Social Determinants Of Health Factors Research Articles

Impact of social determinants of health on progression from potentially life-threatening complications to near miss events and death during pregnancy and post partum in a middle-income setting: an observational study.

To assess the potential associations between social determinants of health (SDH) and severe maternal outcomes (SMO), to better understand the social structural framework and the contributory, non-clinical mechanisms associated with SMO. Prospective observational study. Tertiary referral centre in south-eastern region of India. One thousand and thirty-three women with potentially life-threatening complications (PLTC) were identified using WHO criteria. Social Determinants of Health (SDH). Severe maternal outcomes, which include maternal near-miss and maternal death. Logistic regression to assess the association between SDH and clinical factors on SMO, expressed as adjusted ORs (aOR) with a 95% CI. Of the 37 590 live births, 1833 (4.9%) sustained PLTC, and 380 (20.7%) developed SMO. Risk of SMO was higher with increasing maternal age (adjusted OR (aOR) 1.04 (95% CI 1.01 to 1.07)), multiparity (aOR 1.44 (1.10 to 1.90)), medical comorbidities (aOR 1.50 (1.11 to 2.02)), obstetric haemorrhage (aOR 4.63 (3.10 to 6.91)), infection (aOR 2.93 (1.83 to 4.70)), delays in seeking care (aOR 3.30 (2.08 to 5.23)), and admissions following a referral (aOR 2.95 (2.21 to 3.93)). SMO was lower in patients from socially backward community (aOR 0.45 (0.33 to 0.61)), those staying more than 10 km from hospital (aOR 0.56 (0.36 to 0.78)), those attending at least four antenatal visits (aOR=0.53 (0.36 to 0.78)) and those referred from resource-limited facilities (aOR=0.62 (0.46 to 0.84)). This study demonstrates the independent contribution of SDH to SMO among those sustaining PLTC in a middle-income setting, highlighting the need to formulate preventive strategies beyond clinical considerations.

Prediction of Readmission Following Sepsis Using Social Determinants of Health.

To determine the predictive value of social determinants of health (SDoH) variables on 30-day readmission following a sepsis hospitalization as compared with traditional clinical variables. Multicenter retrospective cohort study using patient-level data, including demographic, clinical, and survey data. Thirty-five hospitals across the United States from 2017 to 2021. Two hundred seventy-one thousand four hundred twenty-eight individuals in the AllofUs initiative, of which 8909 had an index sepsis hospitalization. None. Unplanned 30-day readmission to the hospital. Multinomial logistic regression models were constructed to account for survival in determination of variables associate with 30-day readmission and are presented as adjusted odds rations (aORs). Of the 8909 sepsis patients in our cohort, 21% had an unplanned hospital readmission within 30 days. Median age (interquartile range) was 54 years (41-65 yr), 4762 (53.4%) were female, and there were self-reported 1612 (18.09%) Black, 2271 (25.49%) Hispanic, and 4642 (52.1%) White individuals. In multinomial logistic regression models accounting for survival, we identified that change to nonphysician provider type due to economic reasons (aOR, 2.55 [2.35-2.74]), delay of receiving medical care due to lack of transportation (aOR, 1.68 [1.62-1.74]), and inability to afford flow-up care (aOR, 1.59 [1.52-1.66]) were strongly and independently associated with a 30-day readmission when adjusting for survival. Patients who lived in a ZIP code with a high percentage of patients in poverty and without health insurance were also more likely to be readmitted within 30 days (aOR, 1.26 [1.22-1.29] and aOR, 1.28 [1.26-1.29], respectively). Finally, we found that having a primary care provider and health insurance were associated with low odds of an unplanned 30-day readmission. In this multicenter retrospective cohort, several SDoH variables were strongly associated with unplanned 30-day readmission. Models predicting readmission following sepsis hospitalization may benefit from the addition of SDoH factors to traditional clinical variables.

Abstract PO3-03-10: Race and neoadjuvant treatment of triple negative breast cancer (TNBC) in the US community oncology setting

Abstract Background: TNBC is an aggressive subtype of breast cancer with limited targeted therapies. Black women have twice the incidence of TNBC compared to White women and within TNBC, Black women have worse outcomes than White women. Differences in both tumor biology of TNBC and social determinants of health (SDOH) play a role in observed disparities. The focus of this study is to evaluate SDOH factors associated to differences in the use of neoadjuvant chemotherapy (NC) in Black and White women in the US community oncology setting. Methods: This study was a retrospective, observational, cross-sectional design and used iKnowMed SM EHR data from the The US Oncology Network. Patients diagnosed with TNBC between 03/31/2017 and 09/30/2021 with stages II-III disease of tumor size ≥ 2cm (T2 or higher) were included. The index date was date of TNBC diagnosis and records were assessed from 6 months pre- to 6 months post-diagnosis for NC initiation. Univariable and multivariable logistic regression was conducted to evaluate impact of self-reported race on NC. Age, stage, BMI, insurance, area deprivation index (ADI), size of practice represented by physician count and geographical region, were studied in their mediating and moderating effects1 on the relationship between race and NC treatment. Results: Of the 3321 patients with TNBC identified in this study, 1969 self-reported white and 494 self-reported black (80% and 20% respectively). In multivariable regression accounting for all variables, Black race (OR = 1.57, 95% CI [ 1.02, 2.44], p=0.04), younger age, more advanced stage, obesity, non-Medicaid insurance, and West region, were all found to be positively associated with use of NC. Higher physician count was nominally associated, (p = 0.07). ADI was not found to be associated to NC. Mediator and moderator analysis for the relationship between race and NC showed that only stage and ADI variable inclusion in the model are required for the positive association between black race and NC. This is driven by a significant interaction between ADI and stage (p = 0.027) which differed for Black and White women. Mainly, for Black women ADI is positively associated to NC treatment in stage IIA, but negatively associated in all other stages (interaction term, p = 0.033). For White women, ADI is negatively associated to NC treatment in all stages. Only Black women with stage IIA tend to be treated more instead of less with NC in areas of greater deprivation (greater ADI). BMI presents nominal interactions with both race and stage, where obesity was more strongly associated with NC treatment in Black women (p = 0.088) and in stage IIA (p = 0.086). All other variables presented association to NC treatment without mediation or moderation of the race effect and without detectable differences across stages. Conclusions: Black women with stage IIA appear to be a special subgroup of TNBC patients for whom treatment with NC increases with ADI. Increased ADI generally results in less standard of care treatment; this is observed in this study for White women overall and for Black women in stages > IIA. Black women in areas of greater deprivation with stage IIA disease, may be perceived to be presenting with more aggressive disease and thus offered NC preferentially. This result lends support to the hypothesis that young black women present with a distinct, more aggressive subtype of TNBC in the early stages. Mediator and moderator analyses are important tools in elucidating the relationships between factors underlying racial disparities in both care and outcomes. 1. Hayes AF, Rockwood NJ. Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation. Behav Res Ther. 2017 Nov;98:39-57. Odds ratios for multivariable analysis –insert figure image– Race, stage and ADI –insert figure image– Race and BMI in stage IIA –insert figure image– Citation Format: Paola Raska, Joseph Dye, Nicholas J Robert, Angel Kidd, Michael Danso. Race and neoadjuvant treatment of triple negative breast cancer (TNBC) in the US community oncology setting [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-03-10.

Impact of COVID-19 Pandemic on Social Determinants of Health Issues of Marginalized Black and Asian Communities: A Social Media Analysis Empowered by Natural Language Processing.

This study aims to understand the impact of the COVID-19 pandemic on social determinants of health (SDOH) of marginalized racial/ethnic US population groups, specifically African Americans and Asians, by leveraging natural language processing (NLP) and machine learning (ML) techniques on race-related spatiotemporal social media text data. Specifically, this study establishes the extent to which Latent Dirichlet Allocation (LDA) and Gibbs Sampling Dirichlet Multinomial Mixture (GSDMM)-based topic modeling determines social determinants of health (SDOH) categories, and how adequately custom named-entity recognition (NER) detects key SDOH factors from a race/ethnicity-related Reddit data corpus. In this study, we collected race/ethnicity-specific data from 5 location subreddits including New York City, NY; Los Angeles, CA; Chicago, IL; Philadelphia, PA; and Houston, TX from March to December 2019 (before COVID-19 pandemic) and from March to December 2020 (during COVID-19 pandemic). Next, we applied methods from natural language processing and machine learning to analyze SDOH issues from extracted Reddit comments and conversation threads using feature engineering, topic modeling, and custom named-entity recognition (NER). Topic modeling identified 35 SDOH-related topics. The SDOH-based custom NER analyses revealed that the COVID-19 pandemic significantly impacted SDOH issues of marginalized Black and Asian communities. On average, the Social and Community Context (SCC) category of SDOH had the highest percent increase (366%) from the pre-pandemic period to the pandemic period across all locations and population groups. Some of the detected SCC issues were racism, protests, arrests, immigration, police brutality, hate crime, white supremacy, and discrimination. Reddit social media platform can be an alternative source to assess the SDOH issues of marginalized Black and Asian communities during the COVID-19 pandemic. By employing NLP/ML techniques such as LDA/GSDMM-based topic modeling and custom NER on a race/ethnicity-specific Reddit corpus, we uncovered various SDOH issues affecting marginalized Black and Asian communities that were significantly worsened during the COVID-19 pandemic. As a result of conducting this research, we recommend that researchers, healthcare providers, and governments utilize social media and collaboratively formulate responses and policies that will address SDOH issues during public health crises.

Social determinants of health Z-code documentation practices in mental health settings: a scoping review.

Mental health remains an urgent global priority, alongside efforts to address underlying social determinants of health (SDoH) that contribute to the onset or exacerbate mental illness. SDoH factors can be captured in the form of International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM), SDoH Z codes. In this scoping review, we describe current SDoH Z-code documentation practices, with a focus on mental health care contexts. Among 2 743 061 374 health care encounters noted across 12 studies in the United States, SDoH Z-code documentation rates ranged from 0.5% to 2.4%. Documentation often involved patients under 64 years of age who are publicly insured and experience comorbidities, including depression, bipolar disorder and schizophrenia, chronic pulmonary disease, and substance abuse disorders. Documentation varied across hospital types, number of beds per facility, patient race/ethnicity, and geographic region. Variation was observed regarding patient sex/gender, although SDoH Z codes were more frequently documented for males. Documentation was most observed in government, nonfederal, and private not-for-profit hospitals. From these insights, we offer policy and practice recommendations, as well as considerations for patient data privacy, security, and confidentiality, to incentivize more routine documentation of Z codes to better assist patients with complex mental health care needs.

Social Determinants of Health Factors and Loss-To-Follow-Up in the Field of Vascular Surgery

It is estimated that 22-57% of vascular patients are lost to follow-up (LTF) which is of concern as the Society of Vascular Surgery recommends annual patient follow-up. The purpose of this report was to identify social determinants of health factors (SDoH) and their relationship to LTF in vascular patients. The methods employed were a systematic literature review of 29 empirical articles and a retrospective quality improvement report with 27 endovascular aortic repair (EVAR) and thoracic endovascular aortic repair (TEVAR) patients at the University of Chicago. The systematic literature review resulted in 2,931 articles which were reduced to 29 articles meeting the inclusion criteria. Demographic variables were more frequently cited than SDoH factors, but the most common were smoking, transportation, and socioeconomic status/insurance. Additionally, 176 EVAR and TEVAR patients were called resulting in 27 patients who completed a SDoH questionnaire. Twenty-six percent indicated they had missed at least 1 appointment with the top reasons being work or family responsibilities. Due to limited patient size no statistical analyses were performed, but frequencies of responses to SDoH questions were reported to augment the existing limited literature and guide future research into variables such as one's ability to pay for basics like food or mortgage. SDoH factors are important yet understudied aspects of endovascular repairs that require more research to understand their impact on vascular surgery follow-up rates and outcomes. Additional research is needed as lack of consideration of such factors may impact the generalizability of existing research and such knowledge may help in informing clinician treatment plans.

23 AHA’s Essential Eight: Opportunities for Preventive Care among Adults with Peripheral Arterial Disease

OBJECTIVES/GOALS: The objective was to examine the American Heart Association’s (AHA) Essential Eight metrics of cardiovascular (CV) health among Black and White adults with peripheral arterial disease (PAD) collected via validated surveys and medical records. Each metric was examined in association with available social determinants of health (SDoH) factors. METHODS/STUDY POPULATION: This observational study completed data collection through surveys and medical record review. Validated surveys were used to collect Essential Eight metrics of diet, physical activity, sleep, and smoking status. Medical records were used to collect data on body mass index, blood lipids, blood glucose, and blood pressure. Participants with a diagnosis of lower extremity PAD, ability to complete surveys, and provided informed written consent were eligible. Equal numbers of Black and White participants were enrolled. Essential Eight metrics were used to calculate CV health scores for each participant. Scores were examined for association with SDoH factors and by race using Student’s T-test or ANOVA for continuous variables or Chi-Square tests for categorical variables. RESULTS/ANTICIPATED RESULTS: A total of 50 participants will be enrolled, with the expected majority being men and half self-reporting as Black individuals. Worse SDoH is expected to be associated with lower CV health metrics, including lower levels of physical activity and higher levels of saturated fatty food consumption. Higher levels of blood lipids, blood glucose, and blood pressure are expected to be associated with worse SDoH factors. We expect this association to be attenuated by rates of CV medications, such as statin therapy, antiglycemic medications, and antihypertensive medications. No effect modification by rurality is expected, although our projected sample size is small and may impact the ability to examine this interaction. DISCUSSION/SIGNIFICANCE: Black Americans, particularly in the Deep South, are at elevated risk for PAD and critical limb ischemic events, such as amputation. Understanding CV health metrics and SDoH characteristics among adults with PAD is essential to reduce disparities in care and provide valuable information for those at highest risk for complications.

203 Assessing social determinants of health and psychosocial factors critical to sustaining recovery among pregnant and parenting women with opioid use disorder

OBJECTIVES/GOALS: This study explored personal recovery support, including social determinants of health and psychosocial needs to understand factors for sustaining recovery among parenting and pregnant women with opioid use disorder. METHODS/STUDY POPULATION: This study used a mixed method quantitative/qualitative design and recruited women from residential/transitional facilities in an urban area. We used the Accountable Health Communities Health-Related Social Needs tool to assess social determinants of health factors, level of physical activity, family/community support, and mental health (stress). Through focus groups, we interviewed women to describe challenges to recovery and to resources including access to providers, housing, childcare, and food assistance from lived experiences. RESULTS/ANTICIPATED RESULTS: Survey analysis showed social determinants of health factors such as food and transportation were partially mitigated by residential living; however, parenting and pregnant women with opioid use disorder remained concerned about housing and finances; and encountered low levels of physical activity and significant stress. Preliminary results from the focus groups revealed a theme of positive recovery and retention experiences from residential living. DISCUSSION/SIGNIFICANCE: Evidence from studies suggests focused interventions for recovering women to reduce relapse risk factors and adverse maternal outcomes. Opportunities for improving personal recovery capital are accessible in residential facilities, however, further exploration of unmet social determinants of health factors are needed for recovery retention.

Social determinants of health and COVID-19 recovery after inpatient rehabilitation.

Neighborhoods with more social determinants of health (SDOH) risk factors have higher rates of infectivity, morbidity, and mortality from COVID-19. Patients with severe COVID-19 infection can have long-term functional deficits leading to lower quality of life (QoL) and independence measures. Research shows that these patients benefit greatly from inpatient rehabilitation facilities (IRF) admission, but there remains a lack of studies investigating long-term benefits of rehabilitation once patients are returned to their home environment. To determine SDOH factors related to long-term independence and QoL of COVID-19 patients after IRF stay. Multisite cross-sectional survey. Two urban IRFs. Primary outcome measures were Post-COVID Functional Status Scale (PCFS) and Short Form-36 (SF-36) scores. Secondary outcomes were quality indicator (QI) scores while at IRF and a health care access questionnaire. Results were analyzed using analysis of variance and multivariate logistic regression analyses. Participants (n = 48) who were greater than 1 year post-IRF stay for severe COVID-19 were enrolled in the study. Higher SF-36 scores were associated with male gender (p = .002), higher income (≥$70,000, p = .004), and living in the city (p = .046). Similarly, patients who were of the male gender (p = .004) and had higher income (≥$70,000, p = .04) had a greater odds of a 0 or 1 on the PCFS. Age was not associated with differences. Women were more likely to seek follow-up care (p = .014). Those who sought follow-up care reported lower SF-36 overall and emotional wellness scores, p = .041 and p = .007, respectively. Commonly reported barriers to health care access were financial and time constraints. Patients with SDOH risk factors need to be supported in the outpatient setting to maintain functional gains made during IRF stays. Female gender, income, and urban setting are potential predictors for long-term QoL and independence deficits after rehabilitation for COVID-19 infection. Low emotional wellness is an indicator for patients to seek out care as far out as 1 year from their rehabilitation stay.

Abstract P386: Associations of Gut Microbiome, but Not Microbial Metabolites, With Hypertension Differ by Race: Findings From the Baltimore Longitudinal Study of Aging

Introduction: Social determinants of health (SDoH) are thought to drive race disparities in hypertension (HTN) and in the gut microbiome (GMB). Additionally, studies suggest that associations of GMB and microbial metabolites with HTN differ by race. Whether this effect modification persists after accounting for SDoH factors has not been investigated. Hypothesis: Race-specific associations of GMB and microbial metabolites with HTN are attenuated when accounting for SDoH factors. Methods: We selected N=100 Baltimore Longitudinal Study of Aging participants for a fecal metabolomics study. We grouped participants by self-reported race (Black or White) and HTN status (HTN: SBP/DBP ≥ 130/80 mmHg without anti-HTN medication vs. normal blood pressure: SBP/DBP < 120/80), with matching on age, sex, and BMI category. After removal for missing SDoH data, we had N=95 participants for analysis. Metabolon measured fecal metabolites using their global, untargeted panel. Diversigen measured fecal GMB features (diversity, composition, and functional potential) using shotgun metagenomic sequencing. We tested univariable and multivariable associations of GMB alpha diversity and microbial metabolites with HTN using logistic regression, GMB beta diversity with HTN using PERMANOVA, and microbial species and functional potential with HTN using ANCOM-BC and MaAsLin2 methods, respectively. We analyzed associations overall and stratified by race. We adjusted for upstream (employed for pay, income meets needs, marital status, household size, educational attainment) and midstream (stress and depression scores, alternative healthy eating index, total calories, physical activity, smoking, and having private health insurance) SDoH factors. Results: HTN groups did not differ by age (66.3±11.1 years), sex (N=62/95 female), BMI (28.6±4.9 kg/m 2 ), or race (N=45/95 Black). Carnitine, a precursor for bacterial trimethylamine N-oxide (TMAO), was inversely associated with HTN (OR: 0.30; 95%CI [0.13,0.61]) and was not modified by race. Among GMB features, abundance of Roseburia intestinalis was lower among those with HTN (logfold-change [LFC]: -3.53, p=0.0132). Race modified associations of GMB evenness and Shannon diversity with hypertension, with effects generally being stronger among White participants (e.g.: Shannon Black OR [95%CI]: 0.99 [0.59,1.65]; White OR [95%CI]: 1.33 [0.87,2.86], interaction p=0.0242). Race also modified associations of bacterial species with HTN, including Roseburia intestinalis, which was stronger for White (LFC: -4.44) than for Black (LFC: -0.40) participants. Adjustment for SDoH factors did not attenuate effect modification of associations by race. Conclusions: In our study, which was balanced on race and HTN status (without medications), race modified associations of GMB diversity and composition with HTN, and this was not attenuated by SDoH factors.

Association between social determinants of health and pediatric traumatic brain injury outcomes.

Social determinants of health (SDH) are factors that may impact outcomes following pediatric traumatic brain injuries (TBI). The purpose of this study was to investigate the relationship between race and functional outcomes in a diverse pediatric population. We further explored how this association may be modified by SDH factors, including insurance status, social vulnerability, and child opportunity. A cohort study (N = 401) of children aged 0-18 [median = 9.22 years (IQR: 3.56-13.59)] presenting to the Emergency Department at Level I and II Trauma Centers with mild to severe head injuries. Geocoded variables were used to evaluate SDH. The sample was described overall and by racial/ethnic group, which were adjusted for confounders using inverse propensity treatment weights (IPTW). Weighted and unweighted Firth logistic regression models (mortality) and generalized linear regression models (GOS-E scores) were reported without and then with potential effect modifiers. The sample is majority male (65.84%); race/ethnicity are as follows: White (52.37%), Black/African Americans (35.91%), and Hispanic (11.72%). Black (31.25%) and Hispanic (27.66%) patients had higher rates of severe TBI. 35.89% of White patients were categorized as more socially vulnerable compared to 62.68% Black and 70.21% Hispanic patients. A total 63.64% of White patients were from higher opportunity neighborhoods, compared to 25.87% of Black and 51.06% of Hispanic patients. A total 50.95% of White patients, 25.87% of Black patients, and 17.02% of Hispanic patients were privately insured. There were no differences found between racial and ethnic groups on mortality or GOS-E scores. Patients from minority backgrounds had more severe injuries, many resulting from pedestrian vs. motor vehicle accidents. Additionally, patients from minority backgrounds experience more social vulnerability and lower opportunity. Despite these discrepancies, we did not observe differences on rates of mortality or functional outcomes in either racial or ethnic groups. SDH were not found to impact outcomes. Further research is needed to determine how these complex social and environmental variables impact health outcomes.

Measuring value in health care: lessons from accountable care organizations.

Accountable care organizations (ACOs) were created to promote health care value by improving health outcomes while curbing health care expenditures. Although a decade has passed, the value of care delivered by ACOs is yet to be fully understood. We proposed a novel measure of health care value using data envelopment analysis and examined its association with ACO organizational characteristics and social determinants of health (SDOH). We observed that the value of care delivered by ACOs stagnated in recent years, which may be partially attributed to challenges in care continuity and coordination across providers. ACOs that were solely led by physicians and included more participating entities exhibited lower value, highlighting the role of coordination across ACO networks. Furthermore, SDOH factors, such as economic well-being, healthy food consumption, and access to health resources, were significant predictors of ACO value. Our findings suggest a "skinny in scale, broad in scope" approach for ACOs to improve the value of care. Health care policy should also incentivize ACOs to work with local communities and enhance care coordination of vulnerable patient populations across siloed and disparate care delivery systems.

Connected Community Classification (C3): Development, Validation, and Geospatial Application for Population Health Promotion and Equity.

Social determinants of health (SDOH) impact population health. Leveraging community-level strengths related to SDOH through a social infrastructure perspective can optimize health behaviors and health outcomes to promote health equity. Our aims were to develop, validate, and apply the Connected Community Classification (C3) as comprehensive community-level measure of protective SDOH and structural factors in the Four Corners states region of the United States. C3 was developed using an iterative principal component analysis of publicly available data mapped to 5 SDOH domains. Regional clustering of C3 by zip code tabulation area (ZCTA) was identified using spatial autocorrelation methods. In adjusted spatial autoregressive models, we analyzed the association of C3 with high-risk health behaviors and chronic disease prevalence using publicly available data for population-level estimates of fruit and vegetable intake, physical activity, obesity, smoking, alcohol use, coronary heart disease (CHD), diabetes, and cancer. C3 was found to be reliable and valid; a C3 value of 10 indicates communities with greater connection (high), while a value of 1 indicates communities with greater separation (low) to social infrastructure. Lower connection, as measured by C3, was significantly inversely associated with lower fruit and vegetable intake, lower physical activity, and higher rates of obesity, smoking, CHD, diabetes, and cancer. C3 was significantly positively associated with heavy alcohol use. These findings demonstrate that communities connected to social infrastructure have better population health outcomes. C3 captures protective community attributes and can be used in future applications to assist health researchers, practitioners, nonprofits, and policymakers to advance social connection and health equity in geographically diverse underserved regions.

Social Determinants of Health Including Child Opportunity Index Leading to Gaps in Care for Patients With Significant Congenital Heart Disease.

Gaps in care (GIC) are common for patients with congenital heart disease (CHD) and can lead to worsening clinical status, unplanned hospitalization, and mortality. Understanding of how social determinants of health (SDOH) contribute to GIC in CHD is incomplete. We hypothesize that SDOH, including Child Opportunity Index (COI), are associated with GIC in patients with significant CHD. A total of 8554 patients followed at a regional specialty pediatric hospital with moderate to severe CHD seen in cardiology clinic between January 2013 and December 2015 were retrospectively reviewed. SDOH factors including race, ethnicity, language, and COI calculated based on home address and zip code were analyzed. GIC of >3.25 years were identified in 32% (2709) of patients. GIC were associated with ages 14 to 29 years (P<0.001), Black race or Hispanic ethnicity (P<0.001), living ≥150 miles from the hospital (P=0.017), public health insurance (P<0.001), a maternal education level of high school or less (P<0.001), and a low COI (P<0.001). Multivariable analysis showed that GIC were associated with age ≥14 years, Black race or Hispanic ethnicity, documenting <3 caregivers as contacts, mother's education level being high school or less, a very low/low COI, and insurance status (C statistic 0.66). One-third of patients followed in a regional referral center with significant CHD experienced a substantial GIC (>3.25 years). Several SDOH, including a low COI, were associated with GIC. Hospitals should adopt formal GIC improvement programs focusing on SDOH to improve continuity of care and ultimately overall outcomes for patients with CHD.

Explaining racial and ethnic disparities in antiretroviral therapy adherence and viral suppression among U.S. men who have sex with men.

To identify factors - including social determinants of health (SDOH) - that explain racial/ethnic disparities in antiretroviral therapy (ART) adherence and sustained viral suppression (SVS) among U.S. men who have sex with men (MSM) with HIV. We used weighted data from 2017-2021 cycles of the Medical Monitoring Project. Among MSM taking ART, we calculated prevalence differences (PDs) with 95% confidence intervals (CIs) of ART adherence (100% ART adherence, past 30 days) and SVS (all viral loads in past 12 months <200 copies/ml or undetectable) for Black MSM (BMSM) and Hispanic/Latino MSM (HMSM) compared with White MSM (WMSM). Using forward stepwise selection, we calculated adjusted PDs with 95% CIs to examine if controlling for selected variables reduced PDs. After adjusting for age, any unmet service need, federal poverty level (FPL), food insecurity, homelessness, time since HIV diagnosis, gap in health coverage, and education, the BMSM/WMSM PD for ART adherence reduced from -16.9 to -8.2 (51.5%). For SVS, the BMSM/WMSM PD reduced from -8.3 to -3.6 (56.6%) after adjusting for ART adherence, age, homelessness, food insecurity, gap in health coverage, FPL, any unmet service need, time since diagnosis, and ER visit(s). The HMSM/WMSM PD for ART adherence reduced from -9.3 to -2.9 (68.8%) after adjusting for age and FPL. The unadjusted HMSM/WMSM PD for SVS was not statistically significant. Adjusting for SDOH and other factors greatly reduced racial/ethnic disparities in ART adherence and SVS. Addressing these factors - particularly among BMSM - could substantially improve health equity among MSM with HIV.

Social Determinants of Health Framework to Identify and Reduce Barriers to Imaging in Marginalized Communities.

Social determinants of health (SDOH) are conditions influencing individuals' health based on their environment of birth, living, working, and aging. Addressing SDOH is crucial for promoting health equity and reducing health outcome disparities. For conditions such as stroke and cancer screening where imaging is central to diagnosis and management, access to high-quality medical imaging is necessary. This article applies a previously described structural framework characterizing the impact of SDOH on patients who require imaging for their clinical indications. SDOH factors can be broadly categorized into five sectors: economic stability, education access and quality, neighborhood and built environment, social and community context, and health care access and quality. As patients navigate the health care system, they experience barriers at each step, which are significantly influenced by SDOH factors. Marginalized communities are prone to disparities due to the inability to complete the required diagnostic or screening imaging work-up. This article highlights SDOH that disproportionately affect marginalized communities, using stroke and cancer as examples of disease processes where imaging is needed for care. Potential strategies to mitigate these disparities include dedicating resources for clinical care coordinators, transportation, language assistance, and financial hardship subsidies. Last, various national and international health initiatives are tackling SDOH and fostering health equity.

A greening theory of change: How neighborhood greening impacts adolescent health disparities.

Neighborhoods are one of the key determinants of health disparities among young people in the United States. While neighborhood deprivation can exacerbate health disparities, amenities such as quality parks and greenspace can support adolescent health. Existing conceptual frameworks of greening-health largely focus on greenspace exposures, rather than greening interventions. In this paper, we develop and propose a Greening Theory of Change that explains how greening initiatives might affect adolescent health in deprived neighborhoods. The theory situates greening activities and possible mechanisms of change in the context of their ability to modify distal social determinants of health factors, stemming from macrostructural and historical processes that lead to resource inequalities, affecting both the social and built environment in which adolescents live and develop. The framework illustrates both short- and long-term health, economic, and security effects of greening. We also describe how the theory informed the development of Project VITAL (Vacant lot Improvement to Transform Adolescent Lives) in Baltimore, MD, which aims to (1) build a citywide sharable database on vacant lot restoration activities, (2) evaluate the impact of greening initiatives on adolescent health outcomes, (3) conduct cost-effectiveness analyses, and (4) develop best practices for greening programs for improved adolescent health.

Screening for health literacy, social determinants, and discrimination in health plans.

Health inequities are frequently driven by social determinants of health (SDOH) and structural determinants of health. Our pilot sought to test the feasibility of screening for health literacy (HL) and perceived health care discrimination (PHD) through a live telephonic-facilitated survey experience with managed care patients. Cross-sectional study. Newly enrolled Medicare Advantage patients were screened for self-reported PHD, HL, and multiple SDOH using validated screening tools. Response rates for both HL and PHD screens were analyzed. A χ2 test for association between response to PHD screen and patient race was conducted. A weighted logistic regression model was used to understand how HL is associated with SDOH and demographic factors (age, gender, race/ethnicity, andincome). HL and PHD screening questions have different levels of feasibility. Administering the HL screen did not present a challenge, and patients felt comfortable responding to it. On the other hand, the PHD question had a lower response rate among patients, and some concierge advocates felt uncomfortable asking patients the question. Based on the self-reported HL data collected, low/limited HL is associated with patients who were Black, were low income, reported loneliness or isolation, or reported food insecurity. It is important to note that the study's findings are limited by the small sample size and that study results do not imply causality. It is feasible to collect self-reported HL data through a live telephonic format at the time of patient enrollment into a health plan. Health plans can leverage such screenings to better understand patient barriers for health equity-oriented interventions.

Abstract WMP51: Patient-Related Factors and Social Determinants of Health Associated With Discharge to Home Following Acute Ischemic Stroke: Findings From the Get With the Guidelines Stroke Registry

Background: Medical comorbidities and stroke risk factors explain only a proportion of stroke incidence and outcomes in different populations. Our analysis aimed to determine if social determinants of health (SDOH) are associated with discharge home following acute ischemic stroke (AIS) hospitalization. Methods: The analyses included AIS patients hospitalized from January 1, 2015 to December 31, 2019 who were ambulating at baseline and had a known county of residence in the GWTG stroke registry. The primary outcome measure was discharge to home. County-level SDOH included income, education, owner-occupied home, unemployment, foreign-born, and insurance coverage and were the main predictors. Estimates of county-level SDOH were classified into quartiles, and the relative odds of outcome were assessed using a multivariable logistic regression. Results: Of 1,171,519 observations included in our analysis, median age was 71 years, 49% were female and 78% were of white race. As shown in the Table, demographic factors associated with lower likelihood of discharge home after AIS hospitalization included being female, black race, and age &gt;80 years. County-level SDOH factors associated with increased likelihood of discharge home included education (lowest vs highest quartile), owner occupied home (lowest vs highest quartile), foreign-born (lowest vs highest quartile), self-pay/no insurance (vs Medicare). Income (lowest vs highest quartile) and unemployment (lowest vs highest quartile) were associated with lower likelihood of discharge home. Conclusion: County-level SDOH are associated with discharge to home after AIS. Our findings can be used to develop interventions that reduce inequity in AIS outcomes.

Analyzing Multiple Social Determinants of Health Using Different Clustering Methods.

Social determinants of health (SDoH) have become an increasingly important area to acknowledge and address in healthcare; however, dealing with these measures in outcomes research can be challenging due to the inherent collinearity of these factors. Here we discuss our experience utilizing three statistical methods-exploratory factor analysis (FA), hierarchical clustering, and latent class analysis (LCA)-to analyze data collected using an electronic medical record social risk screener called Protocol for Responding to and Assessing Patient Assets, Risks, and Experience (PRAPARE). The PRAPARE tool is a standardized instrument designed to collect patient-reported data on SDoH factors, such as income, education, housing, and access to care. A total of 2380 patients had complete PRAPARE and neighborhood-level data for analysis. We identified a total of three composite SDoH clusters using FA, along with four clusters identified through hierarchical clustering, and four latent classes of patients using LCA. Our results highlight how different approaches can be used to handle SDoH, as well as how to select a method based on the intended outcome of the researcher. Additionally, our study shows the usefulness of employing multiple statistical methods to analyze complex SDoH gathered using social risk screeners such as the PRAPARE tool.