State of the States’ Health

Inequalities in access to health and health care are especially important forms of inequality because they speak to who lives long and who lives well. It is well known that, even though the United States spends more on health care per capita than any other country, it has some of the worst access and outcome results among wealthy nations.1 While important, such cross-country comparisons hide substantial health inequality within the United States. Even a cursory inspection of the data suggests that some states are indeed better performers on key health measures. For example, only one in ten adults in Utah smoke, whereas more than one in four do so in West Virginia. The purpose of this brief is to examine whether state differences of this magnitude are commonly found across various other health measures. We focus not just on average levels of health access, behaviors, and outcomes, but also on how unequally they are distributed. Although everyone would presumably prefer a state with high average health scores, it also matters whether the health disparities between the poor and relatively well-off are very large. If a state has a high mean level of health but also subjects its poor residents to a large “health penalty,” then anyone who is at risk of being poor would presumably want to avoid that state (at least insofar as the penalty is large enough to render them worse off than their counterparts in other states). Therefore, we examine two important features of a state’s health profile: the average level of health, behavioral, or access problems in the state; and the variation in the distribution of these outcomes by income

Health Inequality

There are many reasons why poverty matters, but it is especially troubling that it affects such fundamental outcomes as health and access to health care. If poverty did not bring about all manner of health risks, we would likely be somewhat less troubled by it. But of course poverty and other forms of social and economic disadvantage do often translate into deficits in health and health care. The purpose of this brief is to examine long-term trends in American health and to lay out the current state of evidence on the extent to which health and health care are unequally distributed. We also note how the recent economic downturn affected these trends and disparities. The key backdrop to this assessment is the tripling of U.S. health expenditures since the 1960s. In 2012, per capita expenditures on health were $8,915, more than double those from 1995, though growth has slowed in the past 4 years.1 Some of this rise is attributable to population aging. Costs associated with Medicare, a program established in 1965 to subsidize health care for those aged 65 and older, have grown as the elderly population constitutes an ever-larger portion of the U.S. population. Still, overall U.S. health expenditures have increased faster than the growth of the elderly population and faster than health expenditures in other OECD countries.2 It is possible that such rising costs have led to a more unequal distribution of health and health care. At the same time, health inequalities may also be affected by the economy (e.g., recessions), changes in how insurance is provided, and any number of other factors. In this brief, our objective is not to attempt to tease out the causes of any possible changes in health inequalities, but rather to provide a descriptive summary of the current evidence on trends in (a) health, (b) foregone health care and insurance coverage, and (c) health risk factors. To preview our results, we find first that some health indicators, such as life expectancy, show an overall improvement. But not all indicators are improving. For example, an increasing number of Americans report delaying or foregoing health care, particularly during the recent economic recession. Second, economic and racial disparities in health indicators are often substantial, and when changes in these disparities are observed, they usually take the form of an increase in absolute size. Third, a large proportion of Americans still remain uninsured in 2012 (i.e., 15 percent), although the proportion of children who are uninsured declined by nearly 2 percentage points between the late 1990s and 2012

REDI for Binned Data: A Random Empirical Distribution Imputation Method for Estimating Continuous Incomes

Researchers often need to work with categorical income data. The typical nonparametric (including midpoint) and parametric estimation methods used to estimate summary statistics both have advantages, but they carry assumptions that cause them to deviate in important ways from real-world income distributions. The method introduced here, random empirical distribution imputation (REDI), imputes discrete observations using binned income data, while also calculating summary statistics. REDI achieves this through random cold-deck imputation from a real-world reference data set (demonstrated here using the Current Population Survey Annual Social and Economic Supplement). This method can be used to reconcile bins between data sets or across years and handle top incomes. REDI has other advantages for computing values of an income distribution that is nonparametric, bin consistent, area and variance preserving, continuous, and computationally fast. The author provides proof of concept using two years of the American Community Survey. The method is available as the redi command for Stata

The Undergraduate RA: Benefits and Challenges for Sociology Faculty and Research Assistants

Reprinted with permission

The Pandemic Penalty: The Gendered Effects of COVID-19 on Scientific Productivity

Academia serves as a valuable case for studying the effects of social forces on workplace productivity, using a concrete measure of output: scholarly papers. Many academics, especially women, have experienced unprecedented challenges to scholarly productivity during the coronavirus disease 2019 (COVID-19) pandemic. The authors analyze the gender composition of more than 450,000 authorships in the arXiv and bioRxiv scholarly preprint repositories from before and during the COVID-19 pandemic. This analysis reveals that the underrepresentation of women scientists in the last authorship position necessary for retention and promotion in the sciences is growing more inequitable. The authors find differences between the arXiv and bioRxiv repositories in how gender affects first, middle, and sole authorship submission rates before and during the pandemic. A review of existing research and theory outlines potential mechanisms underlying this widening gender gap in productivity during COVID-19. The authors aggregate recommendations for institutional change that could ameliorate challenges to women’s productivity during the pandemic and beyond

Teaching & learning guide for disability and climate justice

Disability is widespread: nearly one in four Americans has a disability (Taylor, 2018) and disability cuts across demographic categories. Among individuals aged 15 and over, 12.6% had some type of mobility disability; above age 65, it is nearly 40% (Brault, 2012). Mobility disabilities heighten vulnerability to climate change and climate-related disasters (UNHCHR, 2020). Reduced information resources and mobility, increased health risks, and a lack of visibility in climate change discourse put people with disabilities in a more vulnerable position in the climate crisis. However, this vulnerability can be mitigated through relevant and sufficient access to information, risk mitigation strategies, and policy-shaping power. However, when these resilience-building resources are not accessible to disabled people, it exacerbates their vulnerability to climate change and becomes an issue of climate (in)justice. This guide and the accompanying article explore ways to teach the intersection of disability and climate justice for a better understanding of each

Critical connectivity in banking networks

The financial crisis of 2007-2009 demonstrated the need to understand the macrodynamics of interconnected financial systems. A fruitful approach to this problem regards financial infrastructures as weighted directed networks, with banks as nodes and loans as links. Using a simple banking model in which banks are linked through interbank lending, with an exogenous shock applied to a single bank, we find a closedform analytical solution for the degree at which failures begin to propagate in the network. This critical degree is expressed as a function of four financial parameters: banking leverage; interbank exposure; return on the investment opportunity; and interbank lending rate. While the transition to failure propagation is sharpest with regular networks, we observe it numerically for random and scale-free networks as well. We find that, if the expected number of failures is not strongly dependent on the network topology and is well captured by the notion of critical degree, the frequency of catastrophic cascades (with a single shock inducing all or most banks in the network to fail) tends to be much larger on scale-free networks than on classical random networks. We interpret this finding as a manifestation of the “robust-yet-fragile” property of scale-free networks