Keeping It Political and Powerful: Defining the Structural Determinants of Health.

Policy Points The structural determinants of health are 1) the written and unwritten rules that create, maintain, or eliminate durable and hierarchical patterns of advantage among socially constructed groups in the conditions that affect health, and 2) the manifestation of power relations in that people and groups with more power based on current social structures work-implicitly and explicitly-to maintain their advantage by reinforcing or modifying these rules. This theoretically grounded definition of structural determinants can support a shared analysis of the root causes of health inequities and an embrace of public health's role in shifting power relations and engaging politically, especially in its policy work. Shifting the balance of power relations between socially constructed groups differentiates interventions in the structural determinants of health from those in the social determinants of health.

Is White Evangelical Antistructural Theology Related to Poor Health Outcomes?

Policy Points White evangelical theology has an "antistructural" component. Counties with a high percentage of White evangelicals have higher mortality rates and more persons with fair/poor health. The potential influence of antistructural components in evangelical theology on decision making and resource allocation and, ultimately, the length and quality of life of community members presents a point of intervention for religious leaders and policymakers to improve population health. CONTEXT: Structural factors are important determinants of health. Because antistructuralism has been identified as a tenet of White evangelical theology, we explored if there is an association of the percentage of White evangelicals in a US county with two county health outcomes: premature mortality and percentage of fair/poor health. METHODS: Regression analysis was performed with data from 2022 County Health Rankings and the American Value Atlas from the Public Religion Research Institute. FINDINGS: Every percent of evangelicals in a county is associated with 4.01 more premature deaths per 100,000 population and 0.13% fair/poor health. After controlling for income, education, political ideology, and county school funding adequacy (a proxy for antistructuralism), the associations remain positive and significant. CONCLUSIONS: We hope these findings could inform dialogue and critical analysis among individuals of evangelical faith, particularly fundamental and Pentecostal subsets, regarding a belief system that is inclusive of individual dimensions and health-promoting structural policies like school funding, Medicaid expansion, and antipoverty programs. These findings also demonstrate the importance of considering cultural factors like religion and political ideology in population health outcomes research.

Discounting Health Grades for Disparity: The 2021 Wisconsin Population Health and Equity Report Card.

We describe updates to the University of Wisconsin Population Health Institute's methodology for a state health report card, first described in Preventing Chronic Disease in 2010, and the considerations that were weighed in making those updates. These methods have been used since 2006 to issue a periodic report entitled Health of Wisconsin Report Card. The report highlights Wisconsin's standing among other states and serves as an example for others seeking to measure and improve their population's health. For 2021, we revisited our approach with an increased emphasis on disparities and health equity, which required many choices about data, analysis, and reporting methods. In this article, we outline the decisions, rationale, and implications of several choices we made in assessing Wisconsin's health by answering several questions, among them: Who is the intended audience and which measures of length (eg, mortality rate, years of potential life lost) and quality of life (eg, self-reported health, quality-adjusted life years) are most relevant to them? Which subgroups should we report disparities about, and which metric is most easily understood? Should disparities be summarized with overall health or reported separately? Although these decisions are applicable to 1 state, the rationale for our choices could be applied to other states, communities, and nations. Consideration of the purpose, audience, and context for health and equity policy making is important in developing report cards and other tools that can improve the health of all people and places.

What Do We Know About the Drivers of Health and Equity? A Narrative Review of Graphic Representations.

Purpose: Frameworks can be influential tools for advancing health and equity, guiding population health researchers and practitioners. We reviewed frameworks with graphic representations that address the drivers of both health and equity. Our purpose was to summarize and discuss graphic representations of population health and equity and their implications for research and practice. Methods: We identified publicly available frameworks that were scholarly or practice oriented and met defined inclusion and exclusion criteria. The identified frameworks were then described and coded based on their primary area of focus, key elements included, and drivers of health and equity specified. Results: The variation in purpose, concepts, drivers, underlying theory or scholarly evidence, and accompanying measures was highlighted. Graphic representations developed over the last 20 years exhibited some consistency in the drivers of health; however, there has been little uniformity in depicting the drivers of equity, disparities or interplay among the determinants of health, or transparency in underlying theories of change. Conclusion: We found that current tools do not offer consistency or conceptual clarity on what shapes health and equity. Some variation is expected as it is difficult for any framework to be all things to all people. However, keeping in mind the importance of audience and purpose, the field of population health research and practice should work toward greater clarity on the drivers of health and equity to better guide critical analysis, narrative development, and strategic actions needed to address structural and systemic issues perpetuating health inequities.

Joinpoint Trend Analysis of Infant Mortality Disparities in Wisconsin, 1999-2016.

OBJECTIVES: To address shortcomings of previous research exploring trends in racial, educational, and race by educational disparities in infant mortality rates (IMRs) by using nonlinear methods to compare improvement within and between disparity domains. METHODS: We used joinpoint regression modeling to perform a cross-sectional analysis of IMR trends from linked birth and death certificates in Wisconsin between 1999 and 2016. RESULTS: In the race and education domains, IMR decreased by 1.9% per year for infants of White mothers and 1.1% per year for infants of less-educated mothers. Further analysis showed these IMR reductions to be among infants of White mothers with more education (-0.6%/year) and Black mothers with less education (-2.0%/year). CONCLUSIONS: As previously reported, gaps in IMR by race and education in Wisconsin appear to be closing; however, only the change by education is statistically significant. Evidence suggests the racial divide in IMR might soon widen after years of progress in reducing IMR among infants of Black mothers. Public Health Implications. Those advancing strategies to address IMR disparities should pursue data and methods that provide the most accurate and refined information about the challenges that persist and progress that has been realized.

Separate and Sick: Residential Segregation and the Health of Children and Youth in Metropolitan Statistical Areas.

The purpose of this study was to better understand residential segregation and child/youth health by examining the relationship between a measure of Black-White residential segregation, the index of dissimilarity, and a suite of child and youth health measures in 235 U.S. metropolitan statistical areas (MSAs). MSAs are urban areas with a population of 50,000 or more and adjacent communities that share a high degree of economic and social integration. MSAs are defined by the Office of Management and Budget. Health-related measures included child mortality (CDC WONDER), teen births (NCHS natality data), children in poverty (SAIPE program), and disconnected youth (Measure of America). Simple linear regression and two-level hierarchical linear regression models, controlling for income, total population, % Black, and census region, examined the association between segregation and Black health, White health, and Black-White disparities in health. As segregation increased, Black children and youth had worse health across all four measures, regardless of MSA total and Black population size. White children and youth in small MSAs with large Black populations had worse levels of disconnected youth and teen births with increasing segregation, but no associations were found for White children and youth in other MSAs. Segregation worsened Black-White health disparities across all four measures, regardless of MSA total and Black population size. Segregation adversely affects the health of Black children in all MSAs and White children in smaller MSAs with large Black populations, and these effects are seen in measures that span all of childhood. Residential segregation may be an important target to consider in efforts to improve neighborhood conditions that influence the health of families and children.

A Balanced Investment Portfolio For Equitable Health And Well-Being Is An Imperative, And Within Reach.

Health investments, defined as formal expenditures to either produce or care for health, in the US are extremely inefficient and have yet to unlock the country's full potential for equitable health and well-being. A major reason for such poor performance is that the US health investment portfolio is out of balance, with too much spent on certain aspects of health care and not enough spent to ensure social, economic, and environmental conditions that are vital to maintaining health and well-being. This commentary summarizes the evidence for this assertion, along with the opportunities and challenges involved in rebalancing investments in ways that would improve overall population health, reduce health gaps, and help build a culture of health for all Americans.

Hospital Community Benefit in the Context of the Larger Public Health System: A State-Level Analysis of Hospital and Governmental Public Health Spending Across the United States.

CONTEXT: Achieving meaningful population health improvements has become a priority for communities across the United States, yet funding to sustain multisector initiatives is frequently not available. One potential source of funding for population health initiatives is the community benefit expenditures that are required of nonprofit hospitals to maintain their tax-exempt status. OBJECTIVE: In this article, we explore the importance of nonprofit hospitals' community benefit dollars as a funding source for population health. DESIGN: Hospitals' community benefit expenditures were obtained from their 2009 IRS (Internal Revenue Service) Form 990 Schedule H and complemented with data on state and local public health spending from the Association of State and Territorial Health Officials and the National Association of County & City Health Officials. Key measures included indicators of hospitals' community health spending and governmental public health spending, all aggregated to the state level. Univariate and bivariate statistics were used to describe how much hospitals spent on programs and activities for the community at large and to understand the relationship between hospitals' spending and the expenditures of state and local health departments. RESULTS: Tax-exempt hospitals spent a median of $130 per capita on community benefit activities, of which almost $11 went toward community health improvement and community-building activities. In comparison, median state and local health department spending amounted to $82 and $48 per capita, respectively. Hospitals' spending thus contributed an additional 9% to the resources available for population health to state and local health departments. Spending, however, varied widely by state and was unrelated to governmental public health spending. Moreover, adding hospitals' spending to the financial resources available to governmental public health agencies did not reduce existing inequalities in population health funding across states. CONCLUSIONS: Hospitals' community health investments represent an important source for public health activities, yet inequalities in the availability of funding across communities remain.

The Value Of The Nonprofit Hospital Tax Exemption Was $24.6 Billion In 2011.

The federal government encourages public support for charitable activities by allowing people to deduct donations to tax-exempt organizations on their income tax returns. Tax-exempt hospitals are major beneficiaries of this policy because it encourages donations to the hospitals while shielding them from federal and state tax liability. In exchange, these hospitals must engage in community benefit activities, such as providing care to indigent patients and participating in Medicaid. The congressional Joint Committee on Taxation estimated the value of the nonprofit hospital tax exemption at $12.6 billion in 2002--a number that included forgone taxes, public contributions, and the value of tax-exempt bond financing. In this article we estimate that the size of the exemption reached $24.6 billion in 2011. The Affordable Care Act (ACA) brings a new focus on community benefit activities by requiring tax-exempt hospitals to engage in communitywide planning efforts to improve community health. The magnitude of the tax exemption, coupled with ACA reforms, underscores the public's interest not only in community benefit spending generally but also in the extent to which nonprofit hospitals allocate funds for community benefit expenditures that improve the overall health of their communities.

Population health improvement: a community health business model that engages partners in all sectors.

Because population health improvement requires action on multiple determinants--including medical care, health behaviors, and the social and physical environments--no single entity can be held accountable for achieving improved outcomes. Medical organizations, government, schools, businesses, and community organizations all need to make substantial changes in how they approach health and how they allocate resources. To this end, we suggest the development of multisectoral community health business partnership models. Such collaborative efforts are needed by sectors and actors not accustomed to working together. Healthcare executives can play important leadership roles in fostering or supporting such partnerships in local and national arenas where they have influence. In this article, we develop the following components of this argument: defining a community health business model; defining population health and the Triple Aim concept; reaching beyond core mission to help create the model; discussing the shift for care delivery beyond healthcare organizations to other community sectors; examining who should lead in developing the community business model; discussing where the resources for a community business model might come from; identifying that better evidence is needed to inform where to make cost-effective investments; and proposing some next steps. The approach we have outlined is a departure from much current policy and management practice. But new models are needed as a road map to drive action--not just thinking--to address the enormous challenge of improving population health. While we applaud continuing calls to improve health and reduce disparities, progress will require more robust incentives, strategies, and action than have been in practice to date. Our hope is that ideas presented here will help to catalyze a collective, multisectoral response to this critical social and economic challenge.

Monitoring progress in population health: trends in premature death rates.

INTRODUCTION: Trends in population health outcomes can be monitored to evaluate the performance of population health systems at the national, state, and local levels. The objective of this study was to compare and contrast 4 measures for assessing progress in population health improvement by using age-adjusted premature death rates as a summary measure of the overall health outcomes in the United States and in all 50 states. METHODS: To evaluate the performance of statewide population health systems during the past 20 years, we used 4 measures of age-adjusted premature (<75 years of age) death rates: current rates (2009), baseline trends (1990s), follow-up trends (2000s), and changes in trends from baseline to the follow-up periods (ie, "bending the curve"). RESULTS: Current premature death rates varied by approximately twofold, with the lowest rate in Minnesota (268 deaths per 100,000) and the highest rate in Mississippi (482 deaths per 100,000). Rates improved the most in New York during the baseline period (-3.05% per year) and in New Jersey during the follow-up period (-2.87% per year), whereas Oklahoma ranked last in trends during both periods (-0.30%/y, baseline; +0.18%/y, follow-up). Trends improved the most in Connecticut, bending the curve downward by -1.03%; trends worsened the most in New Mexico, bending the curve upward by 1.21%. DISCUSSION: Current premature death rates, recent trends, and changes in trends vary by state in the United States. Policy makers can use these measures to evaluate the long-term population health impact of broad health care, behavioral, social, and economic investments in population health.

HealthPartners adopts community business model to deepen focus on nonclinical factors of health outcomes.

Clinical care contributes only 20 percent to overall health outcomes, according to a population health model developed at the University of Wisconsin. Factors contributing to the remainder include lifestyle behaviors, the physical environment, and social and economic forces--all generally considered outside the realm of care. In 2010 Minnesota-based HealthPartners decided to target nonclinical community health factors as a formal part of its strategic business plan to improve public health in the Twin Cities area. The strategy included creating partnerships with businesses and institutions that are generally unaccustomed to working together or considering how their actions could help improve community health. This article describes efforts to promote healthy eating in schools, reduce the stigma of mental illness, improve end-of-life decision making, and strengthen an inner-city neighborhood. Although still in their early stages, the partnerships can serve as encouragement for organizations inside and outside health care that are considering undertaking similar efforts in their markets.

Even as mortality fell in most US counties, female mortality nonetheless rose in 42.8 percent of counties from 1992 to 2006.

Researchers increasingly track variations in health outcomes across counties in the United States, but current ranking methods do not reflect changes in health outcomes over time. We examined trends in male and female mortality rates from 1992-96 to 2002-06 in 3,140 US counties. We found that female mortality rates increased in 42.8 percent of counties, while male mortality rates increased in only 3.4 percent. Several factors, including higher education levels, not being in the South or West, and low smoking rates, were associated with lower mortality rates. Medical care variables, such as proportions of primary care providers, were not associated with lower rates. These findings suggest that improving health outcomes across the United States will require increased public and private investment in the social and environmental determinants of health-beyond an exclusive focus on access to care or individual health behavior.

Is hospital 'community benefit' charity care?

CONTEXT: The Affordable Care Act is drawing increased attention to the Internal Revenue Service (IRS) Community Benefit policy. To qualify for tax exemption, the IRS requires nonprofit hospitals to allocate a portion of their operating expenses to certain "charitable" activities, such as providing free or reduced care to the indigent. OBJECTIVE: To determine the total amount of community benefit reported by Wisconsin hospitals using official IRS tax return forms (Form 990), and examine the level of allocation across allowable activities. DESIGN: Primary data collection from IRS 990 forms submitted by Wisconsin hospitals for 2009. MAIN OUTCOME MEASURE: Community benefit reported in absolute dollars and as percent of overall hospital expenditures, both overall and by activity category. RESULTS: For 2009, Wisconsin hospitals reported $1.064 billion in community benefits, or 7.52% of total hospital expenditures. Of this amount, 9.1% was for charity care, 50% for Medicaid subsidies, 11.4% for other subsidized services, and 4.4% for Community Health Improvement Services. CONCLUSION: Charity care is not the primary reported activity by Wisconsin hospitals under the IRS Community Benefit requirement. Opportunities may exist for devoting increasing amounts to broader community health improvement activities.

Are community-level financial data adequate to assess population health investments?

The variation in health outcomes among communities results largely from different levels of financial and nonfinancial policy investments over time; these natural experiments should offer investment and policy guidance for a business model on population health. However, little such guidance exists. We examined the availability of data in a sample of Wisconsin counties for expenditures in selected categories of health care, public health, human services, income support, job development, and education. We found, as predicted by the National Committee on Vital and Health Statistics in 2002, that availability is often limited by the challenges of difficulty in locating useable data, a lack of resources among public agencies to upgrade information technology systems for making data more usable and accessible to the public, and a lack of enterprise-wide coordination and geographic detail in data collection efforts. These challenges must be overcome to provide policy-relevant information for optimal population health resource allocation.