those affected. Combining information from these three data sources I develop a predictor of a person’s future or past internment based on Census observables. Using a differencein-differences framework I find a positive average effect of internment on earnings in the long run, robust to different control group choices. I consider exposure to socioeconomically diverse peers followed by increased occupational and geographic mobility as likely mechanisms, finding support in the data for both. I do not find evidence of other potential drivers such as increased labor supply or changes in cultural preferences. These findings provide evidence of labor market frictions preventing people from accessing their most productive occupations and locations, how exposure to socioeconomically diverse peers can lower these barriers, and the possibility of overcoming adverse shocks.

Senior participation in the Supplemental Nutrition Assistance Program (SNAP) has traditionally been lower than other groups among those eligible, with historical estimates below 50%. We examine the impacts of state SNAP policies on program participation among low-income senior (age 60 and older) and nonsenior households using data from the 2001 to 2014 December Current Population Survey Food Security Supplement. Our results suggest that policies designed to expand SNAP eligibility modestly increased participation among seniors but led to larger increases among nonseniors. In contrast, we find little evidence of effects of policies related to transaction costs, stigma, or outreach on either group.

Background Precipitated by an unusual winter storm, the 2021 Texas Power Crisis lasted February 10 to 27 leaving millions of customers without power. Such large-scale outages can have severe health consequences, especially among vulnerable subpopulations such as those reliant on electricity to power medical equipment, but limited studies have evaluated sociodemographic disparities associated with outages. Objective To characterize the 2021 Texas Power Crisis in relation to distribution, duration, preparedness, and issues of environmental justice. Methods We used hourly Texas-wide county-level power outage data to estimate geographic clustering and association between outage exposure (distribution and duration) and six measures of racial, social, political, and/or medical vulnerability: Black and Hispanic populations, the Centers for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI), Medicare electricity-dependent durable medical equipment (DME) usage, nursing homes, and hospitals. To examine individual-level experience and preparedness, we used a preexisting and non-representative internet survey. Results At the peak of the Texas Power Crisis, nearly 1/3 of customers statewide (N = 4,011,776 households/businesses) lost power. We identified multiple counties that faced a dual burden of racial/social/medical vulnerability and power outage exposure, after accounting for multiple comparisons. County-level spatial analyses indicated that counties where more Hispanic residents resided tended to endure more severe outages (OR = 1.16, 95% CI: 1.02, 1.40). We did not observe socioeconomic or medical disparities. With individual-level survey data among 1038 respondents, we found that Black respondents were more likely to report outages lasting 24+ hours and that younger individuals and those with lower educational attainment were less likely to be prepared for outages. Significance Power outages can be deadly, and medically vulnerable, socioeconomically vulnerable, and marginalized groups may be disproportionately impacted or less prepared. Climate and energy policy must equitably address power outages, future grid improvements, and disaster preparedness and management.

Introduction: Structural racism is strongly related to racial health disparities. However, surprisingly few studies have developed empirical tools to measure structural racism. In addition, the few measures that have been employed have only considered structural racism at the neighborhood level. To expand upon previous studies, this paper uses a novel measure to measure structural racism at the county level for the non-Hispanic Black population. Methods: We used confirmatory factor analysis to create a model to measure the latent construct of structural racism for 1181 US counties. The model included five indicators across five dimensions: racial segregation, incarceration, educational attainment, employment, and economic status/wealth. Structural equation modeling and factor analysis were used to generate factor scores that weighted the indicators in order to produce the best model fit. The resulting factor scores represented the level of structural racism in each county. We demonstrated the utility of this measure by demonstrating its strong correlation with Black-White disparities in firearm homicide rates. Results: Our calculations revealed striking geographic differences across counties in the magnitude of structural racism, with the highest values generally being observed in the Midwest and Northeast. Structural racism was significantly associated with higher Black firearm homicide rates, lower White homicide rates, and a higher Black-White racial disparity in firearm homicide. Conclusions: These new measures can be utilized by researchers to relate structural racism to racial health disparities at the county level.

Background The COVID-19 pandemic has focused attention on race and income disparities in SARS-CoV-2 mortality and morbidity. Much less attention has been paid to other socioeconomic factors including income. Objective The goal of this study was to compare disparities in medical care utilization and related expenditures associated with income to those associated with race and ethnicity in the US for those aged 0 to 64 for four categories of medical services: hospital, emergency room, ambulatory care, and prescription medications. Methods We used Medical Expenditure Panel Survey data for years 2017 through 2019. For each of the four medical services, there were three measures. First was the percentage of those aged 0-64 with or without utilization and expenditures. Due to statistical issues related to zero values for utilization and expenditures, the second and third measures were average utilization and expenditures only for those with both utilization and expenditures. Disparities by income and race-ethnicity were measured by calculating the percent difference between the group with the lowest utilization or expenditures and the group with the highest utilization or expenditures. Results For 9 of the 12 separate differences the income differences exceed the corresponding race-ethnicity difference and the income differences are generally much greater in magnitude. Within the income comparisons, those on Medicaid had the greatest utilization in 7 of the 8 comparisons. The High Income group had greatest expenditures for 3 of the 4 medical services. Non-Hispanic Whites had the greatest utilization and expenditures for 9 of the 12 measures and Hispanics had the least utilization and expenditures for 9 of the 12 measures. Conclusions These results indicate that income inequalities are more strongly associated with medical care utilization and expenditures than race-ethnicity among those aged 0-64. Although more research should focus on income related health disparities in the United States, it is time to recognize that sound health policy must include reducing socioeconomic inequalities, especially those related to income.

The relationship between access to nature and public health outcomes has been well-studied and established in the literature. However, most studies use simple greenness indices as a proxy for access to nature, which ignores the “quality” of the nature since greenness indices are not able to predict biodiversity. My objective was to investigate the relationship between citizen scientist collected biodiversity data from the eBird platform, urban greenness and four human health outcomes (asthma, coronary heart disease, and self-assessed mental and physical health). I mapped and tested for correlations among eBird record species richness, greenness as NDVI and PLACES human health data in urban census tracts located in three metro areas/ecological zones (Albany, NY: eastern deciduous forest, Kansas City, MO: tallgrass prairie, and Phoenix, AZ: Sonoran Desert). eBird species richness was related to greenness, measures of urbanization and several human health factors; however, the correlations varied by metro area and in strength. Provided confounders are controlled for, eBird data could help to refine models surrounding relationships between public health and nature access. It is established in the literature that proximity and access to “nature” and green space is related to subjective wellness and health outcomes (Jennings et al. 2016, Mavoa et al. 2019). Greenness indices are often used to evaluate the availability of natural areas in urban landscapes, and while NDVI is often a good estimator of green spaces, in some situations it may be over-simplification to suggest that the health benefits of nature areas are simply a function of local greenness (Markevych et al. 2017, Reid et al. 2018, Jarvis et al. 2020). There is also evidence that exposure to biodiversity, that is, the “quality” of the green space and the variety of habitats it offers, influences health outcomes (Fuller et al. 2007, Hanski et al. 2012, Shanahan et al. 2015, Mills et al. 2020). It is often assumed that greenness and biodiversity are synonymous and yet a functional crop field can be low in biodiversity but have a high NDVI. While there have been many attempts to model diversity based on vegetative reflectance, effectiveness and portability of these methods vary (Wang and Gamon 2019, Leveau et al. 2020), and ground truthing biodiversity is costly. Investigation of the mechanisms behind the relationship between greenness and health outcomes continues (Markevych et al. 2017); this study proposes to further probe this question using citizen gathered data from the eBird platform (Cornell Lab of Ornithology 2020), particularly in urban areas. With rapid increases in data and data-driven decisions, citizen science has begun to play a larger role in scientific investigations, despite its inherent flaws. eBird, which was initiated in 2002, is a well-established, crowdsourced, georeferenced database to which more than 600,000 citizens and scientists submit bird sightings. The quantity of eBird data collected by citizen birders may be useful in further elucidating relationships among greenness, biodiversity, and human health. Urban development tends to homogenize bird communities, meaning that species richness and diversity decrease at high urban densities (Melles 2005, Tratalos et al. 2007), and trends in bird diversity and density may indicate biodiversity status in general. I may be able to use eBird contributor record species richness to provide a proxy measure of biodiversity and relate this to greenness and human health. My objectives were to: 1) Map eBird records of bird species and determine bird species richness at the census tract level, and 2) Relate eBird record species richness to census tract level NDVI, development intensity and local human health outcome measures to elucidate relationships.