Background: Black women living in southern states have the highest breast cancer mortality rate in the United States. The prognosis of de novo metastatic breast cancer is poor. Given these mortality rates, we are the first to link nationally representative data on breast cancer mortality hot spots (counties with high breast cancer mortality rates) with cancer mortality data in the United States and investigate the association of geographic breast cancer mortality hot spots with de novo metastatic breast cancer mortality among Black women. Methods: We identified 7292 Black women diagnosed with de novo metastatic breast cancer in Surveillance, Epidemiology, and End Results (SEER). The county-level characteristics were obtained from 2014 County Health Rankings and linked to SEER. We used Cox proportional hazards models to calculate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for mortality between hot spot and non-hot spot counties. Results: Among 7292 patients, 393 (5.4%) resided in breast cancer mortality hot spots. Women residing in hot spots had similar risks of breast cancer-specific mortality (aHR ¼ 0.99, 95% CI ¼ 0.85 to 1.15) and all-cause mortality (aHR ¼ 0.97, 95% CI ¼ 0.84 to 1.11) as women in non-hot spots after adjusting for individual and tumor-level factors and treatments. Additional adjustment for county-level characteristics did not impact mortality. Conclusion: Living in a breast cancer mortality hot spot was not associated with de novo metastatic breast cancer mortality among Black women. Future research should begin to examine variation in both individual and population-level determinants, as well as in molecular and genetic determinants that underlie the aggressive nature of de novo metastatic breast cancer.

The Danish archives comprise some of the world's most comprehensive source coverage but despite large-scale digitization and transcription projects by diverse actors, there are no shared standards or possibilities for data linkage. The Denmark-based Link-Lives research project (2019-2024) is tackling this disparity by linking individual-level Danish records in census and parish record sources from 1787-1968 to create a multigenerational database for research using a combination of domain expertise and machine learning techniques. In contrast to small-sample linking or fully automated processes, Link-Lives is creating its own manually-linked data to train machine learning as well as exploring the impacts of different approaches to linking. Due to personal data protection legislation and propriety agreements, the data cannot be fully open access, but data outputs will be made available to both researchers and the general public via a website. The project's interdisciplinary team is based at the Danish National Archives and the University of Copenhagen, in partnership with Copenhagen City Archives, and funded by Carlsberg and Innovation Fund Denmark.

Objectives: To examine changes in Healthy Life Expectancy (HLE) against the backdrop of rising mortality among lesseducated white Americans during the first decade of the twenty-first century. Methods: This study documented changes in HLE by education among U.S. non-Hispanic whites, using data from the U.S. Multiple Cause of Death public-use files, the Integrated Public Use Microdata Sample (IPUMS) of the 2000 Census and the 2010 American Community Survey, and the Health and Retirement Study (HRS). Changes in HLE were decomposed into contributions from: (i) change in age-specific mortality rates; and (ii) change in disability prevalence, measured via Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL). Results: Between 2000 and 2010, HLE significantly decreased for white men and women with less than 12 years of schooling. In contrast, HLE increased among college-educated white men and women. Declines or stagnation in HLE among less-educated whites reflected increases in disability prevalence over the study period, whereas improvements among the college educated reflected decreases in both age-specific mortality rates and disability prevalence at older ages. Discussion: Differences in HLE between education groups increased among non-Hispanic whites from 2000 to 2010. In fact, education-based differences in HLE were larger than differences in total life expectancy. Thus, the lives of less-educated whites were not only shorter, on average, compared with their college-educated counterparts, but they were also more burdened with disability.

Prior research finds that human capital may explain racial housing inequality, whereas others note the historical role that race played in creating unequal housing conditions. This study uses the case of Cubans in the United States to examine whether human capital explains Black–White housing inequalities, or if they are a result of nativity/cohort differences—a proxy for the federal policies that supported Cubans’ economic and social incorporation. Using pooled data from the American Community Survey, I examine how human capital characteristics and nativity/migration cohorts shape odds of homeownership and predicted home values among Cubans. Extended analyses using decomposition methods find that although human capital characteristics are important, they play a smaller role in explaining Black–White differences in homeownership and home values. Indicative of the changing structure of racial stratification in the United States, results reveal substantial inequality among the oldest of Cuban immigrants and U.S.-born Cubans, despite a trend toward declining inequality among recent arrivals. Supported by the literature of systemic racism, the case of Cubans shows how human capital explanations do not sufficiently explain racial housing inequalities and how the future of racial stratification is one of inter- and intra-ethnic group inequality.

Alberto Burgos is one of thousands of Mexican migrants living in the United States who dug deep and sent extra money to family back home last year to alleviate the devastating impact of the coronavirus pandemic.

Many older adults struggle to meet their daily expenses, but persons of color have amplified risk of economic insecurity. In this article, by situating older adults in their geographic locations of residence, we discuss how life-course experiences intersect with aspects of older people’s communities to produce disparities in experiencing precarious financial situations. Race-based risks and disadvantages that accumulate over time yield racial disparities in income among older adults. Taking into account local cost of living reveals substantial disparities in economic security by race. Disparities are far greater in some states than in others.

This article details the challenges and issues of using race and ethnicity data to measure American Indian and Alaska Native (AI/AN) identity. In 2019, the Bureau of Indian Education prepared a preliminary report that considered an array of estimates of the AI/AN precollegiate population to proxy for the number of students eligible to participate in the Johnson O’Malley program, a federally funded program driven by community involvement and student needs assessments to design services that meet the specific academic and cultural needs of AI/AN precollegiate students. The data sets included in that report are analyzed to illustrate that estimating the total number of AIs/ANs is complicated by many factors, the current approach for processing and reporting AI/AN identity in federal data sets needs revision, and the current state of data collection does not meet the needs of policymakers, researchers, or community organizations. Finally, an algorithm is developed to improve on currently published estimates of the AI/AN precollegiate population by using the strengths of existing data sets to compensate for their weaknesses.

Immigrant children in the US have very limited health insurance coverage and health care access. Immigration status is not static: Census data show that the majority of census respondents who enter as noncitizen children eventually become citizens. Eligibility restrictions that prevent noncitizen children from being publicly insured can contribute to their experiencing poorer health and higher medical costs in their adult lives. We isolate the impact of lack of citizenship from socioeconomic factors by comparing citizen and noncitizen siblings living in mixed-status families, using fixed-effects models to net out socioeconomic factors shared within families. Lacking citizenship increased a child’s risk of being uninsured and lowered by 26 percentage points the chances that they would have Medicaid or Children’s Health Insurance Program coverage. Noncitizen children had significantly more delays in needed medical care because of cost, primarily mediated by the lack of insurance coverage. The US should reexamine policies that exclude noncitizen children from public health insurance programs.

Today, the Washington region is known for having very diverse suburbs, including Prince George’s County, the largest suburban majority-African-American county in the country. However, 50 years ago, the region’s suburbs were nearly entirely white, while non-white racial and ethnic groups were largely concentrated in the District east of 16th Street NW.

Drug overdose is a leading cause of unintentional death in the United States and has contributed significantly to a decline in life expectancy from 2015 to 2018. Overdose deaths, especially from opioids, have also been recognized in recent years as a significant public health issue. To address this public health problem, this study sought to identify neighborhood-level (e.g., block group) factors associated with drug overdose and develop a spatial model using machine learning (ML) algorithms to predict the likelihood or risk of drug overdoses across South Carolina. This study included block group level sociodemographic factors and drug use variables which may influence the incidence of drug overdose. In particular, this study developed a new index of access to measure spatial access to treatment facilities and incorporated these variables to assess the relationship between drug overdose and accessibility to the treatment centers. We explored different ML algorithms (e.g., XGBoost, Random Forest) to identify optimum predictors in each category. The categories were combined into a final ensemble predictive model that addressed spatial dependency. An evaluation was conducted to validate that the final model generalized well across the different datasets and geographical areas. Results of the study identified strong neighborhood-level predictors of a drug overdose, pinpointing the most critical neighborhood-level factor(s) that place a community at risk and protect communities from developing such problems. These factors included proportion of households receiving food stamps, households with income less than $35,000, high opioid prescription rates, smoking accessories expenditures, and low accessibility to opioid treatment programs and hospitals. The generalized error of spatial models did not increase considerably in spatial cross-validation compared to the error estimated from normal crossvalidation. Our model also outperformed the geographic weighted regression method. Our Results show that variables regarding socio-demographic factors, drug use variables, and protective resources can assist in spatial drug overdose prediction. Our finding highlights several specific pathways toward community-level intervention targeted to a vulnerable population facing potentially high burdens of drug abuse and overdose.

I use data for consistently defined municipalities to describe spatial patterns in population growth in Puerto Rico across all stages of economic development and rule by Spain and then the United States. The spatial distribution of population began to resemble the modern distribution after the turn of the twentieth century, around the time that municipal population densities diverged. Municipal population growth was positively correlated with crop production in the preindustrial era and was negatively correlated with agricultural employment from 1899 to 1970. Urbanization commenced around 1900, decades earlier than generally believed and before most of the Caribbean and Central America.

New technologies, such as automation, artificial intelligence and industrial robots, are often seen as a real danger for existing jobs and also for future job-creation prospects. There is a perception that they will make work redundant and lead to massive job destruction. However, others believe that automation, like previous technological waves , will increase the demand for labor in other sectors and create new jobs that did not exist in the past, and therefore lead to higher wages and improvements in the standards of living. It is important to note that technological advances have historically increased productivity, generated sustained increases in living standards and created more jobs than they have destroyed . However, this progress has sometimes been accompanied, especially during the transition period, by several disruptions, particularly in the labor market. Indeed, technology has brought about profound structural economic change, creating new jobs and sectors, while destroying and modifying others, with major consequences for certain categories of the population, especially low-skilled workers. Ongoing technological advances offer new prospects for higher productivity and economic growth. However, they are also accompanied by growing concerns about their future impact on the workforce , especially in the current context of high and rising levels of inequality and polarization in the labor market. It should be noted that we have experienced in the past both an increase in incomes and a stable labor share because of other technological changes that have generated new tasks for labor and, thus, offset the job losses induced by automation. The future of work will certainly depend on how artificial intelligence (AI), robots, and automation impact the allocation of tasks to labor and capital. It will also depend on the preparation and measures taken by governments, in particular, for effectively supporting the population during this transition, to ensure that new technologies are inclusive and beneficial to all social categories of society.

The COVID-19 pandemic and the public health measures adopted in response to it have triggered plenty of speculation about the potential impact on fertility in different regions across the globe. This study provides evidence on the fertility response in four sub-Saharan African countries during the early stage of the pandemic. Using harmonized and representative data from the Performance Monitoring for Action (PMA) data series, the study presents pregnancy rates during the period from 2014 to mid-2020. There is no indication of a general increase in pregnancy rates in the year 2020 compared to previous years. This finding is preserved when pregnancy rates are differentiated by age, marital status, and contraceptive use of the surveyed women.

Registraron un incremento del 11.44% en 2020, al totalizar 40 mil 606.6 millones de dólares, sobre los 36 mil 438.7 millones del año anterior

In this dissertation, I discuss three papers. The first two, “Fixing the Leaky Pipeline: The Role of Beliefs About Ability in STEM Major Choice” and “Knowing What it Takes: The Effect of Information About Returns to Studying on Study Effort and Achievement”, use field experiments to influence student beliefs to study student decision making. These papers demonstrate both the need to focus on students’ mental models of decision characteristics when creating education policy, as well as the potential for thoughtful information interventions to influence student behavior. The third paper, “The Economic Impacts of Hurricane Maria”, studies how a sudden influx of workers into a labor market influences the local economy. We find that these new workers grow the economy overall, with heterogeneous effects by sector. These three papers each show how rigorous research designs and econometric techniques can help us study complex social phenomenon.

We use a five percent sample of Americans' credit bureau data, combined with a regression discontinuity approach, to estimate the effect of universal health insurance at age 65-when most Americans become eligible for Medicare-at the national, state, and local level. We find a 30 percent reduction in debt collections-and a two-thirds reduction in the geographic variation in collections-with limited effects on other financial outcomes. The areas that experienced larger reductions in collections debt at age 65 were concentrated in the Southern United States, and had higher shares of black residents, people with disabilities, and for-profit hospitals.

The present paper explores the Concept of Digital Earth with its key elements and the associated information and communication technologies; the bases, history and impact of Digital Revolution on Geography; major challenges ahead of geographers and the potential applications of Digital technology towards the geographical study of Earth’s surface.

Recent years have seen an increase in the use of secondary data in climate adaptation research. While these valuable datasets have proven to be powerful tools for studying the relationships between people and their environment, they also introduce unique oversights and forms of invisibility, which have the potential to become endemic in the climate adaptation literature. This is especially dangerous as it has the potential to introduce a double exposure where the individuals and groups most likely to be invisible to climate adaptation research using secondary datasets are also the most vulnerable to climate change. Building on significant literature on invisibility in survey data focused on hard-to-reach and under-sampled populations, we expand the idea of invisibility to all stages of the research process. We argue that invisibility goes beyond a need for more data. The production of invisibility is an active process in which vulnerable individuals and their experiences are made invisible during distinct phases of the research process and constitutes an injustice. We draw on examples from the specific subfield of environmental change and migration to show how projects using secondary data can produce novel forms of invisibility at each step of the project conception, design, and execution. In doing so, we hope to provide a framework for writing people, groups, and communities back into projects that use secondary data and help researchers and policymakers incorporate individuals into more equitable climate planning scenarios that “leave no one behind.”

Progress in narrowing education and employment gender gaps is being observed in many countries across the world and has come to be known as the “gender revolution”. Today, women are entering higher education in large numbers and have begun to outperform men. They are spending more time in the labour market and, in some countries, the employment rates of both genders have converged. These changes are impacting women’s family and work lives globally, and Egypt is no exception. Similar to other patriarchal Arab countries, however, is that gender relations in Egypt have remained unequal in the family, and expectations of marriage and motherhood are commonplace. These continuing gender inequalities remain understudied. To fill this gap, this thesis explores the ways in which resources and cultural constraints in modern-day Egypt shape gender inequalities at the work-family interface during key life stages and events: adolescence, marriage, and reproduction. Specifically, I examine how gender inequalities persist across generations in the Egyptian family, and what these mean for women’s socioeconomic well-being in marriage. To do so, attention is paid to three key dimensions of gender inequality: women’s employment stability, their risk of intimate partner violence (IPV), and their household decision-making power. Using both cross-sectional and longitudinal data from Egypt permitted a quantitative analysis of women’s resources, cultural norms, and their interaction, on women’s empowerment in the Egyptian family. The thesis is ordered to follow a woman’s normative life trajectory in Egypt. It begins by providing the first investigation of the intergenerational link between maternal employment during women’s own adolescence and their subsequent adult employment stability. While identifying the positive impact of maternal employment, this study finds that this link is mediated by women’s education, and moderated by the employment sector. Next, building on existing research, this thesis explores how, if at all, the Arab Spring has altered women’s risk of IPV in marriage. I consider whether women’s employment offers more effective protection against IPV, using data before and after the revolution. Finally, I examine whether women’s household decision-making power is affected by women’s command of resources. Here, I move beyond considering the resources of education and employment to also consider women’s patrilineal fertility—that is, having at least one son—and how it operates alongside women’s education and employment. The thesis fills an important gap by assessing how cultural, economic, and noneconomic resources come together to configure power relations in the family and gender inequalities in the labour market in a non-Western context. It uncovers the mechanisms that maintain and reinforce gender inequality within the Egyptian family. By drawing attention to contextual changes and historic events such as the Arab Spring, it also highlights how these inequalities have remained stubborn, despite sweeping sociopolitical changes. Together, the findings from this study reveal a mosaic of social changes characterised by both progress and stasis. Thus, the thesis documents an incomplete gender revolution in Egypt—maternal employment enhances women’s employment stability, and, in turn, women’s employment reduces their risk of IPV; yet their marital power remains contingent on the birth of a son, regardless of their education and employment.

The negative impacts of the Great Recession (GR) (2007 to 2009) on the lives of families with low incomes warrant social work concerns about how well antipoverty policy responded to meet economic needs over this period and since. Given America's long-standing tension between welfare state adequacy and market-oriented policies, how well did the safety net respond to the economic downturn? Did GR-era changes reverse or accelerate trends in public assistance? This article examines key policy changes and indicators of caseloads, inclusion, and generosity for three antipoverty policies: the Temporary Assistance for Needy Families, the Supplemental Nutrition Assistance Program (SNAP, formerly Food Stamp Program), and the Earned Income Tax Credit from 2007 to 2017. Authors' analysis shows a continuation of market-oriented U.S. antipoverty policy. Authors argue that the reemphasis of conditioning benefits on employment undermines the countercyclical feature of the social safety net and perpetuates the inequitable redistribution of public resources between those inside and outside of the labor market. Authors discuss social workers' role in strengthening antipoverty policies to improve the economic well-being of people with low incomes and the economic justice of the social safety net.