Racial Categories Research Articles

Cognitive Difficulty in Middle Eastern and North African Adults Living in the United States Compared With Other Racial and Ethnic Categories, 2017-2021.

Objectives. To estimate the odds of having cognitive difficulties among Middle Eastern and North African (MENA) American adults and compare these odds with those of White, Black, Hispanic/Latino, Asian, American Indian or Alaska Native (AI/AN), and Native Hawaiian/Other Pacific Islander adults nationally and in the 4 states with the largest MENA populations (California, New York, Michigan, and Texas) after adjusting for sociodemographic factors. Methods. We analyzed 2017-2021 American Community Survey data (aged ≥ 45 years; n = 7 284 988), comparing presence of cognitive difficulties by race/ethnicity. Results. MENA adults had greater odds of reporting cognitive difficulties than did White (odds ratio [OR] = 1.49; 95% confidence interval [CI] = 1.42, 1.56), Black (OR = 1.20; 95% CI = 1.14, 1.26), Hispanic (OR = 1.46; 95% CI = 1.39, 1.53), Asian (OR = 1.31; 95% CI = 1.25, 1.38), and AI/AN (OR = 1.07; 95% CI = 1.01, 1.14) adults. In all 4 states, odds of having cognitive difficulties were higher among MENA than Asian adults. Other racial/ethnic comparisons differed by state. Conclusions. A separate checkbox for MENA Americans approved by the Office of Management and Budget is important so health outcomes can be studied in more detail and funds can be allocated for research and resources at state and national levels. (Am J Public Health. 2024;114(11):1265-1274. https://doi.org/10.2105/AJPH.2024.307803).

The Interaction of Race and Pregnancy Intentions on Breastfeeding Initiation Rates and Duration in the United States.

Background: Unintended pregnancy increases adverse perinatal health outcomes. Limited studies exist on the influence of pregnancy intention on breastfeeding. This study examines the interaction of Race and couples' pregnancy intention on breastfeeding initiation and duration. Methods: Using the National Survey of Family Growth (2017-2019), we categorized breastfeeding into three categories (never breastfed, breastfed for 6 months or less, and breastfed for more than 6 months). Multinomial logistic regression and probability marginal effects were estimated across racial categories (Hispanics, non-Hispanic [NH] White, Black, and NH-others or multiracial). Results: The probability (Pr.) of never breastfeeding was the greatest among NH-Black women for all pregnancy intentions-both intended (Pr.: 0.34), mother-only (Pr.: 0.27), father-only (Pr.: 0.45), ambivalent (Pr.: 0.55), and neither intended (Pr.: 0.37). The probability of breastfeeding for 6 months or less is highest for Hispanics for both intended (Pr.: 0.41), NH-White for mother-only intended (Pr.: 0.49), Hispanics for father-only intended (Pr.: 0.56), ambivalent pregnancy intentions (Pr.: 0.60), and NH-others or multiracial for neither intended pregnancies (Pr.: 0.48). The probability of breastfeeding for more than 6 months is highest for NH-others or multiracial for both intended (Pr.: 0.50), ambivalent (Pr.: 0.49), and neither intended (Pr.: 0.36), while highest for NH-Black for mother-only intended (Pr.: 0.43). Conclusions: Our study demonstrates the interaction of Race and couples' pregnancy intention on breastfeeding initiation and duration. Owing to the high volume of unintended pregnancies in the United States, the current study might help maternal and child healthcare providers understand the interaction between race and pregnancy intentions on breastfeeding initiation and duration in the United States.

The International and the Local Worker: Understanding Multi-layered Processes of Racialisation in International Development Organisations

AbstractThis article seeks to examine how institutional hierarchies relate to processes of racialisation in development organisations that are multiracial. Complementing and building on existing literature focussed on race and development it shows how processes of racialisation help to produce and legitimate distinctions between local and international development professionals. It argues these divides cannot always be neatly mapped onto phenotype but are related to processes of racialisation tied to knowledge and class and this, in turn, helps to produce inequalities—power imbalances, pay differences and differential access to organisational benefits—between development workers. Therefore, while forms of racism and their material impacts shape the experiences of international staff of colour, there is another layer of racialisation at play that cannot be explained through existing racial categories but that draws on colonial ideas of epistemic superiority to create specific forms of racialisation within development organisations.

Prevalence of Glaucoma Among US Adults in 2022

Glaucoma is the leading cause of irreversible blindness worldwide and, in the US, disproportionately affects people from racial and ethnic minority groups. Glaucoma prevalence has not been estimated for the US in more than a decade, and state- and county-level estimates are not available. To estimate glaucoma and vision-affecting glaucoma prevalence by demographic factors and US state and county for the Centers for Disease Control and Prevention's Vision and Eye Health Surveillance System (VEHSS). This meta-analysis used data from the National Health and Nutrition Examination Survey (2005-2008), Medicare fee-for-service claims (2019), IBM MarketScan commercial insurance claims (2016), population-based studies of eye disease (1985-2003), and 2022 population estimates from the US Census Bureau. PubMed was searched for population-based studies of glaucoma prevalence published between 1991 and 2016. Bayesian meta-regression methods were used to estimate the prevalence of glaucoma and vision-affecting glaucoma stratified by age, undifferentiated sex/gender (a measure that captures an unclear mix of aspects of sex and or gender), race and ethnicity, and US county and state. Prevalence of any type of glaucoma (open or closed angle) among people 18 years or older and vision-affecting glaucoma, defined as glaucoma and a visual field abnormality. For 2022, an estimated 4.22 million people (95% uncertainty interval [UI], 3.46 million to 5.23 million) in the US were living with glaucoma, with a prevalence of 1.62% (UI, 1.33%-2.00%) among people 18 years or older and 2.56% (UI, 2.10%-3.16%) among people 40 years or older. An estimated 1.49 million people (UI, 1.17 million to 1.90 million) were living with vision-affecting glaucoma, with a prevalence of 0.57% (UI, 0.45%-0.73%) among people 18 years or older and 0.91% (UI, 0.71%-1.16%) among people 40 years or older. Prevalence of glaucoma among people 18 years or older ranged from 1.11% (UI, 0.89%-1.40%) in Utah to 1.95% (UI, 1.57%-2.39%) in Mississippi. Black adults had a prevalence of 3.15% (UI, 2.32%-4.09%) compared with 1.42% (UI, 1.10%-1.85%) among White adults; adults in the Hispanic and all other racial and ethnic categories combined had a prevalence of 1.56% (UI, 1.13%-2.06%). This meta-analysis found that an estimated 2.56% of people 40 years or older have glaucoma, slightly more than estimated by previous studies. Black individuals are disproportionately affected. Prevalence estimates at the state and county level can help guide public health planning.

Race, Sex, and Ejection Fraction-Based Differences in Transthyretin Amyloid Cardiomyopathy (ATTR-CM) Risk Prediction

Background: The early detection of transthyretin cardiac amyloidosis (ATTR-CM) is essential, with Tc-99m pyrophosphate scintigraphy (PYP scan) being a key diagnostic tool. Although a previously validated score has shown promise in predicting PYP scan positivity among patients with HFpEF, further evaluation in diverse cohorts is necessary. Objectives: To assess the effectiveness of the ATTR-CM score in predicting PYP scan positivity within our patient population. Methods: We analyzed patients referred for PYP with SPECT at the Cleveland Clinic from January 2012 to January 2020, all of whom had undergone echocardiography within the previous year. The ATTR-CM score was determined using the following criteria: Age (60–69, +2; 70–79, +3; ≥80, +4), sex (male, +2), hypertension (present, −1), left ventricular ejection fraction (LVEF <60%, +1), posterior wall thickness (≥12 mm, +1), and relative wall thickness (>0.57, +2). A score of ≥6 indicated high risk. Results: Among the 540 patients (32% female, 33% black), 27% had an LVEF <40%. The score demonstrated good discrimination by AUC, with consistent performance across different racial groups, sexes, and LVEF categories. For scores ≥6, sensitivity was lower in women and black patients; however, lowering the cutoff to 5 markedly improved sensitivity. Conclusions: The ATTR-CM score displayed consistently good performance by AUC across our cohort, including patients with HFrEF. Nevertheless, its sensitivity was reduced in black patients and women. Efforts to scale ATTR-CM diagnosis tools should be mindful of demographic differences in risk prediction models.

Dear Mixed People: Critically Examining Monoracism in College-Related TV Series

Multiracial youth are one of the fastest-growing demographics in the United States. What messages might these multiracial young people be receiving about multiraciality in college-related television series? Applying Critical Race Media Literacy and Critical Multiracial Theory (MultiCrit), this study examines representations of multiracial students in Charmed, Dear White People, Ginny & Georgia, Grown-ish, and Black-ish. We find that multiracial college student characters are routinely confronted with “box-checking” on demographic forms and wrestle with the limitations of racial categories to capture complexity and the potential resources/benefits associated with selecting specific boxes. Further, multiracial college student characters question their belonging within monoracial student organizations and interracial relationships. Implications for practice and pedagogy are outlined to better leverage television depictions of multiracial college students toward disrupting rather than reinforcing monoracism in higher education contexts.

Utilizing drawings to understand how our backgrounds and experiences change our plant mental models

Societal Impact StatementOur culture, life experiences, and the places we live teach us about the world around us and the plants within it. This information gives each individual distinct mental models. By delving into plant mental models of young adults, this study offers insights into the complex landscape of plant knowledge, with a special emphasis on Indigenous communities. Beyond broadening our understanding, these findings provide valuable resources for educators and researchers striving to bridge the gap in plant literacy. Moreover, the methods used offer a blueprint for similar investigations globally, which will foster a deeper understanding of plant awareness across diverse populations.Summary Plant mental models, or what people think about when they think of a given plant, give insight into a person's knowledge and understanding of plants. However, little to no research has been conducted on plant mental models of young adults or comparing mental models across demographics. This study assessed college students' plant mental models in the demographic categories of race, gender, rurality, and college type (tribal vs. non‐tribal), as well as experience in art, photography, and plant identification, to determine the impact of these factors on plant mental models. A total of 697 students from three tribal and three non‐tribal colleges enrolled in a specific introductory biology course participated. Participants completed four drawings, which represented their mental model of a plant, flower, grass, and tree. They also completed a short survey about demographics and experience with art, photography, and plant identification. Tree drawings had the most detail, and grass drawings had the least. Gender was the only demographic factor that impacted the detail drawn, with females including more detail for flowers and trees and males for grass. Surprisingly, experience with art, photography, and plant identification did not impact the detail included in the drawings. Overall, participants plant mental models across demographics were simplistic and lacked detail, potentially indicating a lack of plant awareness.

Analytic racecraft: Race-based averages create illusory group differences in perceptions of racism.

Research practices used by social scientists to understand and dismantle the psychological foundations that uphold racist hierarchies can backfire when they rely on racecraft. Racecraft ideology assumes the reality of race(s), an assumption that shapes study designs and inferences to the detriment of theoretical and practical goals. I showcase how racecraft manifests in studies seeking to quantify how perceptions of sociopolitical stimuli differ across racialized perceivers (e.g., black, white, latinx). The typical analysis for quantifying perceptions focuses on comparing group averages, which assumes the existence of discrete "races" whose perceptions can be sufficiently summarized by averages. Across three studies, I used variance component analyses on racism ratings of anti-immigrant tweets from differently racialized perceivers (N = 1,211) to show there was much larger disagreement than agreement within race categories, even when there were average differences in perceptions across race categories. This analysis shows how analytic practices can bolster different assumptions about the nature of race, some of which reify the illusion that race categories are stable cohesive groups. Researchers can improve their analytic inferences and avoid producing race-reifying caricatures of peoples' perceptions by adding variance mapping to their toolkits and attending to racialization as a dynamic process-needed improvements within the psychological study of race and racism, group-based beliefs, and antiracist research endeavors. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Incorporating multiracial and multiethnic experiences into genetic counseling practice and research: A necessary opportunity.

The conflation of race and genetic ancestry can have harmful consequences. Biological conceptualizations of race have long been used to justify inequities and distract from social structures that afford opportunities to some that are unjustly denied to others. Despite recent efforts within the scientific community to distinguish between the sociopolitical constructs of race and ethnicity and the biological constructs of genetic ancestry and genetic similarity, their conflation continues to influence genomic research and its translation into clinical care. One overlooked aspect of this problematic conflation is the extent to which discrete monoracial and monoethnic categorization systems persist and perpetuate unequal benefit-sharing in the clinical translation of genomic technologies. In genetic service delivery, reliance on discrete racial and ethnic categories undermines the clinical translation of genomic technologies for large segments of the global population. For multiracial and multiethnic individuals, who have complex identities that defy discrete categorization systems, the potential benefits of genomic discoveries are especially elusive. Scholars have recently begun to call for the inclusion of multiracial, multiethnic, and admixed individuals in race, ethnicity, and ancestry frameworks in genetics and genomics. However, little work has been done to explore and address the unique challenges and opportunities posed by multiracial/multiethnic individuals in genetic counseling specifically. We discuss how conceptualizing diversity along discrete racial and ethnic lines perpetuates inequitable patient care and limits efforts to increase inclusion and belonging within genetic counseling. Moreover, we argue that ongoing efforts to mitigate racial inequity must actively challenge the paradigm of monoracial and monoethnic categories to accomplish their goal.

The US Census, the MENA Campaign, and Classification Struggles: Neoliberal Distribution of Pride, Fear, and Deception

In this paper, I explore the history of the Middle Eastern and North African (MENA) campaign, which aims to extract Southwest Asian and North Africa populations from the white legal category on the US Census. I use Bourdieu’s classification struggles and theory of field to make sense of different approaches to this campaign. The data presented in the paper are gathered from 65 qualitative interviews with activists and citizens with Southwest Asian and North African backgrounds. The data manifest that although all participants unanimously reject the relevance of their current legal white racial category, they have divergent reasons for their support, or lack thereof, for the campaign, all of which are different from the advocacy organizations’ framing of it. I draw on these variant perspectives to investigate the classification struggles between different actors at different levels and examine how these actors meet in the field and pursue their goals.

8361 Impact of Social Vulnerability on Glycemic Control in Primary Care Patients with Diabetes

Abstract Disclosure: J.N. Tich: None. S.R. MacLeod: None. V. Zhang: None. T. Love: None. R.J. Fortuna: None. Introduction: According to the CDC, 29.7 million Americans are diagnosed with diabetes (DM), contributing to morbidity, mortality and strain on the healthcare system. The impact of social determinants of health (SDOH) and social vulnerability (SV), as measured by the social vulnerability index (SVI), on DM care and control is evident. In populations with lower educational attainment levels, lower income and higher rates of poverty, prevalence of DM and rates of complications are higher. However, less is understood about how the intersectionality between SDOH/SV and race impacts diabetes control. Aims: We sought to examine the impact of SV and race on DM control in primary care patients in Upstate NY. Methods: We examined 26,010 patients with DM in Upstate NY. We defined DM control based on national HEDIS standards. SVI were calculated for each patient based on census track data. The SVI is calculated based on 16 variables in four themes: socioeconomic status, household characteristics, racial/ethnic minority status, and housing/transportation. SVI scores range from 0 (lowest vulnerability) to 1 (highest vulnerability). In addition to calculated SVI scores, we examined patient-reported SDOH, including food insecurity, housing insecurity, transportation, and social isolation. Race and ethnicity related parameters were self-reported. We report preliminary descriptive data. Results: Overall, 73.6% of patients were controlled with a HgA1c <8% based on the HEDIS definition. Control rates varied based on race (white 75.9% Black 66.1%; Asian 73.7%; other race 66.6%), calculated SVI, and patient reported SDOH. Within each racial category, diabetes control rates worsened with increasing SVI. Patients who expressed food insecurity had lower rates of DM control than those who had no food insecurity (68.8% vs 79.7%). Similarly, patients with housing insecurity had lower control rates (67.5%) compared to those who had greater housing security (80.0%). Patients with unmet transportation needs had lower rates of diabetic control (67.4%) compared to those with stable transportation (80.6%). Additional statistical tests and multivariate regression models are pending. Conclusions: Across a large sample of patients with diabetes, increasing SV was associated with worsening glycemic control across all racial groups studied. In preliminary analyses, both race and SVI appear to be independently associated with DM control. SVI did not fully mitigate the influence of rate on DM control. Within same SVI category, non-white participants appeared to have a more negative impact on DM control compared to white participants. While SDOH are well known influences, these findings specifically demonstrate the link between SV and glycemic control, highlighting the fact that at the same SVI quartile, non-white participants may be more vulnerable to dysglycemia. Presentation: 6/2/2024 6/2/2024

Exploring the association of social connections and food security among adults with uncontrolled type 2 diabetes: a population-based study

BackgroundPrimary health care professionals are held accountable for various quality measures in the treatment of patients with chronic diseases such as diabetes. Uncontrolled type 2 diabetes (T2D) remains a considerable health problem; thus, further studying patients with this condition is important for delivering effective interventions. Social determinants of health (SDoH) have been shown to affect various aspects of diabetes care in different subpopulations. We studied the association of SDoH with uncontrolled T2D in a population of adult primary care patients.MethodsWe retrospectively searched our electronic health record for adult patients (≥18 years) with a diagnosis of T2D and a hemoglobin A1c (HbA1c) level of 8% or higher. Patients were empaneled to 2 primary care clinic sites between January 1, 2021, and January 31, 2022. Patients were grouped by HbA1c level to stratify patients according to the extent of uncontrolled T2D. Patient characteristics were compared among groups. Unadjusted and adjusted multinomial logistic regression analysis was used to estimate the odds of various SDoH factors among patient groups with different levels of uncontrolled T2D.ResultsThe study cohort included 1,596 patients. Most patients were White (79%), and the median age was 58.8 years. The median HbA1c level was 8.9%, and approximately 68% of patients were obese (body mass index [BMI] ≥30). When the study population was grouped by HbA1c level (8% to < 9% [n = 806], ≥9% to < 12% [n = 684], and ≥12% [n = 106]), significant differences among groups were observed in age group (P < .001), marital status (P < .001), race (P < .001), ethnicity (P = .001), and BMI category (P = .01). In groups with higher HbA1c levels, we noticed a higher percentage of patients who were aged 51 to 65 years or single. Among patients with uncontrolled HbA1c levels, more patients were obese than overweight. Patients in the intermediate HbA1c group had increased odds of food insecurity and some decreased social connections, even after adjusting for age, sex, race, ethnicity, and marital status.ConclusionsAmong patients with uncontrolled T2D, higher HbA1c levels were associated with decreased social connections and increased food insecurity. Our findings provide insight into the role of these SDoH in managing T2D and have important implications for primary care practice.

Share the wealth: Neurophysiological and motivational mechanisms related to racial discrimination in economic decision making

Social interactions are influenced by rapid judgements about interaction partners that are assumed to contribute to various behavioral biases. While often negligible in a given instance, such biases can accumulate to contribute to persistent inequities between social groups. Here, we used event-related potentials (ERPs) to determine the extent to which early attention to racial category information during simulated interpersonal interactions contributes to race bias in financial decisions. Undergraduate participants (N = 67; 36 women, 31 men; all White/Non-Hispanic) completed an economic decision-making task in which they decided how much money to invest in a series of male interaction partners (i.e., trustees) who varied in their apparent racial group memberships. Black male trustees received lower investments than White male trustees, replicating prior findings. Of greater interest, an ERP index of attention to trustees' faces predicted racial bias in investments, and was moderated by participants' internalized motivation to respond without prejudice (i.e., a difference score reflecting the extent to which participants' motivation reflected internal [e.g., personal egalitarian values] compared to external [e.g., concerns about social norms] reasons to respond without prejudice). Consistent with motivational models of prejudice control, greater early attention to a trustee's face led to more-biased lending among participants with lower internalized motivation but to less-biased lending among participants with higher internalized motivation. Findings demonstrate a crucial role for within-person variability in attention to race-related cues when interacting with others, along with between-person bias regulation motives, in determining whether attention to race will increase or decrease bias in financial lending.

Motivations for Direct-to-Consumer Genetic Testing: Understanding Interpretations of Ancestry Results

AbstractDirect-to-consumer genetic testing (DTCGT) has the potential to significantly impact racial and ethnic identities as well as social concepts of race and ethnicity. Prior literature challenges the binary choice of essentialism vs. constructionism in understanding consumers’ interpretations of genetic ancestry results. Largely focusing on differences by race and ethnicity, this research finds that test takers selectively apply genetically determinist logic depending on their prior identities and interests. We extend this line of inquiry using in-depth interviews with thirty-six mostly white participants who had previously taken a DTCGT offering combined health and ancestry results, which provided an opportunity to explore how different motivations for testing – e.g., for health or ancestry information – impact interpretations of ancestry results. Our analysis reveals distinct patterns in how health- vs. ancestry-motivated consumers invoke genetic determinism in their interpretations of DTCGT results. At the same time, regardless of motivation for testing, we found little use of genetic results to challenge the coherence or biological basis of racial or ethnic categories. Our results suggest that even if genetic determinism is only selectively applied, and in ways that vary between consumers with different motivations for testing, at least among whites, discourses of genetics as “truth” and white normativity are nonetheless the prevailing interpretive frameworks for genetic ancestry results.

Bias in Prediction Models to Identify Patients With Colorectal Cancer at High Risk for Readmission After Resection

PURPOSE Machine learning (ML) algorithms are used for predictive modeling in medicine, but studies often do not evaluate or report on the potential biases of the models. Our purpose was to develop clinical prediction models for readmission after surgery in patients with colorectal cancer (CRC) and to examine their potential for racial bias. METHODS We used the 2012-2020 American College of Surgeons' National Surgical Quality Improvement Program Participant Use File and Targeted Colectomy File. Patients were categorized into four race groups—White, Black or African American, other, and unknown/not reported. Potential predictive features were identified from studies of risk factors of 30-day readmission in patients with CRC. We compared four ML-based methods—logistic regression, multilayer perceptron, random forest, and XGBoost (XGB). Model bias was assessed using false-negative rate (FNR) difference, false-positive rate (FPR) difference, and disparate impact (DI). RESULTS In all, 112,077 patients were included, 67.2% of whom were White, 9.2% Black, 5.6% other race, and 18% with race not recorded. There were significant differences in the area under the receiver operating characteristics curve, FPR, and FNR between race groups across all models. Notably, patients in the other race category had higher FNR compared with Black patients in all but the XGB model, while Black patients had higher FPR than White patients in some models. Patients in the other category consistently had the lowest FPR. Applying the 80% rule for DI, the models consistently met the threshold for unfairness for the other race category. CONCLUSION Predictive models for 30-day readmission after colorectal surgery may perform unequally for different race groups, potentially propagating to inequalities in delivery of care and patient outcomes if the predictions from these models are used to direct care.

Factors associated with delays in receipt of neoadjuvant chemotherapy in patients with operable breast cancer.

126 Background: Delays in neoadjuvant chemotherapy initiation (NACTI) after breast cancer (BC) diagnosis have been associated with worse outcomes. We evaluated incidence and predictors of delays of NACTI among high clinical risk patients treated with NACT on a national level. Methods: We conducted a retrospective cohort study using the National Cancer Database. Eligibility included age ≥18 years, diagnosis of non-metastatic BC between 1/1/2010 – 12/31/2020, who were treated with NACT within 180 days of diagnosis. Patients who received neoadjuvant endocrine therapy were excluded. Time to chemotherapy (TTC) in days was recorded. Patients were categorized into sub-cohorts by receptor status and clinical stage: 1) Hormone Receptor positive/HER-2 negative (HR+/HER2-) and were lymph node (LN) LN+; 2) HER-2 positive (HER2+) cT2+ or LN+; and 3) triple negative BC (TNBC) cT2+ or LN+. Multivariable logistic regression, adjusted for demographic, socioeconomic and tumor characteristics, was used to identify characteristics associated with delays &gt; 60 days from diagnosis to NACTI. Multiple imputation was used for missing data. Results: We identified 145,697 eligible patients, 74% were White, 18% were Black, 3.3% were Asian, and 4.6% were Other/Unknown. Across all racial categories, 9.2% were Hispanic. Median age at diagnosis was 52 years (range 18-90), median TTC was 32 days (range 0-180), and 10% had a delay &gt; 60 days. There were 40,345 patients in the HR+/HER2- cohort, 56,868 in the HER2+ cohort, and 48,484 in the TNBC cohort; 12%, 9.0%, and 8.9% (p &lt; 0.001) had a delay in NACTI, respectively. In multivariable analysis among the HR+/HER2- sub-cohort, characteristics associated with delays in NACTI included Black race (OR 1.71, 95%CI 1.57-1.86) and Hispanic ethnicity (OR 1.76, 95%CI 1.60-1.94) compared to White and non-Hispanic patients. Patients with Medicare, Medicaid, or who were uninsured were more likely to be delayed (OR 1.44 95%CI 1.30-1.58, 2.10, 95%CI 1.92-2.29, 2.28, 95%CI 1.99-2.61) compared to those with commercial insurance. Results were similar in the HER2+and TNBC cohorts, as seen (Table). Conclusions: Among patients with operable BC who received NACT, patients who were Black, Hispanic, had Medicaid or no insurance had as high as a twofold increase in odds of a delay in NACTI. Targeted interventions to address these racial and socioeconomic disparities are necessary to ensure equitable care. Multivariable logistic regression adjusted for demographic, socioeconomic, and tumor characteristics variables (n = 145,697). HR+/HER2-N= 40,345 HER2+N= 56,868 TNBCN= 48,484 OR 95%CI OR 95%CI OR 95%CI Black Race 1.71 1.57-1.86 1.89 1.74-2.04 1.90 1.76-2.06 Hispanic Ethnicity 1.76 1.60-1.94 2.18 2.00-2.36 2.00 1.80-2.21 Medicare 1.44 1.30-1.58 1.46 1.34-1.61 1.45 1.32-1.61 Medicaid 2.10 1.92-2.29 2.13 1.96-2.31 2.14 1.96-2.34 No Insurance 2.28 1.99-2.61 2.36 2.07-2.70 2.25 1.96-2.59

Costs and Healthcare Utilization of Heart Disease by COVID-19 Diagnosis and Race and Ethnicity

Introduction: Heart disease (HD) poses a significant health and economic burden in the United States, with considerable variations in outcomes across different racial and ethnic groups. The COVID-19 pandemic has further highlighted disparities in healthcare utilization and costs associated with HD. ac Methods: We used the 2021 Merative MarketScan Medicaid claims database to estimate medical costs and healthcare utilization associated with HD by racial and ethnic groups and COVID-19 diagnosis status. Our study focused on individuals aged ≥18 years old continuously enrolled in a non-capitated insurance plan in 2021. The outcome measures included total medical expenditures and healthcare utilization, including numbers of emergency department (ED) visits and inpatient admissions, and length of inpatient stay. We employed a generalized linear model with a family of gamma and log links was used for medical costs, and a negative binomial regression for healthcare utilization. Three-way interactions of HD, COVID-19 diagnosis, and race and ethnicity categories were implemented after adjusting for age, sex, and comorbidities. We reported average marginal effects with 95% CIs. Results: Among 1,008,166 Medicaid beneficiaries, 8% had HD in 2021. The cost associated with HD was $10,819 per beneficiary in 2021 (95% CI, 10,292–11,347; P<0.001). The cost was $15,840 (95% CI, 14,389–17,291; P<0.001) for non-Hispanic Black individuals, $9,945 (95% CI, 9,172–10,718; P<0.001) for non-Hispanic White, and $8,511 (95% CI, 7,490–9,531; P<0.001) for Hispanic individuals. Individuals with a COVID-19 diagnosis ($19,638) had $9,541 (95% CI, 7,049–12,032; P<0.001) higher costs associated with HD than those without COVID-19 ($10,098) (P<0.001). Individuals with HD had higher numbers of ED visits (0.937 per beneficiary, 95% CI, 0.913–0.960), inpatient admissions (0.463 per beneficiary, 95% CI, 0.455–0.471), and average length of stay (2.541 days per admission, 95% CI, 2.405–2.677) than those without HD. Conclusions: Our findings showed that costs and healthcare utilization associated with HD are substantial in all racial and ethnic groups and the highest among non-Hispanic Black individuals. Furthermore, individuals with a COVID-19 diagnosis had approximately two times higher costs associated with heart disease compared with individuals without a COVID-19 diagnosis.

Race and ethnicity representation in phase 2/3 oncology clinical trial publications in the United States: A systematic review.

20 Background: The five 1997 Office of Management and Budget (OMB) races in the US include American Indian or Alaskan Native (AI/AN), Asian, Black or African American, Native Hawaiian or Other Pacific Islander (NHPI), and White, with Hispanic ethnicity. Despite the Affordable Care Act (ACA) mandating OMB-based collecting/reporting standards, race and ethnicity publishing in medical journals is inconsistent, despite being necessary to achieve health equity. We aimed to quantify race and ethnicity reporting rates and calculate representation quotients (RQs) in published oncology clinical trials. Methods: In this systematic review, PubMed/Embase were queried for phase 2/3 clinical trials of the 6 most common noncutaneous solid malignancies, published between 2012-2022, in 4 high-impact journals. Trial characteristics were recorded. The RQs for each race and ethnicity were calculated by dividing the percent of representation in clinical trial publications by the percent of year-matched, site-specific incident cancers in the US, compared with Kruskal-Wallis tests with Bonferroni Correction (BC). Reporting was compared between journal publications and ClinicalTrials.gov. Results: Among 1,202 publications evaluated, 364 met inclusion criteria: 16 JAMA , 241 JCO , 19 Lancet , and 88 NEJM . Publications included 268,209 patients (171,132 women [64%]), with a median of 356 (IQR, 131-800) patients per publication. Reported race and ethnicity included AI/AN in 52 (14%) publications, Asian in 196 (54%), Black or African American in 215 (59%), Hispanic in 67 (18%), NHPI in 28 (8%), and White in 254 (70%). Median RQ varied across race (P &lt; .001 BC) with 1.04 (IQR, 0.09-4.77) for Asian, 0.98 (IQR, 0.86-1.06) for White, 0.42 (IQR, 0.12-0.75) for Black or African American, and 0.00 (IQR, 0.00-0.00) for both AI/AN and NHPI patients. Sensitivity analyses showed similar findings upon subset analysis for US-only clinical trials. There was significantly less race and ethnicity reporting in the clinical trial publications compared with ClinicalTrials.gov documentation for AI/AN (14% vs 45%, P &lt; .001 per McNemar χ 2 with continuity correction [MC]) and NHPI (7.7% vs 43%; P &lt; .001 MC). Conclusions: While most phase 2/3 oncology clinical trials published in high-impact journals report race and ethnicity, most did not report AI/AN and NHPI racial categories. Our findings support a call to action for consistent journal policies and transparent race and ethnicity reporting, in alignment with ACA-concordant race and ethnicity federal reporting requirements.

Associations Between Infant Formula Exposure, Housing Instability and Postneonatal Mortality Among Participants in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC).

To quantify infant mortality rates (IMR) using expanded racial categories, and to examine associations between infant formula exposure, housing instability and postneonatal mortality among Minnesota WIC Participants. Births in Minnesota from 2014 through 2019 (n = 404,102) and associated infant death records (n = 2034) were used to calculate neonatal and postneonatal rates using expanded racial categories. Those births that participated in the WIC program (n = 170,011) and their linked death records (n = 853) were analyzed using logistic regression to examine associations between formula exposure, housing instability, and postneonatal death. Postneonatal IMR was more than twice as prevalent among Black (African American) as East African immigrant infants (IMR = 3.9 vs 1.5). After adjustment for confounding (term status and nativity of mother (U.S. vs foreign born), infants exposed to formula by 28days were four times as likely to die in the postneonatal period as those without formula exposure (aOR = 4.0; 95% CI 3.2-4.9). WIC participants who experienced housing instability at birth were 1.7 times as likely to lose an infant in the postneonatal period (28 to 364days of age) as those in stable housing (aOR = 1.7; 95% CI 1.2, 2.4). Disaggregating Black mortality rates revealed inequities in infant mortality among Black families of varied backgrounds. Formula exposure and housing instability are modifiable risk factors associated with postneonatal mortality. Appropriate interventions to reduce barriers to breastfeeding and provide housing stability for vulnerable families could reduce disparities in postneonatal mortality.

Differences in the treatment patterns of small renal masses: A disaggregated analyses by race/ethnicity

ObjectiveTo characterize differences in the management of small renal masses among disaggregated race/ethnic subgroups. Material and MethodsWe used the National Cancer Database to identify patients diagnosed with clinically localized kidney cancer and tumor size ≤4cm. We studied 16 predefined racial/ethnic subgroups and compared 1) the use of surveillance for tumors <2cm and 2) the use of radical nephrectomy for tumors ≤4cm. We used multivariable logistic regression to evaluate the independent association of race/ethnicity with management, adjusting for baseline characteristics. We also compared our disaggregated analyses to the 6 National Institute of Health aggregate race categories. ResultsWe identified 286,063 patients that met inclusion criteria. For tumors <2cm, Black Non-Hispanic (aOR 1.43) and Mexican patients (aOR 1.29) were significantly more likely to undergo surveillance compared to White patients. For tumors ≤4cm, Black Non-Hispanic (aOR 1.43), Filipino (aOR 1.28), Japanese (aOR 1.28), Mexican (aOR 1.32), and Native Indian patients (aOR 1.15) were significantly more likely to undergo radical nephrectomy compared to White patients. When comparing our disaggregated analyses to the NIH categories, we found that many disaggregated race/ethnic subgroups had associations with management strategies that were not represented by their aggregated group. ConclusionsIn this study, we found that the use of surveillance for tumors <2cm and radical nephrectomy for tumors ≤4cm varied significantly among certain race/ethnic subgroups. Our disaggregated approach provides information on differences in treatment patterns in particular subgroups that warrant further study to optimize kidney cancer care for all patients.