Black-White health disparities in the United States and Chicago: a 15-year progress analysis

Race and ethnic disparities arthroplasty trends and hotspots: Bibliometric analysis

Introduction

Despite continual advancements in total joint arthroplasty and perioperative optimization, there remains national variability in outcomes. These outcome variabilities have been in part attributed to racial and ethnic disparities in healthcare quality and access to care. This study aims to identify arthroplasty racial and ethnic disparities research and to predict future hotspots.

Methods

Ethnic and racial disparities articles between 1992 and 2022 were queried from the Web of Science Core Collection of Clarivate Analytics. Bibliometric indicators in excel format were extracted and subsequently imported for further analysis. Bibliometrix and VOSviewer analyzed current and previous research.

Results

Database search yielded 234 total articles assessing racial and ethnic disparities between 1992 and 2022. Twenty-six countries published manuscripts with the United States producing the majority of publications. The Veterans Health Administration and University of Pittsburgh were the most relevant institutions. Ibrahim SA was the most relevant and influential author within this field. Visuals of thematic map and co-occurrences identified the basic, motor, and niche themes within the literature.

Conclusions

Racial and ethnic disparity within arthroplasty literature demonstrate growing traction with global contributions. United States authors and institutions are the largest contributors within this field. This bibliometric analysis identified previous, current, and future trends for prediction of future hotspots.

Financial, Social, and Health Impacts from the COVID-19 Pandemic: Findings from the Healthy Chicago Survey

BACKGROUND

This study examines self-reported impacts of the COVID-19 pandemic among Chicago residents and disparities of these impacts across demographic characteristics. Six logistic regression models were developed to identify demographic and socioeconomic factors associated with each COVID-19 impact.

METHOD

The study used de-identified and weighted data from the 2020 Healthy Chicago Survey (HCS). HCS is an annual survey using an address-based random sampling method administered by the Chicago Department of Public Health (CDPH) across the city of Chicago on adults aged 18 or older living between July 17 and November 11, 2020, and received 4517 responses.

RESULTS

Chicago residents with lower socioeconomic status had a higher likelihood of food and housing insecurity. Non-Hispanic (NH) Black residents were more likely to report being unable to obtain food (OR: 2.996; 95% CI: 2.268-2.324); being unable to pay for rent, mortgage, or bills (OR: 2.352; 95% CI: 2.325-2.380); and grief from a loss of someone to COVID-19 (OR: 2.037; 95% CI: 2.013-2.061) compared to NH White residents. NH White residents were more likely than other racial/ethnic groups to report loss of social connections, worsened mental health, and canceling or postponing medical care.

CONCLUSIONS

The analysis showed higher odds of social contact loss and worsened mental health from COVID-19 in NH White and higher education populations. By implementing strategies to address specific challenges faced by different racial groups, Chicago may effectively mitigate pandemic's adverse effects. These strategies can promote a more inclusive approach to distributing COVID investments for programs and policies.

Increased Mortality of Black Incarcerated and Hospitalized People: a Single State Cohort Analysis

OBJECTIVE

To quantify racial disparities in mortality and post-hospitalization outcomes among incarcerated individuals that were hospitalized during their incarceration period.

METHODS

We designed a retrospective cohort study using administrative and hospital data collected from a preferred healthcare referral center for all Massachusetts jails and prisons between January 2011 and December 2018 with linkage to Massachusetts Vital Records and Statistics. We identified 4260 incarcerated individuals with complete data on race/ethnicity that were hospitalized during the study period. The primary study indicators were age, race, ethnicity, length of hospital stay, Elixhauser comorbidity score, incarceration facility type, and number of hospital admissions. The primary outcome was time to death.

RESULTS

Of the incarcerated individuals that were hospitalized, 2606 identified as White, 1214 identified as Black, and 411 people who identified as some other race. The hazard of death significantly increased by 3% (OR: 1.03; 95% CI: 1.02-1.03) for each additional yearly increase in age. After adjusting for the interaction between race and age, Black race was significantly associated with 3.01 increased hazard (95% CI: 1.75-5.19) of death for individuals hospitalized while incarcerated compared to White individuals hospitalized while incarcerated. Hispanic ethnicity and being incarcerated in a prison facility was not associated with time to mortality, while increased mean Elixhauser score (HR: 1.07; 95% CI: 1.06-1.08) and ≥ 3 hospital admissions (HR: 2.47; 95% CI: 2.07-2.95) increased the hazard of death.

CONCLUSIONS

Our findings suggest disparities exist in the mortality outcomes among Black and White individuals who are hospitalized during incarceration, with an increased rate of death among Black individuals. Despite hypothesized equal access to healthcare within correctional facilities, our findings suggest that incarcerated and hospitalized Black individuals may experience worse disparities than their White counterparts, which has not been previously explored or reported in the literature. In addition to decarceration, advocacy, and political efforts, increased efforts to support research access to datasets of healthcare outcomes, including hospitalization and death, for incarcerated people should be encouraged. Further research is needed to identify and address the implicit and explicit sources of these racial health disparities across the spectrum of healthcare provision.

Household air pollution disparities between socioeconomic groups in Chicago

Purpose: To assess household air pollution levels in urban Chicago households and examine how socioeconomic factors influence these levels. Methods: We deployed wireless air monitoring devices to 244 households in a diverse population in Chicago to continuously record household fine particulate matter (PM2.5) concentration. We calculated hourly average PM2.5 concentration in a 24-hour cycle. Four factors-race, household income, area deprivation, and exposure to smoking-were considered in this study. Results: A total of 93085 h of exposure data were recorded. The average household PM2.5 concentration was 43.8 μg m-3. We observed a significant difference in the average household PM2.5 concentrations between Black/African American and non-Black/African American households (46.3 versus 31.6 μg m-3), between high-income and low-income households (18.2 versus 52.5 μg m-3), and between smoking and non-smoking households (69.7 versus 29.0 μg m-3). However, no significant difference was observed between households in less and more deprived areas (43.7 versus 43.0 μg m-3). Implications: Household air pollution levels in Chicago households are much higher than the recommended level, challenging the hypothesis that household air quality is adequate for populations in high income nations. Our results indicate that it is the personal characteristics of participants, rather than the macro environments, that lead to observed differences in household air pollution.

Exploring predictors of substance use disorder treatment engagement with machine learning: The impact of social determinants of health in the therapeutic landscape

BACKGROUND

Improved knowledge of factors that influence treatment engagement could help treatment providers and systems better engage patients. The present study used machine learning to explore associations between individual- and neighborhood-level factors, and SUD treatment engagement.

METHODS

This was a secondary analysis of the Global Appraisal of Individual Needs (GAIN) dataset and United States Census Bureau data utilizing random forest machine learning and generalized linear mixed modelling. Our sample (N = 15,873) included all people entering SUD treatment at GAIN sites from 2006 to 2012. Predictors included an array of demographic, psychosocial, treatment-specific, and clinical measures, as well as environment-level measures for the neighborhood in which patients received treatment.

RESULTS

Greater odds of treatment engagement were predicted by adolescent age and psychiatric comorbidity, and at the neighborhood-level, by low unemployment and high population density. Lower odds of treatment engagement were predicted by Black/African American race, and at the neighborhood-level by high rate of public assistance and high income inequality. Regardless of the degree of treatment engagement, individuals receiving treatment in areas with high unemployment, alcohol sale outlet concentration, and poverty had greater substance use and related problems at baseline. Although these differences reduced with treatment and over time, disparities remained.

CONCLUSIONS

Neighborhood-level factors appear to play an important role in SUD treatment engagement. Regardless of whether individuals engage with treatment, greater loading on social determinants of health such as unemployment, alcohol sale outlet density, and poverty in the therapeutic landscape are associated with worse SUD treatment outcomes.

Targeting Machine Learning and Artificial Intelligence Algorithms in Health Care to Reduce Bias and Improve Population Health

Policy Points Artificial intelligence (AI) is disruptively innovating health care and surpassing our ability to define its boundaries and roles in health care and regulate its application in legal and ethical ways. Significant progress has been made in governance in the United States and the European Union. It is incumbent on developers, end users, the public, providers, health care systems, and policymakers to collaboratively ensure that we adopt a national AI health strategy that realizes the Quintuple Aim; minimizes race-based medicine; prioritizes transparency, equity, and algorithmic vigilance; and integrates the patient and community voices throughout all aspects of AI development and deployment.

Ethical and Policy Implications of Racial and Ethnic Healthcare Disparities in Sleep Health

Despite efforts in recent years, including in policy and research, to address health disparities in the United States, many of those disparities continue to fester in marginalized racial/ethnic populations. Understanding sleep health disparities is critical in understanding the health and wellness of these groups. Using obstructive sleep apnea (OSA) in Black populations as a focus, this paper presents the role of race and ethnicity in the clinical understanding of sleep health-related issues by medical practitioners and the implications of the lack of clear policies or best practices to guide medical practitioners' attempts to meet sleep-related needs of marginalized racial/ethnic populations. Furthermore, the knowledge gap may be further complicated by the poor understanding and integration of existing evidence with the many, complex, sleep-associated co-morbidities. Policymaking in this area ought to be based on the ethical implications of disparate sleep-related health outcomes by race and ethnicity. So, we conclude by offering recommendations for developing ethically sound policies for addressing sleep problems in marginalized racial and ethnic populations.

The Landscape of Health Technology for Equity Deserving Groups in Rural Communities: A Systematic Review

BACKGROUND

Equity-deserving groups face well-known health disparities that are exacerbated by rural residence. Health technologies have shown promise in reducing disparities among these groups, but there has been no comprehensive evidence synthesis of outcomes.

PURPOSE

The purpose of this systematic review was to examine the patient, healthcare, and economic outcomes of health technology applications with rural living equity-deserving groups.

RESEARCH DESIGN

The databases searched included Medline and Embase. Articles were assessed for bias using the McGill mixed methods appraisal tool.

ANALYSIS

Data were synthesized narratively using a convergent integrated approach for qualitative and quantitative findings.

RESULTS

This evidence synthesis includes papers (n = 21) that reported on health technologies targeting rural equity-deserving groups. Overall, patient outcomes - knowledge, self-efficacy, weight loss, and clinical indicators - improved. Healthcare access improved with greater convenience, flexibility, time and travel savings, though travel was still occasionally necessary. All studies reported satisfaction with health technologies. Technology challenges reported related to connectivity and infrastructure issues influencing appointment quality and modality options. While some studies reported additional costs, overall, studies indicated cost savings for patients.

CONCLUSIONS

There is a paucity of research on health technologies targeting rural equity-deserving groups, and the available research has primarily focused on women. While current evidence was primarily of high quality, research is needed inclusive of equity-deserving groups and interventions co-designed with users that integrate culturally sensitive approaches. Review registered with Prospero ID = CRD42021285994.

Estimated Childhood Lead Exposure From Drinking Water in Chicago

Importance

There is no level of lead in drinking water considered to be safe, yet lead service lines are still commonly used in water systems across the US.

Objective

To identify the extent of lead-contaminated drinking water in Chicago, Illinois, and model its impact on children younger than 6 years.

Design, Setting, and Participants

For this cross-sectional study, a retrospective assessment was performed of lead exposure based on household tests collected from January 2016 to September 2023. Tests were obtained from households in Chicago that registered for a free self-administered testing service for lead exposure. Machine learning and microsimulation were used to estimate citywide childhood lead exposure.

Exposure

Lead-contaminated drinking water, measured in parts per billion.

Main Outcomes and Measures

Number of children younger than 6 years exposed to lead-contaminated water.

Results

A total of 38 385 household lead tests were collected. An estimated 68% (95% uncertainty interval, 66%-69%) of children younger than 6 years were exposed to lead-contaminated water, corresponding to 129 000 children (95% uncertainty interval, 128 000-131 000 children). Ten-percentage-point increases in block-level Black and Hispanic populations were associated with 3% (95% CI, 2%-3%) and 6% (95% CI, 5%-7%) decreases in odds of being tested for lead and 4% (95% CI, 3%-6%) and 11% (95% CI, 10%-13%) increases in having lead-contaminated drinking water, respectively.

Conclusions and Relevance

These findings indicate that childhood lead exposure is widespread in Chicago, and racial inequities are present in both testing rates and exposure levels. Machine learning may assist in preliminary screening for lead exposure, and efforts to remediate the effects of environmental racism should involve improving outreach for and access to lead testing services.

The Integration of Value Assessment and Social Network Methods for Breast Health Navigation Among African Americans

OBJECTIVES

A major strategy to reduce the impact of breast cancer (BC) among African Americans (AA) is patient navigation, defined here as individualized assistance for reducing barriers to healthcare use. The primary focus of this study was to estimate the added value of incorporating breast health promotion by navigated participants and the subsequent BC screenings that network members may obtain.

METHODS

In this study, we compared the cost-effectiveness of navigation across 2 scenarios. First, we examine the effect of navigation on AA participants (scenario 1). Second, we examine the effect of navigation on AA participants and their networks (scenario 2). We leverage data from multiple studies in South Chicago. Our primary outcome (BC screening) is intermediate, given limited available quantitative data on the long-term benefits of BC screening for AA populations.

RESULTS

When considering participant effects alone (scenario 1), the incremental cost-effectiveness ratio was $3845 per additional screening mammogram. When including participant and network effects (scenario 2), the incremental cost-effectiveness ratio was $1098 per additional screening mammogram.

CONCLUSION

Our findings suggest that inclusion of network effects can contribute to a more precise, comprehensive assessment of interventions for underserved communities.

The effects of race and class on community-level stigmatization of opioid use and policy preferences

BACKGROUND

With opioid use and overdose rates continuing to plague minority communities in the U.S., we explored whether a geographic community's racial composition and social class affect how opioid use in the community is stigmatized and what policy preferences arise in response.

METHODS

We use case vignettes in a randomized, between-subjects study (N = 1478) with a nation-wide survey. The vignettes describe a community where opioids are harmfully used, varying whether the community was (1) wealthy or poor, (2) predominantly Black or White and (3) facing prevalent use of painkillers or heroin. We tested how these variables affect public stigmatization of opioid use (measured with ratings of responsibility, dangerousness, sympathy, concern, anger, and disappointment) preferred levels of social distance from communities with opioid use (measured with responses to questions about living, working, and interacting in the community), and policy preferences for responding to opioid use (measured with levels of support for providing a safe-consumption site in the community, treating drug use in the community punitively, treating drug use in the community as an illness, and funding drug treatment in the community through income redistribution).

RESULTS

Compared to wealthy communities with opioid use, poor communities with opioid use were less stigmatized in terms of responsibility, sympathy, concern, anger, and disappointment; they were also met with less support for punitiveness, more support for treating drug use as an illness, and preferences for greater social distance. Compared to White communities with opioid use, Black communities with opioid use were less stigmatized in terms of responsibility, and they were met with stronger preferences to not live and work there and with reduced support for using income redistribution to provide drug treatment for people in the community. Poor-Black communities with opioid use were also perceived to be more dangerous than both poor-White and wealthy-Black communities with opioid use.

CONCLUSION

These results point to class- and race-based territorial stigma affecting how communities with opioid use are judged and whether policies for providing communities with treatment are supported.

Machine Learning for Digital Scoring of PRMT6 in Immunohistochemical Labeled Lung Cancer

Lung cancer is the leading cause of cancer death in the U.S. Therefore, it is imperative to identify novel biomarkers for the early detection and progression of lung cancer. PRMT6 is associated with poor lung cancer prognosis. However, analyzing PRMT6 expression manually in large samples is time-consuming posing a significant limitation for processing this biomarker. To overcome this issue, we trained and validated an automated method for scoring PRMT6 in lung cancer tissues, which can then be used as the standard method in future larger cohorts to explore population-level associations between PRMT6 expression and sociodemographic/clinicopathologic characteristics. We evaluated the ability of a trained artificial intelligence (AI) algorithm to reproduce the PRMT6 immunoreactive scores obtained by pathologists. Our findings showed that tissue segmentation to cancer vs. non-cancer tissues was the most critical parameter, which required training and adjustment of the algorithm to prevent scoring non-cancer tissues or ignoring relevant cancer cells. The trained algorithm showed a high concordance with pathologists with a correlation coefficient of 0.88. The inter-rater agreement was significant, with an intraclass correlation of 0.95 and a scale reliability coefficient of 0.96. In conclusion, we successfully optimized a machine learning algorithm for scoring PRMT6 expression in lung cancer that matches the degree of accuracy of scoring by pathologists.

Quantifying Adverse Childhood Experiences in Oklahoma With the Oklahoma Adversity Surveillance Index System (OASIS): Development and Cross-Sectional Study

BACKGROUND

Developmental trauma depending on several factors may lead to later adult health risks and is an increasing public health concern, especially in states with predominantly rural populations. Oklahoma remains one of the states in America with the highest count of adverse childhood experiences (ACEs); therefore, more refined research methods for quantifying ACEs are vital for ensuring proper statewide interventions.

OBJECTIVE

While data sets already exist at the state level measuring specific ACEs like divorce or child abuse, the state currently lacks a single source for specific ACEs that can incorporate regions to allow for the identification of counties where ACEs are especially high. This county identification will allow for assessing trends in adversity prevalence over time to indicate where targeted interventions should be done and which counties experience amplified long-term consequences of high ACE rates. Thus, the model for the Oklahoma Adversity Surveillance Index System (OASIS) was born-a public health tool to map ACEs at the county level and grade them by severity over time.

METHODS

County-level data for 6 ACEs (mental illness, divorce, neglect, child abuse, domestic violence, and substance use) were collected from the Oklahoma Department of Human Services, Oklahoma State Department of Health, and Oklahoma Community Mental Health Centers for the years 2010 to 2018. First, a potential ACEs score (PAS) was created by standardizing and summing county rates for each ACE. To examine the temporal change in the PAS, a bivariate regression analysis was conducted. Additionally, an ACEs severity index (ASI) was created as a standardized measure of ACE severity across time. This included scoring counties based on severity for each ACE individually and summing the scores to generate an overall ASI for each county, capturing the severity of all ACEs included in the analysis.

RESULTS

Mental illness and substance use showed the highest rates at the state level. Results from the regression were significant (F1,76=5.269; P=.02), showing that county PAS showed an increase over years. The ASI scores ranged from 0 to 6, and 4 Oklahoma counties (Adair, McCurtain, Muskogee, and Pittsburg) received a score of 6.

CONCLUSIONS

OASIS involves the identification of counties where ACEs are most prevalent, allowing for the prioritization of interventions in these "hot spot" counties. In addition, regression analysis showed that ACEs increased in Oklahoma from 2010 to 2018. Future efforts should center on adding additional ACEs to the ASI and correlating adverse outcome rates (such as violence and medical disorder prevalence) at the county level with high ASI scores.

Cumulative Risk Evaluation of Phthalates Under TSCA

The U.S. Environmental Protection Agency (EPA) is currently conducting separate Toxic Substances Control Act (TSCA) risk evaluations for seven phthalates: dibutyl phthalate (DBP), butyl benzyl phthalate (BBP), di(2-ethylhexyl) phthalate (DEHP), diisobutyl phthalate (DIBP), dicyclohexyl phthalate (DCHP), di-isodecyl phthalate (DIDP), and diisononyl phthalate (DINP). Phthalates are highly abundant plastic additives used primarily to soften materials and make them flexible, and biomonitoring shows widespread human exposure to a mixture of phthalates. Evidence supports biological additivity of phthalate mixture exposures, including the enhancement of toxicity affecting common biological targets. Risk estimates based on individual phthalate exposure may not be protective of public health. Thus, a cumulative risk approach is warranted. While EPA initially did not signal that it would incorporate cumulative risk assessment (CRA) as part of its current risk evaluation for the seven phthalates, the agency recently announced that it is reconsidering if CRA for phthalates would be appropriate. Based on our review of existing chemical mixtures risk assessment guidance, current TSCA scoping documents for the seven phthalates, and pertinent peer-reviewed literature, we delineate a CRA approach that EPA can easily implement for phthalates. The strategy for using CRA to inform TSCA risk evaluation for existing chemicals is based upon integrative physiology and a common adverse health outcome algorithm for identifying and grouping relevant nonchemical and chemical stressors. We recommend adjustments for how hazard indices (HIs) or margins of exposure (MOEs) based on CRA are interpreted for determining "unreasonable risk" under TSCA.

The Effect of Neighborhood Disorganization on Care Engagement Among Children With Chronic Conditions Living in a Large Urban City

Neighborhood context plays an important role in producing and reproducing current patterns of health disparity. In particular, neighborhood disorganization affects how people engage in health care. We examined the effect of living in highly disorganized neighborhoods on care engagement, using data from the Coordinated Healthcare for Complex Kids (CHECK) program, which is a care delivery model for children with chronic conditions on Medicaid in Chicago. We retrieved demographic data from the US Census Bureau and crime data from the Chicago Police Department to estimate neighborhood-level social disorganization for the CHECK enrollees. A total of 6458 children enrolled in the CHECK between 2014 and 2017 were included in the analysis. Families living in the most disorganized neighborhoods, compared with areas with lower levels of disorganization, were less likely to engage in CHECK. Black families were less likely than Hispanic families to be engaged in the CHECK program. We discuss potential mechanisms through which disorganization affects care engagement. Understanding neighborhood context, including social disorganization, is key to developing more effective comprehensive care models.

Unmet needs of homeless U.S. veterans by gender and race/ethnicity: Data from five annual surveys

There has been insufficient research on gender, race, and ethnic differences in unmet needs of homeless populations. This study analyzed 5 years of data collected by Project Community Homelessness Assessment, Local Education, and Networking Groups (CHALENG) surveys from 2012 to 2016 to examine gender, race, and ethnic differences in "literally homeless" veterans (i.e., veterans living in the streets, shelters, vehicles, or any other place not meant for habitation). Of 7,040 participants, there were 6,335 male and 705 female literally homeless veterans from 4 self-identified racial/ethnic categories (White, Black, Hispanic, and Other). The results showed that homeless female veterans were significantly more likely to report unmet needs related to emergency shelter, transitional housing, and dental care than male veterans. Among men, White veterans reported greater unmet needs in housing, healthcare, basic needs, and specialized needs than racial/ethnic minority veterans. Among women, veterans who were racial/ethnic minorities reported greater unmet needs than their White counterparts. These findings suggest programmatic attention to gender, race, and ethnicity is important in addressing diverse needs of homeless veterans and specialized services may be needed to address their specific and consistent unmet needs. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Childhood Maltreatment and Dementia Risk Factors in Midlife: A Prospective Investigation

BACKGROUND

Previous studies have linked childhood adversities to dementia risk, yet most studies are cross-sectional in design and utilize retrospective self-reports to assess childhood experiences. These design characteristics make it difficult to establish temporal order and draw firm conclusions.

OBJECTIVES

Using a longitudinal design, we sought to determine whether childhood maltreatment predicts dementia risk factors in middle adulthood.

METHODS

Data have been obtained from a prospective cohort design study of children with documented cases of childhood maltreatment (ages 0-11 years at case identification) and demographically matched controls who were followed up and interviewed in middle adulthood. Outcomes were assessed through a medical examination and interview, and 807 of the cases that included blood collection at mean age 41. Dementia risk were investigated using 11 potentially modifiable risk factors.

RESULTS

Compared to controls, individuals with histories of childhood maltreatment had a higher risk of low educational attainment, low social contact, smoking, and clinical depression, and a higher total number of dementia risk factors. In general, childhood maltreatment predicted a higher risk of dementia for females, males, and Black and White participants. Black maltreated participants had a greater risk for traumatic brain injury compared to Black controls. Physical abuse, sexual abuse, and neglect, each predicted a higher number of dementia risk factors in mid-life.

CONCLUSION

These findings provide evidence that childhood maltreatment increases the risk for dementia in mid-life and has a demonstrable impact lasting over 30 years. Reducing the prevalence of mid-life dementia risk factors could reduce the risk of later-life dementia.

Using Association Rules to Understand the Risk of Adverse Pregnancy Outcomes in a Diverse Population

Racial and ethnic disparities in adverse pregnancy outcomes (APOs) have been well-documented in the United States, but the extent to which the disparities are present in high-risk subgroups have not been studied. To address this problem, we first applied association rule mining to the clinical data derived from the prospective nuMoM2b study cohort to identify subgroups at increased risk of developing four APOs (gestational diabetes, hypertension acquired during pregnancy, preeclampsia, and preterm birth). We then quantified racial/ethnic disparities within the cohort as well as within high-risk subgroups to assess potential effects of risk-reduction strategies. We identify significant differences in distributions of major risk factors across racial/ethnic groups and find surprising heterogeneity in APO prevalence across these populations, both in the cohort and in its high-risk subgroups. Our results suggest that risk-reducing strategies that simultaneously reduce disparities may require targeting of high-risk subgroups with considerations for the population context.

Obstetric experiences of young black mothers: An intersectional perspective

BACKGROUND

In Chicago, maternal morbidity and mortality is six times more likely among Black birthing people than white, despite policy initiatives to promote maternal health equity. Disparities in maternal morbidity and mortality reflect experiences of structural inequities - including limited quality obstetric care, implicit bias, and racism resulting patient mistrust in the health care system, inadequate social support, and financial insecurity. Although there is published literature on Black women's experiences with obstetric care, including experiences with individual and structural racism, little is known about the intersection of age and race and experiences with health care. The purpose of this study was to explore the maternal health and pregnancy experiences of young Black women utilizing an intersectional theoretical lens.

METHODS

In this study, we conducted two focus groups in a sample of 11 young Black pregnant people. We conducted a thematic analysis to identify codes, themes, and subthemes of the data.

RESULTS

We developed two overarching themes: obstetric racism and obstetric resistance. To elucidate how obstetric racism framed our participants' healthcare experiences, we identified sub-themes: intersectional identities as young Black women, medical mistrust, and pregnancy trauma. The second major theme describes ways in which participants protected themselves against obstetric racism to engender positive health experiences. These methods of resistance included identifying advocates and relying on trusted providers.

CONCLUSIONS

The current standard of obstetric care in the US is suboptimal due to individual and structural racism. This study provides unique data on the experiences with health care for young, Black pregnant individuals and delivers valuable insight into how individual and structural racism impacts obstetric care for young Black women.

Institutional Variability in Representation of Women and Racial and Ethnic Minority Groups Among Medical School Faculty

IMPORTANCE

Bolstering the ranks of women and underrepresented groups in medicine (URM) among medical faculty can help address ongoing health care disparities and therefore constitutes a critical public health need. There are increasing proportions of URM faculty, but comparisons of these changes with shifts in regional populations are lacking.

OBJECTIVE

To quantify the representation of women and URM and assess changes and variability in representation by individual US medical schools.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cross-sectional study assessed US medical school faculty rosters for women and URM, including American Indian and Alaska Native, Black, Hispanic, and Native Hawaiian or other Pacific Islander faculty. US allopathic medical schools participating in the Association of American Medical Colleges (AAMC) Faculty Administrative Management Online User System from 1990 to 2019 (updated December 31 for each year), were included. Faculty data were analyzed from yearly cross-sections updated as of December 31 for each year from 1990 to 2019. For census data, decennial census data were used for years 1990, 2000, and 2010. Intercensal estimates were used for all other years from 1990 to 2019.

MAIN OUTCOMES AND MEASURES

Trends and variability in representation quotient (RQ), defined as representation of a group within an institution's faculty compared to its respective US county.

RESULTS

There were 121 AAMC member institutions (72 076 faculty) in 1990, which increased to 144 institutions (184 577 faculty) in 2019. The median RQ of women faculty increased from 0.42 (IQR, 0.37-0.46) to 0.80 (IQR, 0.74-0.89) (slope, +1.4% per year; P < .001). The median RQ of Black faculty increased from 0.10 (IQR, 0.06-0.22) to 0.22 (IQR, 0.14-0.41) (slope, +0.5% per year; P < .001), but remained low. In contrast, the median RQ of Hispanic faculty decreased from 0.44 (IQR, 0.19-1.22) to 0.34 (IQR, 0.23-0.62) (slope, -1.7% per year; P < .001) between 1990 and 2019. Absolute total change in RQ of URM showed an increase; however, the 30-year slope did not differ from zero (+0.1% per year; P = .052). Although RQ of women faculty increased for most institutions (127 [88.2%]), large variability in URM faculty trends were observed (57 institutions [39.6%] with increased RQ and 10 institutions [6.9%] with decreased RQ). Nearly one-quarter of institutions shifted from the top to bottom 50th percentile institutional ranking by URM RQ with county vs national comparisons.

CONCLUSIONS AND RELEVANCE

The findings of this cross-sectional study suggest that representation of women in academic medicine improved with time, while URM overall experienced only modest increases with wide variability across institutions. Among URM, the Hispanic population has lost representational ground. County-based population comparisons provide new insights into institutional variation in representation among medical school faculty.

Melanated Group Midwifery Care: Centering the Voices of the Black Birthing Community

Access to safe and dignified pregnancy, childbirth, and postpartum experiences is a fundamental right for all pregnant and postpartum people. In the United States, systemic racism fuels distrust and disengagement in a health care system that continues to dehumanize the Black community. The respectful maternity care literature explains how these systemic, structural, and institutional failings produce maternal health disparities and expose a pattern whereby Black women receive less adequate maternity care. The implementation of trustworthy policies and practices is urgently needed because no single intervention has or will substantially reduce maternal disparities. The purpose of this article is to describe a multicomponent maternity care innovation, Melanated Group Midwifery Care (MGMC). MGMC was codesigned with community partners and is responsive to the needs and desires of Black women, making MGMC a culturally adapted and patient-centered model. Racial concordance among care providers and patients, group prenatal care, perinatal nurse navigation, and 12 months of in-home postpartum doula support are 4 evidence-based interventions that are bundled in MGMC. We posit that a model that restructures maternity care to increase health system accountability and aligns with the needs and desires of Black pregnant and postpartum people will increase trust in the health care system and result in better clinical, physical, emotional, and social outcomes.

Urban Spatial Accessibility of Primary Care and Hypertension Control and Awareness on Chicago's South Side: A Study From the COMPASS Cohort

BACKGROUND

Understanding the relationship between hypertension and spatial accessibility of primary care can inform interventions to improve hypertension control and awareness, especially among disadvantaged populations. This study aims to investigate the association between spatial accessibility of primary care and hypertension control and awareness.

METHODS

Participant data from the COMPASS (Chicago Multiethnic Prevention and Surveillance Study) between 2013 and 2019 were analyzed. All participants were geocoded. Locations of primary care providers in Chicago were obtained from MAPSCorps. A score was generated for spatial accessibility of primary care using an enhanced 2-step floating catchment area method. A higher score indicates greater accessibility. Measured hypertension was defined as systolic blood pressure ≥130 mm Hg or diastolic blood pressure ≥80 mm Hg. Logistic regression was used to estimate odds ratio and 95% CI for hypertension status in relation to accessibility score quartiles.

RESULTS

Five thousand ninety-six participants (mean age, 53.4±10.8) were included. The study population was predominantly non-Hispanic black (84.0%), over 53% reported an annual household income <$15 000, and 37.3% were obese. Measured hypertension prevalence was 78.7% in this population, among which 37.7% were uncontrolled and 41.0% were unaware. A higher accessibility score was associated with lower measured hypertension prevalence. In fully adjusted models, compared with the first (lowest) quartile of accessibility score, the odds ratio strengthened from 0.82 (95% CI, 0.67-1.01) for the second quartile to 0.75 (95% CI, 0.62-0.91) for the third quartile, and further to 0.73 (95% CI, 0.60-0.89) for the fourth (highest) quartile. The increasing trend had a P<0.01. Similar associations were observed for both uncontrolled and unaware hypertensions. When stratified by neighborhood socioeconomic status, a higher accessibility score was associated with lower rates of unaware hypertension in both disadvantaged and nondisadvantaged neighborhoods.

CONCLUSIONS

Better spatial accessibility of primary care is associated with improved hypertension awareness and control.

Patient activation reduces effects of implicit bias on doctor-patient interactions

Disparities between Black and White Americans persist in medical treatment and health outcomes. One reason is that physicians sometimes hold implicit racial biases that favor White (over Black) patients. Thus, disrupting the effects of physicians' implicit bias is one route to promoting equitable health outcomes. In the present research, we tested a potential mechanism to short-circuit the effects of doctors' implicit bias: patient activation, i.e., having patients ask questions and advocate for themselves. Specifically, we trained Black and White standardized patients (SPs) to be "activated" or "typical" during appointments with unsuspecting oncologists and primary care physicians in which SPs claimed to have stage IV lung cancer. Supporting the idea that patient activation can promote equitable doctor-patient interactions, results showed that physicians' implicit racial bias (as measured by an implicit association test) predicted racially biased interpersonal treatment among typical SPs (but not among activated SPs) across SP ratings of interaction quality and ratings from independent coders who read the interaction transcripts. This research supports prior work showing that implicit attitudes can undermine interpersonal treatment in medical settings and provides a strategy for ensuring equitable doctor-patient interactions.

Assessing inequities underlying racial disparities of COVID-19 mortality in Louisiana parishes

High COVID-19 mortality among Black communities heightened the pandemic's devastation. In the state of Louisiana, the racial disparity associated with COVID-19 mortality was significant; Black Americans accounted for 50% of known COVID-19-related deaths while representing only 32% of the state's population. In this paper, we argue that structural racism resulted in a synergistic framework of cumulatively negative determinants of health that ultimately affected COVID-19 deaths in Louisiana Black communities. We identify the spatial distribution of social, environmental, and economic stressors across Louisiana parishes using hot spot analysis to develop aggregate stressors. Further, we examine the correlation between stressors, cumulative health risks, COVID-19 mortality, and the size of Black populations throughout Louisiana. We hypothesized that parishes with larger Black populations (percentages) would have larger stressor values and higher cumulative health risks as well as increased COVID-19 mortality rates. Our results suggest two categories of parishes. The first group has moderate levels of aggregate stress, high population densities, predominately Black populations, and high COVID-19 mortality. The second group of parishes has high aggregate stress, lower population densities, predominantly Black populations, and initially low COVID-19 mortality that increased over time. Our results suggest that structural racism and inequities led to severe disparities in initial COVID-19 effects among highly populated Black Louisiana communities and that as the virus moved into less densely populated Black communities, similar trends emerged.

Associations between perceived discrimination and immune cell composition in the Jackson Heart Study

African American adults suffer disproportionately from several non-communicable and infectious diseases. Among numerous contributing factors, perceived discrimination is considered a stressor for members of historically marginalized groups that contributes to health risk, although biological pathways are incompletely understood. Previous studies have reported associations between stress and both an up-regulation of non-specific (innate) inflammation and down-regulation of specific (adaptive) immunity. While associations between perceived discrimination and markers of inflammation have been explored, it is unclear if this is part of an overall shift that also includes down-regulated adaptive immunity. Relying on a large cross-section of African American adults (n = 3,319) from the Jackson Heart Study (JHS) in Jackson, Mississippi, we tested whether perceived everyday and lifetime discrimination as well as perceived burden from lifetime discrimination were associated with counts of neutrophils (innate), monocytes (innate), lymphocytes (adaptive), and the neutrophil-to-lymphocyte ratio (NLR), derived from complete white blood cell counts with differential. In addition, DNA methylation (DNAm) was measured on the EPIC array in a sub-sample (n = 1,023) of participants, allowing estimation of CD4T, CD8T and B lymphocyte proportions. Unexpectedly, high lifetime discrimination compared to low was significantly associated with lower neutrophils (b : -0.14, [95% CI: -0.24, -0.04]) and a lower NLR (b : -0.15, [95% CI: -0.25, -0.05]) after controlling for confounders. However, high perceived burden from lifetime discrimination was significantly associated with higher neutrophils (b : 0.17, [95% CI: 0.05, 0.30]) and a higher NLR (b : 0.16, [95% CI: 0.03, 0.29]). High perceived burden was also associated with lower lymphocytes among older men, which our analysis suggested might have been attributable to differences in CD4T cells. These findings highlight immune function as a potentially important pathway linking perceived discrimination to health outcomes.

Factors Mediating Racial/Ethnic Disparities in Delayed Treatment of Breast Cancer

BACKGROUND

Despite improvements, disparities in breast cancer care have led to an inequitable distribution of treatment delays and worse outcomes among patients with breast cancer. This study aimed to quantify the contribution of mediators that may explain racial/ethnic disparities in breast cancer treatment delays.

PATIENTS AND METHODS

We conducted a retrospective analysis of patients from the National Cancer Database with stage I-III breast cancer who underwent surgical resection. Mediation analyses estimated the extent to which racial/ethnic disparities in the distribution of patient characteristics account for racial/ethnic disparities in delayed treatment.

RESULTS

Of the 1,349,715 patients with breast cancer included, 10%, 5%, and 4% were Black, Hispanic, and other non-white race/ethnicity, respectively. Multivariable models showed that patients in these racial/ethnic groups had 73%, 81%, and 24% increased odds of having a treatment delay relative to white patients. Mediation analyses suggested that 15%, 19%, and 15% of the treatment delays among Black, Hispanic, and other non-white race/ethnicity patients, respectively, are explained by disparities in education, comorbidities, insurance, and facility type. Therefore, if these mediators had been distributed equally among all races/ethnicities, a reduction of 15-19% in the delayed treatment disparities experienced by minority patients would have been observed. Academic facility type was the factor that could yield the largest reduction in time to treatment disparities, contributing to 8-13% of racial/ethnic disparities.

CONCLUSIONS

Patients with breast cancer who identified as Black, Hispanic, and other non-white races/ethnicities are exposed to longer treatment delays relative to white patients. Efforts to equalize mediators could remove substantial portions of racial/ethnic disparities in delayed treatment.

Impact of the COVID-19 pandemic on cardiovascular disease mortality in a major metropolitan area

Background

The mortality from COVID-19 alone cannot account for the impact of the pandemic. Cardiovascular disease (CVD) mortality has increased disproportionately in specific racial/ethnic populations.

Objective

This study aimed to characterize how the COVID-19 pandemic impacted the association between CVD mortality and social and demographic factors as characterized by the Social Vulnerability Index (SVI).

Methods

Medical Examiner Case Archive of Cook County, Illinois was utilized to identify CVD deaths in 2019 (pre-pandemic) and 2020 (pandemic). Rate ratios (RRs) were used to compare age-adjusted mortality rates (AAMRs). Addresses of deaths were geocoded to Chicago Community Areas. The Spearman's rank correlation coefficient (ρ) test was used to identify the association between SVI and CVD mortality.

Results

AAMRs of CVD deaths significantly increased among non-Hispanic Black individuals (AAMRR, 1.1; 95 % CI, 1.1–1.2) and Hispanic individuals (AAMRR, 1.8; 95 % CI, 1.5–2.1) from 2019 to 2020. Among non-Hispanic White individuals, the AAMR did not significantly increase (AAMRR, 1.0; 95 % CI, 0.9–1.1). A significant positive association was observed between SVI and the percentage of non-Hispanic Black residents (ρ = 0.45; P < 0.05), while the inverse was observed with the percentage of non-Hispanic White residents (ρ = −0.77; P < 0.05). A significant positive association between SVI and CVD mortality rate increased (ρ = 0.24 and 0.28; P < 0.05).

Conclusions

Significant association between SVI and CVD mortality was strengthened from 2019 to 2020, and CVD mortality increased among non-Hispanic Black and Hispanic populations. These findings demonstrate that the COVID-19 pandemic has led to an exacerbation of health inequities among different racial/ethnic populations resulting in increased CVD mortality.

The contribution of smoking-attributable mortality to differences in mortality and life expectancy among US African-American and white adults, 2000–2019

BACKGROUND

The role of smoking in racial disparities in mortality and life expectancy in the United States has been examined previously, but up-to-date estimates are generally unavailable, even though smoking prevalence has declined in recent decades.

OBJECTIVE

We estimate the contribution of smoking-attributable mortality to observed differences in mortality and life expectancy for US African-American and white adults from 2000–2019.

METHODS

The indirect Preston–Glei–Wilmoth method was used with national vital statistics and population data and nationally representative never-smoker lung cancer death rates to estimate the smoking-attributable fraction (SAF) of deaths in the United States by sex-race group from 2000–2019. Mortality rates without smoking-attributable mortality were used to estimate life expectancy at age 50 (e₅₀) by group during the period.

RESULTS

African-American men had the highest estimated SAF during the period, beginning at 26.4% (95% CI:25.0%–27.8%) in 2000 and ending at 12.1% (95% CI:11.4%–12.8%) in 2019. The proportion of the difference in e₅₀ for white and African-American men that was due to smoking decreased from 27.7% to 14.8%. For African-American and white women, the estimated differences in e₅₀ without smoking-attributable mortality were similar to observed differences.

CONCLUSIONS

Smoking continues to contribute to racial disparities in mortality and life expectancy among men in the United States.

CONTRIBUTION

We present updated estimates of the contribution of smoking to mortality differences in the United States using nationally representative data sources.

The Strong Black Woman Concept: Associated Demographic Characteristics and Perceived Stress Among Black Women

Being a “Strong Black Woman” (SBW) is a frequent cultural demand for Black Women. The physical and emotional disadvantages of this persistent racial gender role expectation are notable. The purpose of the current exploratory study was to (1) confirm a link between endorsement of the SBW schema and self-reported perceived stress and (2) investigate the potential demographic features that predict the level of endorsement of the SBW schema. A community sample of n = 185 Black women completed an online survey containing the Giscombé Superwoman Schema Questionnaire ( Woods-Giscombé et al., 2019 ), the Perceived Stress Scale-10 ( Cohen & Williamson, 1988 ), and a demographic questionnaire. The results indicated that more endorsement of SBW ideals uniquely predicted greater perceived stress. Also, only the demographic variables of age and number of children were predictors of SBW endorsement. Endorsement of SBW expectations did not vary across the other demographic variables indicating the SBW schema was prominent for most participants in the sample.

Longitudinal Predictive Curves of Health Risk Factors for American Adolescent Girls

PURPOSE

The aim of this study is to compare age-variant 18 health risk factors by constructing longitudinal predictive curves between African-American (AA) and Caucasian American (CA) adolescent girls.

METHODS

A total of 2,379 girls (51% AA) from ages 9 to 10 were recruited in the National Heart, Lung, and Blood Institute Growth and Health Study. The various health indicators and dietary habits of these girls were assessed annually for 10 years. We model 2nd, 5th, 95th, and 98th percentile values of the health risk factors to compare trajectories between AA and CA adolescents by employing novel kernel smoothing regression and global tests of equality for regression curves. Health risk factors such as dietary fiber, intake of sodium, sugar, and total calories, systolic blood pressure, weight, body fat percentage, and high-density lipoprotein levels were compared.

RESULTS

Trajectories of sugar, sodium, and total calories intake and systolic blood pressure, weight, body fat percentage, and high-density lipoprotein among AA girls were significantly higher than those of CA girls throughout their adolescence.

CONCLUSIONS

AA girls exhibit several health risk factors that are significantly higher than those of CA adolescent girls at the 95th and 98th percentile. Interventions may be warranted for the purposes of ensuring access to health risk information as well as a greater ease of access to healthier food choices within the educational food system.

User Perception of Public Parks: A Pilot Study Integrating Spatial Social Media Data with Park Management in the City of Chicago

User-generated content (UGC) is a relatively young field of research; however, it has been proven useful in disciplines such as hospitality and tourism, to elicit public opinions of place usage. In landscape architecture and urban planning, UGC has been used to understand people’s emotions and movement in a space, while other areas and additional functions are yet to be discovered. This paper explores the capability of UGC in revealing city-scale park management problems and the applicability of social media as a future tool in bridging visitor feedback to city parks and recreation department staff. This research analyzed the spatial characteristics and patterns of Google Maps review quantity, rating score, and review comments. The results of this pilot study indicate the spatial and structural features of the Chicago parks and demonstrate distribution problems, financial investment priority concerns, park usage characteristics, and user preferences of the park attributes. Findings affirm that user-generated online reviews can be used as an alternative and self-reporting data source to effectively assess the natural performance and users’ experience of city parks and can potentially serve as an evaluative tool for public park management.

Cultural trauma as a fundamental cause of health disparities

Health disparities disproportionately affect minority cultural groups (e.g., Indigenous, immigrant, refugee) worldwide; enduring across time, disease states, and risk factors despite co-occurring advancements in health and medicine. Fundamental cause theory holds that important social factors (e.g., socioeconomic status, stigma, racism) produce health disparities by restricting equitable access to health-protective resources. Yet, extant literature has not utilized fundamental cause theory to describe the health disparities impact of cultural trauma: an overwhelming, often ongoing physical or psychological assault by an oppressive dominant group on another group's cultural resources through force, threats of force, or oppressive policies. This paper presents a novel conceptual model detailing cultural trauma and the mechanisms through which it may disrupt health and create disparities by damaging three health-protective cultural resources: cultural modes, institutions, and lands. Following cultural trauma, we propose affected groups are socially disadvantaged and exposed to pervasive stress, stigma, and diminished resources, perpetuating health disparities across generations. Consequently, cultural trauma may represent an unrecognized fundamental cause of health disparities, offering potential avenues for promoting health equity through targeted research, interventions, and policies.

Patient-specific risk factors contributing to blood culture contamination

Objective:

Contaminated blood cultures result in extended hospital stays and unnecessary antibiotic therapy. Patient-specific factors associated with blood culture contamination remain largely unexplored. Identifying patients at higher risk of blood culture contamination could alert healthcare providers to take extra precautionary measures to limit contamination in these patients, and thereby prevent associated adverse outcomes. We sought to identify patient-related factors that contribute to blood culture contamination in hospitalized patients.

Design and setting:

We conducted a secondary data analysis of a retrospective cohort study at an academic medical center.

Patients:

Study participants included 19,255 adult patients who had blood culture(s) performed during a hospital admission between June 2014 and December 2016.

Methods:

Data were analyzed to evaluate risk factors for blood culture contamination using logistic regression.

Results:

Among adult patients, we identified 464 contaminated episodes and 11,010 negative blood-culture episodes. Chronic obstructive pulmonary disease (adjusted odds ratio [AOR], 1.67; 95% confidence interval [CI], 1.20–2.34) and stay in an intensive care unit (ICU) during an admission (AOR, 1.41; 95% CI, 1.14–1.74) were associated with blood culture contamination. Other risk factors included race, body mass index, and admission from the emergency department. Subgroup analyses of patients admitted from the emergency department showed similar results.

Conclusions:

We identified patient-specific factors that increase the odds of false-positive blood cultures. By introducing mitigation strategies to limit contamination in patients with these risk factors, it may be possible to reduce the adverse clinical impact of blood culture contamination.

Diagnosing Mild Cognitive Impairment Among Racially Diverse Older Adults: Comparison of Consensus, Actuarial, and Statistical Methods

BACKGROUND

Actuarial and statistical methods have been proposed as alternatives to conventional methods of diagnosing mild cognitive impairment (MCI), with the aim of enhancing diagnostic and prognostic validity, but have not been compared in racially diverse samples.

OBJECTIVE

We compared the agreement of consensus, actuarial, and statistical MCI diagnostic methods, and their relationship to race and prognostic indicators among diverse older adults.

METHODS

Participants (N = 354; M age = 71; 68% White, 29% Black) were diagnosed with MCI or normal cognition (NC) according to clinical consensus, actuarial neuropsychological criteria (Jak/Bondi), and latent class analysis (LCA). We examined associations with race/ethnicity, longitudinal cognitive and functional change, and incident dementia.

RESULTS

MCI rates by consensus, actuarial criteria, and LCA were 44%, 53%, and 41%, respectively. LCA identified three MCI subtypes (memory; memory/language; memory/executive) and two NC classes (low normal; high normal). Diagnostic agreement was substantial, but agreement of the actuarial method with consensus and LCA was weaker than the agreement between consensus and LCA. Among cases classified as MCI by actuarial criteria only, Black participants were over-represented, and outcomes were generally similar to those of NC participants. Consensus diagnoses best predicted longitudinal outcomes overall, whereas actuarial diagnoses best predicted longitudinal functional change among Black participants.

CONCLUSION

Consensus diagnoses optimize specificity in predicting dementia, but among Black older adults, actuarial diagnoses may be more sensitive to early signs of decline. Results highlight the need for cross-cultural validity in MCI diagnosis and should be explored in community- and population-based samples.

Associations of Race, Insurance, and Zip Code-Level Income with Nonadherence Diagnoses in Primary and Specialty Diabetes Care

INTRODUCTION

Evidence suggests that clinicians may view or label patients as nonadherent in a biased manner. Therefore, we performed a retrospective cohort analysis exploring associations between patient demographics and zip code-level income with the International Classification of Diseases, Tenth Version (ICD-10) diagnoses for nonadherence among type 2 diabetes mellitus (T2DM) patients, comparing primary and specialty care settings. Providers in the primary care group included internal medicine and family medicine physicians. In the specialty care group, providers included endocrinologists and diabetologists only.

METHODS

Participants were identified from 5 primary care and 4 endocrinology sites in the University of Pennsylvania Health System between January 1, 2015, and January 1, 2019. Demographics, hemoglobin A1c (HbA1c), and ICD-10 codes for T2DM and nonadherence were extracted from the electronic health record and analyzed in October 2019. Log-binomial regression models were used to estimate patients' risk of nonadherence labeling by race, insurance, and zip code-level median household income, controlling for patient characteristics and HbA1c as a proxy for diabetes self-management. Results were compared between primary and specialty care sites.

RESULTS

A total of 6072 patients aged 18-70 years were included in this study. Black race, Medicare, and Medicaid were associated with increased nonadherence labeling while controlling for patient characteristics ([ARR = 2.48, 95% CI: 2.01, 3.04], [ARR = 1.82, 95% CI: 1.50, 2.18], [ARR = 1.61, 95% CI: 1.32, 1.93], respectively). The results remained significant on adjustment with zip code-level income and showed no differences between primary and specialty sites. Lower-income zip codes showed a significant association with increased rates of nonadherence labeling.

CONCLUSIONS

Black race, non-private insurance, and lower-income zip codes were associated with disproportionately high rates of nonadherence labeling in both primary and specialty management of T2DM, possibly suggestive of racial or class bias.

Association of Race and Ethnicity with Sedation Management in Pediatric Intensive Care

Rationale: Racial disparities in pain management have been previously reported for children receiving emergency care.Objectives: To determine whether patient race or ethnicity is associated with the broader goal of pain management and sedation among pediatric patients mechanically ventilated for acute respiratory failure.Methods: Planned secondary analysis of RESTORE (Randomized Evaluation of Sedation Titration for Respiratory Failure). RESTORE, a cluster-randomized clinical trial conducted in 31 U.S. pediatric intensive care units, compared protocolized sedation management (intervention arm) with usual care (control arm). Participants included 2,271 children identified as non-Hispanic white (white, n = 1,233), non-Hispanic Black (Black, n = 502), or Hispanic of any race (Hispanic, n = 536).Results: Within each treatment arm, neither opioid nor benzodiazepine selection, nor cumulative dosing, differed significantly among race and ethnicity groups. Black patients experienced fewer days with an episode of pain (compared with white patients in the control arm and with Hispanic patients in the intervention arm) and experienced less iatrogenic withdrawal syndrome (compared with white patients in either arm or with Hispanic patients in the intervention arm). The percentage of days awake and calm while intubated was not significantly different in pairwise comparisons by race and ethnicity groups in either the control arm (median: white, 75%; Black, 71%; Hispanic, 75%) or the intervention arm (white, 86%; Black, 88%; Hispanic, 85%).Conclusions: Across multiple measures, our study found scattered differences in sedation management among critically ill Black, Hispanic, and white children that did not consistently favor any group. However, racial disparities related to implicit bias cannot be completely ruled out.Clinical trial registered with clinicaltrials.gov (NCT00814099).

The Impact of Race and Gender on 30-Day Urologic Surgery Complications

OBJECTIVE

To assess the effect of race and gender on complications after urologic surgeries.

MATERIALS AND METHODS

The American College of Surgeons' National Surgical Quality Improvement Program data was utilized for patients undergoing urologic surgeries. Patient demographics and comorbidities were analyzed. Postoperative complications occurring in a 30-day postoperative period were noted and classified per the Clavien-Dindo classification.

RESULTS

From 2008-2018, 284,050 patients underwent urologic surgery. The majority were men (80%) and identified as non-Hispanic white (80%). Complications occurred in 12%, including 9% minor, 5% major, and mortality in 0.6%. Univariate analysis found female gender, non-Hispanic black and Native American race, and patient comorbidities (hypertension, diabetes, heart failure, lung disease, chronic kidney disease) to be associated with increased risk of complications. Female gender remained a significant predictor on multivariable logistic regression, and Hispanic race was found to be an independent negative predictor of postoperative complications, although these results did not appear clinically significant. On exclusion of gender-specific urologic surgeries, female gender was associated with higher likelihood of minor complications, but male gender was associated with higher likelihood of major complications or mortality.

CONCLUSION

Race was not associated with postoperative complication rate. Patient comorbidities are associated with an increased risk of 30-day postoperative complications. Females were more likely to have minor and males were more likely to major complications. Optimizing patient comorbidities preoperatively is key to improving postoperative outcomes.

Linking discrimination and sleep with biomarker profiles: An investigation in the MIDUS study

Self-reported experiences of discrimination and sleep dysfunction have both been shown to adversely impact biological functioning; however, few studies have examined how they are jointly associated with health. The current study draws from two samples of the Midlife in the United States (MIDUS) data (n = 617 participants; 59.8% female; 72.3% White and 27.7% African American; Age: Mean = 52.6, SD = 12.22) to identify profiles of sleep (duration, variability, onset latency, wake after sleep onset, naps) and discrimination (everyday, lifetime, impact). Associations with latent profiles of biomarkers of inflammation (CRP, fibrinogen, IL-6) and endocrine stress (cortisol, epinephrine, norepinephrine) were examined. Three profiles were identified for sleep/discrimination (good, fair, poor) and for biomarkers (average, high inflammation, high neuroendocrine). Chi-square analyses indicated that adults in the good sleep/low discrimination profile were more likely to be in the average biomarker profile but less likely to be in the high inflammation profile. Adults in the fair sleep/moderate discrimination risk profile were more likely to be in the high inflammation profile. Adults in the poor sleep/high discrimination risk profile were less likely to be in the average biomarker profile but more likely to be in the high inflammation profile. The current study identified configurations of sleep and discrimination among midlife adults which were associated with profiles of biological risk. The findings provide implications for identifying individuals who may be at increased risk of developing stress-related tertiary outcomes of morbidity and disease.

Evidence of Social and Structural COVID-19 Disparities by Sexual Orientation, Gender Identity, and Race/Ethnicity in an Urban Environment

The ongoing COVID-19 pandemic has had widespread social, psychological, and economic impacts. However, these impacts are not distributed equally: already marginalized populations, specifically racial/ethnic minority groups and sexual and gender minority populations, may be more likely to suffer the effects of COVID-19. The COVID-19 Resiliency Survey was conducted by the city of Chicago to assess the impact of COVID-19 on city residents in the wake of Chicago's initial lockdown, with particular focus on the experiences of minority populations. Chi-square tests of independence were performed to compare COVID-19-related outcomes and impacts on heterosexual vs. sexual minority populations, cisgender vs. gender minority populations, and White vs. racial/ethnic minority subgroups. Marginalized populations experienced significant disparities in COVID-19 exposure, susceptibility, and treatment access, as well as in psychosocial effects of the pandemic. Notably, Black and Latinx populations reported significant difficulties accessing food and supplies (p = 0.002). Healthcare access disparities were also visible, with Black and Latinx respondents reporting significantly lower levels of access to a provider to see if COVID-19 testing would be appropriate (p = 0.013), medical services (p = 0.001), and use of telehealth for mental health services (p = 0.001). Sexual minority respondents reported significantly lower rates of using telehealth for mental health services (p = 0.011), and gender minority respondents reported significantly lower levels of primary care provider access (p = 0.016). There are evident COVID-19 disparities experienced in Chicago especially for Black, Latinx, sexual minority, and gender minority groups. A greater focus must be paid to health equity, including providing increased resources and supplies for affected groups, adapting to inequities in the built environment, and ensuring adequate access to healthcare services to ameliorate the burden of COVID-19 on these marginalized populations.

The Duffy-null genotype and risk of infection

Many medical treatments, from oncology to psychiatry, can lower white blood cell counts and thus access to these treatments can be restricted to individuals with normal levels of white blood cells, principally in order to minimize risk of serious infection. This adversely affects individuals of African or Middle Eastern ancestries who have on average a reduced number of circulating white blood cells, because of the Duffy-null (CC) genotype at rs2814778 in the ACKR1 gene. Here, we investigate whether the Duffy-null genotype is associated with the risk of infection using the UK Biobank sample and the iPSYCH Danish case-cohort study, two population-based samples from different countries and age ranges. We found that a high proportion of those with the Duffy-null genotype (21%) had a neutrophil count below the threshold often used as a cut-off for access to relevant treatments, compared with 1% of those with the TC/TT genotype. In addition we found that despite its strong association with lower average neutrophil counts, the Duffy-null genotype was not associated with an increased risk of infection, viral or bacterial. These results have widespread implications for the clinical treatment of individuals of African ancestry and indicate that neutrophil thresholds to access treatments could be lowered in individuals with the Duffy-null genotype without an increased risk of infection.

Partnering with Churches to Conduct a Wide-Scale Health Screening of an Urban, Segregated Community

West Side Alive (WSA) is a partnership among pastors, church members and health researchers with the goal of improving health in the churches and surrounding community in the West Side of Chicago, a highly segregated African American area of Chicago with high rates of premature mortality and social disadvantage. To inform health intervention development, WSA conducted a series of health screenings that took place in seven partner churches. Key measures included social determinants of health and healthcare access, depression and PTSD screeners, and measurement of cardiometabolic risk factors, including blood pressure, weight, cholesterol and hemoglobin A1C (A1C). A total of 1106 adults were screened, consisting of WSA church members (n = 687), members of the local community served by the church (n = 339) and 80 individuals with unknown church status. Mean age was 52.8 years, 57% were female, and 67% reported at least one social risk factor (e.g. food insecurity). Almost all participants had at least one cardiovascular risk factor (92%), including 50% with obesity, 79% with elevated blood pressure and 65% with elevated A1C. A third of participants experienced ≥ 4 potentially traumatic events and 26% screened positive for depression and/or post-traumatic stress disorder. Participants were given personalized health reports and referred to services as needed. Information from the screenings will be used to inform the design of interventions targeting the West Side community and delivered in partnership with the churches. Sharing these results helped mobilize community members to improve their own health and the health of their community.

The Role of Ethnic Prejudice in the Modulation of Cradling Lateralization

The left-cradling bias is the tendency to cradle an infant on the left side, regardless of the individuals' handedness, culture or ethnicity. Many studies revealed associations between socio-emotional variables and the left-side bias, suggesting that this asymmetry might be considered as a proxy of the emotional attunement between the cradling and the cradled individuals. In this study we examined whether adult females with high levels of prejudice toward a specific ethnic group would show reduced left-cradling preferences when required to cradle an infant-like doll with ethnical features of the prejudiced group. We manipulated the ethnicity of the cradled individual by asking 336 Caucasian women to cradle a White or a Black doll and then assessed their prejudice levels toward African individuals. Significant correlations were shown only in the Black doll group indicating that the more the prejudice toward Africans, the more the cradling-side preferences shifted toward the right. Furthermore, participants exhibiting low levels-but not those exhibiting high levels-of ethnic prejudice showed a significant left-cradling bias. These findings show that ethnic prejudice toward the specific ethnic group of the cradled individual can interfere with the left preference in the cradling woman. The present study corroborates our suggestion that the left-cradling bias might be considered as a natural index of a positive socio-communicative relationship between the cradling and cradled individuals. On the contrary, the right-cradling bias might be considered as a cue of the presence of affective dysfunctions in the relationship.

Disparities in cancer mortality in Los Angeles County, 1999-2013: an analysis comparing trends in under-resourced and affluent regions

PURPOSE

While cancer mortality has declined by 27% between 1991 and 2016 in the United States, there are large disparities in cancer mortality by racial/ethnic groups, socioeconomic status and access to care. The purpose of this analysis is to compare trends in cancer mortality among regions (Service Planning Areas, SPAs) in Los Angeles (LA) County that vary with respect to racial/ethnic distribution and social determinants of health, including poverty, education and access to care.

METHODS

We estimated age- and race/ethnicity-standardized mortality for lung, colorectal (CRC) and breast cancer for eight SPAs from 1999 to 2013. We calculated three recommended measures of disparities that reflect absolute, relative and between-group disparities.

RESULTS

In all of LA County, statistically significant declines in age- and race/ethnicity-standardized mortality ranged from 30% for lung cancer to 20% for CRC to 15% for breast cancer. Despite some of the largest declines in the most under-resourced SPAs (South LA, East LA, South Bay), disparities between the lowest and highest mortality by SPA did not significantly change from 1999 to 2013.

CONCLUSIONS

Despite significant declines in cancer mortality in LA County from 1999 to 2013, and in racial/ethnic groups, there was little progress toward reducing disparities among SPAs. Highest mortalities for the three cancers were observed in Antelope Valley, San Fernando Valley, San Gabriel Valley, South LA and East LA. Findings demonstrate the importance of examining regional differences in cancer mortality to identify areas with highest needs for interventions and policies to reduce cancer disparities.

Cohort profile: the ChicagO Multiethnic Prevention and Surveillance Study (COMPASS)

PURPOSE

The ChicagO Multiethnic Prevention and Surveillance Study or 'COMPASS' is a population-based cohort study with a goal to examine the risk and determinants of cancer and chronic disease. COMPASS aims to address factors causing and/or exacerbating health disparities using a precision health approach by recruiting diverse participants in Chicago, with an emphasis on those historically underrepresented in biomedical research.

PARTICIPANTS

Nearly 8000 participants have been recruited from 72 of the 77 Chicago community areas. Enrolment entails the completion of a 1-hour long survey, consenting for past and future medical records from all sources, the collection of clinical and physical measurement data and the on-site collection of biological samples including blood, urine and saliva. Indoor air monitoring data and stool samples are being collected from a subset of participants. On collection, all biological samples are processed and aliquoted within 24 hours before long-term storage and subsequent analysis.

FINDINGS TO DATE

The cohort reported an average age of 53.7 years, while 80.5% identified as African-American, 5.7% as Hispanic and 47.8% as men. Over 50% reported earning less than US$15 000 yearly, 35% were obese and 47.8% were current smokers. Moreover, 38% self-reported having had a diagnosis of hypertension, while 66.4% were measured as hypertensive at enrolment.

FUTURE PLANS

We plan to expand recruitment up to 100 000 participants from the Chicago metropolitan area in the next decade using a hybrid community and clinic-based recruitment framework that incorporates data collection through mobile medical units. Follow-up data collection from current cohort members will include serial samples, as well as longitudinal health, lifestyle and behavioural assessment. We will supplement self-reported data with electronic medical records, expand the collection of biometrics and biosamples to facilitate increasing digital epidemiological study designs and link to state and/or national level databases to ascertain outcomes. The results and findings will inform potential opportunities for precision disease prevention and mitigation in Chicago and other urban areas with a diverse population.

REGISTRATION

NA.

Social Vulnerability and Racial Inequality in COVID-19 Deaths in Chicago

Although the current COVID-19 crisis is felt globally, at the local level, COVID-19 has disproportionately affected poor, highly segregated African American communities in Chicago. To understand the emerging pattern of racial inequality in the effects of COVID-19, we examined the relative burden of social vulnerability and health risk factors. We found significant spatial clusters of social vulnerability and risk factors, both of which are significantly associated with the increased COVID-19-related death rate. We also found that a higher percentage of African Americans was associated with increased levels of social vulnerability and risk factors. In addition, the proportion of African American residents has an independent effect on the COVID-19 death rate. We argue that existing inequity is often highlighted in emergency conditions. The disproportionate effects of COVID-19 in African American communities are a reflection of racial inequality and social exclusion that existed before the COVID-19 crisis.

Assessing the spatial heterogeneity in black-white differences in optimal cardiovascular health and the impact of individual- and neighborhood-level risk factors: The Multi-Ethnic Study of Atherosclerosis (MESA)

Racial disparities in cardiovascular health (CVH) continue to remain a public health concern in the United States. We use unique population-based data from the Multi-Ethnic Study of Atherosclerosis cohort to explore the black-white differences in optimal CVH. Utilizing geographically weighted regression methods, we assess the spatial heterogeneity in black-white differences in optimal CVH and the impact of both individual- and neighborhood-level risk factors. We found evidence of significant spatial heterogeneity in black-white differences that varied within and between the five sites. Initial models showed decreased odds of optimal CVH for blacks that ranged from 60% to 70% reduced odds - with noticeable variation of these decreased odds within each site. Adjusting for risk factors resulted in reductions in the black-white differences in optimal CVH. Further understanding of the reasons for spatial heterogeneities in black-white differences in nationally representative cohorts may provide important clues regarding the drivers of these differences.

Relationships Between the Great Recession and Widening Maternal and Child Health Disparities: Findings From Washington and Florida

The purpose of this study was to explore relationships between the Great Recession in the United States and maternal and child health (MCH) disparities in prenatal care, birth weight, gestational age, and infant mortality. Using annual, 2005-2011 individual-level Washington (WA) and Florida (FL) birth certificate data, we analyzed MCH outcome rates and disparities among subpopulation component groups (e.g., subpopulation 'maternal ethnicity' divided into component groups such as non-Hispanic White, non-Hispanic Black). We focused on whether disparities widened during two recession periods: Period 1 (December 2007-June 2009-official dates of Great Recession) and Period 2 (January 2010-December 2011) and compared these to a Baseline Period 0 (January 2005-March 2007). Subpopulations (n=14) and component groups (n=47) were identified a priori. Results indicate that disparities widened on at least one MCH outcome for 22 component groups in WA during Period 1 and 37 component groups during Period 2, compared to baseline. In FL, disparities widened for 25 component groups during Period 1 and 31 during Period 2. Disparities increased in both periods on the same outcomes for 11 WA component groups and 7 component groups in FL. Disparity increases tended to cluster among those with young age, low education, and among members of minority race/ethnicity groups-particularly Black mothers. Findings support hypothesized relationships between expected increases in need during the Great Recession, and worsening MCH outcomes and disparities. Compared to baseline, there were more disparity increases in Period 2 than 1. Additional research regarding specific factors influencing changes in disparities are needed.