Social Determinants Of Health Indicators Research Articles

Abstract 4123509: The Intersection of Race and Ethnicity, Social Determinants of Health, and Hypertension Prevalence: A Community-Level Analysis

Background: Despite being one of the most diverse cities in the United States, Chicago is also notably segregated. The distinct separation among its 77 communities provides an opportunity to examine racial and ethnic segregation and the impact of social determinants of health (SDOH) on health outcomes. Research Question: How do race/ethnicity and SDOH influence hypertension (HTN) prevalence? Aim: To examine the relationships between race/ethnicity, SDOH, and HTN prevalence at the community level. Methods: This cross-sectional study used data from the Chicago Health Atlas collected between 2021 and 2022. The sample included data from all 77 Chicago communities and 2,738,956 of its residents. Two-step latent profile analyses were performed to classify each of the community according to the predominant race/ethnicity of its residents (Asian, Black, Hispanic, or White) and SDOH level (low, moderate, high), which was defined as how favorable the physical and social conditions are within the community and determined using 14 indicators (Table 1). Kruskal-Wallis tests were used to compare the prevalence of HTN among the communities by predominant race/ethnicity and SDOH level. Results: Among the 77 communities, 28 were predominantly Black, 27 were predominantly White, 21 were predominantly Hispanic, and 1 was predominantly Asian. HTN prevalence was highest in predominantly Black communities (39.9%), then the Asian community (35.8%), Hispanic communities (28.8%), and White communities (25.2%), p <.001. Based on the 14 SDOH indicators, 26 of the communities were classified as low SDOH (unfavorable conditions), 25 as moderate SDOH (moderately favorable), and 26 as high SDOH (favorable). HTN prevalence was highest in low SDOH communities (36.3%), followed by moderate SDOH communities (31.4%), and lowest in high SDOH communities (27.2%), p =.003. Conclusions: The findings highlight significant disparities in HTN prevalence across Chicago's communities, with higher rates observed in predominantly Black and low SDOH areas. These results underscore the need for targeted public health interventions to address the intersection of racial/ethnic segregation and SDOH.

Social determinants of health affect disease severity among preschool children with sickle cell disease

AbstractIndividuals with sickle cell disease (SCD) face the burden of managing a lifelong chronic illness, increasing vulnerability to social determinants of health (SDoH). However, how SDoH contributes to health disparities is understudied. We hypothesized that preschool children with SCD living in poor neighborhoods with higher socio-economic distress would experience increased acute care utilization (ACU; described as emergency department visits plus hospitalizations) despite disease-modifying therapy. Participants' home addresses (aged 0-6 years) were mapped using census tract environmental data from the US Department of Agriculture Food Access Research Atlas. In multivariable analyses controlled for sickle genotype and disease-modifying therapies (hydroxyurea and chronic transfusion), SDoH indicators, that is, limited access to food, lack of vehicle, low income, and inadequate education, were associated with higher ACU. Living in households with children >1 mile from a supermarket was associated with more hospitalizations (odds ratio [OR], 1.44; 95% confidence interval [CI], 1.13-1.85) and ACU (OR, 1.37; 95% CI, 1.06-1.80) among children with SCD (aged <6 years). In households with at least 1 bachelor's degree, children with SCD experienced less ACU (OR, 0.67; 95% CI, 0.50-0.93) and hospitalizations (OR, 0.67; 95% CI, 0.49-0.92). Preschool children with SCD with limited access to food and transportation are at a higher risk of acute complications despite receiving free evidence-based therapy and social support. The family education level may have a protective effect. Although SDoH in crowded households and health care maintenance visits were not a focus of this study, future research should consider these factors. Understanding the SCD and SDoH association is crucial for directing resources to improve affected children's health.

Social Vulnerability and Mental Health Among People with HIV and Substance Use: The Role of Race.

Poor mental health significantly impacts people with HIV (PWH) and those who drink alcohol. Limited data exist on the combined effects of social determinants of health (social vulnerability) on mental health in PWH with unhealthy substance use. We investigated the relationship between social vulnerability and poor mental health in PWH and whether this relationship differed by race/ethnicity. We conducted a cross-sectional analysis using data from the Boston ARCH Cohort among PWH with current or past unhealthy substance use. We created a 23-item social vulnerability index (SVI) using a deficit accumulation approach comprised of social determinants of health indicators. We estimated whether higher SVI score is associated with anxiety and depressive symptoms using logistic regression analysis. Among 251 participants with a mean age of 52 (SD = 10) years, 67.3% were male, 52% Black, 21% Hispanic, 19% White, and 73% unemployed. The SVI had a mean of 9.30 (SD = 3.4) with a 1.5-18 range. Nearly two in five persons reported past month heavy alcohol use and 35% illicit drug use. The prevalence of anxiety and depressive symptoms was 34.4% and 54.2% respectively. Higher SVI score was associated with anxiety symptoms (adjusted odds ratio [aOR] = 2.01, 95% confidence interval [CI] 1.46, 2.76, p ≤ 0.001), and depressive symptoms (aOR = 2.42, 95% CI 1.74, 3.36, p ≤ 0.001). Race/ethnicity did not moderate the relationship between SVI and each mental health outcome. SVI was significantly associated with poor mental health across racial/ethnicity groups in this cohort. Interventions that address social vulnerability may improve well-being and quality of life for PWH.

The Role of Social Determinants in Diagnosis Timing for Fetal Care Center-Eligible Conditions: A Scoping Review.

Timely identification of fetal conditions enables comprehensive evaluation, counseling, postnatal planning, and prenatal treatments. This study assessed the existing evidence on how social determinants of health (SDOH) influence diagnosis timing of fetal conditions appropriate for care in fetal care centers (FCCs). Eligible studies were conducted in the U.S. and published in English after 1999. We employed the Healthy People 2020 SDOH framework to categorize and analyze data from 16 studies, where 86% focused solely on congenital heart disease (CHD). Studies primarily focused on individual-level SDOH, with only 36% addressing structural-level factors. A total of 31 distinct indicators of SDOH were identified, with 68% being unique to individual studies. Indicators often varied in definition and specificity. Three studies covered all five SDOH categories in the Healthy People 2020 Framework. Studies revealed varying and often conflicting associations with SDOH indicators, with race and ethnicity being the most explored (100%), followed by socioeconomic status (69%), maternal age (57%), residence (43%), and structural factors (29%). Our findings highlight the need for more comprehensive research, including conditions beyond CHD, and the establishment of consensus on indicators of SDOH. Such efforts are necessary to gain a deeper understanding of the underlying factors driving disparities in fetal diagnosis and treatment.

QOL-45. SOCIAL DETERMINANTS OF HEALTH PREDICT NEUROPSYCHOLOGICAL OUTCOMES IN PEDIATRIC BRAIN TUMOR SURVIVORS

Abstract BACKGROUND Pediatric brain tumors and their treatment impact cognition including intellectual functioning (IQ), attention, working memory, and processing speed. Few studies have examined the role of social determinants of health (SDoH) on cognition in pediatric brain tumors. To date, studies have primarily focused on family-related SDoH factors such as insurance status or parental education as predictors of cognition. To our knowledge, no study has examined multiple indicators of SDoH to determine which family-based and community-based predict cognition. METHODS Participants included 151 pediatric brain tumor patients (M diagnosis age=8.82) seen for a clinical neuropsychological evaluation (M evaluation age=13.71). IQ, brief attention (WISC/DAS-II Digits Forward), working memory (WISC/DAS-II Digits Backwards), and processing speed (WISC Coding) were obtained from age-appropriate measures (WISC&amp;gt;6 years, DAS-II&amp;lt;6 years). Family-based SDoH indicators include insurance type (public, private) and maternal education (&amp;lt;high school degree, some college, ≥college degree). Community-based SDoH include the Area Deprivation Index (ADI) and Childhood Opportunity Index (COI). Multiple regressions examined variance in IQ, attention, working memory, and processing speed accounted for by the SDoH measures, after controlling for treatment exposures using the Neurological Predictor Scale. RESULTS Insurance accounted for 14.9% of the IQ variance [β=-.316, t(151)=-4.18; p&amp;lt;.001]; COI accounted for 18.3% of the IQ variance [β=.202, t(151)=2.70; p=.008]. Insurance accounted for 12% of the variance in attention [β=-.324, t(152)=-4.22; p&amp;lt;.001], and 17.5% of the variance in processing speed [F(2,134)=15.399, p&amp;lt;.001]. In the working memory model, insurance [β=-.179, t(148)=-2.19; p=.03] and ADI [β=-.171, t(148)=-2.11; p=.04], accounted for 5.3% and 7.5% of the variance, respectively. CONCLUSIONS Findings highlight the important contribution of both family and community factors on neuropsychological outcomes in pediatric brain tumors. Nuances of the data will be discussed as they relate to clinical care and research.

HPR153 Improving Prediction of Medical Costs Among Medicare Beneficiaries By Incorporating Social Determinants of Health Indicators in Risk Prediction

HPR153 Improving Prediction of Medical Costs Among Medicare Beneficiaries By Incorporating Social Determinants of Health Indicators in Risk Prediction

The Influence of Patient Characteristics and Social Determinants of Health on Postoperative Complications Following Achilles Tendon Rupture.

The influence of social determinants of health (SDH) on postoperative complications has been investigated in several studies, although correlation with Achilles tendon rupture (ATR) repair remains uninvestigated. SDH encompasses several factors, including insurance status and area-based measurements, including the Area Deprivation Index (ADI) and Social Vulnerability Index (SVI), which ranks neighborhoods by social disadvantage. This study investigated the correlation between patient demographics, SDH, and complications following ATR repair. A retrospective cohort study was conducted on 521 patients who presented with acute ATR and met the inclusion criteria, including age ≥18 years, a minimum of 30-day follow-up, and repair within 28 days of rupture. We reviewed patient demographics, time to surgery (TTS), and postoperative complications, including venous thromboembolism (VTE), rerupture, surgical site infection (SSI), wound dehiscence, and sural nerve injury. SDH variables included race, smoking status, insurance status, level of education, ADI, and SVI. Univariate regression tested the correlation between complications and SDH indicators. Significant variables (P < .05) were included in a multivariate regression. Sixty-eight complications occurred in 59 patients (11.3%). Multivariate regression showed that a higher ADI, that is, socially deprived individuals, was associated with lower rates of VTE (OR = 0.41, P = .04). Higher body mass index (BMI) was associated with rerupture (OR = 8.73, P < .01). Male patients had lower rates of wound dehiscence (OR = 0.31, P = .03) and VTE (OR = 0.32, P = .02) compared with women. Longer TTS correlated with sural nerve injuries (OR = 2.23, P < .01) and shorter TTS with reruptures (OR = 0.02, P = .02). Some measures of SDH were associated with postoperative complications. Gender also may have an effect, with male sex associated with lower rates of wound dehiscence and VTE. BMI was associated with higher rates of reruptures and overall general complications.

Social determinants of health and their relation to suboptimal health status in the context of 3PM: a latent profile analysis.

Suboptimal health is identified as a reversible phase occurring before chronic diseases manifest, emphasizing the significance of early detection and intervention in predictive, preventive, and personalized medicine (PPPM/3PM). While the biological and genetic factors associated with suboptimal health have received considerable attention, the influence of social determinants of health (SDH) remains relatively understudied. By comprehensively understanding the SDH influencing suboptimal health, healthcare providers can tailor interventions to address individual needs, improving health outcomes and facilitating the transition to optimal well-being. This study aimed to identify distinct profiles within SDH indicators and examine their association with suboptimal health status. This cross-sectional study was conducted from June 16 to September 23, 2023, in five regions of China. Various SDH indicators, such as family health, economic status, eHealth literacy, mental disorder, social support, health behavior, and sleep quality, were examined in this study. Latent profile analysis was employed to identify distinct profiles based on these SDH indicators. Logistic regression analysis by profile was used to investigate the association between these profiles and suboptimal health status. The analysis included 4918 individuals. Latent profile analysis revealed three distinct profiles (prevalence): the Adversely Burdened Vulnerability Group (37.6%), the Adversity-Driven Struggle Group (11.7%), and the Advantaged Resilience Group (50.7%). These profiles exhibited significant differences in suboptimal health status (p < 0.001). The Adversely Burdened Vulnerability Group had the highest risk of suboptimal health, followed by the Adversity-Driven Struggle Group, while the Advantaged Resilience Group had the lowest risk. Distinct profiles based on SDH indicators are associated with suboptimal health status. Healthcare providers should integrate SDH assessment into routine clinical practice to customize interventions and address specific needs. This study reveals that the group with the highest risk of suboptimal health stands out as the youngest among all the groups, underscoring the critical importance of early intervention and targeted prevention strategies within the framework of 3PM. Tailored interventions for the Adversely Burdened Vulnerability Group should focus on economic opportunities, healthcare access, healthy food options, and social support. Leveraging their higher eHealth literacy and resourcefulness, interventions empower the Adversity-Driven Struggle Group. By addressing healthcare utilization, substance use, and social support, targeted interventions effectively reduce suboptimal health risks and improve well-being in vulnerable populations. The online version contains supplementary material available at 10.1007/s13167-024-00365-5.

Assessing preconception health in Australia to support better outcomes in the first 2000 days - A critical need for building a core indicator framework.

In 2021, the Preconception Health Network Australia co-developed preconception health core indicators identified as critical to ensuring optimal maternal and child outcomes following conception. We conducted an audit of perinatal databases across each state and territory to identify whether preconception core indicator data were available. Seven health domains co-developed by the Preconception Health Network were mapped against the data collected in the perinatal databases. Indicator data were lacking across all seven health domains, with data missing for social determinants of health indicators. Better data linkage and developing a national evidence-based framework would allow ongoing monitoring of women's preconception health nationally.

Cognitive behavioral therapy for chronic pain supported by digital patient feedback and artificial intelligence: Do patients with socioeconomic risk factors benefit?

BackgroundIn a recent comparative effectiveness trial, patients with chronic pain receiving cognitive behavioral therapy supported by artificial intelligence and digital feedback (AI-CBT-CP) were more likely to report clinically meaningful improvements in pain-related disability and intensity at six months than patients randomized to standard telephone CBT-CP. Concerns persist about the impact of AI and digital interventions among socially disadvantaged patients. We examined variation in the proportion of patients completing all treatment sessions and reporting clinically meaningful improvements in pain-related disability and intensity across subgroups of patients defined by social determinants of health (SDOH). MethodsSDOH indicators included age, race, gender, education, income, marital status, geographic access, and clinical severity. Multivariate models with interaction terms tested SDOH indicators as potential moderators of treatment engagement and response to AI-CBT-CP versus standard telephone CBT-CP. FindingsRoughly half of participants (52.9 %) were 65+ years of age, 10.8 % were women, and 19.1 % reported Black race or multiple racial identities. Relatively favorable session completion was observed among patients randomized to AI-CBT-CP across SDOH subgroup, with no groups more likely to complete all session weeks when receiving standard telephone CBT-CP. The relative benefits of AI-CBT-CP in terms of pain-related disability and intensity were generally confirmed across SDOH subgroups. AI-CBT-CP had a greater relative impact on pain-related disability among patients <65 years old (p = .002). In none of the SDOH subgroups, did standard telephone CBT-CP have a greater impact on pain-related disability or intensity than AI-CBT-CP. InterpretationThese findings do not suggest that patients with SDOH disadvantages experience poorer treatment engagement or outcomes when offered CBT-CP supported by AI and digital feedback instead of standard telephone CBT-CP. AI-CBT-CP can help overcome treatment access barriers without exacerbating disparities, benefiting underserved populations with chronic pain. FundingUS Department of Veterans Affairs Health Services Research and Development program.

Social determinants of health explored within an electronic patient reported outcomes (ePROs) remote symptom monitoring platform for patients with acute myeloid leukemia (AML).

353 Background: Social determinants of health (SDoH) are non-medical factors, such as income, education, employment, and area of residence that can influence health outcomes. Research shows SDoH impact people’s health, well-being, and quality of life (QoL) and, for patients with cancer, treatment outcomes. Electronic Patient Reported Outcomes (ePROs) integration into routine oncology practice improves patient time on therapy, survival, and resource utilization. This study explores the use of an ePRO platform for routine gathering of SDoH into care for Acute Myeloid Leukemia (AML). Methods: Adult patients with AML undergoing treatment were enrolled in the Carevive remote symptom monitoring (RSM) platform between March 1, 2021 and April 20, 2023. Patients received baseline and weekly surveys to assess symptom burden, physical function, and overall health throughout treatment. Baseline characteristics included age, sex, race, frailty status (modified Geriatric Assessment, CARE survey item, and/or self-reported activity level), comorbidities, and SDoH (living-, caregiver-, marital-, employment-, education-, insurance-status, travel distance to cancer center. Symptoms (derived from the PRO-CTCAE) and QoL (EORTC QLC C30 #29 &amp; #30) were assessed weekly, along with survey compliance. Results were stratified by SDoH status and compared by symptom burden and QoL. Results: 124 patients were included in analysis, with median follow-up time of 12 weeks. Half were male (50%); median age was 66 (range 21-88), majority were White (76%) and had at least one comorbidity (69%). Survey compliance was 69%, measured by total number of surveys completed out of total number of surveys assigned by each patient. Among the 71 (57%) who completed all SDoH responses, 38 (54%) were married, 35 (49%) had at least a bachelor’s degree, 45 (63%) were retired, 45 (63%) reported having a full- or part-time caregiver, 26 (37%) lived with at least one other adult, and 48 (68%) lived more than 20 miles from their nearest cancer center. Patients living with at least one other adult reported symptoms more often than patients living alone (1.65 vs. 1.24 total symptoms per patient-week). Symptom reporting was comparable across all other SDoH responses. Conclusions: This study illustrates feasibility of using RSM for gathering SDoH indicators in routine care. While overall survey compliance was high, 43% did not complete all SDoH items, indicating possible patient reticence to respond to some questions. Symptom reporting differences may indicate a potential need to focus on patients living alone or without a caregiver. Results support the importance and utility of SDoH indicators to identify actionable risk factors for poor health outcomes. Further exploration is needed to understand reporting of symptoms and caregiver/lifestyle arrangements.

Social determinants of health explored within an electronic patient reported outcomes (ePROS) remote symptom monitoring platform for patients with multiple myeloma (MM).

354 Background: Social determinants of health (SDoH) are non-medical factors, such as income, education, employment, and area of residence, that can influence health outcomes. Research shows SDoH impact people’s health, well-being, and quality of life (QoL) and, for patients with cancer, treatment outcomes. Electronic Patient Reported Outcomes (ePROs) integration into routine oncology practice improves patient time on therapy, survival, and resource utilization. This study explores the use of an ePRO platform for routine gathering of SDoH incorporated into care for Multiple Myeloma (MM). Methods: Adult patients with MM undergoing treatment were enrolled in the Carevive remote symptom monitoring (RSM) platform between March 1, 2021 and April 20, 2023. Patients received baseline and weekly surveys to assess patient-reported symptom burden, physical function, overall health, and survey compliance. Baseline characteristics included age, sex, race, frailty status (modified Geriatric Assessment, CARE survey item, and/or self-reported activity level), comorbidities, and SDoH (living-, caregiver-, marital-, employment-, education-, insurance-status, travel distance to cancer center). Symptoms (derived from the PRO-CTCAE) and QoL (EORTC QLQ-C30 items #29 &amp; #30) were assessed weekly. Results were stratified by SDoH status and compared by symptom burden and QoL. Results: A total of 151 patients were included in analysis, with median follow-up time of 12 weeks: majority were male (56%) and white (75%); median age was 66 years old (range 20-87), and 70% had at least one comorbidity. Survey compliance was 71%, measured by the total number of surveys completed out of the total number of surveys assigned by each patient. Among 84 (56)% patients with SDoH responses, 67 (80%) were married, 45 (54%) had at least a bachelor’s degree, 49 (58%) were retired, 21 (25%) reported having a full- or part-time caregiver, 73 (87%) lived with at least one other adult, and 39 (46%) lived more than 20 miles from their nearest cancer center. Symptoms were reported more often by patients with a caregiver compared to patients without a caregiver (1.67 vs. 1.12 total symptoms per patient-week) and by patients living with at least one other adult compared to patients living alone (1.53 vs. 1.21 symptoms per patient-week). Conclusions: This study illustrates the feasibility of using RSM for gathering SDoH and patience experience indicators in routine clinical care. While overall survey compliance was high, 44% did not complete all SDoH items, indicating possible patient reticence to respond to some questions. Differences in symptom reporting rates indicate a potential need to focus on patients living alone, or without a caregiver. This further supports the importance and utility of SDoH indicators to identify actionable risk factors for poor health outcomes.

Treatment Initiation, Substance Use Trajectories, and the Social Determinants of Health in Persons Living With HIV Seeking Medication for Opioid Use Disorder.

People living with HIV and opioid use disorder (OUD) are disproportionally affected by adverse socio-structural exposures negatively affecting health, which have shown inconsistent associations with uptake of medications for OUD (MOUD). This study aimed to determine whether social determinants of health (SDOH) were associated with MOUD uptake and trajectories of substance use in a clinical trial of people seeking treatment. Data are from a 2018 to 2019 randomized trial comparing the effectiveness of different MOUD to achieve viral suppression among people living with HIV and OUD. SDOH were defined by variables mapping to Healthy People 2030 domains: education (Education Access and Quality), income (Economic Stability), homelessness (Neighborhood and Built Environment), criminal justice involvement (Social and Community Context), and recent SUD care (Health Care Access and Quality). Associations between SDOH and MOUD initiation were assessed with Cox proportional hazards models, and SDOH and substance use over time with generalized estimating equation models. Participants (N = 114) averaged 47 years old, 63% were male, 56% were Black, and 12% Hispanic. Participants reported an average of 2.3 out of 5 positive SDOH indicators (SD = 1.2). Stable housing was the most commonly reported SDOH (61%), followed by no recent criminal justice involvement (59%), having a high-school level education or greater (56%), income stability (45%), and recent SUD care (13%). Each additional favorable SDOH was associated with a 25% increase in the likelihood of MOUD initiation during the study period [adjusted HR = 1.25, 95% CI = (1.01, 1.55), P = .044]. Positive SDOH were also associated with a decrease in the odds of baseline opioid use and a greater reduction in opioid use during subsequent weeks of the study (P < .001 for a joint test of baseline and slope differences). Positive social determinants of health, in aggregate, may increase the likelihood of MOUD treatment initiation among people living with HIV and OUD.

Neighborhood socioeconomic disadvantage measures in rehabilitation clinical trials: Lessons learned in recruitment

PurposeThe Area Deprivation Index (ADI) measures the relative disadvantage of an individual or social network using US Census indicators. Although a strong re-hospitalization predictor, ADI has not been routinely incorporated into rehabilitation research. The purposes of this paper are to examine the use of ADI related to study recruitment, association with carepartner psychosocial factors, and recruitment strategies to increase participant diversity. MethodsDescriptive analysis of baseline data from a pilot stroke carepartner-integrated therapy trial. Participants were 32 carepartners (N = 32; 62.5 % female; mean age 57.8 ± 13.0 years) and stroke survivors (mean age (60.6 ± 14.2) residing in an urban setting. Measures included ADI, Bakas Caregiver Outcome Scale, Caregiver Strain Index, and Family Assessment Device. ResultsMost carepartners were Non-Hispanic White participants (61.3 %), part or fully employed (43 %), with >$50,000 (67.7 %) income, and all had some college education. Most stroke survivors were Non-Hispanic White participants (56.3 %) with some college (81.3 %). Median ADI state deciles were 3.0 (interquartile range 1.5–5, range 1–9), and mean national percentiles were 41.7 ± 23.5 with only 6.3 % of participants from the most disadvantaged neighborhoods. For the more disadvantaged half of the state deciles, the majority were Black or Asian participants. No ADI and carepartner factors were statistically related. ConclusionsThe use of ADI data highlighted a recruitment gap in this stroke study, lacking the inclusivity of participants from disadvantaged neighborhoods and with lower education. Using social determinants of health indicators to identify underrepresented neighborhoods may inform recruitment methods to target marginalized populations and broaden the generalizability of clinical trials.

Social determinants of health and disparate disability accumulation in a cohort of Black, Hispanic, and White patients with multiple sclerosis.

Black and Hispanic patients with multiple sclerosis (MS) have been shown to accumulate greater multiple sclerosis-associated disability (MSAD) than White patients. Disparities in social determinants of health (SDOH) among these groups have also been reported. To determine the extent to which associations of race and ethnicity with MSAD may be attributable to differences in SDOH. Retrospective chart analysis of patients at an academic MS center grouped by self-identified Black (n = 95), Hispanic (n = 93), and White (n = 98) race/ethnicity. Individual patient addresses were geocoded and matched with neighborhood-level area deprivation index (ADI) and social vulnerability index (SVI). Average Expanded Disability Status Scale (EDSS) scores at last-recorded evaluations of White patients (1.7 ± 2.0) were significantly lower than Black (2.8 ± 2.4, p = 0.001) and Hispanic (2.6 ± 2.6, p = 0.020) patients. Neither Black race nor Hispanic ethnicity was significantly associated with EDSS in multivariable linear regression models that included individual-level SDOH indicators and either ADI or SVI. Black race and Hispanic ethnicity are not significantly associated with EDSS in models that include individual and neighborhood-level SDOH indicators. Further research should elucidate mechanisms by which structural inequities affect MS disease course.

The impact of social determinants of health (SDOH) on use of germline genetic testing for triple-negative breast cancer (TNBC) in the community oncology setting.

1094 Background: TNBC presents at an earlier age of onset and at a more advanced stage, and is associated with a worse outcome in African American women. In a subset of patients, TNBC is associated with germline BRCA1 and/or BRCA2 mutations. Genetic testing improves breast cancer and other surveillance as well as treatment outcomes. Current NCCN Guidelines recommend germline testing for all patients with any stage TNBC. Previous versions recommended testing in patients aged 60 years or younger. This study aimed to identify factors associated with receiving genetic testing among patients with TNBC in the community oncology setting. Methods: This was a retrospective observational cross-sectional study examining patient profiles, demographics, SDOH indicators, and germline genetic testing data. Patients in The US Oncology Network diagnosed with any stage TNBC between 3/31/2017 and 9/30/2021 aged 60 years or younger were identified.Data from the iKnowMed EHR was used for patient identification, baseline characteristics, and social determinants, including area deprivation index (ADI), a validated measure of socioeconomic status (SES) based on address. Mean ADI percentile scores using national and state level benchmarks were calculated as well as stratifications above and below the 80th percentile (where higher scores &gt; 80 are markers of low SES). Evidence of germline genetic testing (yes/no) was compiled from iKM, network genetic databases, and confirmatory chart audits. Only US Oncology Network sites participating in confirmatory audits were included in this analysis. Results: Among participating sites, 1318 patients with TNBC were identified with a mean age of 49 years; 58% were White, 22% Black, 3% Asian, and 16% other/unknown; and evidence for germline genetic testing was found for 981 (74.4%). Statistically significant differences in germline testing rates were found for age (48.4 years for tested, 50.7 years for not tested); race (67% for Black patients, 77% for White); US census region (68% in South, 70% in Midwest, 83% in Northeast, and 87% in West); practice size (mean number of physicians: 32.8 per practice for testing group, 29.2 for untested); and for nationally benchmarked ADI score (mean ADI of 42.3: tested and 47.1 for not tested). No significant difference was seen across the spectrum of ethnicity, with 82% testing among Hispanic or Latino patients compared with 74% for non-Hispanic or Latino, p = 0.074. No significant differences were observed for clinical variables. Conclusions: We report that 75% of patients with TNBC in our community oncology network received genetic testing. However, significantly lower testing rates were observed for patients who were Black, had lower SES, and resided in the South and Midwest geographic regions. Further research should be performed to understand reasons why testing was not done, to address barriers.

Social determinants of health and utilization of neoadjuvant chemotherapy in patients with triple negative breast cancer (TNBC) in the community oncology setting.

610 Background: TNBC has a higher incidence in African American women compared to European American, often presents at a younger age or more advanced stage, and is associated with worse outcomes. The use of multi-agent neoadjuvant chemotherapy (NC) improves event-free survival and overall survival in patients with early-stage TNBC and is considered standard of care. Race and other social determinants of health (SDOH) have been shown to affect outcomes in patients with TNBC. Differences in use of NC associated with SDOH may be a contributing factor to inferior outcomes. The aim of this study is to determine if SDOH measures affect utilization of NC in patients with early-stage TNBC. Methods: This retrospective observational cross-sectional study examined patient profiles, treatment patterns and SDOH indicators among patients newly diagnosed with early-stage breast cancer in The US Oncology Network. Using iKnowMed EHR data, patients diagnosed with TNBC between 03/31/2017 and 09/30/2021 with stages II-IIIB disease or tumor size ≥2cm (T2 or higher) were included. The initial TNBC diagnosis date was used as the index date for each patient and records were assessed from 6 months pre- to 6 months post-diagnosis for NC initiation, baseline characteristics, and social determinants, including Area Deprivation Index (ADI), a validated measure of socioeconomic status. Results: 3321 patients with TNBC were identified, with a mean age of 58 years; 59% were White, 15% Black, 3% Asian, and 23% other/unknown; and 2139 (64%) received NC. Patients who received NC relative to those who did not were younger (mean 55.9 vs 61.8; p=0.001), had higher BMIs (70% with BMI&gt;25 vs ≤25, p=0.045), and had commercial or Medicaid insurance (67.5% with commercial insurance or Medicaid vs. 52.5% with Medicare; p=0.001). Regional differences were observed, with proportionally fewer patients receiving neoadjuvant chemotherapy in the south US census regions and more in the west. There was no difference in NC use in Black vs White patients (66% vs 64%). No significant differences in receipt of NC were found for race, ethnicity, or ADI. Conclusions: In the community oncology setting, we did not observe inequities in the use of NC based on social determinants analyzed in this study, such as race, ethnicity, and ADI. Poorer outcomes observed in Black patients with TNBC may not be a result of underutilization of NC.

COVID-19 in the Eastern Brazilian Amazon: Incidence, Clinical Management, and Mortality by Social Determinants of Health, Symptomatology, and Comorbidities in the Xingu Health Region

This study aims to investigate the relationship between social determinants of health (SDH), incidence, and mortality to verify which sociodemographic factors, symptoms, and comorbidities predict clinical management; second, this study aims to conduct a survival analysis of individuals with COVID-19 in the Xingu Health Region. Consequently, this study adopted an ecological framework, employing secondary data of COVID-19-positive individuals from the Xingu Health Region, Pará State, Brazil. The data were obtained through the database of the State of Pará Public Health Secretary (SESPA) for the period from March 2020 to March 2021. The incidence and mortality were higher in Vitória do Xingu and Altamira. Municipalities with a higher percentage of citizens with health insurance and higher public health expenditure showed a higher incidence and mortality. A higher gross domestic product was associated with a higher incidence. Females were found to be associated with better clinical management. To live in Altamira was a risk factor for intensive care unit admission. The symptoms and comorbidities that predicted worse clinical management were dyspnea, fever, emesis, chills, diabetes, cardiac and renal diseases, obesity, and neurological diseases. There were higher incidence, mortality, and lower survival rates among the elderly. Thus, it can be concluded that SDH indicators, symptomatology, and comorbidities have implications for the incidence, mortality, and clinical management of COVID-19 in the Xingu Health Region of eastern Amazonia, Brazil.

Abstract P659: Cluster Analysis of County-Level Cardiovascular Disease Mortality in the United States

Introduction: In the United States, cardiovascular disease (CVD) mortality has been declining since 1980s. However, the decline in CVD mortality is not uniform across regions and may show different trajectories that are driven by place-based social determinants of health (SDOH) such as physical and built environment, social-cultural environment, and health care system. We conducted a cluster analysis of county-level CVD mortality and SDOH indicators from 2009 to 2018. Hypothesis: We test the hypothesis that CVD mortality in US counties show different trajectories that can be grouped by clusters, and within each cluster, there are different SDOH variables that predict CVD mortality. Methods: We linked the Centers for Disease Control and Prevention's CVD mortality data with the Agency for Healthcare Research and Quality's public database on SDOH using county identifiers. CVD mortality rate was calculated as the number of deaths per 100,000 people in each county. There were 179 SDOH variables included in the model, classified into five different domains: the biological, behavioral, built and physical environment, health care system, and sociocultural environment domain. We employed a linear mixed-effects model fitted with a doubly penalized likelihood to induce sparsity for parameter estimation and effect selection. Results: We identified three clusters among a total of 3,136 counties. Overall, 1,182 counties were identified as cluster 1 that showed a consistent decline of CVD mortality over the past decade. The most important driving factor of CVD mortality in cluster 1 was population distribution - the percentage of population aged 15-17 (coefficient=7.032). Secondly, 1,116 counties were identified as cluster 2 that showed a decline between 2009 and 2012, and then a steady increase in CVD mortality after 2012. Within cluster 2, the number of mild drought months was the most predictive factor of CVD mortality (coefficient= -1.065), and the percentage of adults reporting no leisure-time physical activity was the second important predictor (coefficient= 0.646). Finally, 838 counties were identified as cluster 3 that showed a flattening trend in CVD mortality. Within cluster 3, the total number of obstetrics and gynecology, generalist, and primary care hospital residents plays the most important role (coefficient = -25.537). Each cluster has unique pattern and distinctive associations between certain SDOH variables and CVD mortality. Conclusions: In conclusion, we identified three intrinsic clusters that showed distinguishing trajectories of CVD mortality during the past decade. The SDOH indicators most predictive of CVD mortality were different within each cluster. This study suggests that place based SDOH drive substantial differences in CVD outcomes across regions.

Abstract A049: Racial/ethnic and socioeconomic inequities in clinical trial participation among US community oncology patients, 2011-2021

Abstract Introduction: While oncology clinical trials disproportionately recruit from academic medical centers, most patients receive care in the community setting. However, there is limited information regarding clinical trial participation rates, including inequities by race/ethnicity and the social determinants of health (SDoH), in community practices. Here we assessed factors associated with clinical study drug (CSD, proxy for trial participation) receipt among patients diagnosed with 21 common cancers in community practices. Methods: This retrospective study used the nationwide Flatiron Health electronic health record-derived de-identified database of patients with cancer. The cohort included patients (≥ 18 years) diagnosed with cancer (initial, advanced, or metastatic diagnosis; depending on the cancer type) between January 2011 and November 2021 (follow-up through March 2022). We examined inequities in receipt of CSD after diagnosis by race/ethnicity, insurance coverage, and area-level SDoH indicators (e.g., socioeconomic status [SES] and predominant race/ethnicity [proxy for residential segregation]). SDoH indicators contextualizing where patients live were defined using Census block group/tract data from the American Community Survey (2015-2019). To evaluate factors associated with CSD receipt, we used time-to-event analysis where patients were followed from index diagnosis to their first documented receipt of CSD, death, or last recorded activity. Separate Cox proportional hazards models adjusted for clinical characteristics (i.e., age, sex, performance status, and stage) were used to calculate hazard ratios (HR) and 95% confidence intervals (CI). Results: This study included 196,270 patients (median age: 69 years, 49.5% women; 75.2% non-Hispanic/Latinx [NH] White, 6.2% NH-Black, 3.3% Latinx), of whom 3.7% received CSDs. Black (2.6%, HR 0.56 [CI: 0.51- 0.62]) and Latinx patients (2.6% (HR 0.54 [CI: 0.48-0.62]) were less likely to receive CSDs than white patients (4.3%). Individual and area-level SDoH were associated with CSD receipt. For example, patients without documented insurance (2.7%, HR 0.61 [CI: 0.56-0.66]) or with Medicaid coverage (2.6%, HR 0.58 [CI: 0.52-0.65]) were less likely to receive CSDs than patients with commercial coverage (4.7%). Patients living in predominately non-white and lower SES neighborhoods were less likely to receive CSDs, as were those in neighborhoods whose residents disproportionately lacked U.S. citizenship, had limited English proficiency, and had low rates of vehicle ownership. Conclusion: There are substantial inequities in CSD receipt among patients who receive care in community cancer clinics. Black, Latinx, and uninsured patients, as well as those from historically marginalized neighborhoods were less likely to receive CSDs. Without focused policy and operational efforts to increase clinical trial enrollment of racially, ethnically, and socio-demographically diverse patient populations, clinical trials may proliferate inequities in investigational drug access and potentially cancer outcomes. Citation Format: Jenny Guadamuz, Ronac Mamtani, Xiaoliang Wang, Cleo A. Ryals, Ivy Altomare, Alemseged A. Asfaw, Wendy Camelo Castillo, Harlan Pittell, Gregory S. Calip, Somnath Sarkar. Racial/ethnic and socioeconomic inequities in clinical trial participation among US community oncology patients, 2011-2021 [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 A049.