Health insurance coverage varies substantially between racial and ethnic groups in the United States. Compared to non-Hispanic whites, African Americans and people of Hispanic origin had persistently lower insurance coverage rates at all ages. This article describes age- and group-specific dynamics of insurance gain and loss that contribute to inequalities found in traditional cross-sectional studies. It uses the longitudinal 2008 Panel of the Survey of Income and Program Participation (N = 114,345) to describe age-specific patterns of disparity prior to the Affordable Care Act (ACA). A formal decomposition on increment–decrement life tables of insurance gain and loss shows that coverage disparities are predominately driven by minority groups’ greater propensity to lose the insurance that they already have. Uninsured African Americans were faster to gain insurance compared to non-Hispanic whites, but their high rates of insurance loss more than negated this advantage. Disparities from greater rates of loss among minority groups emerge rapidly at the end of childhood and persist throughout adulthood. This is especially true for African Americans and Hispanics, and their relative disadvantages again heighten in their 40s and 50s.
Mortality rates among black individuals exceed those of white individuals throughout much of the life course. The black–white disparity in mortality rates is widest in young adulthood, and then rates converge with increasing age until a crossover occurs at about age 85 years, after which black older adults exhibit a lower mortality rate relative to white older adults. Data quality issues in survey-linked mortality studies may hinder accurate estimation of this disparity and may even be responsible for the observed black–white mortality crossover, especially if the linkage of surveys to death records during mortality follow-up is less accurate for black older adults. This study assesses black–white differences in the linkage of the 1986–2009 National Health Interview Survey to the National Death Index through 2011 and the implications of racial/ethnic differences in record linkage for mortality disparity estimates. Match class and match score (i.e., indicators of linkage quality) differ by race/ethnicity, with black adults exhibiting less certain matches than white adults in all age groups. The magnitude of the black–white mortality disparity varies with alternative linkage scenarios, but convergence and crossover continue to be observed in each case. Beyond black–white differences in linkage quality, this study also identifies declines over time in linkage quality and even eligibility for linkage among all adults. Although linkage quality is lower among black adults than white adults, differential record linkage does not account for the black–white mortality crossover.
By the end of 2014, twenty-four states rejected Medicaid expansion, providing a unique opportunity to examine changes in insurance coverage rates after the implementation of the Affordable Care Act within and between states that did versus did not expand Medicaid. Using multilevel regression analyses of county-level non-elderly adult small area health insurance estimates (N = 3135) from the US Census Bureau, several important findings emerge. Compared to counties located in states that did not expand Medicaid, counties located in states that did expand experienced significantly larger increases in adult health insurance coverage rates between 2013 and 2014, net of the county baseline insurance coverage rate, socioeconomic and demographic composition, and labor market characteristics. In states that did not expand Medicaid, counties with larger shares of vulnerable residents (i.e., poor adults and low education) experienced lagging improvements in health insurance coverage. However, counties in states that expanded Medicaid were protected from several of these exacerbated disparities, and in some cases, experienced larger insurance coverage improvements than counties with less disadvantaged populations. These findings suggest that although insurance coverage increased in nearly all counties between 2013 and 2014, increases would have been larger and disparities would have been further alleviated if more states with highly concentrated vulnerable populations had expanded Medicaid.
The large literature on health differentials between rural and urban areas relies almost exclusively on cross-sectional data. Bringing together the demographic literature on area-level health inequalities with the bio-physiological literature on children’s catch-up growth over time, this paper uses panel data to investigate the stability and origins of rural–urban health differentials. Using data from the Young Lives longitudinal study of child poverty, I present evidence of large level differences but similar trends in rural versus urban children’s height for age in four developing countries. Further, observable characteristics of children’s environment such as their household wealth, mother’s education, and epidemiological environment explain these differentials in most contexts. In Peru, where they do not, children’s birthweight and mothers’ health and other characteristics suggest that initial endowments—even before birth—may play an important role in explaining "residual" rural–urban child height inequalities. These latter results imply that prioritizing maternal nutrition and health is essential—particularly where rural–urban height inequalities are large. Interventions to reduce area-level health inequalities should begin even before birth.
The substantial growth and geographic dispersion of Hispanics is among the most important demographic trends in recent U.S. demographic history. Our county-level study examines how widespread Hispanic natural increase and net migration has combined with the demographic change among non-Hispanics to produce an increasingly diverse population. This paper uses U.S. Census Bureau data and special tabulations of race/ethnic specific births and deaths from NCHS to highlight the demographic role of Hispanics as an engine of new county population growth and ethnoracial diversity across the U.S. landscape. It highlights key demographic processes—natural increase and net migration—that accounted for 1990–2010 changes in the absolute and relative sizes of the Hispanic and non-Hispanic populations. Hispanics accounted for the majority of all U.S. population growth between 2000 and 2010. Yet, Hispanics represented only 16 % of the U.S. population in 2010. Most previous research has focused on Hispanic immigration; here, we examine how natural increase and net migration among both the Hispanic and non-Hispanic population contribute to the nation’s growing diversity. Indeed, the demographic impact of rapid Hispanic growth has been reinforced by minimal white population growth due to low fertility, fewer women of reproductive age and growing mortality among the aging white population America’s burgeoning Hispanic population has left a large demographic footprint that is magnified by low and declining fertility and increasing mortality among America’s aging non-Hispanic population.
Following every U.S. decennial census since 1960, the U.S. Census Bureau has evaluated the completeness of coverage using two different methods. Demographic analysis (DA) compares the census counts to a set of independent population estimates to infer coverage differences by age, sex, and race. The survey-based approach (also called dual system estimation or DSE) provides coverage estimates based on matching data from a post-enumeration survey to census records. This paper reviews the fundamentals of the two methodological approaches and then initially examines the results of these two methods for the 2010 decennial census in terms of consistency and inconsistency for age groups. The authors find that the two methods produce relatively consistent results for all age groups, except for young children. Consequently, the paper focuses on the results for children. Results of the 1990, 2000, and 2010 decennial censuses are shown for the overall population in this age group and by demographic detail (age, race, and Hispanic origin). Among children, the DA and DSE results are most inconsistent for the population aged 0–4 and most consistent for ages 10–17. Results also show that DA and DSE are more consistent for Black than non-Black populations. The authors discuss possible explanations for the differences in the two methods for young children and conclude that the DSE approach may underestimate the net undercount of young children due to correlation bias.
This study examined if differences exist in the number and timing of antenatal care (ANC) visits for users of public and private health care facilities in Ghana. Also, the study explored if such variations could be attributed to health-provider factors or the selective socioeconomic characteristics of the users. Data were drawn from the recently collected Ghana Demographic and Health Survey and from a representative sample of t 2135 women who attended antenatal care in a health facility 6 months preceding the survey. Random-effects Poisson and logit models were employed for analysis. Results showed statistically significant differences between users of private and public health facilities for number of ANC visits, but not for the timing of such visits. Although some health-provider factors were significantly associated with ANC visits, these factors did not explain why users of private health facilities had significantly higher number of ANC visits than users of public health facilities. Differences in ANC visits for both private and public health facilities were rather explained by the selective socioeconomic characteristics of the users, especially as wealthy and educated women patronized private health care than poorer and uneducated women. The study concludes that Ghanaian women attending private health facilities may not have improved access to antenatal care compared to those attending public health facilities, and adds to the emerging body of literature that questions private health care in sub-Saharan Africa as more effective than public health care.
Using restricted data from the 2001–2014 California Health Interview Surveys, this research illuminates the role of legal status in health care among Mexican-origin children. The first objective is to provide a population-level overview of trends in health care access and utilization, along with the legal statuses of parents and children. The second objective is to examine the nature of associations between children’s health care and legal status over time. We identify specific status-based distinctions that matter and investigate how their importance is changing. Despite the continuing significance of child nativity for health care, the descriptive analysis shows that the proportion of Mexican-origin children who are foreign born is declining. This trend suggests a potentially greater role of parental legal status in children’s health care. Logistic regression analyses demonstrate that the importance of parental legal status varies with the health care indicator examined and the inclusion of child nativity in models. Moreover, variation in some aspects of children’s health care coalesced more around parents’ citizenship than documentation status in the past. With one exception, the salience of such distinctions has dissipated over time.
We draw upon a framework outlining household recognition and response to child illness proposed by Colvin et al. (Soc Sci Med 86:66–78, 2013) to examine factors predictive of treatment sought for a recent child illness. In particular, we model whether no treatment, middle layer treatment (traditional healer, pharmacy, community health worker, etc.), or biomedical treatment was sought for recent episodes of diarrhea, fever, or cough. Based on multinomial, multi-level analyses of Demographic and Health Surveys from 19 countries in sub-Saharan Africa, we determine that if women have no say in their own healthcare, they are unlikely to seek treatment in response to child illness. We find that women in sub-Saharan Africa need healthcare knowledge, the ability to make healthcare decisions, as well as resources to negotiate cost and travel, in order to access biomedical treatment. Past experience with medical services such as prenatal care and a skilled birth attendant also increases the odds that biomedical treatment for child illness is sought. We conclude that caregiver decision-making in response to child illness within households is critical to reducing child morbidity and mortality in sub-Saharan Africa.
Associations between unemployment, work, and disability have been researched in many studies. The findings are often based on cross-sectional data and single outcomes. The present study analysed multiple outcomes over a period of 15 years among long-term unemployed individuals. Based on all individuals aged 20–40 living in Sweden in 1995, prospective cohort analyses were conducted. Individual annual labour market proximity 1995–2010 was estimated and categorised into three mutually exclusive categories: “Jobless”, “Self-sufficient” (i.e. main income from work), or “Disabled”. Individuals in the category “Jobless” (n = 638,622) in 1995 constituted the study population. Using autoregressive multinomial logistic regression, transitions between the three states during 1997–2010 were analysed. Socio-economic factors, previous inpatient care, and national unemployment rates in different time periods were included in the regression models. Among those “Jobless” in 1995, 17 % were also “Jobless” in 2010, while 10 % were “Disabled” and 61 % “Self-sufficient”. The transitions were stable over time periods for transitions into “Self-sufficient” and “Disabled” but less so for “Jobless”. Previous state was the best predictor of subsequent state. “Jobless” individuals with previous morbidity had a higher transition probability into “Disabled” and a lower transition probability into “Self-sufficient”. The transition rates into “Self-sufficient” were higher in periods with lower unemployment levels. The study supports the interpretation that return to work was affected both by the individuals’ previous health status and by the national unemployment level. Transition from being “Jobless” into “Disability” may be influenced by previous ill health and by negative health effects of being “Jobless”.
Mortality rates are often disaggregated by different attributes, such as sex, state, education, religion, or ethnicity. Forecasting mortality rates at the national and sub-national levels plays an important role in making social policies associated with the national and sub-national levels. However, base forecasts at the sub-national levels may not add up to the forecasts at the national level. To address this issue, we consider the problem of reconciling mortality rate forecasts from the viewpoint of grouped time-series forecasting methods (Hyndman et al. in, Comput Stat Data Anal 55(9):2579–2589, 2011). A bottom-up method and an optimal combination method are applied to produce point forecasts of infant mortality rates that are aggregated appropriately across the different levels of a hierarchy. We extend these two methods by considering the reconciliation of interval forecasts through a bootstrap procedure. Using the regional infant mortality rates in Australia, we investigate the one-step-ahead to 20-step-ahead point and interval forecast accuracies among the independent and these two grouped time-series forecasting methods. The proposed methods are shown to be useful for reconciling point and interval forecasts of demographic rates at the national and sub-national levels, and would be beneficial for government policy decisions regarding the allocations of current and future resources at both the national and sub-national levels.
Administrative data from multiple sources are combined to measure pregnancy (excluding those ending in abortion or miscarriage) and high school dropout in a cohort of girls who were 9th graders in the 1994–1995 academic year. Rates of pregnancy (as identified in the data) and dropout are substantially higher among Hispanic high school students than among African-Americans or non-Hispanic whites. Previous studies of teen pregnancy and dropout typically focus on pregnancy rates conditional on dropout status, or dropout rates conditional on fertility. This paper presents estimates of pregnancy and dropout as a joint-dependent variable. Estimates of their joint probability distribution conditional on individual, family, neighborhood, and high school characteristics are reported. The estimates use longitudinal administrative data collected as annual censuses of all public school students in Texas with individual-level ids. Neighborhood characteristics (from the US Census data geographically linked to Texas high schools) have large effects on pregnancy and dropout. Immigrant Hispanic girls’ pregnancy rates are significantly lower than native-born Hispanic girls’ pregnancy rates. Above-normal-age status in the 9th grade is among the strongest predictors of pregnancy and dropout in later years. Ethnic differences in age distributions within grade level appear to explain a large share of ethnic differences in pregnancy and dropout rates.
Rapid growth in the population of children of immigrants has occurred during an era of soaring college costs in the United States. Despite well-established knowledge that immigrant parents hold high educational expectations for their children and that children of immigrants will make up a large share of the U.S. college-aged population, little is known about how immigrant families prepare financially for their children’s postsecondary education. We use data from the Education Longitudinal Study of 2002 to examine the patterns and predictors of college savings behavior among Asian and Latino foreign-born parents of high school students in the United States. Relative to white U.S.-born parents, Asian immigrant parents have higher odds of saving and have more money saved for their 10th-grader’s college education. In contrast, Latino immigrant parents are less likely than white U.S.-born parents to save for their children’s college education. However, among parents who save, Latino immigrant parents do not differ from white U.S.-born parents in the amount saved. For both Asian and Latino immigrant parents, income is less predictive of saving than it is for white U.S.-born parents, and the odds of saving increase with U.S. experience. Findings improve understanding of college access and the long-term socioeconomic prospects of children of immigrants in the U.S.
This paper uses the natural experiment of a large imbalance between men and women of marriageable age in Taiwan in the 1960s to test the hypothesis that higher sex ratios lead to husbands (wives) having a lower (higher) share of couple’s time in leisure and higher (lower) share of the couple’s total work time (employment, commuting, and housework). The sample includes 18,134 Taiwanese couples’ time diaries from 1987, 1990, and 1994. The OLS analysis finds evidence of the predicted effects of the county-level sex ratio on husbands’ and wives’ share of leisure and total work time. The county-level sex ratio’s impact on college-educated husbands’ time use is shown to be larger than the impact on non-college-educated husbands’ time use. A two-stage least square analysis controlling for possible endogeneity of county of residence returns similar findings.
Researchers have extensively documented a strong and consistent education gradient for mortality, with more highly educated individuals living longer than those with less education. This study contributes to our understanding of the education–mortality relationship by determining the effects of years of education and degree attainment on mortality, and by including non-degree certification, an important but understudied dimension of educational attainment. We use data from the mortality-linked restricted-use files of the Panel Study of Income Dynamics (PSID) sample (N = 9821) and Cox proportional hazards models to estimate mortality risk among U.S. adults. Results indicate that more advanced degrees and additional years of education are associated with reduced mortality risk in separate models, but when included simultaneously, only degrees remain influential. Among individuals who have earned a high school diploma only, additional years of schooling (beyond 12) and vocational school certification (or similar accreditation) are both independently associated with reduced risks of death. Degrees appear to be most important for increasing longevity; the findings also suggest that any educational experience can be beneficial. Future research in health and mortality should consider including educational measures beyond a single variable for educational attainment.
This paper grounds its analysis in a novel model (Bachrach and Morgan in Popul Dev Rev, 39:459–485, 2013) that suggests that responses to questions about fertility intentions may reflect distinct phenomena at distinct points in the life course. The model suggests that women form "true" intentions when their circumstances make the issue of childbearing salient and urgent enough to draw the cognitive resources needed to make a conscious plan; before this, women report intentions based on cognitive images of family and self. We test the implications of this model for reported fertility expectations using NLSY79 data that measure expectations throughout the life course. We find that early in the life course, before marriage and parenthood, women’s fertility expectations are associated with family background and cognitive images of family and future self. Later in the life course, as women experience life course transitions that confer statuses normatively associated with childbearing—such as marriage—and parenthood itself, their reported expectations are better predictors of their fertility than before they passed these life course milestones. Our empirical results provide support for a model which has important implications for both the measurement and conceptualization of women’s intended and expected fertility.
Based in a minority social stress perspective, this study uses propensity score matching techniques to assess the impact of self-reported discrimination on mental health. Using a sample of 14,609 young adults from the National Longitudinal Study of Adolescent to Adult Health, we explore whether the effects of discrimination vary across status characteristics (e.g., gender, race/ethnicity, sexual orientation, and body mass), including both majority and minority populations. Further we investigate the heterogeneous effects of discrimination across propensity scores, or probabilities of experiencing discrimination. We find that self-reported discrimination increases the average perceived stress score and depressive symptoms score by roughly ½ standard deviation, but is not related to anxiety. Further, our results show that while all groups are negatively affected by discrimination, the magnitude of the impact is largest among groups with the lowest propensity scores.
Multipartnered fertility (“MPF”) has become a major topic of interest in the United States due to potential negative linkages with parental, child, and family wellbeing. A first step in studying any newly emerging (or newly identified) social phenomenon is to properly define the issue and identify its prevalence. However, this is problematic in the case of MPF because most existing sources of data were not originally designed to study MPF. We examine the major data sources used to produce estimates of MPF in the United States, discussing the methodological issues that produce conflicting prevalence estimates and providing guidelines for producing comparable estimates. We also discuss important considerations for research seeking to link MPF and outcomes. Our recommendations will help researchers situate their findings in the broader literature and spur future research.
This study expands on previous findings of racial/ethnic and allostatic load (AL) associations with mortality by addressing whether differential AL levels by race/ethnicity may explain all-cause mortality differences. This study used data from the third National Health and Nutrition Survey public-use file, gathered between 1988 and 1994, with up to 18 years of mortality follow-up (n = 11,733). AL scores were calculated using a 10-biomarker algorithm based on clinically determined thresholds. Results of discrete-time hazard models suggest that AL is associated with increased mortality risks, independent of other factors, including race/ethnicity and SES. The results also suggest that the AL–mortality association is stronger for non-Hispanic blacks than for non-Hispanic whites, and that at low levels of AL observed mortality differences between non-Hispanic blacks and non-Hispanic whites are non-significant. These findings suggest that mortality differences between non-Hispanic blacks and non-Hispanic whites may be the result of how early life exposure causes premature aging and increased mortality risks. More attention to resource allocation and local environments is needed to understand why non-Hispanic blacks experience premature aging that leads to differential mortality risks compared to non-Hispanic whites.