Association of community-level inequities and premature mortality: Chicago, 2011-2015

Evaluating Socioeconomic, Racial, and Ethnic Disparities in Survival Among Patients Undergoing Allogeneic Hematopoietic Stem Cell Transplants

This study was undertaken to monitor potential disparities in survival after allogeneic hematopoietic stem cell transplantation (HSCT) with the aim of optimizing access and outcomes for minority and low-income patients. We analyzed 463 patients transplanted over a 72-month study period with a median 19-month follow-up, focused on differences by individual patient race/ethnicity and patients' household income derived from geocoded addresses at the census block group level. Patient sociodemographic and clinical characteristics were abstracted from electronic health records and our HSCT registry, including disease category and status, donor age, transplant type, and conditioning. Approximately, 15% of HSCT patients were non-Hispanic Black or Hispanic with a similar proportion from block groups below the median metropolitan Index of Concentration at the Extremes income score. The overall survival probability was 61.8% at 36 months. Non-Hispanic white (63.6%) and especially Hispanic patients (49.2%) had lower survival probabilities at 36 months than non-Hispanic Black patients (75.6%, p = 0.04). There were no other patient characteristics significantly associated with survival at the p < 0.01 level. The lack of significant differences likely reflects the careful selection of patients for transplants. However, the proportion of minority and low-income patients relative to expected disease prevalence in our area population raises important considerations about which patients successfully make it to transplant. We conclude with recommendations to increase the diversity of patients who receive HSCT by reviewing potential barriers in the transplant referral and selection process and advocating for needed psychosocial and community resources.

Effects of residential socioeconomic polarization on high blood pressure among nursing home residents

OBJECTIVE

Neighborhood concentration of racial, income, education, and housing deprivation is known to be associated with higher rates of hypertension. The objective of this study is to examine the association between tract-level spatial social polarization and hypertension in a cohort with relatively equal access to health care, a Veterans Affairs nursing home.

METHODS

41,973 long-term care residents aged ≥65 years were matched with tract-level Indices of Concentration at the Extremes across four socioeconomic domains. We modeled high blood pressure against these indices controlling for individual-level cardiovascular confounders.

RESULTS

We found participants who had resided in the most disadvantaged quintile had a 1.10 (95% 1.01, 1.19) relative risk of high blood pressure compared to those in the other quintiles for the joint measuring race/ethnicity and income domain.

CONCLUSIONS

We achieved our objective by demonstrating that concentrated deprivation is associated with worse cardiovascular outcomes even in a population with equal access to care. Measures that jointly consider economic and racial/ethnic polarization elucidate larger disparities than single domain measures.

Cause-Specific Mortality and Racial Differentials in Life Expectancy, Chicago 2018-2019

BACKGROUND

In Chicago in 2018, the average life expectancy (ALE) for NH Blacks was 71.5 years, 9.1 fewer years than for NH Whites (80.6 years). Inasmuch as some causes of death are increasingly recognized products of structural racism, in urban areas, such causes may have potential for reducing racial inequities through public health intervention. Our purpose is to allocate racial inequities in ALE in Chicago to differentials in cause-specific mortality.

METHODS

Using multiple decrement processes and decomposition analysis, we examine cause-specific mortality in Chicago to determine the causes of death that contribute to the gap in life expectancy between NH Blacks and NH Whites.

RESULTS

Among females, the racial difference in ALE was 8.21 years; for males, it was 10.53 years. We find that cancer and heart disease mortality account for 3.03 years or 36% of the racial gap in average life expectancy among females. Differences in homicide and heart disease mortality rates comprised over 45% of the disparity among males.

CONCLUSIONS

Strategies for improving inequities in life expectancy should account for differences between males and females in cause-specific mortality rates. In urban areas with high levels of segregation, reducing inequities in ALE may be possible by dramatically reducing mortality rates from some causes.

CONTRIBUTION

This paper illustrates the state of inequities in ALE between NH Blacks and NH Whites in Chicago for the period just prior to the onset of the COVID-19 pandemic, using a well-established method of decomposing mortality differentials for sub-populations.

Community Teens' COVID-19 Experience: Implications for Engagement Moving Forward

Data collected from pediatric primary care settings during the pandemic suggest an increase in internalizing symptoms and disparities in care based upon minoritized identity status(es). To inform care moving forward, the current study characterized the pandemic and related technology usage experiences of teenaged pediatric patients from communities with high hardship indexes. As part of a larger mixed-methods study, 17 teens (Mean age = 15.99 ± .99) and 10 caregivers independently voiced experiences related to the pandemic during remote focus group and interview sessions. Thematic analyses were used to assess qualitative data; descriptive analyses were used to characterize qualitative data. Despite no direct queries about the pandemic, 41% of teens and 40% of caregivers described their lived experiences during the pandemic. Two subthemes emerged within the primary theme of COVID-19: (1) Wellness/Mental Health and (2) Smartphone Use and Utility. Although distress and negative effects were voiced, questionnaire data indicated normative psychosocial functioning for both teen self-report and caregiver proxy report. Informed by the voiced experiences of teens and their caregivers from communities with high hardship indexes, methods for better assessing and managing internalizing symptoms in teen patients are presented. A multi-modal and multi-informant approach that leverages technology to garner information about teens' experiences and deliver care may help improve the well-being of teens in communities systemically burdened with disparities.

Evaluation of Inequities in Cancer Treatment Delay or Discontinuation Following SARS-CoV-2 Infection

IMPORTANCE

There is a disproportionately greater burden of COVID-19 among Hispanic and non-Hispanic Black individuals, who also experience poorer cancer outcomes. Understanding individual-level and area-level factors contributing to inequities at the intersection of COVID-19 and cancer is critical.

OBJECTIVE

To evaluate associations of individual-level and area-level social determinants of health (SDOH) with delayed or discontinued cancer treatment following SARS-CoV-2 infection.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective, registry-based cohort study used data from 4768 patients receiving cancer care who had positive test results for SARS-CoV-2 and were enrolled in the American Society for Clinical Oncology COVID-19 Registry. Data were collected from April 1, 2020, to September 26, 2022.

EXPOSURES

Race and ethnicity, sex, age, and area-level SDOH based on zip codes of residence at the time of cancer diagnosis.

MAIN OUTCOMES AND MEASURES

Delayed (≥14 days) or discontinued cancer treatment (any cancer treatment, surgery, pharmacotherapy, or radiotherapy) and time (in days) to restart pharmacotherapy.

RESULTS

A total of 4768 patients (2756 women [57.8%]; 1558 [32.7%] aged ≥70 years at diagnosis) were included in the analysis. There were 630 Hispanic (13.2%), 196 non-Hispanic Asian American or Pacific Islander (4.1%), 568 non-Hispanic Black (11.9%), and 3173 non-Hispanic White individuals (66.5%). Compared with non-Hispanic White individuals, Hispanic and non-Hispanic Black individuals were more likely to experience a delay of at least 14 days or discontinuation of any treatment and drug-based treatment; only estimates for non-Hispanic Black individuals were statistically significant, with correction for multiple comparisons (risk ratios [RRs], 1.35 [95% CI, 1.22-1.49] and 1.37 [95% CI, 1.23-1.52], respectively). Area-level SDOH (eg, geography, proportion of residents without health insurance or with only a high school education, lower median household income) were associated with delayed or discontinued treatment. In multivariable Cox proportinal hazards regression models, estimates suggested that Hispanic (hazard ratio [HR], 0.87 [95% CI, 0.71-1.05]), non-Hispanic Asian American or Pacific Islander (HR, 0.79 [95% CI, 0.46-1.35]), and non-Hispanic Black individuals (HR, 0.81 [95% CI, 0.67-0.97]) experienced longer delays to restarting pharmacotherapy compared with non-Hispanic White individuals.

CONCLUSIONS AND RELEVANCE

The findings of this cohort study suggest that race and ethnicity and area-level SDOH were associated with delayed or discontinued cancer treatment and longer delays to the restart of drug-based therapies following SARS-CoV-2 infection. Such treatment delays could exacerbate persistent cancer survival inequities in the United States.

mHealth Uses and Opportunities for Teens from Communities with High Health Disparities: A Mixed-Methods Study

Despite widespread access to smartphones, teens from communities facing significant behavioral health disparities typically have low mobile health (mHealth) engagement. The purpose of this study was to characterize teen and caregiver perspectives about smartphone use and access, mHealth, and how mHealth could address teens' behavioral health needs during the pandemic and beyond. Remote recruitment and methodologies were used to engage 17 teens (M age = 15.9 ± 0.9) and 10 caregivers living in urban communities with significant socioeconomic and health disparities. Participants completed a focus group or interview session (based on preference) and self-report questionnaires (e.g., behavioral health history, pandemic impacts, technology use). Qualitative and quantitative data were analyzed using thematic and descriptive analyses, respectively. Both quantitative and qualitative data indicated relevant behavioral health concerns for teens and their families, impacts from the pandemic, and frequent smartphone use. Primary teen and caregiver themes included (1) health and wellness concerns, (2) barriers, (3) use of smartphones, (4) impacts of smartphones, and (5) opinions/suggestions for mHealth. This multi-method and multi-informant study highlighted the lived experiences of teens from marginalized communities and offered key insights to increase the acceptability and real-world engagement of mHealth tools. To address barriers to care for this population beyond the pandemic, clear messaging must be used for mHealth tools (e.g., data privacy, expectations of use). These findings testify to the importance of collaboration with teens and caregivers from communities facing large health disparities in future mHealth design, development, and deployment.

Digital Screening and Automated Resource Identification System to Address COVID-19-Related Behavioral Health Disparities: Feasibility Study

BACKGROUND

Digital mental health (DMH) tools use technology (eg, websites and mobile apps) to conveniently deliver mental health resources to users in real time, reducing access barriers. Underserved communities facing health care provider shortages and limited mental health resources may benefit from DMH tools, as these tools can help improve access to resources.

OBJECTIVE

This study described the development and feasibility evaluation of the Emotional Needs Evaluation and Resource Guide for You (ENERGY) System, a DMH tool to meet the mental health and resource needs of youth and their families developed in the context of the COVID-19 pandemic. The ENERGY System offers a brief assessment of resource needs; problem-solving capabilities; and symptoms of depression, anxiety, trauma, and alcohol and substance use followed by automated, personalized feedback based on the participant's responses.

METHODS

Individuals aged ≥15 years were recruited through community partners, community events, targeted electronic health record messages, and social media. Participants completed screening questions to establish eligibility, entered demographic information, and completed the ENERGY System assessment. Based on the participant's responses, the ENERGY System immediately delivered digital resources tailored to their identified areas of need (eg, relaxation). A subset of participants also voluntarily completed the following: COVID-19 Exposure and Family Impact Survey (CEFIS) or COVID-19 Exposure and Family Impact Survey Adolescent and Young Adult Version (CEFIS-AYA); resource needs assessment; and feedback on their experience using the ENERGY System. If resource needs (eg, housing and food insecurity) were endorsed, lists of local resources were provided.

RESULTS

A total of 212 individuals accessed the ENERGY System link, of which 96 (45.3%) completed the screening tool and 86 (40.6%) received resources. Participant responses on the mental health screening questions triggered on average 2.04 (SD 1.94) intervention domains. Behavioral Activation/Increasing Activities was the most frequently launched intervention domain (56%, 54/96), and domains related to alcohol or substance use were the least frequent (4%, 4/96). The most frequently requested support areas were finances (33%, 32/96), transportation (26%, 25/96), and food (24%, 23/96). The CEFIS and CEFIS-AYA indicated higher than average impacts from the pandemic (ie, average scores >2.5). Participants were satisfied with the ENERGY System overall (65%, 39/60) as well as the length of time it took to answer the questions (90%, 54/60), which they found easy to answer (87%, 52/60).

CONCLUSIONS

This study provided initial support for the feasibility of the ENERGY System, a DMH tool capable of screening for resource and mental health needs and providing automated, personalized, and free resources and techniques to meet the identified needs. Future studies should seek direct feedback from community members to further improve the ENERGY System and its dissemination to encourage use.

Diagnosis and treatment of vulnerable migrants: a retrospective study at a Doctors of the World clinic in Stockholm

Background

At Doctors of the World Medical Clinic in Stockholm (DWMCS), medical care is offered to migrants who live under particularly vulnerable conditions and who lack access to subsidized care. The demographic, diagnostic and therapeutic panorama of vulnerable migrants is unknown.

Methods

A quantitative, retrospective study mapping gender, age, diagnostic group, primary diagnosis, therapeutics, referrals, and session timing (whether the care session took place in summer -April to September, or winter - October to March) by reading all patients’ electronic journals at DWMCS between 2014-04-01 and 2017-12-31. Diagnostic groups were classified according to the classification system ICPC-2 which contains six diagnostic groups: symptoms/complaints, infections, neoplasms, injuries, congenital anomalies and other diagnoses. Primary diagnosis was defined as the diagnosis that was first in the diagnosis list for the visit. Difference in median age was calculated with the Mann-Whitney test (MW), and two-group analysis of nominal data was performed with Monte Carlo simulations (MC) and chi square test´s (X²).

Results

The study included 1323 patients: 838 women and 485 men. The median age for women 37 years (29-47) was slightly lower than for men, 40 years (31-47) MW (p = 0.002). The largest diagnostic group was symptoms / complaints. The five most common primary diagnoses were cough (4%), back symptom / complaint (4%), cystitis (3%), upper respiratory infection acute (3%) and abdominal pain epigastric (2%). The most common therapeutic (55%) was pharmaceutical. Referrals accounted for 12% of the therapeutics and 25% of the referrals were to an emergency room. Tests of significance indicated an uneven distribution of diagnostic groups MC (p = 0.003), infectious primary diagnoses MC (p = 0.0001) and referrals MC (p = 0.006) between men and women and an uneven seasonal distribution among the Other diagnoses MC (0.04) and ten most common drug treatments MC (p=0.002).

Conclusions

The demographic, diagnostic and therapeutic panorama of vulnerable migrants at DWMCS was elucidated. Vulnerable migrants have differences in morbidity depending on gender and season, differences in therapeutics depending on gender and differences among their most common drug treatments depending on season. This knowledge is important when addressing the health problems of vulnerable migrants.

Racialized economic segregation and health outcomes: A systematic review of studies that use the Index of Concentration at the Extremes for race, income, and their interaction

Extensive research shows that residential segregation has severe health consequences for racial and ethnic minorities. Most research to date has operationalized segregation in terms of either poverty or race/ethnicity rather than a synergy of these factors. A novel version of the Index of Concentration at the Extremes (ICERace-Income) specifically assesses racialized economic segregation in terms of spatial concentrations of racial and economic privilege (e.g., wealthy white people) versus disadvantage (e.g., poor Black people) within a given area. This multidimensional measure advances a more comprehensive understanding of residential segregation and its consequences for racial and ethnic minorities. The aim of this paper is to critically review the evidence on the association between ICERace-Income and health outcomes. We implemented the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to conduct a rigorous search of academic databases for papers linking ICERace-Income with health. Twenty articles were included in the review. Studies focused on the association of ICERace-Income with adverse birth outcomes, cancer, premature and all-cause mortality, and communicable diseases. Most of the evidence indicates a strong association between ICERace-Income and each health outcome, underscoring income as a key mechanism by which segregation produces health inequality along racial and ethnic lines. Two of the reviewed studies examined racial disparities in comorbidities and health care access as potential explanatory factors underlying this relationship. We discuss our findings in the context of the extant literature on segregation and health and propose new directions for future research and applications of the ICERace-Income measure.

Socioeconomic and Racial Segregation and COVID-19: Concentrated Disadvantage and Black Concentration in Association with COVID-19 Deaths in the USA

INTRODUCTION

This study's objective was to examine the association of the percentage of county population residing in concentrated disadvantage and Black-concentrated census tracts with county-level confirmed COVID-19 deaths in the USA, concentrated disadvantage and Black concentration at census tract-level measure socioeconomic segregation and racial segregation, respectively.

METHODS

We performed secondary data analysis using tract (N = 73,056) and county (N = 3142) level data from the US Census Bureau and other sources for the USA. Confirmed COVID-19 deaths per 100,000 population was our outcome measure. We performed mixed-effect negative binomial regression to examine the association of county population's percentage residing in concentrated disadvantage and Black-concentrated tracts with COVID-19 deaths while controlling for several other characteristics.

RESULTS

For every 10% increase in the percentage of county population residing in concentrated disadvantage and Black-concentrated tracts, the rate for confirmed COVID-19 deaths per 100,000 population increases by a factor of 1.14 (mortality rate ratio [MMR] = 1.14; 95% confidence interval [CI]:1.11, 1.18) and 1.11 (MMR = 1.11; 95% CI:1.08, 1.14), respectively. These relations stayed significant in all models in further sensitivity analyses. Moreover, a joint increase in the percentage of county population residing in racial and socioeconomic segregation was associated with a much greater increase in COVID-19 deaths.

CONCLUSIONS

It appears that people living in socioeconomically and racially segregated neighborhoods may be disproportionately impacted by COVID-19 deaths. Future multilevel and longitudinal studies with data at both individual and aggregated tract level can help isolate the potential impacts of the individual-level characteristics and neighborhood-level socioeconomic and racial segregation with more precision and confidence.

Parkinson's Disease in African Americans: A Review of the Current Literature

Parkinson’s disease (PD) is the second most common neurodegenerative disease, though evidence suggests that this disorder does not affect all racial groups similarly. Research in African Americans, in particular, has been conflicting. Some studies have found similar prevalence rates in African Americans and whites whereas other studies have found much lower prevalence and incidence rates in African Americans. A few studies identify potential factors underlying these discrepancies, including biologic differences as well as disparities in healthcare access. However, African Americans remain underrepresented in research studies, which make understanding the underlying reasons for these differences difficult. The purpose of this paper is to summarize existing research in African Americans with PD, highlight some of the reasons why differences exist in diagnostic rates of PD in this population, and briefly discuss interventions that may need to be made in order to ensure adequate care is provided to these patients.

Association of Social and Economic Inequality With Coronavirus Disease 2019 Incidence and Mortality Across US Counties

IMPORTANCE

It is now established that across the United States, minoritized populations have borne a disproportionate burden from coronavirus disease 2019 (COVID-19). However, little is known about the interaction among a county's racial/ethnic composition, its level of income inequality, political factors, and COVID-19 outcomes in the population.

OBJECTIVE

To quantify the association of economic inequality, racial/ethnic composition, political factors, and state health care policy with the incidence and mortality burden associated with COVID-19.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used data from the 3142 counties in the 50 US states and for Washington, DC. Data on the first 200 days of the COVID-19 pandemic, from the first confirmed US case on January 22 to August 8, 2020, were gathered from the Centers for Disease Control and Prevention and USAFacts.org, the US Census Bureau, the American Community Survey, GitHub, the Kaiser Family Foundation, the Council of State Governments, and the National Governors Association.

EXPOSURES

Racial/ethnic composition was determined as percentage of the population that is Black or Hispanic; income inequality, using the Gini index; politics, political affiliation and sex of the state governor, gubernatorial term limits, and percentage of the county's population that voted Republican in 2016; and state health care policy, participation in the expansion of Medicaid under the Affordable Care Act. Six additional covariates were assessed.

MAIN OUTCOMES AND MEASURES

Cumulative COVID-19 incidence and mortality rates for US counties during the first 200 days of the pandemic. Main measures include percentage Black and Hispanic population composition, income inequality, and a set of additional covariates.

RESULTS

This study included 3141 of 3142 US counties. The mean Black population was 9.365% (range, 0-86.593%); the mean Hispanic population was 9.754% (range, 0.648%-96.353%); the mean Gini ratio was 44.538 (range, 25.670-66.470); the proportion of counties within states that implemented Medicaid expansion was 0.577 (range, 0-1); the mean number of confirmed COVID-19 cases per 100 000 population was 1093.882 (range, 0-14 019.852); and the mean number of COVID-19-related deaths per 100 000 population was 26.173 (range, 0-413.858). A 1.0% increase in a county's income inequality corresponded to an adjusted risk ratio (RR) of 1.020 (95% CI, 1.012-1.027) for COVID-19 incidence and adjusted RR of 1.030 (95% CI, 1.012-1.047) for COVID-19 mortality. Inequality compounded the association of racial/ethnic composition through interaction, with higher income inequality raising the intercepts of the incidence curve RR by a factor of 1.041 (95% CI, 1.031-1.051) and that of the mortality curve RR by a factor of 1.068 (95% CI, 1.042-1.094) but slightly lowering their curvatures, especially for Hispanic composition. When state-level specificities were controlled, none of the state political factors were associated with COVID-19 incidence or mortality. However, a county in a state with Medicaid expansion implemented would see the incidence rate RR decreased by a multiplicative factor of 0.678 (95% CI, 0.501-0.918).

CONCLUSIONS AND RELEVANCE

This county-level ecological analysis suggests that COVID-19 surveillance systems should account for county-level income inequality to better understand the social patterning of COVID-19 incidence and mortality. High levels of income inequality may harm population health irrespective of racial/ethnic composition.

Structural racism, socio-economic marginalization, and infant mortality

OBJECTIVES

We examine associations between infant mortality rates (IMRs) and measures of structural racism and socio-economic marginalization in Chicago, Illinois. Our purpose was to determine whether the Index of Concentration at the Extremes (ICE) was significantly related to community-level IMRs.

STUDY DESIGN

We use a cross-sectional ecological public health design to examine community-level factors related to IMRs in Chicago neighborhoods.

METHODS

We use data from the Chicago Department of Public Health and the American Community Survey to examine IMR inequities during the period 2012-2016. Calculations of the ICE for race and income were undertaken. In addition, we calculated racialized socio-economic status, which is the concentration of affluent Whites relative to poor Blacks in a community area. We present these ICE measures, as well as hardship, percent of births with inadequate prenatal care (PNC), and the percent of single-parent households as quintiles so that we can compare neighborhoods with the most disadvantage with neighborhoods with the least. Negative binomial regression was used to determine whether the ICE measures were independently related to community IMRs, net of hardship scores, PNC, and single-parent households.

RESULTS

Spearman correlation results indicate significant associations in Chicago communities between measures of racial segregation and economic marginalization and IMRs. Community areas with the lowest ICE_Race scores (those with the largest concentrations of Black residents, compared with White) had IMRs that were 3.63 times higher than those communities with the largest concentrations of White residents. Most associations between community IMRS and measures of structural racism and socioeconomic marginalization are accounted for in fully adjusted negative binomial regression models. Only ICERace remained significantly related to IMRs.

CONCLUSIONS

We show that structural racism as represented by the ICE is independently related to IMRs in Chicago; community areas with the largest concentrations of Blacks residents compared with Whites are those with the highest IMRs. This relationship persists even after controlling for socio-economic marginalization, hardship, household composition/family support, and healthcare access. Interventions to improve birth outcomes must address structural determinants of health inequities.

Racial Disparities in Associations between Neighborhood Demographic Polarization and Birth Weight

Neighborhood demographic polarization, or the extent to which a privileged population group outnumbers a deprived group, can affect health by influencing social dynamics. While using birth records from 2001 to 2013 in Massachusetts (n = 629,675), we estimated the effect of two demographic indices, racial residential polarization (RRP) and economic residential polarization (ERP), on birth weight outcomes, which are established predictors of the newborn's future morbidity and mortality risk. Higher RRP and ERP was each associated with higher continuous birth weight and lower odds for low birth weight and small for gestational age, with evidence for effect modification by maternal race. On average, per interquartile range increase in RRP, the birth weight was 10.0 g (95% confidence interval: 8.0, 12.0) higher among babies born to white mothers versus 6.9 g (95% CI: 4.8, 9.0) higher among those born to black mothers. For ERP, it was 18.6 g (95% CI: 15.7, 21.5) higher among those that were born to white mothers versus 1.8 g (95% CI: -4.2, 7.8) higher among those born to black mothers. Racial and economic polarization towards more privileged groups was associated with healthier birth weight outcomes, with greater estimated effects in babies that were born to white mothers than those born to black mothers.

Opioid-related overdose deaths by race and neighborhood economic hardship in Chicago

Compared to national findings, Chicago has both a higher rate of opioid-related overdose death and a markedly different distribution by demographics. The Chicago Department of Public Health analyzed fatal overdoses by level of neighborhood economic hardship. The highest rate of opioid-related deaths occurred in neighborhoods with high economic hardship (36.9 per 100,000 population) compared to medium- (20.5) and low- (12.3) hardship neighborhoods. However, these patterns were not consistent across racial/Hispanic ethnicity subgroups. These data support the need to consider the role of racism and other structural, social, and economic factors when designing interventions to reduce opioid-related overdose deaths.