Latinos are increasingly driving the demographic fortunes of the United States. Between 2000 and 2011, the number of white children in the country declined by 4.9 million, a decrease of 11 percent. Blacks and American Indians and Alaska Natives also saw their child populations decline. The nations total child population, however, increased by 1.7 million in the same period, largely due to the growth in the Latino child population. The number of Latino children rose by 5.1 million during this period (Figure 1), an increase of 42 percent. The number of multiracial and Asian and Pacific Islander children also expanded, but much less than the increase of Latino youth.

The U.S. recession of 2007-2009 saw unemployment rates for men rise by significantly more than those for women, resulting in the downturns characterization as a mancession. This paper uses data from the Census Bureaus American Community Survey to reexamine gender-related dimensions of the 20072009 recession. Unlike most previous work, we analyze data that connects men's and women's employment status to that of their spouses. A difference-in-difference framework is used to characterize how labor-market outcomes for one spouse varied according to outcomes for the other. Results show that that employment rates of women whose husbands were non-employed rose significantly in the recession, while those for people in other situations held steady or fell consistent with the view that women took on additional bread-winning responsibilities to make up for lost income. However, probabilities of non-participation did not rise by more for men with working wives than they did for other men, casting doubt on ideas that men in this situation made weaker efforts to return to work because they could count on their wives paychecks to support the household.

This study examines the career pathway of biomedical scientists along the educational pipeline from high school to advanced degree and on through to NIH-funded investigator. Using a relevant labor market perspective, we examine U.S. Census data to determine how transition points along this path vary by gender, race, and citizenship. Critical transition points are high school, associate, bachelor, and graduate degree completion, as well as the award of an NIH research grant. With recent data (2008-2012), we update previously published estimates and identify where various groups are leaving or entering the pipeline and to what extent.

Beginning with the discovery of male predominant sex ratios among new-born infants in the seventeenth century, demographers have documented predictable variations in the gender composition of human populations. Higher rates of male mortality. . .

The status exchange hypothesis suggests that in black-white marriages one spouses educational status is traded for the other spouses racial status. Exchange is claimed to emerge from strong barriers between racial groups. If so, exchange should decline as interracial marriage becomes more common. We examine trends in status exchange among black-white marriages between 1980 and 2010, a period over which these unions have increased from 0.4% to 2.2% of all young couples. Contrary to expectations, status exchange between black men and white women has not declined but somewhat increased, suggesting that racial stratification in the marriage market remains strong. This trend is the product of two countervailing forces: exchange has increased across cohorts but declines as cohorts age and experience late marriage and remarriage. Trends over time are similar for married and cohabiting couples, suggesting that status exchange defines all types of interracial unions.

Obesity is an important public health problem because it is a risk factor for numerous diseases and is associated with a higher death risk. Evidence concerning the prevalence of excess weight in health professionals is scarce and this group is often overlooked in weight interventions programs. This paper aims to estimate the prevalence of obesity and overweight among Portuguese primary health care professionals and to describe differences between occupational groups. Material and Methods: This was a cross sectional study based on a primary care setting in Portugal in2011. We collected data on occupation, age, sex and height of professionals from four primary care centers. We did a descriptive analysis of the main variables and an analysis of covariance to compare mean Body Mass Index. Results: Our sample represented 52.8% of the total population of the four primary care centers, and 38.6% were overweight and 16.9% were obese. When adjusted for age and gender, health service personnel had the highest average Body Mass Index, followed by nurses, physicians, and superior technicians, in that order. Discussion: Although we can’t ensure the generalisation of the results and cannot exclude the possibility of sampling bias, these results suggest high prevalence obesity and overweight in workers of primary health care in Portugal. Conclusion: In this primary care setting more than half of the health care professionals were overweight or obese. Tailored interventions might be needed to tackle this issue.

Women's ability to have children declines sharply with age. This fecundity loss may nega-tively affect marital prospects for women who delay marriage to make career investments. To test this, I implement an incentive-compatible online experiment where age is randomly assigned to dating profiles. I find that men have strong preferences for younger partners, but only when they have no children of their own and are aware of the age–fertility tradeoff. I then incorporate depreciating " reproductive capital " into a marriage matching model with optional human capi-tal investments. The model predicts potentially worse marriage market outcomes for educated women, matching historical data. JEL Codes: C78, D10, I26, J12, J13, J16 Women's ability to conceive children falls off rapidly around age 40. This decline in fecundity has

We assess the extent to which the recent housing boom and bust affected employment, wages, and college enrollment and attainment during the 2000s. We exploit cross-city variation in local housing booms, and we identify plausibly exogenous variation in housing demand using sharp structuralbreaks in local housing prices. We find that positive housing demand shocks significantly increased wages and employment between 2000 and 2007, particularly for less-skilled workers. Consistent with the idea that the housing boom increased the opportunity cost of college for workers on the margin of college attendance, housing demand shocks during the boom reduced college enrollment and attainment for both young men and women, with the effects concentrated at community colleges. Over the longertime horizon spanning the housing boom and bust, we find that the positive wage and employment effects of the boom were generally undone during the bust. However, the negativeeffects of the housing boom on schooling persist, suggesting that reduced educational attainment may be an enduring effect of the large, temporary increase in housingdemand.

We construct a new dataset of linked census records to study internal migrants selection and destination choices during the first decades of the Great Migration (1910 to 1930). While there is some evidence of positive selection into migration, the degree of selection was generally small and participation in migration was widespread. Differences in background characteristics, including initial location, cannot account for racial differences in destination choices. Black and white men were similarly responsive to pre-existing migrant networks, but black men were more deterred by distance, attracted to manufacturing centers, and responsive to variation in labor demand.

This paper reexamines the first viable and a still leading explanation for mid-twentieth century baby booms: Richard Easterlins relative income hypothesis. He suggested that when incomes are higher than material aspirations (formed in childhood), birth rates would rise. This paper uses microeconomic data to formulate a measure of an individuals relative income. The use of microeconomic data allows the researcher to control for both state fixed effects and cohort fixed effects, both have been absent in previous examinations of Easterlins hypothesis. The results of the empirical analysis are consistent with Easterlins assertion that relative income influenced fertility decisions, although the effect operates only through childhood income. When the estimated effects are contextualized, they explain 12 percent of the U.S. baby boom.

Sensitive biomedical data is often collected from distributed sources, involving different information systems and different organizational units. Local autonomy and legal reasons lead to the need of privacy preserving integration concepts. In this article, we focus on anonymization, which plays an important role for the re-use of clinical data and for the sharing of research data. We present a flexible solution for anonymizing distributed data in the semi-honest model. Prior to the anonymization procedure, an encrypted global view of the dataset is constructed by means of a secure multi-party computing (SMC) protocol. This global representation can then be anonymized. Our approach is not limited to specific anonymization algorithms but provides pre- and postprocessing for a broad spectrum of algorithms and many privacy criteria. We present an extensive analytical and experimental evaluation and discuss which types of methods and criteria are supported. Our prototype demonstrates the approach by implementing k-anonymity, -diversity, t-closeness and -presence with a globally optimal de-identification method in horizontally and vertically distributed setups. The experiments show that our method provides highly competitive performance and offers a practical and flexible solution for anonymizing distributed biomedical datasets.

After a hundred years of contributions, the debate about how to measure inequality is still open. We provide a brief review of the literature, showing that inequality has been assessed through a relative approach, from Gini's pioneering article [Atti del Reale Istituto Veneto di Scienze, Lettere ed Arti 73 (1914), no. 2, 1203–1248]. Analyzing historical census data for Flint and other American cities, we observe how mean values of income in population subgroups capture the shape of the distributions of income and their comparisons state the overall situation of inequality. Namely, we adopted the approach introduced in [Statistica & Applicazioni 5 (2007), no. 1, 3–27] to assess inequality. Our first findings show that prosperity is distributed unevenly across America's metropolitan areas. More interestingly, unbalanced wealth can be related to other concomitant facts [The New Geography of Jobs, Houghton Mifflin Harcourt, New York, 2012], such as population growth, income growth, unemployment rates and women participation to the labor force. Gaps between more and less educated areas were modest 40 years ago, but they have become quite large nowadays [Cities and skills, technical report, National Bureau of Economic Research, 1994].

Background: In estimating the association between discrimination and depression, existing research using standard regression models has generally relied on a single parameter estimate based on the conditional mean that reflects the relationship size for the average individual. Such estimates that focus on the average individual, however, may provide limited information regarding the true nature of the discriminationdepression relationship, which may vary across different points of the distribution of depressive symptoms conditional on various personal and social attributes. Objective: This study examined the size of the differential associations between perceived discrimination and depressive symptoms among immigrant youth in the USa rapidly growing and potentially vulnerable demographic group. Conclusions: Findings from this study may stand to present substantive implications for both practitioners and policy makers who are often most interested in understanding the daily stressful experiences and their correlates concerning the most marginalizing situations.

Multidimensional data have various representations. Thanks to their simplicity in modeling multidimensional data and the availability of various mathematical tools (such as tensor decomposition) that support multi-aspect analysis of such data, tensors are increasingly being used in many application domains including scientific data management, sensor data management, and social network data analysis. Relational model, on the other hand, enables semantic manipulation of data using relational operators, such as projection, selection, Catesian-product and set operators. For many multidimensional data applications, tensor operations as well as relational operations need to be supported throughout the data life cycle. In this thesis, we introduce a tensor-based relational data model (TRM), which enables both tensor-based data analysis and relational manipulations of multidimensional data, and define tensor-relational operations on this model. Then we introduce a tensor-relational data management system, so called, Tensor DB. TensorDB is based on TRM, which brings together relational algebraic operations (for data manipulation and integration) and tensor algebraic operations (for data analysis). We develop optimization strategies for tensor-relational operations in both in-memory and in-database TensorDB. The goal of the TRM and TensorDB is to serve as a single environment that supports the entire life cycle of data; that is, data can be manipulated, integrated, processed, and analyzed.

This paper reviews recent literature that considers and explains the tendency for neighborhood and city-level economic status to rise and fall. A central message is that although many locations exhibit extreme persistence in economic status, change in economic status as measured by various indicators of per capita income is common. At the neighborhood level, we begin with a set of stylized facts, and then follow with discussion of static and dynamic drivers of neighborhood economic status. This is mirrored at the metropolitan level. Durable but slowly decaying housing, transportation infrastructure, and self-reinforcing spillovers, all influence local income dynamics, as do enduring natural advantages, amenities and government policy. Three recurring themes run throughout the paper: (i) Long sweeps of time are typically necessary to appreciate that change in economic status is common; (ii) history matters; and (iii) a combination of static and dynamic forces ensure that income dynamics can and do differ dramatically across locations but in ways that can be understood.

This paper reviews recent literature that considers and explains the tendency for neighborhood and city-level economic status to rise and fall. A central message is that although many locations exhibit extreme persistence in economic status, change in economic status as measured by various indicators of per capita income is common. At the neighborhood level, we begin with a set of stylized facts, and then follow with discussion of static and dynamic drivers of neighborhood economic status. This is mirrored at the metropolitan level. Durable but slowly decaying housing, transportation infrastructure, and self-reinforcing spillovers, all influence local income dynamics, as do enduring natural advantages, amenities and government policy. Three recurring themes run throughout the paper: (i) Long sweeps of time are typically necessary to appreciate that change in economic status is common; (ii) history matters; and (iii) a combination of static and dynamic forces ensure that income dynamics can and do differ dramatically across locations but in ways that can be understood.

Making co-existent and convergent the need for efficiency of relational query processing over Clouds and the security of data themselves is figuring-out how one of the most challenging research problems in the Big Data era. Indeed, in actual analytics-oriented engines, such as Google Analytics and Amazon S3, where key-value storage-representation and efficient-management models are employed as to cope with the simultaneous processing of billions of transactions, querying encrypted data is becoming one of the most annoying problem, which has also attracted a great deal of attention from the research community. While this issue has been applied to a large variety of data formats, e.g. relational, RDF and multidimensional data, very few initiatives have pointed-out skyline query processing over encrypted data, which is, indeed, relevant for database analytics. In order to fulfill this methodological and technological gap, in this paper we present eSkyline, a prototype system and query interface that enables the processing of skyline queries over encrypted data, even without preserving the order on each attribute as order-preserving encryption would do. Our system comprises of an encryption scheme that facilitates the evaluation of domination relationships, hence allows for state-of-the-art skyline processing algorithms to be used. In order to prove the effectiveness and the reliability of our system, we also provide the details of the underlying encryption scheme, plus a suitable GUI that allows a user to interact with a server, and showcases the efficiency of computing skyline queries and decrypting the results.

This study compared the changes in the healthy food accessibility landscape of St. Paul from 2002 to 2012. Food deserts are areas of limited or no accessibility to healthy food options. Local food landscapes in the U.S. and Canada have changed significantly over the past 50 years as many supermarkets have relocated out of the inner cities and into the suburbs. As a result, many inner city neighborhoods no longer have adequate access to healthy food. Despite supermarkets relocating out of the inner city, small and mid-sized grocers could stock healthy food options. The research questions answered are: Where are the underserved areas in St. Paul at the Census Block Group (CBG) level? How has the food desert landscape changed from 2002 to 2012? Which socioeconomic groups have the highest and lowest access to grocery stores and supermarkets? Grocery stores included all types of grocery stores and supermarkets were defined as grocery stores with more than 50 employees. Each food outlet location from 2002 and 2012 was geocoded and distances were calculated from each population-weighted CBG centroid to the nearest food outlet using the Network Analyst extension in ArcGIS 10.1. To be classified as a potential food desert, CBGs have to be more than 1,000 meters from the nearest food establishment by walking distance and more than 3,000 meters or 5,000 meters from the nearest grocery store by public transit. In addition to these criteria, potential food deserts must have a socioeconomic deprivation index above the fifth quintile of all CBGs in St. Paul. The results showed that there were few food deserts in St. Paul in 2002 and 2012 with the inclusion of public transit at the 3,000-meter threshold for grocery stores and at the 5,000-meter threshold for supermarkets. In 2012, the general trend showed more underserved CBGs by both walking and public transit to grocery stores and supermarkets than in 2002. Socioeconomic deprivation was linked to higher grocery store access but lower supermarket access for both 2002 and 2012. Future research and ground truth data is needed to verify if some of the smaller grocers stock healthy food or if there are other sources of healthy food that are accessible to the underserved CBGs identified in this analysis.