Health Disparities Research Research Articles

Health care policy that relies on poor measurement is ineffective: Lessons from the hospital readmissions reduction program.

Health care policy that relies on poor measurement is ineffective: Lessons from the hospital readmissions reduction program.

A historical review of pain disparities research: Advancing toward health equity and empowerment

Background and PurposeThis theory-guided review draws on 30 years of published data to examine and interrogate the current and future state of pain disparities research. MethodsUsing the Hierarchy of Health Disparity Research framework, we synthesize and present an overview of “three generations” of pain disparities scholarship, while proposing directions for adopting a “fourth generation” that redefines, explains, and theorizes future pain disparities research in a diverse society. DiscussionPrior research has focused on describing the scope of disparities, and throughout the historical context of human existence, racialized groups have been subjected to inadequate pain care. It is imperative that research not only illuminates existing problems but also provides solutions that can be implemented and sustained across varying social milieus. ConclusionWe must invest in new theoretical models that expand on current perspectives and ideals that position all individuals at the forefront of justice and equity in their health.

A call to address structural barriers to Hispanic/Latino representation in clinical trials on Alzheimer's disease and related dementias: A micro-meso-macro perspective.

This perspective paper addresses the US Hispanic/Latino (herein, Latino) experience with regards to a significant public health concern-the underrepresentation of Latino persons in Alzheimer's disease and related dementias (AD/ADRD) clinical trials. Latino individuals are at increased risk for AD/ADRD, experience higher disease burden, and low receipt of care and services. We present a novel theoretical framework-the Micro-Meso-Macro Framework for Diversifying AD/ADRD Trial Recruitment-which considers multi-level barriers and their impact on Latino trial recruitment. Based on a review of the peer-reviewed literature and our lived experience with the Latino community, we drew from our interdisciplinary expertise in health equity and disparities research, Latino studies, social work, nursing, political economy, medicine, public health, and clinical AD/ADRD trials. We discuss factors likely to impede or accelerate Latino representation, and end with a call for action and recommendations for a bold path forward. In the 200+ clinical trials conducted with over 70,000 US Americans, Latino participants comprise a fraction of AD/ADRD trial samples. Efforts to recruit Latino participants typically address individual- and family-level factors (micro-level) such as language, cultural beliefs, knowledge of aging and memory loss, limited awareness of research, and logistical considerations. Scientific efforts to understand recruitment barriers largely remain at this level, resulting in diminished attention to upstream institutional- and policy-level barriers, where decisions around scientific policies and funding allocations are ultimately made. These structural barriers are comprised of inadequacies or misalignments in trial budgets, study protocols, workforce competencies, healthcare-related barriers, criteria for reviewing and approving clinical trial funding, criteria for disseminating findings, etiological focus and social determinants of health, among others. Future scientific work should apply and test the Micro-Meso-Macro Framework for Diversifying AD/ADRD Trial Recruitment to examine structural recruitment barriers for historically underrepresented groups in AD/ADRD research and care.

MP20-02 27 HYDROXYCHOLESTEROL AND DNA DAMAGE REPAIR: IMPLICATIONS IN PROSTATE CANCER

You have accessJournal of UrologyCME1 Apr 2023MP20-02 27 HYDROXYCHOLESTEROL AND DNA DAMAGE REPAIR: IMPLICATIONS IN PROSTATE CANCER Cecilia G. Galvan, Nadine A. Friedrich, Sanjay Das, James P. Daniels, Michael R. Freeman, Ryusuke Suzuki, Sergio Sanders, Sara Pollan, Shweta Dambal, and Stephen J. Freedland Cecilia G. GalvanCecilia G. Galvan More articles by this author , Nadine A. FriedrichNadine A. Friedrich More articles by this author , Sanjay DasSanjay Das More articles by this author , James P. DanielsJames P. Daniels More articles by this author , Michael R. FreemanMichael R. Freeman More articles by this author , Ryusuke SuzukiRyusuke Suzuki More articles by this author , Sergio SandersSergio Sanders More articles by this author , Sara PollanSara Pollan More articles by this author , Shweta DambalShweta Dambal More articles by this author , and Stephen J. FreedlandStephen J. Freedland More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003245.02AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Recent studies from our group have reported that cholesterol homeostasis in prostate cancer (PC) is controlled by 27-hydroxycholesterol (27HC) and that CYP27A1, the enzyme that converts cholesterol to 27HC, acts as a cellular cholesterol sensor in prostate cells. Furthermore, the loss of the CYP27A1/27HC axis is correlated with PC pathogenesis. Herein, we sought to better understand the mechanism of 27HC-mediated anti-PC effects. METHODS: LNCaP (AR+) and DU145 (AR-) cells were treated with 27HC or control. Transcriptome profiling was done with Affymetrix GeneChip™ microarray assay and key changes validated by qPCR. Differential expression and gene set enrichment analysis was done using the GSEA software with hallmark gene sets from MSigDB. Human transcriptome signatures were analyzed from the Prostate Cancer Transcriptome Atlas (PCTA). DNA damage was assessed via comet assays and cell growth using proliferation assays. RESULTS: In a transcriptome analysis, 27HC treatment resulted in downregulation of Hallmark pathways related to DNA damage repair, decreased expression of key cell cycle genes, and induced BRCAness (Figure 1). FEN1 and RAD51 decreased expression were confirmed by qPCR. Using publicly available data, we found a correlation between higher CYP27A1 expression (i.e. higher intracellular 27HC) and decreased DNA repair gene expression among 1,321 human transcriptomes. While testing the clinical implications of this, we noted that 27HC treatment increased DNA damage in PC cells via neutral comet assay. Effects were reversible by adding back cholesterol, but not androgens. Finally, in combination with Olaparib, a PARP inhibitor, we showed additive anti-tumor activity. CONCLUSIONS: Our research suggests 27HC treatment, via cholesterol depletion, induces BRCAness and leads to increased DNA damage. This DNA damage when combined with PARP inhibitors leads to additive anti-PC effects and may be a potential effective therapy in PC. Additional studies are needed to directly test whether 27HC creates a synthetic lethality to PARP inhibitors and other DNA damaging agents. Source of Funding: Dr. Galvan is funded by the Department of Defense Health Disparities Research Fellowship. Dr. Das was supported by the Patient Centered Outcomes in Urological and Gynecological Cancers (PCORT UroGynCan). Dr. Daniels was funded by the NIH grants TL1 DK132768 and U2C DK129496. Dr. Friedrich was funded by NIH grant T32 CA240172-03. Other funds: Department of Defense Prostate Cancer Research Program © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e275 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Cecilia G. Galvan More articles by this author Nadine A. Friedrich More articles by this author Sanjay Das More articles by this author James P. Daniels More articles by this author Michael R. Freeman More articles by this author Ryusuke Suzuki More articles by this author Sergio Sanders More articles by this author Sara Pollan More articles by this author Shweta Dambal More articles by this author Stephen J. Freedland More articles by this author Expand All Advertisement PDF downloadLoading ...

MP76-19 INVESTIGATING NATIONAL TRENDS IN INTEREST FOR BENIGN PROSTATIC HYPERPLASIA SURGERY OPTIONS USING GOOGLE TRENDS

You have accessJournal of UrologyCME1 Apr 2023MP76-19 INVESTIGATING NATIONAL TRENDS IN INTEREST FOR BENIGN PROSTATIC HYPERPLASIA SURGERY OPTIONS USING GOOGLE TRENDS James Daniels, Cecilia Galvan, Sanjay Das, Nadine Friedrich, Cosimo De Nunzio, and Stephen Freedland James DanielsJames Daniels More articles by this author , Cecilia GalvanCecilia Galvan More articles by this author , Sanjay DasSanjay Das More articles by this author , Nadine FriedrichNadine Friedrich More articles by this author , Cosimo De NunzioCosimo De Nunzio More articles by this author , and Stephen FreedlandStephen Freedland More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003350.19AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Given the plethora of surgical options for benign prostatic hyperplasia (BPH), it is important to understand which treatments patients are most interested in. We used Google Trends to analyze national interest in 5 common BPH surgeries. METHODS: Google trends (http://trends.google.com) was queried with 5 different BPH surgeries using the terms: “TURP”, “Greenlight Laser Therapy”, “Urolift”, “Rezum”, and “Aquablation”. The geographical location was set to the “United States”. The time range was set to “2004 - present” which presented as January 2004 to August 2022. The data are presented as relative search interest (RSI) by each month of the time range. RSI is in the range of 0-100 with 100 being the peak popularity of the term, 50 being half of the peak popularity, and 0 representing insufficient data for the search interest to be determined. The RSI data of the 5 BPH surgeries from January 2004 to August 2022 are shown in Figure 1. RESULTS: There were noted increases in RSI of search terms “Urolift” and “Rezum” that began after publication of randomized control trials (RCTs) that showed adequate symptom relief and preservation of sexual function. Before the L.I.F.T study from January 2004 to December 2013, average RSI for “Urolift” was 1.4. After the L.I.F.T study from January 2014 to August 2022, average RSI was 33.1 with a peak of 93. Before the first multicenter Rezum RCT from January 2004 to May 2016, average RSI for “Rezum” was 0.7. From June 2016 to August 2022, average RSI for “Rezum” was 13.1, with a peak of 22. RSI for “TURP” and “Greenlight Laser Therapy” were stable and held the top two rankings until July 2016 when “Urolift” became the 2nd most searched term. As of August 2018, “Rezum” surpassed “Greenlight Laser Therapy” as the 3rd most searched term. “TURP” retained the top overall RSI the entire study period. RSI for “TURP” reached a peak of 100 in March 2022 and had an average RSI of 66.5 for the entire time range. CONCLUSIONS: Interest in the search terms “Urolift” and “Rezum” increased following the publication of RCTs and interest in “Urolift” is second only to “TURP”. Despite the advent of new surgical approaches, the search term “TURP” remains the most popular search term. Google Trends can be an effective tool for the evaluation of trends in patient interest in BPH surgery. Source of Funding: Dr. Daniels is funded by the NIH grants TL1 DK132768 and U2C DK129496. Dr. Galvan is funded by the Department of Defense Health Disparities Research Fellowship. Dr. Das is funded by the Patient Centered Outcomes in Urological and Gynecological Cancers (PCORT UroGynCan). Dr. Friedrich is funded by NIH grant T32 © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e1099 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information James Daniels More articles by this author Cecilia Galvan More articles by this author Sanjay Das More articles by this author Nadine Friedrich More articles by this author Cosimo De Nunzio More articles by this author Stephen Freedland More articles by this author Expand All Advertisement PDF downloadLoading ...

160 Biopsychosocial Well-being and Identity: Variation in the Experience of Allostatic Load and Depression by Identity Status Using NHANES 2017-2020 Data

OBJECTIVES/GOALS: Chronic stress has vast implications for health. Pathophysiological dysregulation, as evidenced by allostatic load, is associated with increased morbidity and mortality. Health disparities exist in both the incidence and outcomes of chronic stress. This study investigates the intersection of identity, allostatic load, and depression. METHODS/STUDY POPULATION: A nationally representative sample of pre-pandemic health data from the 2017-2020 cycle of the National Health and Nutrition Examination Survey (NHANES) was used to assess variation in depression and allostatic load by identity status. Datasets containing biomarker, mental health, and identity data were merged using Stata. An index of allostatic load was created by generating quartiles for nine biomarkers of cardiovascular (cholesterol, triglycerides, systolic and diastolic blood pressure), metabolic (glucose, body mass index, albumin, creatinine), and immune (c-reactive protein) functioning, and summing the total high risk biomarkers per person. Depression scores were averaged across nine items from the patient health questionnaire, and dichotomous identity variables (e.g., race) were generated. RESULTS/ANTICIPATED RESULTS: People identifying as female (t = 8.25, p < .001) or Black (t = 7.18, p < .001) have higher allostatic load scores, whereas people identifying as White (t = -2.64, p < .01) or Asian (t = -3.80, p < .001) have lower allostatic load scores. People identifying as female (t = 10.76, p < .001), White (t = 2.66, p < .01), or Another/Mixed race (t = 6.23, p < .001) have higher levels of depression, whereas people identifying as Asian (t = 9.17, p < .001) have lower levels of depression. Multiple regression analyses indicate a significant effect of depression on allostatic load when controlling for sociodemographic variables (B = 0.33, SE = 0.05, t = 7.02, p < .001). The identity*depression interaction increases allostatic load for females (B = 0.43, SE = 0.10, t = 4.21, p < .001) and racial/ethnic minority males (B = 0.25, SE = 0.10, t = 2.62, p < .01). DISCUSSION/SIGNIFICANCE: This study highlights differences in the experience of allostatic load and depression based on identity. Depression exerts an independent and moderating effect on allostatic load. Findings have implications for health disparity research, and highlight the dynamic intersection of identity, mental, and physical health in the face of chronic stress.

Using Pointwise Mutual Information for Breast Cancer Health Disparities Research With SEER-Medicare Claims.

Identification of procedures using International Classification of Diseases or Healthcare Common Procedure Coding System codes is challenging when conducting medical claims research. We demonstrate how Pointwise Mutual Information can be used to find associated codes. We apply the method to an investigation of racial differences in breast cancer outcomes. We used Surveillance Epidemiology and End Results (SEER) data linked to Medicare claims. We identified treatment using two methods. First, we used previously published definitions. Second, we augmented definitions using codes empirically identified by the Pointwise Mutual Information statistic. Similar to previous findings, we found that presentation differences between Black and White women closed much of the estimated survival curve gap. However, we found that survival disparities were completely eliminated with the augmented treatment definitions. We were able to control for a wider range of treatment patterns that might affect survival differences between Black and White women with breast cancer.

Health Disparities Investigator Development through a Team-Science Pilot Projects Program.

Profound health disparities are widespread among Native Hawaiians, other Pacific Islanders, and Filipinos in Hawai'i. Efforts to reduce and eliminate health disparities are limited by a shortage of investigators trained in addressing the genetic, socio economic, and environmental factors that contribute to disparities. In this conference proceedings report from the 2022 RCMI Consortium National Conference, we describe our mentoring program, with an emphasis on community-engaged research. Elements include our encouragement of a team-science, customized Pilot Projects Program (PPP), a Mentoring Bootcamp, and a mentoring support network. During 2017-2022, we received 102 PPP preproposals. Of these, 45 (48%) were invited to submit full proposals, and 22 (19%) were awarded (8 basic biomedical, 7 clinical, 7 behavioral). Eighty-three percent of awards were made to early-career faculty (31% ethnic minority, 72% women). These 22 awards generated 77 related publications; 84 new grants were submitted, of which 31 were awarded with a resultant return on investment of 5.9. From 5 to 11 investigators were supported by PPP awards each year. A robust usage of core services was observed. Our descriptive report (as part of a scientific conference session on RCMI specialized centers) focuses on a mentoring vehicle and shows how it can support early-stage investigators in pursuing careers in health disparities research.

Disaggregating Latino nativity in equity research using electronic health records.

To develop and validate prediction models for inference of Latino nativity to advance health equity research. This study used electronic health records (EHRs) from 19,985 Latino children with self-reported country of birth seeking care from January 1, 2012 to December 31, 2018 at 456 community health centers (CHCs) across 15 states along with census-tract geocoded neighborhood composition and surname data. We constructed and evaluated the performance of prediction models within a broad machine learning framework (Super Learner) for the estimation of Latino nativity. Outcomes included binary indicators denoting nativity (US vs. foreign-born) and Latino country of birth (Mexican, Cuban, Guatemalan). The performance of these models was compared using the area under the receiver operating characteristics curve (AUC) from an externally withheld patient sample. Census surname lists, census neighborhood composition, and Forebears administrative data were linked to EHR data. Of the 19,985 Latino patients, 10.7% reported a non-US country of birth (5.1% Mexican, 4.7% Guatemalan, 0.8% Cuban). Overall, prediction models for nativity showed outstanding performance with external validation (US-born vs. foreign: AUC = 0.90; Mexican vs. non-Mexican: AUC = 0.89; Guatemalan vs. non-Guatemalan: AUC = 0.95; Cuban vs. non-Cuban: AUC = 0.99). Among challenges facing health equity researchers in health services is the absence of methods for data disaggregation, and the specific ability to determine Latino country of birth (nativity) to inform disparities. Recent interest in more robust health equity research has called attention to the importance of data disaggregation. In a multistate network of CHCs using multilevel inputs from EHR data linked to surname and community data, we developed and validated novel prediction models for the use of available EHR data to infer Latino nativity for health disparities research in primary care and health services research, which is a significant potential methodologic advance in studying this population.

Bibliometric analysis of published research on pediatric health disparities

This study aimed to examine the current evidence in the medical literature on health disparities in the pediatric population. A bibliometric analysis of published research focused on health disparities in pediatric patients was conducted to analyze publication trends. A search of the Scopus database was conducted using keywords that were determined to be appropriate by the authors. This analysis helps determine which pediatric subspecialties may be lacking in health disparity research. A total of 2,380 publications from 1979 to 2021 met the inclusion criteria using the keywords “pediatric health disparities.” The number of articles published increased over the observation period, with 679 published between 2020-2021. When grouped by subspecialty, the majority of articles were associated with general pediatrics, followed by oncology, cardiology, nephrology, endocrinology, gastroenterology, neurology, pulmonology, and urology. When organized by health disparity risk factor or population, socioeconomics was the most common followed by race, urban, gender, rural, mental disability, physical disability, gender identity, religion and sexual orientation. The United States published more articles than any other country. The National Institute of Health has funded the majority of pediatric health disparities research. Pediatrics was found to be the leading journal of pediatric health disparity research. Research on pediatric health disparities is most frequently published in the United States, and is most focused on socioeconomics in a primary care setting. There is a large gap of research conducted in pediatric subspecialties, and on health disparities such as religion, sexual orientation, gender, and gender identity.

Methodologies used in studies examining substance abuse, violence and HIV/AIDS (SAVA) constructs using a syndemic framework: a scoping review

ABSTRACT The syndemic theoretical framework has been used in health disparities research to explain several co-occurring epidemics, particularly in populations facing disparate health conditions. A prominent example of this is seen in Singer’s Substance Abuse, Violence and HIV/AIDS (SAVA) syndemic theory. However, even though numerous studies support some of the theoretical underpinnings of the SAVA syndemic, the empirical applications of the theory remain methodologically underdeveloped. The current review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review (PRISMA-ScR), to present the state of the science of methodologies examining SAVA constructs using the syndemic framework. Seven bibliographic databases were searched with no language or date restrictions. Studies were synthesized by author, year of publication, study location, total sample size, study population, SAVA outcomes, analytic method of SAVA measurement, intervention type, level of influence, disease interaction and concentration, main findings of the study, and possible future areas of research. Our search yielded a total of 967 articles, and 123 were included in the review. Methodologic and statistical innovation is needed to elevate the impact of syndemic theory for elucidating the synergistic effects of determinants leading to health disparities.

The PhenX Toolkit: Measurement Protocols for Assessment of Social Determinants of Health

Social determinants are structures and conditions in the biological, physical, built, and social environments that affect health, social and physical functioning, health risk, quality of life, and health outcomes. The adoption of recommended, standard measurement protocols for social determinants of health will advance the science of minority health and health disparities research and provide standard social determinants of health protocols for inclusion in all studies with human participants. A PhenX (consensus measures forPhenotypes and eXposures) Working Group of social determinants of health experts was convened from October 2018 to May 2020 and followed a well-established consensus process to identify and recommend social determinants of health measurement protocols. The PhenX Toolkit contains data collection protocols suitable for inclusion in a wide range of research studies. The recommended social determinants of health protocols were shared with the broader scientific community to invite review and feedback before being added to the Toolkit. Nineteen social determinants of health protocols were released in the PhenX Toolkit (https://www.phenxtoolkit.org) in May 2020 to provide measures at the individual and structural levels for built and natural environments, structural racism, economic resources, employment status, occupational health and safety, education, environmental exposures, food environment, health and health care, and sociocultural community context. Promoting the adoption of well-established social determinants of health protocols can enable consistent data collection and facilitate comparing and combining studies, with the potential to increase their scientific impact.

A New Tool for Holistic Residency Application Review: Using Natural Language Processing of Applicant Experiences to Predict Interview Invitation.

Reviewing residency application narrative components is time intensive and has contributed to nearly half of applications not receiving holistic review. The authors developed a natural language processing (NLP)-based tool to automate review of applicants' narrative experience entries and predict interview invitation. Experience entries (n = 188,500) were extracted from 6,403 residency applications across 3 application cycles (2017-2019) at 1 internal medicine program, combined at the applicant level, and paired with the interview invitation decision (n = 1,224 invitations). NLP identified important words (or word pairs) with term frequency-inverse document frequency, which were used to predict interview invitation using logistic regression with L1 regularization. Terms remaining in the model were analyzed thematically. Logistic regression models were also built using structured application data and a combination of NLP and structured data. Model performance was evaluated on never-before-seen data using area under the receiver operating characteristic and precision-recall curves (AUROC, AUPRC). The NLP model had an AUROC of 0.80 (vs chance decision of 0.50) and AUPRC of 0.49 (vs chance decision of 0.19), showing moderate predictive strength. Phrases indicating active leadership, research, or work in social justice and health disparities were associated with interview invitation. The model's detection of these key selection factors demonstrated face validity. Adding structured data to the model significantly improved prediction (AUROC 0.92, AUPRC 0.73), as expected given reliance on such metrics for interview invitation. This model represents a first step in using NLP-based artificial intelligence tools to promote holistic residency application review. The authors are assessing the practical utility of using this model to identify applicants screened out using traditional metrics. Generalizability must be determined through model retraining and evaluation at other programs. Work is ongoing to thwart model "gaming," improve prediction, and remove unwanted biases introduced during model training.

Beyond Biological Essentialism: White Nationalism, Health Disparities Data, and the Cultivation of Lay Agnotology

ABSTRACT Scholars and practitioners position health disparities research as an important tool for redressing race-based inequities and re-conceptualizing racialized health outcomes in non-essentialist terms. Given this context, we explore a peculiar phenomenon, which is the circulation of such research among white nationalists. We discover that white nationalists incorporate and respond to health disparities research not solely to defend racist and essentialist reasoning, but also to project a discourse that indicts the science establishment for ostensibly incorporating liberal politics, corrupting inquiry, and obfuscating understanding of biology in the name of anti-racism or social constructionism. We term this practice “lay agnotology,” as it involves white nationalists capitalizing on their role as non-specialists to charge the health disparities field and its expert contributors with an alleged set of institutionalized biases that produce ignorance about the “truth” of race. We connect this finding to the literature on racialized ignorance, as it demonstrates how stories about the institutional nature of science can be as central to myth-making about race as stories about the scientific nature of people.

Abstract P115: Ethnic Differences in Cardiovascular Disease Deaths Among African American, African Immigrant and Afro-Caribbean Adults in the 1999-2018 National Health Interview Surveys

Background: Black persons are an heterogenous group in the US and bear a disparate higher burden of worse cardiovascular disease (CVD) outcomes. Our objective was to examine ethnic differences in CVD mortality among Black subgroups; African Americans(AAs); African Immigrants(AIs); and Afro Caribbeans(ACs). Methods: We analyzed the 1999-2018 National Health Interview Survey data, prospectively linked to mortality records in the National Death Index on 23,169,679 Black adults. The outcomes was CVD mortality, defined as CVD and cerebrovascular deaths, which was modelled as time till death (in years). This was calculated from each survey year till time of death or December 31, 2019 (administrative censoring) for those who survived. Using multivariable Cox proportional hazards regression analyses to model the survival function, we evaluated differences in CVD-and cerebrovascular-cause specific deaths among the three groups with progressive adjustment for age, sex, socioeconomic status and CVD risk factors. Results: With median of 10 years of mortality follow-up, there were 2.44, and 1.86 CVD deaths per 1,000 person-years among AA, and foreign born black adults (AIs and ACs combined), respectively. CVD mortality hazard was 81% lower in AIs [hazard ratio [HR], 0.19 (95% CI, 0.13–0.29], Table ) and 54% lower in ACs [HR, 0.46 (95% CI, 0.40–0.53], than among AAs. Compared to AAs, age-and sex-adjusted CVD mortality hazard was lower among AIs by 66% [HR, 0.34 (95% CI, 0.23–0.51], Table ) and ACs (HR, 0.46 [95% CI, 0.40–0.53]) by 54% (unchanged from unadjusted). In the fully adjusted model with SES and CVD risk factors adjustment, ACs had 41% lower adjusted CVD mortality hazard than AA adults (HR, 0.59 [95% CI, 0.45–0.77]). Conclusions: Cardiovascular deaths were higher among US-born AAs than foreign-born ACs. Nativity status is an important determinant of CVD mortality, and the heterogeneity of this population should be considered in health disparities research and interventions.

Abstract P377: The Restore Health Equity Research Network: An American Heart Association-Funded Initiative to Prevent Hypertension in Black Communities

Introduction: The RESTORE Network is an American Heart Association-funded health equity research network that is testing the implementation of evidence-based interventions for hypertension prevention in community settings. The goals are to: (1) Work with Black communities to mitigate the negative impact of social determinants of health on blood pressure (BP) in Black adults; (2) Develop and test strategies for implementing evidence-based lifestyle interventions in Black communities; (3) Disseminate findings to policy makers, payors and stakeholders to promote adoption of effective hypertension prevention strategies in Black communities; and (4) Train early-career scientists in health equity and hypertension research. Methods: RESTORE Network investigators across eight institutions are conducting five hybrid implementation-effectiveness trials to test scalable, sustainable, and potentially cost-effective implementation strategies to mitigate adverse social determinants of health that contribute to the high prevalence of hypertension in Black communities. The implementation strategies include the use of: 1) trained community health workers (Alabama, Baltimore, Detroit); 2) community-based organizations as portals of food access and patient navigation (New York City, Alabama, Boston, Detroit); 3) patient activation via home BP monitoring (Baltimore); and 4) digital technologies (Baltimore, Detroit). The social determinants of health targeted are: poor access to care, low health literacy, food insecurity, barriers to physical activity, neighborhood deprivation, under-insurance, and inadequate linkage to medical and social services. The five projects are based on the National Institute on Minority Health and Health Disparities (NIMHD) Research Framework, and evaluation of each implementation strategy is guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation and Maintenance) implementation research framework. The projects are supported by five highly-integrated cores (BP Measurement, Statistical, Intervention, Community Engagement, Training). RESTORE will advance the career of early stage investigators in hypertension, health equity, implementation science and community-engaged research; trainees will work on network projects, develop their own projects, complete rotations across network sites, and attend lectures and workshops. Synergy across projects will facilitate economic and scale-up analyses to inform policy makers on the strategies being tested. Discussion: The RESTORE Network will advance health equity in the U.S. by identifying community-driven, sustainable and effective implementation strategies to deliver lifestyle interventions that prevent hypertension in Black adults. The strong infrastructure of the network will support new collaborations and ancillary studies that are aligned with our mission.

Elucidating factors contributing todisparities in pain-related experiences among adults with or at risk for knee osteoarthritis.

We and others have reported ethnic/race group differences in clinical pain, physical function, and experimental pain sensitivity. However, recent research indicates that with consideration for socioenvironmental factors, ethnicity/race differences become less or non-significant. Understanding of factors contributing to pain inequities are needed. Guided by the NIA and NIMHD Health Disparities Research Frameworks, we evaluate the contributions of environmental and behavioral factors on previously reported ethnic/race group differences in: (1) clinical pain, (2) physical function, and (3) experimental pain in individuals with knee pain. Baseline data from Understanding of Pain and Limitations in Osteoarthritis Disease (UPLOAD) and UPLOAD-2 studies were analyzed. Participants were adults 45 to 85 years old who self-reported as non-Hispanic white (NHW) or black (NHB) with knee pain. A health assessment and quantitative sensory testing were completed. Sociodemographics, environmental, health, clinical and experimental pain, and physical functioning measures were included in nested regressions. Pooled data from 468 individuals, 57 ± 8 years of age, 63% women, and 53% NHB adults. As NHB adults were younger and reported greater socioenvironmental risk than the NHW adults, the term sociodemographic groups is used. With inclusion of recognized environmental and behavioral variables, sociodemographic groups remained a significant predictor accounting for <5% of the variance in clinical pain and physical function and <10% of variance in experimental pain. The incorporation of environmental and behavioral factors reduced relationships between sociodemographic groups and pain-related outcomes. Pain sites, BMI, and income were significant predictors across multiple models. The current study adds to a body of research on the complex array of factors contributing to disparities in pain-related outcomes.

Call to action: Clinical pharmacist roles and opportunities in health disparities research

The roles clinical pharmacists can play in addressing health equity and eliminating health disparities span the areas of quality of care, access to care, use of care, and health outcomes. Through this call to action, we address the importance of dismantling health disparities and describe the potential barriers and challenges to clinical pharmacists becoming involved with and performing health disparities research. Furthermore, we identify solutions to these barriers and challenges by highlighting opportunities for clinical pharmacists to seek training and identify potential funding sources for health disparities research. In addition, we provide examples of previous health disparities research conducted by pharmacists across a wide spectrum of patient populations, areas of practice, and types of research. The goal moving forward is to continue to promote current training opportunities to allow clinical pharmacists to develop and/or improve on their research skillset to expand pharmacist-led research within the focus area of health disparities and ultimately serve as leaders and collaborators in the area.

Evaluation of AIML + HDR-A Course to Enhance Data Science Workforce Capacity for Hispanic Biomedical Researchers.

Artificial intelligence (AI) and machine learning (ML) facilitate the creation of revolutionary medical techniques. Unfortunately, biases in current AI and ML approaches are perpetuating minority health inequity. One of the strategies to solve this problem is training a diverse workforce. For this reason, we created the course "Artificial Intelligence and Machine Learning applied to Health Disparities Research (AIML + HDR)" which applied general Data Science (DS) approaches to health disparities research with an emphasis on Hispanic populations. Some technical topics covered included the Jupyter Notebook Framework, coding with R and Python to manipulate data, and ML libraries to create predictive models. Some health disparities topics covered included Electronic Health Records, Social Determinants of Health, and Bias in Data. As a result, the course was taught to 34 selected Hispanic participants and evaluated by a survey on a Likert scale (0-4). The surveys showed high satisfaction (more than 80% of participants agreed) regarding the course organization, activities, and covered topics. The students strongly agreed that the activities were relevant to the course and promoted their learning (3.71 ± 0.21). The students strongly agreed that the course was helpful for their professional development (3.76 ± 0.18). The open question was quantitatively analyzed and showed that seventy-five percent of the comments received from the participants confirmed their great satisfaction.

Trust and Biomedical Research Engagement of Minority and Under-Represented Communities in Mississippi, USA.

Trust is critical to the development and maintenance of effective research collaborations and community engagement. The purpose of this study was to assess the current attitudes and level of trust pertaining to health research among residents of Central Mississippi, the priority health region for the Research Centers in Minority Institutions (RCMI) Center for Health Disparities Research (RCHDR) at Jackson State University. The cross-sectional study was conducted from November 2021 to April 2022. The data were analyzed using descriptive statistics carried out by SPSS statistical software. A total of 146 participants responded to the survey. The participants were predominately African American (99%) and female (75%). Historical research studies, the researchers' qualities, and potential benefits from participation were factors affecting the level of trust in the research process. Ninety percent (n = 131) expressed that it was important to be involved in the research process, and 98.5% (n = 144) agreed that discussing the research findings with the participants was important for establishing trust in the research process. While trust in the research process does not guarantee participation, trust is a precursor for those who decide to engage in health disparities research. Key findings will be integrated into the RCHDR research agenda to foster further development and implementation of innovative community-based participatory research toward the control and/or prevention of diseases that disproportionately affect minority and under-represented populations in Mississippi.