UNASSIGNED: In this study, we examined associations between county-level measures of structural racism and county-level cancer incidence and mortality rates between race groups while accounting for factors associated with cancer rates and county-level measures of environmental burden.
UNASSIGNED: To explore this relationship, we conducted multiple linear regression analyses. Data for these analyses came from an index of county-level structural racism and publicly available data on 2015 to 2019 age-adjusted cancer rates from the US Cancer Statistics Data Visualization Tool, 2019 County Health Rankings and Roadmaps, the Environmental Protection Agency\'s 2006 to 2010 Environmental Quality Index, and 2015 to 2019 estimates from the US Census American Community Survey.
UNASSIGNED: County-level structural racism was associated with higher county cancer incidence rates among Black (adjusted incidence rate: 17.4, 95% confidence interval [95% CI]: 9.3, 25.5) and Asian/Pacific Islander populations (adjusted incidence rate: 9.3, 95% CI: 1.8, 16.9) and higher mortality rates for American Indian/Alaskan Native (adjusted mortality rate [AMR]: 17.4, 95% CI: 4.2, 30.6), Black (AMR: 11.9, 95% CI: 8.9, 14.8), and Asian/Pacific Islander (AMR: 4.7, 95% CI: 1.3, 8.1) populations than White populations.
UNASSIGNED: Our findings highlight the detrimental impact of structural racism on cancer outcomes among minoritized populations. Strategies aiming to mitigate cancer disparities must embed processes to recognize and address systems, policies, laws, and norms that create and reproduce patterns of discrimination.

UNASSIGNED: The incidence of sudden unexpected infant death (SUID) in the United States has persisted at roughly the same level since the mid-2000s, despite intensive prevention efforts around safe sleep. Disparities in outcomes across racial and socioeconomic lines also persist. These disparities are reflected in the spatial distribution of cases across neighborhoods. Strategies for prevention should be targeted precisely in space and time to further reduce SUID and correct disparities.
UNASSIGNED: We sought to aid neighborhood-level prevention efforts by characterizing communities where SUID occurred in Cook County, IL, from 2015 to 2019 and predicting where it would occur in 2021-2025 using a semiautomated, reproducible workflow based on open-source software and data.
UNASSIGNED: This cross-sectional retrospective study queried geocoded medical examiner data from 2015-2019 to identify SUID cases in Cook County, IL, and aggregated them to \"communities\" as the unit of analysis. We compared demographic factors in communities affected by SUID versus those unaffected using Wilcoxon rank sum statistical testing. We used social vulnerability indicators from 2014 to train a negative binomial prediction model for SUID case counts in each given community for 2015-2019. We applied indicators from 2020 to the trained model to make predictions for 2021-2025.
UNASSIGNED: Validation of our query of medical examiner data produced 325 finalized cases with a sensitivity of 95% (95% CI 93%-97%) and a specificity of 98% (95% CI 94%-100%). Case counts at the community level ranged from a minimum of 0 to a maximum of 17. A map of SUID case counts showed clusters of communities in the south and west regions of the county. All communities with the highest case counts were located within Chicago city limits. Communities affected by SUID exhibited lower median proportions of non-Hispanic White residents at 17% versus 60% (P<.001) and higher median proportions of non-Hispanic Black residents at 32% versus 3% (P<.001). Our predictive model showed moderate accuracy when assessed on the training data (Nagelkerke R2=70.2% and RMSE=17.49). It predicted Austin (17 cases), Englewood (14 cases), Auburn Gresham (12 cases), Chicago Lawn (12 cases), and South Shore (11 cases) would have the largest case counts between 2021 and 2025.
UNASSIGNED: Sharp racial and socioeconomic disparities in SUID incidence persisted within Cook County from 2015 to 2019. Our predictive model and maps identify precise regions within the county for local health departments to target for intervention. Other jurisdictions can adapt our coding workflows and data sources to predict which of their own communities will be most affected by SUID.

OBJECTIVE: Research has documented that adolescent sleep is impacted by various stressors, including interpersonal experiences and structural disadvantage. This study extends existing knowledge by empirically examining interconnected individual experiences of structural inequity and assessing its association with subjective and objective sleep outcomes.
METHODS: We utilized data from the Adolescent Brain and Cognitive Development Study to identify seven conceptual domains of structural inequity: perceived discrimination, low school inclusivity, neighborhood safety, unmet medical needs, legal problems, material hardship, and housing insecurity. We operationalized experiences of structural inequity as latent classes, a cumulative exposure, and each domain separately. Sleep disturbances were measured using the Sleep Disturbance Scale, and sleep duration was assessed using Fitbits. Mixed effects linear regression estimated the association between our measures of structural inequity, longitudinal sleep disturbances, and cross-sectional sleep duration.
RESULTS: Latent class analysis revealed common exposure profiles (low risk, interpersonal, and systemic) of experiences of structural inequity across our sample. In longitudinal models, structural inequity was associated with higher Sleep Disturbance Scale scores, whether measured as latent classes, a cumulative exposure, or individual domains. Individuals with interpersonal exposures, those with at least one exposure, and those with legal problems, material hardship, and housing insecurity had lower mean sleep duration.
CONCLUSIONS: Results are consistent with literature that frames structural inequity as a lifelong determinant of sleep disturbance and duration. Adolescence represents a crucial time for interventions aimed at improving sleep and redressing inequities throughout the life course; our work can inform the development of policies and interventions toward this end.

OBJECTIVE: To investigate racial inequities in the use of therapeutic hypothermia (TH) and outcomes in infants with hypoxic-ischemic encephalopathy (HIE).
METHODS: We queried an administrative birth cohort of mother-baby pairs in California from 2010 through 2019 using International Classification of Diseases codes to evaluate the association between race and ethnicity and the application of TH in infants with HIE. We identified 4779 infants with HIE. Log-linear regression was used to calculate risk ratios (RR) for TH, adjusting for hospital transfer, rural location, gestational age between 35 and 37 weeks, and HIE severity. Risk of adverse infant outcome was calculated by race and ethnicity and stratified by TH.
RESULTS: From our identified cohort, 1338 (28.0%) neonates underwent TH. White infants were used as the reference sample, and 410 (28.4%) received TH. Black infants were significantly less likely to receive TH with 74 (20.0%) with an adjusted risk ratio (aRR) of 0.7 (95% CI 0.5-0.9). Black infants with any HIE who did not receive TH were more likely to have a hospital readmission (aRR 1.36, 95% CI 1.10-1.68) and a tracheostomy (aRR 3.07, 95% CI 1.19-7.97). Black infants with moderate/severe HIE who did not receive TH were more likely to have cerebral palsy (aRR 2.72, 95% CI 1.07-6.91).
CONCLUSIONS: In this study cohort, Black infants with HIE were significantly less likely to receive TH. Black infants also had significantly increased risk of some adverse outcomes of HIE. Possible reasons for this inequity include systemic barriers to care and systemic bias.

Menstrual cycle characteristics are largely considered unmodifiable reproductive factors, a framing that prevents exploration of the ways structural factors interfere with menstrual health. Given the role of structural factors like healthy food and healthcare access on reproductive health and the grave need for structural interventions to known reproductive health disparities that disproportionately target cisgender women racialized as Black, it is imperative that science begin to examine how structural factors influence menstrual health. To explore such research, we employ critical race theory and intersectionality to illustrate what a structural intervention to improve menstrual cycle health could look like. Centering those with the greatest need, persons racialized as Black and/or LatinX living in food and healthcare deserts in Northern Manhattan, our illustrative sample includes four groups of persons who menstruate (e.g., cisgender girls and women) that are pre-menarche, pre-parous, postpartum, or perimenopausal. We describe a hypothetical, multilevel clustered-randomized control trial (cRCT) that provides psychoeducation on racism-related trauma and free delivered groceries to both treatment and control groups, while randomizing 30 clusters of housing associations to receive either sexual health clinics at their housing association or free vouchers for healthcare. We embed mixed methods (diaries, interviews, surveys, mobile apps, observation) into the design to evaluate the effectiveness of the 1-year intervention, in addition to determining the impact on participants through their perspectives. Through this illustration, we provide a novel example of how structural interventions can apply mixed methods to evaluate effectiveness while delivering services to populations impacted by multiple structural factors. We demonstrate how qualitative and quantitative approaches can be paired in clustered RCTs and how a living logic model can empirically incorporate the population perspective into more effective interventions. Lastly, we reveal how sensitive menstrual health is to structural factors and how upstream improvements will trickle down to potentially reduce health disparities in reproductive health.

BACKGROUND: Improving access to healthcare for ethnic minorities is a public health priority in many countries, yet little is known about how to incorporate information on race, ethnicity, and related social determinants of health into large international studies. Most studies of differences in treatments and outcomes of COVID-19 associated with race and ethnicity are from single cities or countries.
METHODS: We present the breadth of race and ethnicity reported for patients in the COVID-19 Critical Care Consortium, an international observational cohort study from 380 sites across 32 countries. Patients from the United States, Australia, and South Africa were the focus of an analysis of treatments and in-hospital mortality stratified by race and ethnicity. Inclusion criteria were admission to intensive care for acute COVID-19 between January 14th, 2020, and February 15, 2022. Measurements included demographics, comorbidities, disease severity scores, treatments for organ failure, and in-hospital mortality.
RESULTS: Seven thousand three hundred ninety-four adults met the inclusion criteria. There was a wide variety of race and ethnicity designations. In the US, American Indian or Alaska Natives frequently received dialysis and mechanical ventilation and had the highest mortality. In Australia, organ failure scores were highest for Aboriginal/First Nations persons. The South Africa cohort ethnicities were predominantly Black African (50%) and Coloured* (28%). All patients in the South Africa cohort required mechanical ventilation. Mortality was highest for South Africa (68%), lowest for Australia (15%), and 30% in the US.
CONCLUSIONS: Disease severity was higher for Indigenous ethnicity groups in the US and Australia than for other ethnicities. Race and ethnicity groups with longstanding healthcare disparities were found to have high acuity from COVID-19 and high mortality. Because there is no global system of race and ethnicity classification, researchers designing case report forms for international studies should consider including related information, such as socioeconomic status or migration background. *Note: \"Coloured\" is an official, contemporary government census category of South Africa and is a term of self-identification of race and ethnicity of many citizens of South Africa.

Racial inequities in life expectancy, driven by structural racism, have been documented at the state and county levels; however, less information is available at the city level where local policy change generally happens. Furthermore, an assessment of life expectancy during the decade preceding COVID-19 provides a point of comparison for life expectancy estimates and trends post COVID-19 as cities recover.
Using National Vital Statistics System mortality data and American Community Survey population estimates, we calculated the average annual city-level life expectancies for the non-Hispanic Black (Black), non-Hispanic White (White), and total populations. We then calculated the absolute difference between the Black and White life expectancies for each of the 30 cities and the U.S. We analyzed trends over four time periods (2008-2010, 2011-2013, 2014-2016, and 2017-2019).
In 2017-2019, life expectancies ranged from 72.75 years in Detroit to 83.15 years in San Francisco (compared to 78.29 years for the U.S.). Black life expectancy ranged from 69.94 years in Houston to 79.04 years in New York, while White life expectancy ranged from 75.18 years in Jacksonville to 86.42 years in Washington, DC. Between 2008-2010 and 2017-2019, 17 of the biggest cities experienced a statistically significant improvement in life expectancy, while 9 cities experienced a significant decrease. Black life expectancy increased significantly in 14 cities and the U.S. but decreased significantly in 4 cities. White life expectancy increased significantly in 17 cities and the U.S. but decreased in 8 cities. In 2017-2019, the U.S. and all but one of the big cities had a significantly longer life expectancy for the White population compared to the Black population. There was more than a 13-year difference between Black and White life expectancies in Washington, DC (compared to 4.18 years at the national level). From 2008-2010 to 2017-2019, the racial gap decreased significantly for the U.S. and eight cities, while it increased in seven cities.
Urban stakeholders and equity advocates need data on mortality inequities that are aligned with city jurisdictions to help guide the allocation of resources and implementation of interventions.

OBJECTIVE: To describe relationships between parental incarceration and child health and flourishing-a measure of curiosity, resilience, and self-regulation-and to identify government programs that moderate this relationship.
METHODS: Using the National Survey of Children\'s Health data from 2016 through 2019 for children 6-17 years old, we estimated associations with logistic regression between parental incarceration and overall health and flourishing, adjusting for child, caregiver, and household factors. We secondarily examined physical health (asthma, headaches), mental health (attention deficit disorder/attention deficit hyperactivity disorder, depression), developmental needs (learning disability, special educational plan use), and educational (missing ≥11 school days, repeated grade) outcomes. We performed interaction analyses to determine whether government program participation (eg, free/reduced lunch, cash assistance) moderated relationships between parental incarceration and child outcomes.
RESULTS: Children with parental incarceration accounted for 9.3% of the sample (weighted n = 4 400 000). Black, American Indian/Alaska Native, and multiracial children disproportionately experienced parental incarceration. Parental incarceration was associated with worse health (aOR, 1.31; 95% CI, 1.11-1.55) and higher odds of not flourishing (aOR, 1.66; 95% CI, 1.46-1.89). Physical health, mental health, developmental issues, and educational needs were also associated with parental incarceration. Participation in free and reduced lunch moderated the relationships between parental incarceration and general health and flourishing, and cash assistance moderated the association between parental incarceration and flourishing. For each, parental incarceration had an attenuated association with health among people who participated in government programs.
CONCLUSIONS: Parental incarceration is disproportionately experienced by Black and Indigenous children and associated with worse child health and well-being. Government support program participation may mitigate negative associations between parental incarceration and child outcomes.

BACKGROUND: The Multiracial population, defined as having parents who are of two or more racial groups, increased from 2.9% of the United States population in 2010 to 10.2% in 2020. Existing research focused on monoracial populations shows that racial disparities and discrimination affect health. This study explores how emerging adults ages 18-29, who identify as Multiracial, describe the impact of identity on their health and experiences seeking health care in the United States.
METHODS: Semi-structured interviews were conducted with 21 participants in May 2021. Interview guide categories were the following: health and wellbeing, racial/ethnic identification, childhood upbringing, family influence, peer engagement, discrimination, forming resilience, language, and demographics. A thematic framework analysis was utilized.
RESULTS: Overarching themes were as follows: mental health and Multiracial identity-related stress, childhood experiences, healthcare experiences, influences on seeking or not seeking care, and the impact of identity on physical health. Our findings suggest that Multiracial emerging adults perceive their identity to influence mental health more than physical health.
CONCLUSIONS: Multiracial emerging adults face challenges with healthcare that are unique (e.g., discrimination based on identity defined or perceived by others) and others that are similar to their monoracial counterparts (e.g., structural racism, access to care). This study illustrates how structural factors trickle down to influence care sought and accessibility via socioeconomic status, insurance, childhood experiences, and racial and cultural beliefs about healthcare. Increased awareness and identification of Multiracial individuals and diversity in the workforce may help the US healthcare system better serve Multiracial emerging adults.

Our goal was to estimate differences in perinatal outcomes by racial differences in political representation, a measure of structural racism.
We gathered data on the racial composition of county-level elected officials for all counties in Georgia (n = 159) in 2022. We subtracted the percent of non-White elected officials from the percent of non-White residents to calculate the \"representation difference,\" with greater positive values indicating a larger disparity. We linked this to data from 2020-2021 birth certificates (n = 238,795) on outcomes (preterm birth, <37 weeks, low birthweight birth <2500 g, birthweight, hypertensive disorders of pregnancy, cesarean delivery). We fit log binomial and linear models with generalized estimating equations, stratified by individual race/ethnicity and including individual and county covariates.
Median representation difference was 17.5% points (interquartile range: 17.2). A 25-percentile point increase in representation difference was associated with a greater risk of hypertensive disorders of pregnancy [White: adjusted risk ratio (RR): 1.12, 95% confidence interval (CI): (1.05, 1.2), Black: 1.06, 95% CI: (0.95, 1.17), other: 1.14, 95% CI: (1.0, 1.3), Hispanic: 1.19, 95% CI: (1.07, 1.32)] and lower mean birthweight for Black birthing people [adjusted beta -15.3, 95% CI: (-25.5, -7.4)].
Parity in political representation may be associated with healthier environments.