Exacerbate Health Disparities Research Articles

Ethics and governance of trustworthy medical artificial intelligence

BackgroundThe growing application of artificial intelligence (AI) in healthcare has brought technological breakthroughs to traditional diagnosis and treatment, but it is accompanied by many risks and challenges. These adverse effects are also seen as ethical issues and affect trustworthiness in medical AI and need to be managed through identification, prognosis and monitoring.MethodsWe adopted a multidisciplinary approach and summarized five subjects that influence the trustworthiness of medical AI: data quality, algorithmic bias, opacity, safety and security, and responsibility attribution, and discussed these factors from the perspectives of technology, law, and healthcare stakeholders and institutions. The ethical framework of ethical values-ethical principles-ethical norms is used to propose corresponding ethical governance countermeasures for trustworthy medical AI from the ethical, legal, and regulatory aspects.ResultsMedical data are primarily unstructured, lacking uniform and standardized annotation, and data quality will directly affect the quality of medical AI algorithm models. Algorithmic bias can affect AI clinical predictions and exacerbate health disparities. The opacity of algorithms affects patients’ and doctors’ trust in medical AI, and algorithmic errors or security vulnerabilities can pose significant risks and harm to patients. The involvement of medical AI in clinical practices may threaten doctors ‘and patients’ autonomy and dignity. When accidents occur with medical AI, the responsibility attribution is not clear. All these factors affect people’s trust in medical AI.ConclusionsIn order to make medical AI trustworthy, at the ethical level, the ethical value orientation of promoting human health should first and foremost be considered as the top-level design. At the legal level, current medical AI does not have moral status and humans remain the duty bearers. At the regulatory level, strengthening data quality management, improving algorithm transparency and traceability to reduce algorithm bias, and regulating and reviewing the whole process of the AI industry to control risks are proposed. It is also necessary to encourage multiple parties to discuss and assess AI risks and social impacts, and to strengthen international cooperation and communication.

Pharmacogenomic variabilities in geo-ancestral subpopulations and their clinical implications: Results of collaborations with Hmong in the United States.

Underrepresentation of subpopulations within geo-ancestral groups engaged in research can exacerbate health disparities and impair progress toward personalized medicine. This is particularly important when implementing pharmacogenomics which uses genomic-based sources of variability to guide medication selection and dosing. This mini-review focuses on pharmacogenomic findings with Hmong in the United States and their potential clinical implications. By actively engaging Hmong community in pharmacogenomic-based research, several clinically relevant differences in allele frequencies were observed within key pharmacogenes such as CYP2C9 and CYP2C19 in Hmong compared to those in either East Asians or Europeans. Additionally, using state-of-the-art genome sequencing approaches, Hmong appear to possess novel genetic variants within CYP2D6, a critical pharmacogene affecting pharmacokinetics of a broad range of medications. The allele frequency differences and novel alleles in Hmong have translational impact and real-world clinical consequences. For example, Hmong patients exhibited a lower warfarin stable dose requirement compared to East Asian patients. This was predicted based on Hmong's unique genetic and non-genetic factors and confirmed using real-world data from clinical practice settings. By presenting evidence of the genetic uniqueness and its translational impact within subpopulations, such as the Hmong, we hope to inspire greater inclusion of other geo-ancestrally underrepresented subpopulations in pharmacogenomic-based research.

Abstract C037: Polyethnic-1000: A New York-based initiative to advance cancer genomics through recruitment of diverse racial & ethnic populations

Abstract Recent advances in DNA sequencing technologies have revolutionized approaches to the prevention, early detection, diagnosis, and treatment of cancers. However, our current knowledge about tumor biology, cancer risk, and response to treatment is limited due to significant underrepresentation of non-European populations in genomic cancer research, including clinical trials. The vast majority of samples in publicly available genomic databases have been derived from patients of European descent. These inequities limit our understanding of cancer and the impact of ancestry on the various manifestations of this disease. Moreover, exclusion of minoritized populations may exacerbate health disparities and stymie their ability to equally benefit from participation in trials or the innovations that result from such studies. Through the Polyethnic-1000 (P1000) initiative, we sought to leverage the racial and ethnic diversity within New York City to conduct initial investigations that address the existing disparities in cancer genomics studies. We recruited healthcare facilities to join the P1000 Consortium with a particular focus on hospitals outside Manhattan that served a diverse racial and ethnic population. In Phase 1, clinical and scientific protocols were implemented to collect and process 176 archival tumor samples representing 39 cancer types from individuals who self-identified as “non-white.” This pilot study confirmed our ability to procure and analyze tissues using whole-exome and RNA sequencing. Importantly, we estimated each participant’s percentage of ancestry at the continental and subregional levels by applying ADMIXTURE software to our tumor samples using the reference populations from the 1000 Genomes Project. We observed that genetic information nearly always correlates at least partially with self-identified origins, but genetic classifications are more specific and allow the identification of mixed ancestry. We entered Phase 2 of the P1000 Initiative by launching a research program. The awards allowed investigators in the Consortium to compete for support of new or recently initiated projects designed to identify ancestry-associated genomic determinants in specific cancer types. We funded seven of the competing groups; the projects span eight primary cancers. All but one of the studies are focused on individuals of African ancestry; one addresses lung cancer in East Asian patients. With support from Illumina, we plan to perform tumor/normal whole genome sequencing and tumor RNASeq on 1000 cases. The resulting data set would be among the largest and most diverse collection of full-genome pairs available in oncology. It will be housed at the NYGC with initial access for all members of the P-1000 Consortium then for the entire research community after an embargo period. P1000 has established a framework to enhance interactions among our region’s academic and health centers to advance cancer genomics. These efforts should improve and widen the use of genomics for all, especially currently underserved racial and ethnic populations. Citation Format: Onyinye Balogun, Melissa Davis, Michelle Mehallow, Nicolas Robine, Lara Winterkorn, Dayna Oschwald, Michael Zody, Samuel Aparicio, Tom Maniatis, Harold Varmus, Charles Sawyers, David Tuveson. Polyethnic-1000: A New York-based initiative to advance cancer genomics through recruitment of diverse racial & ethnic populations [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr C037.

Analyzing disparities in access to teledermatology compared with dermatology clinic visits before, during, and after COVID-19 quarantine.

The COVID-19 pandemic has caused significant changes in dermatologic care, likely exacerbating health disparities for specific minority populations. The use of teledermatology has also become more prevalent during this period. The aim of this study was to determine if the proportion of teledermatology versus office-based visits varied significantly during three study periods of the COVID-19 pandemic. The secondary objective was to determine whether there are significant differences in the use of office-based dermatology versus teledermatology care across the following demographic subgroups: insurance type, race/ethnicity, age, and language during the same periods. A chart review of dermatology visits in electronic medical records at a tertiary referral center in Washington, DC, was conducted. The overall telehealth visit rate was 0% in the prequarantine period, 61.12% during the quarantine period, and 10.59% in the postquarantine period. After assessing telehealth utilization rates among the demographic subgroups, we noted that Medicaid users, Black patients, 64-year-olds or older, and English speakers may benefit the least from telehealth services. Teledermatology use necessitated by the COVID-19 pandemic may have promoted health care disparities for specific marginalized populations.

Health Techequity: Opportunities for Digital Health Innovations to Improve Equity and Diversity in Cardiovascular Care.

In this review, we define health equity, disparities, and social determinants of health; the different components of digital health; the barriers to digital health equity; and cardiovascular digital health trials and possible solutions to improve health equity through digital health. Digital health interventions show incredible potential to improve cardiovascular diseases by obtaining longitudinal, continuous, and actionable patient data; increasing access to care; and by decreasing delivery barriers and cost. However, certain populations have experienced decreased access to digital health innovations and decreased representation in cardiovascular digital health trials. Special efforts will need to be made to expand access to the different elements of digital health, ensuring that the digital divide does not exacerbate health disparities. As the expansion of digital health technologies continues, it is vital to increase representation of minoritized groups in all stages of the process: product development (needs findings and screening, concept generation, product creation, and testing), clinical research (pilot studies, feasibility studies, and randomized control trials), and finally health services deployment.

Equity of referrals to type 2 diabetes rehabilitation in a universal welfare state

ObjectiveDespite aims of equal access to treatment and care in the Nordic countries, marked socioeconomic inequality in the development of type 2 diabetes (T2D) complications persists. The study purpose was to estimate the associations of individual socioeconomic position and deprivation at the general practitioner (GP) level with referrals to T2D rehabilitation.Research Design and Methods: In 2015–2018, 3390 people affiliated with 432 primary GPs living in the municipality of Copenhagen were identified through registry data as newly diagnosed with T2D. Of these, 656 (19%) individuals were referred to municipal rehabilitation services in 2015–2021. Individual socioeconomic position was measured by education, income, and employment. The Danish Deprivation Index (DADI) was used as a measure of GP-level deprivation. ResultsPatients were more likely to be referred to municipal rehabilitation if they had low vs. high income (hazard ratio (HR) 2.87 [women], 1.64 [men]), were not employed vs. employed (HR 1.95 [women], 1.23 [men]) and were affiliated with GPs with a low vs. very high level of deprivation (HR 7.63 [women], 4.30 [men]). The results suggest that GPs practice proportionate universalism by allocating treatment to lower socioeconomic individuals in likely higher need of care. However, the overall HR for referrals was lower among GPs with more deprived patient populations, indicating unequal treatment of all citizens, which conflicts with the aims of general universal health care. Inequality in rehabilitation healthcare services must be further addressed and investigated to prevent exacerbating health disparities.

Providers' reflections on infrastructure and improvements to promote access to care for Veterans experiencing housing instability in rural areas of the United States: A qualitative study.

Veterans in rural areas of the United States face barriers to accessing healthcare and other services, which are intensified for those experiencing housing instability. Recent legislative acts have the potential to address obstacles faced by rural patients in the U.S. This study explores how infrastructure-including features related to the physical and digital environment-impacts the ability of rural Veterans experiencing housing instability to access healthcare and related services from the perspective of homeless service providers within the Veterans Health Administration (VHA). We conducted semi-structured telephone interviews (n=22) with providers in high/low performing and/or resourced communities across the U.S. in May and June 2021 and analysed transcripts using template analysis. Themes described by providers highlight how infrastructure limitations in rural areas can exacerbate health disparities for Veterans experiencing housing instability, the impact of COVID-19 on service access, and recommendations to enhance service delivery. Providers suggested that VHA reconfigure where and how staff work, identify additional resources for transportation and/or alternative transportation models, and increase Veterans' access to technology and broadband Internet. Federal infrastructure investments should address challenges faced by Veterans experiencing housing instability in rural areas and the concerns of providers connecting them with care.

How Dissemination and Implementation Science Can Contribute to the Advancement of Learning Health Systems.

Many health systems are working to become learning health systems (LHSs), which aim to improve the value of health care by rapidly, continuously generating evidence to apply to practice. However, challenges remain to advance toward the aspirational goal of becoming a fully mature LHS. While some important challenges have been well described (i.e., building system-level supporting infrastructure and the accessibility of inclusive, integrated, and actionable data), other key challenges are underrecognized, including balancing evaluation rapidity with rigor, applying principles of health equity and classic ethics, focusing on external validity and reproducibility (generalizability), and designing for sustainability. Many LHSs focus on continuous learning cycles, but with limited consideration of issues related to the rapidity of these learning cycles, as well as the sustainability or generalizability of solutions. Some types of data have been consistently underrepresented, including patient-reported outcomes and preferences, social determinants, and behavioral and environmental data, the absence of which can exacerbate health disparities. A promising approach to addressing many challenges that LHSs face may be found in dissemination and implementation (D&I) science. With an emphasis on multilevel dynamic contextual factors, representation of implementation partner engagement, pragmatic research, sustainability, and generalizability, D&I science methods can assist in overcoming many of the challenges facing LHSs. In this article, the authors describe the current state of LHSs and challenges to becoming a mature LHS, propose solutions to current challenges, focusing on the contributions of D&I science with other methods, and propose key components and characteristics of a mature LHS model that others can use to plan and develop their LHSs.

Addressing Shortcomings in Contingency Standards of Care

Addressing Shortcomings in Contingency Standards of Care

Improving African Americans’ Intentions to Enroll in a Health Registry: Message Development and Evaluation

ABSTRACT African Americans’ enrollment in health registries is low, negatively affecting their representation in clinical research. Young African Americans are particularly underrepresented. Because medical discoveries are typically based on findings from research that lacks minority representation, new treatments may not be equally effective with members of the African American community. This may further exacerbate health disparities. In this two-phase study, we first collected data from five focus groups to (a) investigate young African Americans’ knowledge about and attitudes toward health registries and (b) explore their perceptions about current messages used to recruit participants into health registries. The findings from the first phase of our research showed that participants had limited awareness and understanding of health registries’ functions and held negative attitudes toward research participation. In Phase 2, we conducted an experiment to compare the effects of a current message, a new message designed based on the findings from our Phase 1 study, and a control. Results showed mixed findings on the impact of the new targeted message. Based on the findings from both phases of this study, we present and discuss future strategies.

Legal Needs, Health, and Health Care Utilization Among Patients Participating in the Delaware Medical Legal Partnership.

Context:Unmet legal needs can exacerbate health disparities and contribute to a lack of adherence to treatment plans and medical recommendations for care. Medical legal partnerships (MLPs) are integrated health care and legal aid interventions offered by many health systems in the United States. Although much research has been published regarding the success of MLPs with specific patient groups, there is a gap in literature regarding the nature of MLPs in a more general, at-risk patient population.Objective:We aimed to better understand specific patient characteristics and health outcomes associated with different iHELP legal needs.Design:This is a cross-sectional study of patients who were enrolled in the Delaware MLP (DMLP) from November 2018 to June 2020 (N = 212).Setting:The DMLP is a collaboration between ChristianaCare, a Mid-Atlantic health system, and the Community Legal Aid Society, Inc (CLASI).Participants:Patients must be adults (ie, 18 years or older), below 200% of the federal poverty level (eg, ≤$53 000 for a household of 4 as of 2021), have at least one qualifying legal need, and live in the state.Intervention:The DMLP is designed to address unmet legal needs that fall under a framework called iHELP. iHELP legal domains are income and insurance (i), housing and utilities (H), education and employment (E), legal status (L), and personal and family stability (P).Main Outcome Measures:Outcomes of interest were iHELP legal needs, patient demographics, perceived stress and mental and physical health–related quality of life, comorbidities, and health care utilization.Results:Housing and utilities (46.2%) and income support (41.5%) were the highest reported legal needs. Perceived stress scores were significantly higher for those with income needs (P = .01) as well as those with housing and utilities needs (P = .01).Conclusions:MLP programs offer a value-added service that can address unmet legal needs in vulnerable, at-risk patients.

The relationship between health and political ideology begins in childhood

We investigate whether childhood health status influences adult political ideology and whether health at subsequent life-stages, adolescent personality traits, or adolescent academic aptitude mediate this relationship. Using a national longitudinal cohort sample, we found that better health among children under age 10 was positively related to conservative political ideology among adults over age 64. Children with excellent health compared to very poor health were 16 percentage points more likely to report having a conservative political ideology in adulthood. Children with excellent health compared to very poor health were 13 percentage points less likely to report having a liberal political ideology in adulthood. Adults who had excellent health as children were 30 percentage points more likely to report conservative ideology than liberal ideology. However, the difference in ideological position for adults who had very poor childhood health was negligible. That is, the health and ideology relationship is being driven by those who were healthier early in life, after controlling for family income and material wealth. No evidence was found for mediation by adolescent heath, adult heath, adolescent personality traits, or adolescent academic aptitude. The magnitude of the coefficient for childhood health was substantively and statistically equivalent across race and sex. We discuss the possibility that, instead of being mediated, childhood health may actually be a mediator bridging social, environmental, and policy contexts with political ideology. We also discuss the potential of social policy to influence health, which influences ideology (and voting participation), which eventually circles back to influence social policy. It is important to understand the nexus of political life and population health since disparities in voice and power can exacerbate health disparities.

Ethnoracial Inclusion in Clinical Trials of Ketamine in the Treatment of Mental Health Disorders

Despite strong evidence for the safety and efficacy of ketamine in the treatment of mood disorders, the enrollment of Black, Indigenous, and People of Color (BIPOC) has not been a focus of this research. Health disparities in the treatment of mood disorders in BIPOC indicate a strong need to understand the clinical, social, and pharmacological aspects of this novel treatment in people of color. A comprehensive methodological search for double-blind, placebo-controlled, randomized ketamine clinical trials published from 1993 to 2020 was conducted across several databases to analyze the demographics of trial participants. Researchers contacted corresponding authors to obtain additional information. Only 10 studies provided sufficient information for quantitative analysis. Among these studies (n = 380 participants), 73.7% of the participants were non-Hispanic White, 9.2% were Black, 5.0% were Hispanic/Latinx, and 0.8% were Asian. Higher BIPOC inclusion was negatively correlated with the number of recruitment methods implemented across sites. The present study may underestimate the participation of BIPOC because of the lack of demographic information collected or published. BIPOC are greatly underrepresented in ketamine clinical trials despite high rates of mood disorders. Reported treatment outcomes may not generalize to all ethnic and cultural groups and significant disparities in access to such novel treatment paradigms exacerbate health disparities.

NIH Nutrition Health Disparities Framework: A Model to Advance Health Equity

ObjectivesDisparities in nutrition such as poor diet quality and inadequate nutrient intake arise from multiple factors and are related to adverse health outcomes such as obesity, diabetes, cardiovascular disease, and diet-related cancers. The objective is to develop a nutrition-centric socioecological (SE) framework that delineates determinants and levels of influence that perpetuate diet-related disparities among disadvantaged populations. MethodsAdapted from the National Institute of Minority Health and Health Disparities Research Framework, the Nutrition Health Disparities Framework (NHDF) examines the synergistic interactions across biological, behavioral, and environmental domains at every SE level that contribute to nutrition health disparities. Based on the scientific literature, NIH nutrition experts developed a consensus in selecting nutrition-related determinants of health within each domain and SE level when creating the NHDF. ResultsThe NHDF identifies how neighborhood food availability, access, and affordability (individual/built environment) can intersect with cultural norms and practices (interpersonal/sociocultural environment) to influence dietary behaviors and risk for diet-related disease. Similarly, the NHDF shows how genetic predisposition (individual/biology), family dietary practices (interpersonal/behavioral), and food marketing policies (societal) may promote the consumption of unhealthy foods and increase chronic disease risk. Additionally, family and peer norms (interpersonal/behavior) related to breastfeeding and early childhood nutrition can interact with resource-poor environments such as lack of preventative health care (societal/health care system) and inadequate use of Federal nutrition programs (societal/behavioral), which may increase the risk for childhood malnutrition and food insecurity. ConclusionsThe NHDF expands our understanding of the synergistic interrelationships among factors at different levels of the SE model that influence nutrition-related outcomes and exacerbate health disparities. This framework is an important resource for nutrition professionals and researchers and may inform the development of multilevel nutrition interventions to improve health outcomes and increase health equity in diverse populations. Funding SourcesN/A.

Rural disparities in oncology patient portal enrollment and use.

6557 Background: Patient portals support patient access, engagement, and care coordination, yet could also widen the digital divide and exacerbate disparities among vulnerable populations. There is emerging evidence that racial/ethnic minority patients are less likely to use portals, yet prior research has not examined potential rural differences. We identified sociodemographic factors associated with portal enrollment and use among a racially and geographically diverse population of cancer patients. Methods: We retrospectively examined portal enrollment and use at an NCI-designated comprehensive cancer center from January 2015 until February 2022 among patients 18+ years old with a neoplastic disease diagnosis (ICD-10-CM C00-D49). Potential predictors included gender, race/ethnicity, marital status, age, rural (Rural-Urban Continuum Codes [RUCC] 4-9) vs nonrural (RUCC 1-3) residence, residential distance from the cancer center, and time since diagnosis. We used multivariable logistic regression to generate odds ratios (ORs) for portal enrollment and having ever sent a portal message, and Poisson regression to determine incidence rate ratios (IRRs) for number of logins and number of healthcare team interactions (portal messages or appointment requests), controlling for ICD-10 diagnosis (SAS 9.4). Results: We identified 11,333 patients (average age 67 years, 59% female, 24% rural, 10% Non-Hispanic Black, 1% Hispanic, 20% non-melanoma skin cancer, 14% breast cancer, 9% lung cancer). 36% of patients had enrolled in the portal, and of these, 80% had sent at least one message. Patients logged in a median of 203.5 times and had a median of 19 portal interactions. Rural residents were less likely to enroll in the portal than urban patients (28% vs 38%, p < 0.0001). Non-Hispanic Black patients and Hispanic/Latinx patients were less likely to enroll in the portal compared with non-Hispanic White patients (22% and 27%, respectively, vs 38.5%, p < 0.0001). Women, younger patients, more recently diagnosed cancer patients, and patients who were married/ partnered were significantly more likely to enroll. In multivariable analysis controlling for cancer type, rural patients were half as likely to enroll in the portal (OR: 0.48 [0.43-0.54]). Among those enrolled, rural residents were 25% less likely to have ever sent a portal message (OR: 0.75 [(0.62-0.92]), and had nearly half the login and interaction rates (IRR: 0.66 [0.66-0.67]; IRR: 0.58 [0.58-0.59], respectively). Patients who were Non-Hispanic Black, Hispanic, or unmarried were also significantly less likely to enroll or engage in the portal. Conclusions: Patient portals remain underutilized among cancer patients, despite an increased reliance on virtual communications in the COVID era. Interventions to support portal engagement among rural residents and racial/ethnic minority patients are needed to avoid potentially exacerbating health disparities.

Disparities in Food Insecurity During the Coronavirus Disease 2019 Pandemic

ObjectivesThe prevalence and severity of food insecurity exists disproportionately among different population groups in the United States, with the potential to exacerbate health disparities among at-risk communities. Overall food insecurity has increased during the COVID-19 pandemic, but whether this additional burden is experienced differentially among certain population groups requires further study. This study seeks to investigate the association between food insecurity and socioeconomic factors among the US population during the COVID-19 pandemic, comparing rate of food insecurity by age, gender, and racial groups to identify vulnerable populations. MethodsData from the 2020–21 US Census Bureau’s Household Pulse Survey were used, from 06-January 2021 to 05-July 2021 (N = 884,695). The data were combined to increase the sample size and statistical power. Complex survey design was applied to represent the US population. The outcome of being food insecure was defined as “Sometimes/always don’t have enough food to eat,” and a logistic regression model was fitted to show the association with sociodemographic factors. Proportion of participants reporting food insecurity were examined by age, gender, and racial group to identify the intersection of demographic factors with the highest food insecurity rate. ResultsWe found that compared to males, females had higher likelihood of being food insecure (OR = 1.25, 95%CI:1.21,1.29); compared to 65+ years, people aged 25–39 years were more food insecure (OR = 3.3, 95%CI: 3.06,3.56); compared to white, the non-Hispanic black (NHB) shows an elevated likelihood of food insecurity (OR = 2.18, 95%CI: 2.1,2.27). We also found that the probability of food insecurity increases with more children in the household and decreases with higher education level. Among all job types, people who are self-employed had lowest likelihood of being food insecure. Loss of job was strongly associated with food insecurity (OR = 3.21, 95%CI: 3.10,3.31). The most vulnerable group was NHB, 25–39 years old, male, with a 24.8% (N = 3,857) rate of food insecurity. ConclusionsThis analysis shows national food insecurity disparities among demographic and socioeconomic factors during the COVID-19 pandemic. Future research aims to examine how the additional burden from COVID-19 was managed by communities identified as most at-risk. Funding SourcesN/A.

Disparities among smokers during the COVID-19 pandemic: Examination of COVID-19-related worries by sociodemographic factors in a U.S. Nationally representative survey

Low-socioeconomic status (SES) and certain racial/ethnic minority groups disproportionately experience tobacco-related disease and death. Underserved populations of smokers may be at disproportionate risk for elevated stress and worry related to basic needs and healthcare during the pandemic, which could impede smoking cessation and exacerbate health disparities. This study examined whether experiences with stress and worry among smokers during the COVID-19 pandemic differed by sociodemographic factors, and whether these factors predicted serious psychological distress (SPD). Data came from an October-November 2020 U.S. national representative survey of 1,223 current cigarette smokers. Analyses examined associations between sociodemographic factors with COVID-19-related worries and past-month SPD. Worry in most domains (e.g., food, housing, finances, healthcare) was more prevalent among participants with less than high school education, income less than $30,000, and those who were unemployed. Women and participants aged 30–44, with income less than $30,000, with less than high school education, not working/disabled, or on Medicaid were more likely to experience SPD. Examined separately, each COVID-19 worry predicted higher likelihood of SPD. In adjusted models, COVID-19 worries about finances (aOR = 2.3) and isolation/loneliness (aOR = 3.0) uniquely predicted SPD. Among U.S. adult smokers during the COVID-19 pandemic, those with lower SES indicated disproportionately high worry about access to basic needs and were more likely to experience SPD. Policies and interventions that address basic needs and mental health among marginalized populations of tobacco users are needed.

Health Disparities in Cardiometabolic Traits: Genomics, Gaps, and Paradoxes

Cardiometabolic traits vary considerably across ancestry groups, creating interest in disentangling the contributing factors to minimize health disparities. While environmental factors, such as socioeconomic status, access to healthcare, and lifestyle, are expected to play a large role in these differences, the contribution of genomics is less clear. This presentation will consider health disparities in cardiometabolic traits and the role of genomics can play in disentangling or exacerbating these disparities, with examples drawn from serum lipids and African ancestry populations. Serum lipids (especially HDL cholesterol and triglycerides) manifest clear differences in distribution across ancestries. While individuals of African ancestry often experience worse cardiometabolic outcomes (e.g., higher rates of hypertension, obesity, and diabetes), healthier mean serum lipid concentrations are generally observed among those of African ancestry. This lipid profile persists in those of West African ancestry across the African Diaspora, despite differences in social factors and lifestyle, lending support to genomic influences. This distribution, however, does not translate into a reduced rate of lipids‐associated cardiometabolic diseases, for reasons which are unclear, and this discrepancy has implications for use of lipid biomarkers for identifying individuals with disease risk. Well‐powered genomic studies of serum lipids in African ancestry individuals are emerging, revealing novel loci along with some evidence of gene‐lifestyle interactions and differing associations among subcontinental groups. These studies, along with increasing publications of other cardiometabolic traits in African and other non‐European ancestry individuals, are of great importance in a field plagued by underrepresentation of non‐European ancestry individuals. This underrepresentation has profound implications for the clinical utility of genomic discoveries. Without attention to this issue, genomics is poised to exacerbate health disparities in non‐EUR ancestry groups. African ancestry individuals are poorly represented in key genomic databases, yet their profound genetic diversity makes it likely to find variants among them that are not present in other populations. This imbalance can lead to clinical care that is sub‐optimal for those of African ancestry compared to better‐represented groups, a rising concern with increasing use of genomics in clinical decisions. For example, polygenic risk scores, derived from large, well‐powered GWAS, can predict disease risk for some traits of a magnitude that rivals Mendelian risk transmission, growing closer to clinical utility. Unfortunately, because of the comparatively limited representation of non‐European ancestry individuals in the underlying GWAS, these tools perform more poorly in these individuals. While these findings call for a greater number of genomic studies in diverse populations, attention also must be paid to the way individuals of non‐European ancestry are included and presented to ensure that the results facilitate the advancements their inclusion can address. Genomics has the potential to promote understanding of health disparities, but care must be given that they do not play a role in exacerbating them.

Financial fragility and demographic factors predict pet owners' perceptions of access to veterinary care in the United States.

Access to veterinary care is critical for pet, human, and community health. However, inequities in how easily pet owners can access veterinary care may exacerbate health disparities in vulnerable populations. This research analyzed pet owners' perceptions of access to veterinary care in order to understand how demographic characteristics and financial fragility predict perceived access to veterinary services. This study utilized survey data (n = 750) from a larger cross-sectional survey of adults in the US conducted by the Tufts University Equity Research Group. Survey data were collected in May and June of 2020 from a nationally representative group of pet owners via an online panel. Descriptive statistics, ANOVAs, and a sequential linear regression model were conducted in order to predict perceived access to veterinary care. Results of a sequential linear regression model indicated that race or ethnicity, education, and financial fragility significantly predicted perceived ease of access to veterinary care (F[7,617] = 19.80; P < .001). Additionally, financial fragility was prevalent among most pet owners of almost all income brackets, highlighting the need for more research into the cost burden of veterinary care. Future studies should focus on diverse sampling strategies that capture the experiences of minority pet owners in order to further understand issues of access in veterinary medicine.

Leveraging fine-mapping and multipopulation training data to improve cross-population polygenic risk scores.

Polygenic risk scores (PRS) suffer reduced accuracy in non-European populations, exacerbating health disparities. We propose PolyPred, a method that improves cross-population PRS by combining two predictors: a new predictor that leverages functionally informed fine-mapping to estimate causal effects (instead of tagging effects), addressing LD differences; and BOLT-LMM, a published predictor. When a large training sample is available in the non-European target population, we propose PolyPred+, which further incorporates the non-European training data. We applied PolyPred to 49 diseases/traits in 4 UK Biobank populations using UK Biobank British training data, and observed relative improvements vs. BOLT-LMM ranging from +7% in South Asians to +32% in Africans, consistent with simulations. We applied PolyPred+ to 23 diseases/traits in UK Biobank East Asians using both UK Biobank British and Biobank Japan training data, and observed improvements of +24% vs. BOLT-LMM and +12% vs. PolyPred. Summary statistic-based analogues of PolyPred and PolyPred+ attained similar improvements.