Higher rates of black mortality compared to whites in the United States are longstanding and well documented. Wide variation across racial and socioeconomic groups suggests that many deaths may be preventable. We hypothesize that higher mortality for African Americans is due to the fundamental causes of structural racism and poverty. We developed a new index, the Racial Isolation of Poverty (RIP), to examine how the race/class nexus of disadvantage is associated with higher rates of mortality for African Americans. A wide range of policies has isolated black people into areas with poorer-quality schools and fewer jobs, where over-policing substitutes for community resources. Geographic isolation by race and income has enabled sub-standard resource distribution to African Americans. Geographic isolation also allowed us to measure the effects of racism in US counties. Two main effects, Racial Isolation (RI), and the interaction of RI with economic deprivation, or RIP, were tested in a cross-sectional fixed-effects model. Both RIP and RI increased mortality for blacks while only RIP increased mortality for whites. Universal policies to promote economic security for all and reparations especially designed to promote economic security and wealth for African Americans are proposed.

Importance Health inequities exist for racial and ethnic minorities and persons with lower educational attainment due to differential exposure to economic, social, structural, and environmental health risks and limited access to health care. Objective To estimate the economic burden of health inequities for racial and ethnic minority populations (American Indian and Alaska Native, Asian, Black, Latino, and Native Hawaiian and Other Pacific Islander) and adults 25 years and older with less than a 4-year college degree in the US. Outcomes include the sum of excess medical care expenditures, lost labor market productivity, and the value of excess premature death (younger than 78 years) by race and ethnicity and the highest level of educational attainment compared with health equity goals. Evidence Review Analysis of 2016-2019 data from the Medical Expenditure Panel Survey (MEPS) and state-level Behavioral Risk Factor Surveillance System (BRFSS) and 2016-2018 mortality data from the National Vital Statistics System and 2018 IPUMS American Community Survey. There were 87855 survey respondents to MEPS, 1792023 survey respondents to the BRFSS, and 8416203 death records from the National Vital Statistics System. Findings In 2018, the estimated economic burden of racial and ethnic health inequities was $421 billion (using MEPS) or $451 billion (using BRFSS data) and the estimated burden of education-related health inequities was $940 billion (using MEPS) or $978 billion (using BRFSS). Most of the economic burden was attributable to the poor health of the Black population; however, the burden attributable to American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander populations was disproportionately greater than their share of the population. Most of the education-related economic burden was incurred by adults with a high school diploma or General Educational Development equivalency credential. However, adults with less than a high school diploma accounted for a disproportionate share of the burden. Although they make up only 9% of the population, they bore 26% of the costs. Conclusions and Relevance The economic burden of racial and ethnic and educational health inequities is unacceptably high. Federal, state, and local policy makers should continue to invest resources to develop research, policies, and practices to eliminate health inequities in the US.

Supplemental Table 3. New cancer screening constructs from the National Health Interview Survey (NHIS), Health Information National Trends Survey (HINTS), Behavioral Risk Factor Surveillance Survey (BRFSS), and California Health Information Survey (CHIS)

Introduction: Social determinants are structures and conditions in the biological, physical, built, and social environments that affect health, social and physical functioning, health risk, quality of life, and health outcomes. The adoption of recommended, standard measurement protocols for social determinants of health will advance the science of minority health and health disparities research and provide standard social determinants of health protocols for inclusion in all studies with human participants.Methods: A PhenX (consensus measures for Phenotypes and eXposures) Working Group of social determinants of health experts was convened from October 2018 to May 2020 and followed a well established consensus process to identify and recommend social determinants of health measurement protocols. The PhenX Toolkit contains data collection protocols suitable for inclusion in a wide range of research studies. The recommended social determinants of health protocols were shared with the broader scientific community to invite review and feedback before being added to the Toolkit.Results: Nineteen social determinants of health protocols were released in the PhenX Toolkit (https://www.phenxtoolkit.org) in May 2020 to provide measures at the individual and structural levels for built and natural environments, structural racism, economic resources, employment status, occupational health and safety, education, environmental exposures, food environment, health and health care, and sociocultural community context.Conclusions: Promoting the adoption of well-established social determinants of health protocols can enable consistent data collection and facilitate comparing and combining studies, with the potential to increase their scientific impact. Am J Prev Med 2023;65(3):534-542. Published by Elsevier Inc. on behalf of American Journal of Preventive Medicine. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Results of Multinomial Regressions Showing Correlates of Two Types of Inconsistent Responses to Past Year Mammography Questions (2013), by Age Group (Adjusted)

Supplemental Table 1. Details regarding cancer screening constructs in the National Health Interview Survey (NHIS), Health Information National Trends Survey (HINTS), Behavioral Risk Factor Surveillance System (BRFSS), and California Health Interview Survey (CHIS), 2005

With increased attention to the financing and structure of healthcare, dramatic increases in the cost of diagnosing and treating cancer, and corresponding disparities in access, the study of healthcare economics and delivery has become increasingly important. The Healthcare Delivery Research Program (HDRP) in the Division of Cancer Control and Population Sciences at the National Cancer Institute (NCI) was formed in 2015 to provide a hub for cancer-related healthcare delivery and economics research. However, the roots of this program trace back much farther, at least to the formation of the NCI Division of Cancer Prevention and Control in 1983. The creation of a division focused on understanding and explaining trends in cancer morbidity and mortality was instrumental in setting the direction of cancer-related healthcare delivery and health economics research over the subsequent decades. In this commentary, we provide a brief history of health economics and healthcare delivery research at NCI, describing the organizational structure and highlighting key initiatives developed by the division, and also briefly discuss future directions. HDRP and its predecessors have supported the growth and evolution of these fields through the funding of grants and contracts; the development of data, tools, and other research resources; and thought leadership including stimulation of research on previously understudied topics. As the availability of new data, methods, and computing capacity to evaluate cancer-related healthcare delivery and economics expand, HDRP aims to continue to support this growth and evolution.

Achieving health equity has proven elusive for two reasons. First, most research has focused on changing the behavior of individuals; however, policies that address socioeconomic factors or change the context to facilitate healthy decisions tend to be more effective. Second, health disparity science and evidence are not consistently used to guide policy makers, even those seeking health equity. In this perspective, we discuss economic evaluation tools that researchers can use to assist decision-makers in conducting research or evaluating policy: self-reported health-related quality of life surveys and cost-benefit analysis evaluations informed with willingness to pay research and analyses.

This chapter explores whether Californians in same-sex legal marriages and partnerships reported lower levels of psychological distress than other adult Californians after the 2008 California Supreme Court Decision that legalized same-sex marriage. We pooled 10 years of California Health Interview Survey (CHIS) data and employ a T1-T2 design to approximate a time series design. Dependent variables include overall self-related health, psychological distress, and household income. Independent variables include sexual identity and same-sex spouse. Bi-variate analyses compared self-reported mental and physical health between the two periods. We found decreased reports of poorer health and increased reports of very good health among gay men and lesbian women with legal spouses. Psychological distress decreased for legally coupled gay men and lesbians while increased slightly among unpartnered lesbian women and gay men. Household income increased among coupled lesbian women and gay men and decreased among others. Our project demonstrated positive health influences for Californians with legal same-sex spouses. We recommend future research projects that explore whether and how same- and opposite-sex marriage benefits health, well-being, and prosperity, and for marital status survey questions that are inclusive of sexual and gender identities and elicit the sex/gender of a respondent’s spouse.

With the emerging newer trends in sexuality and clashes with the traditional practice of human sexuality, there is a need for introspection and a framework of ethical principles that may guide human sexuality and its practice. Human sexuality is more than a biological phenomenon. Open discussions about sexual identity and sexual practices will help people better understand themselves, others, and the world around them. This book gives a panoramic view of certain aspects of human sexuality in health and disease.

Health disparities involve a tangled web of influences, defined in terms of populations of individuals who evolve and coevolve over time in varied and dynamic contexts. Multiple causal pathways may interact over time, and in ways that differ substantially across population groups. How health disparities accumulate over the life course and are distributed over geographic space are important factors in identifying, understanding, and addressing them. Complex systems science allows researchers ways to move beyond simply identifying associations between determinants and observed levels of minority health and health disparities outcomes, and instead directly characterize and study heterogeneous, dynamic, and interdependent relationships. In this chapter, we describe how the development and use of complex adaptive systems models can help explain system-level nonlinear behaviors; incorporate consideration of spatial effects, social network structures, and process timing; consider heterogeneity in effect pathways; and act as "policy laboratories," allowing researchers to test interventions that cannot be feasibly explored in the real world due to time, cost, or ethical constraints. We then identify and give illustrative examples of three common model categories: etiological (i.e., ones that are primarily intended to explore how pathways operate within a given system to drive key outcomes), retrospective (i.e., ones intended to study why specific policies, interventions, and/or natural experiments had observed effects), and prospective (which explore the potential impacts of policies and interventions that are under consideration but not yet be implemented). Finally, we provide guidance on best practices in model design, development, use, and dissemination of findings.

Purpose: Previous research has shown that Asian Americans are less likely to receive recommended clinical preventive services especially for cancer compared with non-Hispanic whites. Health insurance expansion has been recommended as a way to increase use of these preventive services. This study examines the extent to which utilization of preventive services by Asians overall and by ethnicity compared with non-Hispanic whites is moderated by health insurance. Methods: Data from the California Health Interview Survey (CHIS) was used to examine preventive service utilization among non-Hispanic whites, Asians, and Asian subgroups 50-64 years of age by insurance status. Six waves of CHIS data from 2001 to 2011 were combined to allow analysis of Asian subgroups. Logistic regression models were run to predict the effect of insurance on receipt of mammography, colorectal cancer (CRC) screening, and flu shots among Asians overall and by ethnicity compared with whites. Results: Privately insured Asians reported significantly lower adjusted rates of mammography (83.1% vs. 87.6%) and CRC screening (54.7% vs. 59.4%), and higher rates of influenza vaccination (48.7% vs. 38.5%) than privately insured non-Hispanic whites. Adjusted rates of cancer screening were lower among Koreans and Chinese for mammography, and lower among Filipinos for CRC screening. Conclusion: This study highlights the limitations of providing insurance coverage as a strategy to eliminate disparities for cancer screening among Asians without addressing cultural factors.

To explore how incremental California legal changes toward the implementation of same-sex marriage influenced self-reported mental and physical health among adult Californians in legal same-sex marriages and partnerships. We analyzed California Health Interview Survey data from 2005 to 2015 to assess the relationship between self-reported mental and physical health and legal same-sex marital/partnership status. Physical health was measured using a single self-report question, mental health using the six-item Kessler distress scale. Independent variables were sexual identity and legal marital/partner status. Bivariate analyses compared mental and physical health before and after the 2008 California Supreme Court decision affirming marriages as a basic civil or human right. Multivariate analyses tested relationships between marital/partnered status, sexual identity by year after adjusting for sociodemographics. Reports of poor and fair health decreased, reports of very good health increased, and psychological distress scores decreased for legally coupled gay men and lesbians but increased slightly for single lesbians and gay men. Household income increased among espoused lesbians and gay men and decreased among unmarried counterparts. Espoused gay and lesbian respondents were more likely to be employed and to have college educations than unmarried counterparts, perhaps a continuing influence of 2005 California legislation requiring private employers to provide health insurance benefits to employees' same-sex partners. Our findings suggest that physical and mental health improved for lesbians and gay men once same-sex marriage became legal throughout California. These findings demonstrate a need for survey questions to elicit information about marital status and the sex/gender of a respondent's spouse inclusive of sexual and gender identities.

ObjectiveTo explore how incremental California legal changes toward the implementation of same‐sex marriage influenced self‐reported mental and physical health among adult Californians in legal same‐sex marriages and partnerships.MethodsWe analyzed California Health Interview Survey data from 2005 to 2015 to assess the relationship between self‐reported mental and physical health and legal same‐sex marital/partnership status. Physical health was measured using a single self‐report question, mental health using the six‐item Kessler distress scale. Independent variables were sexual identity and legal marital/partner status. Bivariate analyses compared mental and physical health before and after the 2008 California Supreme Court decision affirming marriages as a basic civil or human right. Multivariate analyses tested relationships between marital/partnered status, sexual identity by year after adjusting for sociodemographics.ResultsReports of poor and fair health decreased, reports of very good health increased, and psychological distress scores decreased for legally coupled gay men and lesbians but increased slightly for single lesbians and gay men. Household income increased among espoused lesbians and gay men and decreased among unmarried counterparts.ConclusionsEspoused gay and lesbian respondents were more likely to be employed and to have college educations than unmarried counterparts, perhaps a continuing influence of 2005 California legislation requiring private employers to provide health insurance benefits to employees' same‐sex partners. Our findings suggest that physical and mental health improved for lesbians and gay men once same‐sex marriage became legal throughout California.ImplicationsThese findings demonstrate a need for survey questions to elicit information about marital status and the sex/gender of a respondent's spouse inclusive of sexual and gender identities.

Background: Despite decades of research and interventions, significant health disparities persist. Seventeen years is the estimated time to translate scientific discoveries into public health action. This Narrative Review argues that the translation process could be accelerated if representative data were gathered and used in more innovative and efficient ways. Methods: The National Institute on Minority Health and Health Disparities led a multiyear visioning process to identify research opportunities designed to frame the next decade of research and actions to improve minority health and reduce health disparities. "Big data" was identified as a research opportunity and experts collaborated on a systematic vision of how to use big data both to improve the granularity of information for place-based study and to efficiently translate health disparities research into improved population health. This Narrative Review is the result of that collaboration. Results: Big data could enhance the process of translating scientific findings into reduced health disparities by contributing information at fine spatial and temporal scales suited to interventions. In addition, big data could fill pressing needs for health care system, genomic, and social determinant data to understand mechanisms. Finally, big data could lead to appropriately personalized health care for demographic groups. Rich new resources, including social media, electronic health records, sensor information from digital devices, and crowd-sourced and citizen-collected data, have the potential to complement more traditional data from health surveys, administrative data, and investigator-initiated registries or cohorts. This Narrative Review argues for a renewed focus on translational research cycles to accomplish this continual assessment. Conclusion: The promise of big data extends from etiology research to the evaluation of large-scale interventions and offers the opportunity to accelerate translation of health disparities studies. This data-rich world for health disparities research, however, will require continual assessment for efficacy, ethical rigor, and potential algorithmic or system bias.

Introduction: The purpose of this study was to test the hypothesis that patients with Medicaid insurance or Medicaid-like coverage would have longer times to follow-up and be less likely to complete colonoscopy compared with patients with commercial insurance within the same health-care systems. Methods: A total of 35,009 patients aged 50-64 years with a positive fecal immunochemical test were evaluated in Northern and Southern California Kaiser Permanente systems and in a North Texas safety-net system between 2011 and 2012. Kaplan-Meier estimation was used between 2016 and 2017 to calculate the probability of having follow-up colonoscopy by coverage type. Among Kaiser Permanente patients, Cox regression was used to estimate hazard ratios and 95% CIs for the association between coverage type and receipt of follow-up, adjusting for sociodemographics and health status. Results: Even within the same integrated system with organized follow-up, patients with Medicaid were 24% less likely to complete follow-up as those with commercial insurance. Percentage receiving colonoscopy within 3 months after a positive fecal immunochemical test was 74.6% for commercial insurance, 63.10% for Medicaid only, and 37.5% for patients served by the integrated safety-net system. Conclusions: This study found that patients with Medicaid were less likely than those with commercial insurance to complete follow-up colonoscopy after a positive fecal immunochemical test and had longer average times to follow-up. With the future of coverage mechanisms uncertain, it is important and timely to assess influences of health insurance coverage on likelihood of follow-up colonoscopy and identify potential disparities in screening completion. (C) 2019 Published by Elsevier Inc. on behalf of American Journal of Preventive Medicine.

Understanding health disparity causes is an important first step toward developing policies or interventions to eliminate disparities, but their nature makes identifying and addressing their causes challenging. Potential causal factors are often correlated, making it difficult to distinguish their effects. These factors may exist at different organizational levels (e.g., individual, family, neighborhood), each of which needs to be appropriately conceptualized and measured. The processes that generate health disparities may include complex relationships with feedback loops and dynamic properties that traditional statistical models represent poorly. Because of this complexity, identifying disparities' causes and remedies requires integrating findings from multiple methodologies. We highlight analytic methods and designs, multilevel approaches, complex systems modeling techniques, and qualitative methods that should be more broadly employed and adapted to advance health disparities research and identify approaches to mitigate them.

Health disparity populations are socially disadvantaged, and the multiple levels of discrimination they often experience mean that their characteristics and attributes differ from those of the mainstream. Programs and policies targeted at reducing health disparities or improving minority health must consider these differences. Despite the importance of evaluating health disparities research to produce high-quality data that can guide decision-making, it is not yet a customary practice. Although health disparities evaluations incorporate the same scientific methods as all evaluations, they have unique components such as population characteristics, sociocultural context, and the lack of health disparity common indicators and metrics that must be considered in every phase of the research. This article describes evaluation strategies grouped into 3 components: formative (needs assessments and process), design and methodology (multilevel designs used in real-world settings), and summative (outcomes, impacts, and cost). Each section will describe the standards for each component, discuss the unique health disparity aspects, and provide strategies from the National Institute on Minority Health and Health Disparities Metrics and Measures Visioning Workshop (April 2016) to advance the evaluation of health disparities research.

BACKGROUND Because cost may be a barrier to receiving mammography screening, cost sharing for "in-network" screening mammograms was eliminated in many insurance plans with implementation of the Affordable Care Act. We examined prevalence of out-of-pocket payments for screening mammography after elimination in many plans. MATERIALS AND METHODS Using 2015 National Health Interview Survey data, we examined whether women aged 50-74 years who had screening mammography within the previous year (n = 3,278) reported paying any cost for mammograms. Logistic regression models stratified by age (50-64 and 65-74 years) examined out-of-pocket payment by demographics and insurance (ages 50-64 years: private, Medicaid, other, and uninsured; ages 65-74 years: private ± Medicare, Medicare+Medicaid, Medicare Advantage, Medicare only, and other). RESULTS Of women aged 50-64 years, 23.5% reported payment, including 39.1% of uninsured women. Compared with that of privately insured women, payment was less likely for women with Medicaid (adjusted OR 0.17 [95% CI 0.07-0.41]) or other insurance (0.49 [0.25-0.96]) and more likely for uninsured women (1.99 [0.99-4.02]) (p < 0.001 across groups). For women aged 65-74 years, 11.9% reported payment, including 22.5% of Medicare-only beneficiaries. Compared with private ± Medicare beneficiaries, payment was less likely for Medicare+Medicaid beneficiaries (adjusted OR 0.21 [95% CI 0.06-0.73]) and more likely for Medicare-only beneficiaries (1.83 [1.01-3.32]) (p = 0.005 across groups). CONCLUSIONS Although most women reported no payment for their most recent screening mammogram in 2015, some payment was reported by >20% of women aged 50-64 years or aged 65-74 years with Medicare only, and by almost 40% of uninsured women aged 50-64 years. Efforts are needed to understand why many women in some groups report paying out of pocket for mammograms and whether this impacts screening use.