The validity of the general self-rated health (SRH) assessment is well established; however, there are empirical questions as to the utility of health assessment measures that employ more refined comparisons. The aim of this study is to examine subjective health assessment measures in comparison to the most widely used SRH measure (Global SRH) among men and women. We investigate agreement between these measures, by gender, and their correspondence with objective health conditions using a sample of adults over the age of 60 from the 2006 La Encuesta Nacional de Salud y Nutrición (ENSANUT). ENSANUT is a nationally representative, repeated cross-sectional Mexican survey (n = 5511) and advantageous given its inclusion of three distinct subjective health assessment questions including: global self-rated health, self-rated heath today, and 12-month self-rated health. First, we descriptively examine demographic characteristics of the sample and the degree of correspondence between health ratings. Then, we explore congruence between objective health conditions and subjective-health ratings within each SRH measure. We estimate three ordered logistic regression models testing responses on a three-point scale and use predicted probabilities for interpretation. Our findings reaffirm the role of physical health conditions as strong predictors of poor SRH and highlight the significance of mental health as a determinant of subjective health in this sample of older Mexican adults. We caution that future research examining older adults’ health should carefully consider the type of subjective health assessment used.
The study uses administrative data from Luxembourg to investigate fathers’ decisions to use parental leave. We focus on two measures of opportunity cost: the difference between the parental leave benefit and the salary of the father and the mean salary growth for a period of 6 months for each father. The first measure captures the direct opportunity cost, while the second is a proxy for foregone promotion opportunities. We use Cox proportional hazards model for the analysis. The results suggest a negative relationship between foregone income and taking parental leave. Surprisingly, salary growth appears to be positively related to the hazard of taking parental leave. Coefficients of control variables are in line with previous findings: fathers are more likely to use parental leave if they work in larger organization and for the first child.
An increasing number of U.S. adults are progressing through college in decidedly more complex ways. Little is known, however, about how this growing heterogeneity may be associated with the health behaviors and ultimately health of young adults. Using a life course perspective, we investigate whether and why different educational pathways—that is, variation in when people attend and complete school—are associated with daily smoking and binge drinking among U.S. young adults. We use 14 waves (1997–2011) of data from the National Longitudinal Survey of Youth 1997 cohort (n = 7359) that enable us to identify the most common educational pathways, as well as their association with young adult health behaviors. Bachelor’s degree recipients who enrolled immediately after high school but did not attain their degree within 4 years were more likely to smoke daily in early adulthood (i.e., ages 26–32) than those who enrolled in college immediately after high school and attained a bachelor’s degree within 4 years. Conversely, bachelor’s degree recipients who delayed college enrollment were less likely to binge drink in early adulthood than individuals who enrolled in college immediately after high school and attained a bachelor’s degree within 4 years. Marital status and household income in young adulthood accounted for some of the relationships between educational pathways and health behavior. These findings highlight the complexity of education’s relationship to health behavior and strongly suggest that heterogeneity in educational pathways should be explicitly examined in population health research.
This paper describes geographic variation in the sex composition of the foreign-born population in the US since 1990, and uses Blinder-Oaxaca decomposition to identify key sources of variation in regional sex ratios. We use data from the 1990 and 2000 US Censuses, and from the 2007–2011 American Community Survey, to create estimates of the size and characteristics of foreign-born populations at the level of Consistent Public-Use Microdata Areas. We find substantial local- and region-level variation in population sex ratios, with the highest sex ratios in the South and Midwest. This variation is partly explained by differences in the age- and national origin-composition of immigrants, but the effects of immigration history, age, and national origin on sex ratio vary substantially by region. The West in particular stands out as having high levels of unexplained difference from other regions. Future research is necessary to understand these regional differences in gendered immigration patterns.
It has been argued that preferences for the sex of children would be small or non‐existing in relatively gender equal societies. However, previous studies have suggested that a stronger preference for having daughter exists in Scandinavian countries, which are frequently noted for being among the most gender equal societies in the world. Combining new register data on birth rates by sex of the previous children and recent survey data on couples’ stated preferences for the sex of children, we show that the preference for daughters has increased in Sweden over the last decade. In addition to the stronger preference for having daughters among two‐child mothers documented in previous research, our findings show that during the previous decade this preference was noticeable also among one‐child parents. Despite Swedish society being known for holding gender equal social norms, interviewed parents openly expressed some degree of preference for having daughters over sons.
The study presented here has two main purposes. First, we introduce a novel conceptualization of neighborhood effects that includes historical characteristics of place as independent influencers on individual outcomes. Second, we provide two empirical examples of this concept by analyzing the influence that historic neighborhood dropout and poverty rates have on contemporary dropout behavior. Using multilevel logistic models, we find that students living in neighborhoods marked with a dropout or poverty legacy are over 16% more likely to drop out compared to students living outside of these areas. The influence of legacy of place remains even when controlling for contemporary neighborhood attributes including current dropout and poverty rates. The findings set the stage for future conceptual and empirical work that considers the historical development of place as it relates to the impact that these histories have for contemporary individuals.
How does intergenerational educational mobility change under educational expansion? This paper examines this question in Mexico, which enacted two important school expansion plans between 1959 and 1992. Using the 2011 Mexican Social Mobility Survey, I analyze how intergenerational mobility changes under different phases of expansion reform, and how do these trends vary according to the particular stage of the schooling process. Main findings indicate that mobility patterns are not stalled across cohorts, as reproduction theories predict. However, they do not reflect equalization at all levels of education either, as modernization hypotheses anticipate. Expansion reforms, especially the “11-year plan,” are associated with positive trends in mobility in primary and lower-secondary schooling, but also with a decrease in intergenerational mobility at higher levels of education. Thus, these findings are consistent with the maximally maintained inequality hypothesis.
The theoretical and empirical links between public health insurance access and fertility in the United States remain unclear. Utilizing a demographic cell-based estimation approach with panel data (1987–1997), we revisit the large-scale Medicaid expansions to pregnant women during the 1980s to estimate the heterogeneous impacts of public health insurance access on childbirth. While the decision to become a parent (i.e., the extensive margin) appears to be unaffected by increased access to Medicaid, we find that increased access to public health insurance positively influenced the number of high parity births (i.e., the intensive margin) for select groups of women. In particular, we find a robust, positive birth effect for unmarried women with a high school education, a result which is consistent across the two racial groups examined in our analysis: African American and white women. This result suggests that investigating effects along both the intensive and extensive margin is important for scholars who study the natalist effects of social welfare policies, and our evidence provides a more nuanced understanding of the influence of public health insurance on fertility.
Despite the widespread and rapidly growing popularity of Big Data, researchers have yet to agree on what the concept entails, what tools are still needed to best interrogate these data, whether or not Big Data’s emergence represents a new academic field or simply a set of tools, and how much confidence we can place on results derived from Big Data. Despite these ambiguities, most would agree that Big Data and the methods for analyzing it represent a remarkable potential for advancing social science knowledge. In my Presidential address to the Southern Demographic Association, I argue that demographers have long collected and analyzed Big Data in a small way, by parsing out the points of information that we can manipulate with familiar models and restricting analyses to what typical computing systems can handle or restricted-access data disseminators will allow. In order to better interrogate the data we already have, we need to change the culture of demography to treat demographic microdata as Big. This includes shaping the definition of Big Data, changing how we conceptualize models, and re-evaluating how we silo confidential data.
The military has long been seen as an avenue for increasing racial equality for minorities, especially black Americans. In this article, we examine to what extent military veterans also experience residential integration by looking at neighborhood residential outcomes for black and white men utilizing the popular Veterans Affairs (VA) loan program to purchase a home. We draw on data from the Home Mortgage Disclosure Act (HMDA) to examine residential integration among white and black veteran homebuyers compared to homebuyers utilizing conventional loans over three major lending eras: 1990s, 2000–2007, and 2008–2015. By 2015, a quarter of all home purchase mortgages loans to black men were VA loans even though veterans made up only a tenth of the adult black male population. In our multivariate analyses, we uncover a sizeable combined swing toward neighborhood minority-white integration, 14.4% points, among black and white veterans who use VA loans. Compared to those with conventional loans, black veterans live in neighborhoods with % points fewer minorities and, white veterans, 4.4% points fewer whites. Our results illustrate how racial integration in the US military has the potential to foster lasting housing integration among veterans.
Recent studies examine veteran status differences in mortality, but none consider heterogeneity in military-veteran health care coverage. We use data from the 1997–2009 (2011) National Health Interview Survey-Linked Mortality Files (N = 624,610) to estimate Cox regression models of the association between veteran status and mortality taking into account the type of military-veteran health care coverage and sex/gender. Descriptive analyses provide further evidence that veterans who only use Veterans Affairs (VA) health care services are a distinctly disadvantaged subpopulation with substantially increased mortality risk. Results from multivariate analyses confirm a veteran mortality disadvantage, reveal that this disadvantage varies by type of military-veteran health coverage, and demonstrate that the disadvantage is largely but not totally explained by demographic, socioeconomic, and health status differences between groups. Results further indicate that the veteran mortality disadvantage is most pronounced among male veterans who only use VA health care or who have no military-veteran health coverage, respectively, relative to male non-veterans with no military-veteran health care coverage. There is a mortality disadvantage among female veterans who have no military-veteran health care coverage, and a mortality advantage among female non-veterans with military-veteran health care coverage, relative to female non-veterans with no military-veteran health care. Based on these findings, we argue that in order to fully understand veteran status differences in morbidity and mortality, future studies must move beyond the analysis of veteran- and VA-only samples, and should take into account variable connections of subpopulations to the military, resultant differences in types of health care coverage, and sex/gender.
Extensive research has found that marriage provides health benefits to individuals, particularly in the U.S. The rise of cohabitation, however, raises questions about whether simply being in an intimate co-residential partnership conveys the same health benefits as marriage. Here, we use OLS regression to compare differences between partnered and unpartnered, and cohabiting and married individuals with respect to self-rated health in mid-life, an understudied part of the lifecourse. We pay particular attention to selection mechanisms arising in childhood and characteristics of the partnership. We compare results in five countries with different social, economic, and policy contexts: the U.S. (NLSY), U.K. (UKHLS), Australia (HILDA), Germany (SOEP), and Norway (GGS). Results show that living with a partner is positively associated with self-rated health in mid-life in all countries, but that controlling for children, prior separation, and current socio-economic status eliminates differences in Germany and Norway. Significant differences between cohabitation and marriage are only evident in the U.S. and the U.K., but controlling for childhood background, union duration, and prior union dissolution eliminates partnership differentials. The findings suggest that cohabitation in the U.S. and U.K., both liberal welfare regimes, seems to be very different than in the other countries. The results challenge the assumption that only marriage is beneficial for health.
While racial and ethnic differences in mortality are pervasive and well documented, less is known about how mortality risk varies by neighborhood socioeconomic status across racial and ethnic identity. We conducted a prospective analysis on a sample of adults living at or below 300% poverty with 8 years of the National Health Interview Survey (N = 159,400) linked to 11,600 deaths to examine the association between neighborhood disadvantage and mortality for non-Hispanic whites, non-Hispanic blacks, and U.S.- and foreign-born Hispanics. Using multilevel logistic regression, we find that the probability of death from any cause for lower-income adults is higher in more-disadvantaged neighborhoods, compared to less-disadvantaged neighborhoods, but only for whites. The adjusted likelihood of death for blacks and foreign-born Hispanics is not associated with neighborhood disadvantage, and the likelihood of death for U.S.-born Hispanics is lower in more-disadvantaged neighborhoods. While future research and policy should focus on improving health-promoting resources in all communities, care should be given to better understanding why race/ethnic groups have differential mortality returns with respect to area-specific socioeconomic conditions.
Despite acquiring lower levels of attainment and earnings, Mexican immigrants exhibit favorable health outcomes relative to their native-born counterparts. And while scholars attempt to reconcile this so-called paradoxical relationship with a variety of theoretical and empirical approaches, patterns of selective migration continue to receive considerable attention. The present study contributes to the literature on health selection by extending the healthy migrant hypothesis in a number of ways. First, we rely on a unique combination of datasets to assess whether the healthy are disproportionately more likely to migrate. We use the latest wave of the Mexican Family Life Survey and the 2013 Migrante Study, a survey that is representative of Mexican-born persons who are actively migrating through Tijuana. Pooling these data also allow us to differentiate between internal and US-bound migrants to shed light on their respective health profiles. Results provide modest support for the healthy migrant hypothesis. Although those who report better overall health are more likely to migrate, we find that the presence of certain chronic conditions increases migration risk. Our findings also suggest that internal migrants are healthier than those traveling to the US, though this is largely because those moving within Mexico reflect a younger and more educated population. This study takes an important step in uncovering variation across migrant flows and highlights the importance of the timing at which health is measured in the migration process.
Over the twentieth and twenty-first centuries, veterans have been more likely to enter into race/ethnic intermarriages than non-veterans. Theories of race/ethnic intermarriage variously point to how minority race/ethnicity, race/ethnically diverse social settings, progressive racial attitudes, and high socioeconomic status increase individuals’ likelihood of intermarrying. Veterans’ unique racial and socioeconomic characteristics may contribute to their greater likelihood of intermarrying relative to non-veterans: larger percentages of veterans than non-veterans are members of racial and ethnic minority groups, while military service increases individual service members’ long-term economic and educational prospects. At the same time, veterans share in common their exposure to the unique military environment, which may increase their likelihood of intermarriage by diversifying their social circles, and subjecting their attitudes and behavior to group norms that are more explicitly egalitarian than those of society at large. The present study considers these two possible explanations for veterans’ greater likelihood of intermarriage. We use data on seven cohorts of men over six decades in the Current Population Survey, representing a total of 1,456,742 observations, to decompose the difference in likelihood of racial intermarriage between veterans and non-veterans among married men aged 18–65. We find that across cohorts and decades, veterans’ greater likelihood of intermarrying is not fully explained by their race/ethnic and socioeconomic composition. We argue that veterans’ greater likelihood of intermarrying may therefore be driven by their exposure to the military environment.
Over the last 20 years, policymaking related to immigrant populations has increasingly been conducted at the state-level. State immigrant polices may influence immigrant poverty by determining immigrants’ level of access to social, economic, political, and health resources and by shaping the social environment. Further, these immigrant policies may shape the stratification between citizens and noncitizens, potentially contributing to distinct patterns of disparities in poverty by both citizenship and race/ethnicity. To assess the relationship between immigrant policy and socioeconomic stratification of immigrants across citizenship status and race/ethnicity in the U.S., we combined data from the 2014 American Community Survey and a measure of level of inclusion of state immigrant policies. We estimated fixed-effects logistic regressions to test the associations between poverty and the interaction of level of inclusiveness, citizenship, and race/ethnicity, controlling for state- and individual-level characteristics. Results showed that there are significant disparities in poverty by citizenship status and race/ethnicity. Asian/Pacific Islander (API) noncitizens experienced lower levels of poverty in states with higher levels of inclusion. Both Latino and API citizens experienced lower levels of poverty in states with higher versus lower levels of inclusion. Among Latinos, the gap in poverty rates between noncitizens and citizens is larger in more inclusive than less inclusive ones, suggesting that the potential positive impact of more inclusive environments does not necessarily translate to the most vulnerable Latino group. The level of inclusion was not associated with differences among Whites and Blacks. Findings suggest that states with more inclusive immigrant policies may foster environments that advance the economic well-being of API noncitizens, as well as API and Latino citizens.
Deadly violence has spread throughout Mexico, affecting the well-being of citizens. What is the impact of this violence on the daily lives of Mexican adults? Building upon the stress process model, we used a mixed-methods approach to examine relationships between multiple indicators of exposure to and fear of violence and four diagnosed mental health outcomes, as well as self-rated mental health, in a Mexican community using the Survey of Health and Mexican Migration (456 surveys; 49 interviews). The multivariate models provide evidence that perceptions of insecurity are associated with diagnosed depressive episode, agoraphobia, alcohol abuse, a total count of mental health conditions, and poor self-rated mental health. Past victimization is associated with anxiety. Stress and coping behaviors did not formally mediate these violence–mental illness associations. The qualitative results confirm that residents fear violence and cope by adjusting their personal behaviors. These results foreshadow the emergence of mental health conditions as a critical public health concern for Mexicans living under the threat of violence.
India faces a dual burden of increasing obesity and persistent underweight as it experiences the nutrition transition—the dietary and lifestyle changes that accompany globalization, economic development, and technological change. Yet, the nutrition transition is not solely a top-down process; rather, global forces converge with local practices at multiple levels of the social ecology. The family environment, a key site for the transmission of local customs and norms, remains largely unexplored in India. We examined the extent to which opposite-gender siblings and mother–child pairs were concordant or discordant in body weight, and whether domains of the family environment, specifically, food practices, food-related gender norms, and household resources, were associated with patterns of unhealthy weight within and between families. Multilevel dyadic analysis and logistic regression were conducted using survey data from a representative sample of 400 families in a Southern Indian city. We identified substantial clustering of weight among opposite-gender sibling pairs (ICC = 0.43) and mother–child pairs, as well as important patterns of discordance, including 11% of families experiencing a dual burden of underweight and overweight. Household resources, including mother’s education and income, were salient in explaining the distribution of body weight within and between families. Importantly, less examined domains of the family environment were also relevant, including food practices (e.g., grocery shopping frequency), and food-related gender norms (e.g., mother’s control of food served at home). Continued exploration of how global and local practices converge in households will be necessary to develop programming that effectively addresses India’s dual burden of unhealthy weight.
U.S. rates of cesarean section, and in particular, low-risk cesarean section (LRC) births rose dramatically across the late 1990s and early 2000s, and have since remained high. Although previous research explores how trends in LRC vary between states and across maternal characteristics, within-state heterogeneity has not yet been accounted for, nor has the extent to which maternal and county characteristics might interact to shape the likelihood of a LRC birth. Using U.S. county-level birth data for years 2008–2010 from the restricted National Vital Statistics Systems Cohort Linked Birth-Infant Death Files and the Area Health Resource Files, I conduct race-stratified multilevel analyses to explore the association between the mother’s education, the income of the county in which she gives birth, and the odds of LRC delivery. I find that regardless of race/ethnicity, less education at the individual level and lower income at the county level are associated with higher odds of LRC delivery. There are also persistent racial disparities in these relationships. Non-Hispanic black mothers have the highest overall odds of LRC delivery, yet the effect of both education and county income is greatest for non-Hispanic white mothers. The results highlight the importance of analyzing both individual resources and contextual effects of the county when assessing birthing processes, as both contribute to a mother’s access to and knowledge of natal care.
Local area population forecasts have a wide variety of uses in the public and private sectors. But not enough is known about the errors of such forecasts, particularly over the longer term (20 years or more). Understanding past errors is valuable for both forecast producers and users. This paper (i) evaluates the forecast accuracy of past local area population forecasts published by Australian State and Territory Governments over the last 30 years and (ii) illustrates the ways in which past error distributions can be employed to quantify the uncertainty of current forecasts. Population forecasts from the past 30 years were sourced from State and Territory Governments. Estimated resident populations to which the projections were compared were created for the geographical regions of the past projections. The key features of past forecast error patterns are described. Forecast errors mostly confirm earlier findings with regard to the relationship between error and length of projection horizon and population size. The paper then introduces the concept of a forecast ‘shelf life’, which indicates how far into the future a forecast is likely to remain reliable. It also illustrates how past error distributions can be used to create empirical prediction intervals for current forecasts. These two complementary measures provide a simple way of communicating the likely magnitude of error that can be expected with current local area population forecasts.