Social Vulnerability Index Research Articles

A Machine Learning Exploration of Social Determinants of Health and Hospital-Onset Bacteremia, Northern California, 2019–2023

Introduction: Social determinants of health can impact healthcare-associated infections. Hospital-onset bacteremia (HOB) may lead to poor outcomes, increased length of stay, and increased cost of care. We explored the association of social determinants of health and HOB. Methods: We retrieved blood culture data at Stanford Health Care from May 2019 to October 2023. We identified blood cultures ordered ≥4 days of admission. To evaluate the association between social determinants of health and HOB, we employed an unsupervised machine learning approach (K-Means clustering) to discern patterns in HOB rates based on the Social Vulnerability Index (SVI). The SVI indicates the relative vulnerability of every U.S. Census tract. It ranks the tracts on 16 measures of vulnerability across 4 themes: socioeconomic factors, household characteristics, racial and ethnic minority status, and housing/transportation aspects. The number of clusters was determined using the Elbow Method (Figure 1). Results: Out of 209,947 blood cultures from 23,938 unique patients with a California address, we identified 81,653 blood cultures collected after 4 days (40%). The K-Means clustering algorithm identified 3 distinct clusters within the Californian census tracts, suggesting heterogeneity in the relationship between SVI and HOB (Figure 2). Cluster 1 had a higher SVI (median 0.73, range 0.46 – 0.99), with logistic regression indicating a positive SVI-HOB association (OR 4.84, 95% CI 4.02 – 4.81, p <.001). Cluster 2, had a median SVI of 0.29 (range 0.0009 – 0.78), also showed a positive association between SVI and HOB (OR 1.67, 95% CI 1.4 – 1.89, p <.001), aligning with trends of higher infection risks in more vulnerable groups. In contrast, Cluster 3 had a median SVI of 0.22 (range 0.002 –0.84). In this cluster, the SVI showed a negative association with HOB (OR 0.24, 95% CI 0.18 – 0.31, p <.001). Cluster 3 was the cluster with the least number of subjects (15,000, versus 21,761 for Cluster 1 and 29,762 for Cluster 2). Most subjects in Cluster 3 resided in Santa Clara County, whereas those in Clusters 1 and 2 were spread across Santa Clara, San Mateo, Alameda, Merced, and Sacramento Counties (Figure 3). Conclusions: Advanced techniques can be used to explore the complex interplay between social determinants of health and healthcare-associated infections and could guide the development of community-specific strategies to improve outcomes.

Medicare Advantage Plan Star Ratings and County Social Vulnerability.

The star rating of a Medicare Advantage (MA) plan is meant to represent plan performance, and it determines the size of quality bonuses. Consumer access to MA plans with a high star rating may vary by the extent of social vulnerability in geographic regions. To examine the association between a county's Social Vulnerability Index (SVI) and the star rating of a county's MA plans. This cross-sectional study used 2023 Centers for Medicare & Medicaid Services data for all MA plans linked to 2020 county-level SVI data from the Centers for Disease Control and Prevention. Data were analyzed from March to October 2023. Quintile rank of county based on composite and theme-specific SVI scores, with quartile 1 (Q1) representing the least vulnerable counties and Q5, the most vulnerable counties. The SVI is a multidimensional measure of a county's social vulnerability across 4 themes: socioeconomic status, household characteristics (such as disability, age, and language), racial and ethnic minority status, and housing type and transportation. County-level mean star rating and the number of MA plans with low-rated (<3.5 stars), high-rated (3.5 or 4.0 stars), and highest-rated (≥4.5 stars) plans. Across 3075 counties, the median county-level star rating was 4.1 (IQR, 3.9-4.3) in Q1 counties and 3.8 (IQR, 3.6-4.0) in Q5 counties (P < .001). The mean star rating of MA plans was lower (difference, -0.24 points; 95% CI, -0.28 to -0.21 points; P < .001), the number of low-rated plans was higher (incidence rate ratio, 1.81; 95% CI, 1.61-2.06; P < .001), and the number of highest-rated plans was lower (incidence rate ratio, 0.75; 95% CI, 0.70-0.81; P < .001) in Q5 counties compared with Q1 counties. Similar patterns were found across theme-specific SVI score quintiles and for 2022 star ratings. In this cross-sectional study, the most socially vulnerable counties were found to have the fewest highest-rated plans for MA beneficiaries. As MA enrollment grows in socially vulnerable regions, this may exacerbate regional differences in health outcomes for Medicare beneficiaries.

Exploring Socioeconomic Disparities in Surgical Site Infections

Introduction: Social disparities have been shown to impact a wide variety of healthcare outcomes. Surgical site infections (SSIs) are associated with substantial patient morbidity, but studies on the intersection of social disparity and SSI are limited. We sought to evaluate the association between SSI and the Center for Disease Control and Prevention’s social vulnerability index (SVI). Methods: Patients with National Health Safety Network (NHSN) procedure codes for colon, abdominal hysterectomy, hip prosthesis, knee prosthesis and spinal fusion surgeries were retrieved from the electronic medical records of 20 hospitals across 4 geographic markets. SSIs were identified by trained infection preventionists using NHSN definitions. Descriptive statistics were used for baseline demographic and clinical characteristics. Univariate logistic regression was performed to assess the association of demographic, clinical, and procedural factors with the outcome of SSI. Further univariate subgroup analysis was completed by procedure. To account for the nonlinear relationship between the social vulnerability index and SSIs, smoothing splines were used in a Bayesian hierarchical logistic regression model, with random effects to account for the different market practices. Nonlinear effects of procedure duration were also investigated while adjusting for the patient age, procedure type, and health system market. Results: 23,864 surgical procedures among 22,319 unique patients identified between 1 August 2022 and 31 August 2023. 96 patients with infection present at time of surgery were excluded. The study population was mostly white (74%) and female (65%) (Table 1). Less than 13% of the patients had more than one procedure during this time. In a univariate analysis, we found evidence of market and procedure effects, with colon surgery being associated with the highest odds of SSI. Procedure duration was significantly associated with SSI in both univariate and multivariable models, with a drastic increase in the odds of SSI for procedures &gt; 150 mins. In the multivariable model we found that SVIs lower than 0.4 (95% CI 0.28 to 0.55) are associated with an adjusted odds ratio (aOR) &lt; 1. (Figure 1) Conclusions: Our study shows that the relationship of social vulnerability and adverse outcomes is highly complex with nonlinear dynamics at play. After adjusting for procedure type, duration, patient age, gender and health system market the odds of SSIs increase sharply in patients with higher SVI until leveling off at an elevated risk.

Paper 06: Lower Socioeconomic Status is Associated with Recurrent Shoulder Instability Before Surgical Shoulder Stabilization

Objectives: Social determinants of health (SDOH) are comprised of a patient’s environmental conditions including social and economic factors, which influence access to health care and resources. Growing evidence in orthopaedic surgery has revealed that SDOH factors lead to differential access to care and ultimately health disparities after surgery. For shoulder instability, previous literature has demonstrated that the number of previous dislocations before a stabilization procedure increases the risk of recurrent instability after the procedure. The purpose of this study was to investigate the impact of SDOH on the number of dislocation events before surgical intervention. Methods: A retrospective review of patients who underwent shoulder stabilization surgery at a health system in a large metropolitan area between January 1, 2021 and April 13, 2023 were identified. Patients’ demographic and social determinants variables were extracted using the electronic medical record. Social Vulnerability Index (SVI) socioeconomic subscore and Area of Deprivation Index (ADI) were collected using online mapping data based on patient zip codes. The number of dislocation events and the time they occurred were determined using clinical charts. Operative variables collected included the date of surgery to determine the time from clinical presentation to surgery and the procedure performed. Univariate linear regression analysis was used to evaluate potential predictors of increasing time to presentation and increasing time to surgery. Univariate logistic regression analysis was also performed of all potential predictors of having &gt;1 dislocation event. A multivariate model was then created using all predictors with a P value &lt; 0.05 in the univariate models. Results: There were 106 patients who underwent shoulder surgery for instability, including arthroscopic and open stabilization, and had complete social determinant data, with 54% (n = 57) identifying as White, 29% (n = 31) as Black/African American, and 17% (n = 18) as other. A total of 38 (35.8%) patients suffered 1 dislocation (single dislocation cohort) before undergoing surgery, and 68 (64.2%) experienced &gt; 1 dislocation (recurrent cohort) before surgery. No significant variables were associated with increasing time to presentation or surgery. Univariate logistic regression revealed that decreasing age (odds ratio [OR] 0.94 [95% confidence interval (CI) 0.89- 0.99]; P = 0.02), decreasing body mass index (BMI) (OR 0.90 [95% CI 0.83-0.98]; P = 0.02), increasing SVI (OR 1.21 [95% CI 1.05-1.38]; P = 0.006), and increasing area deprivation index (ADI) (third tercile compared to first, OR 6.04 [95% CI 2.05-17.8]; P = 0.003) were associated with increased odds of having &gt; 1 instability event before surgical intervention. There was no association with race found in terms of number of dislocations before surgery. Multivariate logistic regression modeling revealed that decreasing BMI (OR 0.87 [95% CI 0.78-0.98]; P = 0.02) and increasing ADI (third tercile compared to first tercile, OR 7.46 [95% CI 1.26-44.2]; P = 0.02) were associated with increased odds of having &gt; 1 instability event before shoulder instability surgery. Conclusions: Lower socioeconomic status, as measured by ADI, is an independent predictor of a higher likelihood of recurrent instability before shoulder stabilization surgery. Recognizing these relationships may motivate surgeons to create pathways to prevent these treatment disparities among shoulder instability patients. Further studies are required to examine if these SDOH variables lead to disparities in postoperative outcomes.

Disparities in air pollution attributable mortality in the US population by race/ethnicity and sociodemographic factors.

There are large differences in premature mortality in the USA by race/ethnicity, education, rurality and social vulnerability index groups. Using existing concentration-response functions, published particulate matter (PM2.5) air pollution estimates, population estimates at the census tract level and county-level mortality data from the US National Vital Statistics System, we estimated the degree to which these mortality discrepancies can be attributed to differences in exposure and susceptibility to PM2.5. We show that differences in PM2.5-attributable mortality were consistently more pronounced by race/ethnicity than by education, rurality or social vulnerability index, with the Black American population having the highest proportion of deaths attributable to PM2.5 in all years from 1990 to 2016. Our model estimates that over half of the difference in age-adjusted all-cause mortality between the Black American and non-Hispanic white population was attributable to PM2.5 in the years 2000 to 2011. This difference decreased only marginally between 2000 and 2015, from 53.4% (95% confidence interval 51.2-55.9%) to 49.9% (95% confidence interval 47.8-52.2%), respectively. Our findings underscore the need for targeted air quality interventions to address environmental health disparities.

National assessment of social vulnerabilities on head-neck melanoma care: A retrospective cohort study

BackgroundStudies addressing social determinants of health (SDH) in head-neck melanomas (HNM) have only assessed socioeconomic factor impact but not a wider scope of SDH. ObjectiveUtilizing the Social Vulnerability Index (SVI), to assess the influence of specific SDH and their quantifiable associations with HNM-management disparities across the varied community contexts in the US. MethodsThis retrospective cohort study analyzed adults diagnosed with head-neck melanomas between 1975-2017 from the Surveillance, Epidemiology, and End Results Program (SEER) database. Results374,138 HNM in adults between 1975-2017 were assessed for disparities affiliated with increasing overall vulnerability/SVI scores and SDH-themes. For several melanoma subtypes, higher social vulnerability significantly decreased odds (lowest for amelanotic, OR 0.74; 95% CI 0.63-0.86) for indicated surgery, increased odds of indicated radiation (highest for epithelioid cell, 1.44; 1.08-1.96) and advanced staging on first-presentation (highest for acral-lentiginous, 1.13; 1.01-1.27). Household composition, followed by socioeconomic status and minority-language status contributed significantly within the overall trend. LimitationsLimitations include unknown cause of death and SVI score calculation based on county of residency. ConclusionsThis investigation highlights significant detrimental trends in HNM management with overall social vulnerability while showcasing the quantifiable associations of specific SDH-themes on HNM-disparities.

Social Vulnerability and Biological Aging in New York City: An Electronic Health Records-Based Study.

Chronological age is not an accurate predictor of morbidity and mortality risk, as individuals' aging processes are diverse. Phenotypic age acceleration (PhenoAgeAccel) is a validated biological age measure incorporating chronological age and biomarkers from blood samples commonly used in clinical practice that can better reflect aging-related morbidity and mortality risk. The heterogeneity of age-related decline is not random, as environmental exposures can promote or impede healthy aging. Social Vulnerability Index (SVI) is a composite index accounting for different facets of the social, economic, and demographic environment grouped into four themes: socioeconomic status, household composition and disability, minority status and language, and housing and transportation. We aim to assess the concurrent and combined associations of the four SVI themes on PhenoAgeAccel and the differential effects on disadvantaged groups. We use electronic health records data from 31,913 patients from the Mount Sinai Health System (116,952 person-years) and calculate PhenoAge for years with available laboratory results (2011-2022). PhenoAge is calculated as a weighted linear combination of lab results and PhenoAgeAccel is the differential between PhenoAge and chronological age. A decile increase in the mixture of SVI dimensions was associated with an increase of 0.23 years (95% CI: 0.21, 0.25) in PhenoAgeAccel. The socioeconomic status dimension was the main driver of the association, accounting for 61% of the weight. Interaction models revealed a more substantial detrimental association for women and racial and ethnic minorities with differences in leading SVI themes. These findings suggest that neighborhood-level social vulnerability increases the biological age of its residents, increasing morbidity and mortality risks. Socioeconomic status has the larger detrimental role amongst the different facets of social environment.

Comprehensive risk evaluation in Rapti Valley, Nepal: A multi-hazard approach

While research on natural hazards in Nepal has primarily focused on the consequences of individual hazards within an area, it is also essential to analyze the probable occurrence of several types of natural hazards and their interaction, i.e., Multi-hazard assessment. In light of this, the study conducted a Multi-Hazard Risk Assessment of the proposed capital city of Lumbini province, which covers 14 wards from three municipalities. The four prevalent hazards in the area, i.e., flood, landslide, debris flow, and forest fire, have been considered in the study, which includes generating individual susceptibility maps using different geospatial and modeling techniques. The vulnerability and risk assessment was done on a ward level and considered physical, social, economic, and environmental vulnerability indicators. The results on the multi-hazard susceptibility map show that 29.36% of the area was at low susceptibility, while the medium and high zones comprised 46.16% and 24.46% of the total area, respectively. Wards 2, 3, and 7 of Rapti are highly vulnerable, while Ward 8 of Sitganga and Ward 9 of Rapti are the least vulnerable. Moreover, wards 1, 2, and 3 are at high risk to the vulnerability parameters, while ward 8 of Sitganga is at the least risk. The high-risk areas are on the foothills of the Siwalik range, which are prone to landslide, debris flow, and forest fire hazards, as well as are on the bank of West Rapti River, which marks them as potential flood hazard zones. The capital city of Lumbini province is fast developing. Therefore, the results derived from this study assist in identifying potential risk zones to consider while creating a master plan for the area.

Residential history, the electronic health record, and clinical medicine: A descriptive study in a lung transplant cohort

Neighborhood level social determinants of health are commonly measured using a patient's most recent residential location. Not accounting for residential history, and therefore missing accumulated stressors from prior social vulnerabilities, could increase misclassification bias. We tested the hypothesis that the electronic health record could capture the residential history of lung transplant patients –a vulnerable population. After applying the Social Vulnerability Index (SVI) to individual residential histories, the most recent SVI equaled the first SVI in only 15.4% (58/374) of patients. There is a need for databases with residential histories to inform place-based determinants of health and applications to patient care.

Physical, social, and biological attributes for improved understanding and prediction of wildfires: FPA FOD-Attributes dataset

Abstract. Wildfires are increasingly impacting social and environmental systems in the United States (US). The ability to mitigate the adverse effects of wildfires increases with understanding of the social, physical, and biological conditions that co-occurred with or caused the wildfire ignitions and contributed to the wildfire impacts. To this end, we developed the FPA FOD-Attributes dataset, which augments the sixth version of the Fire Program Analysis Fire-Occurrence Database (FPA FOD v6) with nearly 270 attributes that coincide with the date and location of each wildfire ignition in the US. FPA FOD v6 contains information on location, jurisdiction, discovery time, cause, and final size of &gt;2.3×106 wildfires in the US between 1992 and 2020 . For each wildfire, we added physical (e.g., weather, climate, topography, and infrastructure), biological (e.g., land cover and normalized difference vegetation index), social (e.g., population density and social vulnerability index), and administrative (e.g., national and regional preparedness level and jurisdiction) attributes. This publicly available dataset can be used to answer numerous questions about the covariates associated with human- and lightning-caused wildfires. Furthermore, the FPA FOD-Attributes dataset can support descriptive, diagnostic, predictive, and prescriptive wildfire analytics, including the development of machine learning models. The FPA FOD-Attributes dataset is available at https://doi.org/10.5281/zenodo.8381129 (Pourmohamad et al., 2023).

Spatial and Temporal Dynamics of Chikungunya Incidence in Brazil and the Impact of Social Vulnerability: A Population-Based and Ecological Study.

To assess the temporal and spatial dynamics of chikungunya incidence and its association with social vulnerability indicators in Brazil, an ecological and population-based study was conducted herein, with confirmed cases of chikungunya and based on clinical and clinical-epidemiological criteria from 2017 to 2023. Data were obtained from the Notifiable Diseases Information System and social vulnerability indicators were extracted from the official platform of the United Nations Development Program and the Social Vulnerability Atlas. Temporal, spatial, and global spatial regression models were employed. The temporal trend showed that in 2017, the incidence increased by 1.9%, and this trend decreased from 2020 to 2021 (-0.93%). The spatial distribution showed heterogeneity and positive spatial autocorrelation (I: 0.71; p < 0.001) in chikungunya cases in Brazil. Also, the high-risk areas for the disease were concentrated in the northeast and north regions. The social vulnerability indicators associated with the outcome were those related to income, education, and housing conditions. Our analyses demonstrate that chikungunya continues to be a serious health concern in Brazil, but specially in the northeast and north regions. Lastly, mapping risk areas can provide evidence for the development of public health strategies and disease control in endemic regions.

Congruence Between County Dental Health Provider Shortage Area Designations and the Social Vulnerability Index.

Congruence Between County Dental Health Provider Shortage Area Designations and the Social Vulnerability Index.

Provider-to-provider telemedicine for sepsis is used less frequently in communities with high social vulnerability.

Sepsis disproportionately affects patients in rural and socially vulnerable communities. A promising strategy to address this disparity is provider-to-provider emergency department (ED)-based telehealth consultation (tele-ED). The objective of this study was to determine if county-level social vulnerability index (SVI) was associated with tele-ED use for sepsis and, if so, which SVI elements were most strongly associated. We used data from the TELEmedicine as a Virtual Intervention for Sepsis in Rural Emergency Department study. The primary exposures were SVI aggregate and component scores. We usedmultivariable generalized estimating equations to model the association between SVI and tele-ED use. Our study cohort included 1191 patients treated in 23 Midwestern rural EDs between August 2016 and June 2019, of whom 326 (27.4%) were treated with tele-ED. Providers in counties with a high SVI were less likely to use tele-ED (adjusted odds ratio [aOR] = 0.51, 95% confidence interval [CI] 0.31‒0.87), an effect principally attributable to the housing type and transportation component of SVI (aOR = 0.44, 95% CI 0.22-0.89). Providers who treated fewer sepsis patients (1‒10vs. 31+ over study period) and therefore may have been less experienced in sepsis care, were more likely to activate tele-ED (aOR = 3.91, 95% CI 2.08‒7.38). Tele-ED use for sepsis was lower in socially vulnerable counties and higher among providers who treated fewer sepsis patients. These findings suggest that while tele-ED increases access to specialized care, it may not completely ameliorate sepsis disparities due to its less frequent use in socially vulnerable communities.

Area deprivation index and social vulnerability index in Milwaukee County: Impact on hospital outcomes after traumatic injuries

BackgroundPredisposing factors for traumatic injuries are complex and variable. Neighborhood environments may influence injury mechanism or outcomes. The Social Vulnerability Index (SVI) identifies areas at risk for emergencies; Area Deprivation Index (ADI) measures socioeconomic disadvantage. The objective was to assess the impact of SVI or ADI on hospital length of stay (LOS) and mortality for injured patients to determine whether SVI or ADI indicated areas where injury prevention may be most impactful. MethodsAdult patients who resided in Milwaukee County and were treated for injuries from 2015 to 2022 at a level I trauma center were included. Patients’ addresses were geocoded and merged with 2020 state-level SVI and ADI measures. SVI ranks census tracts 0–100 from least to most vulnerable. ADI ranks census block groups 1–10 from least to most disadvantaged. ADI and SVI rankings were converted to deciles. Statistical analyses included descriptive statistics, chi-square tests, and regression models for LOS and in-hospital mortality, adjusted for either SVI or ADI within separate models, age, sex, race or ethnicity, mechanism of injury (MOI), injury severity score (ISS). Results14,542 patients were included; 63 % were male. Mean total hospital LOS was 6.4 ± 9.8 days, and in-hospital mortalities occurred in 5.2 % of patients. Based on SVI and ADI, 5,280 (36 %) patients resided in high vulnerability areas and 5,576 (39 %) lived in highly disadvantaged areas, respectively. After adjusting for patient factors, SVI deciles #6, 9, 10 were associated with increased hospital LOS, and SVI decile #5 was associated with in-hospital mortality (OR = 2.22, 95 %CI:1.06–4.63; p = 0.034). When adjusted for ADI, the 7th-10th deciles were associated with increased hospital LOS. Greater age and ISS were associated with increased hospital LOS and mortality when adjusted for SVI and ADI. ConclusionsSVI and ADI identified a similar proportion of patients in high vulnerability or disadvantaged areas. Higher SVI and ADI deciles were associated with longer hospital LOS, and only the 5th SVI decile was associated with in-hospital mortality. Highly disadvantaged or vulnerable areas may have a longer LOS, but SVI and ADI have limited influence on trauma mortality. Continued research on neighborhood and community factors and trauma outcomes is needed.

Unveiling rural and Appalachian disparities in cigarette smoking through the social vulnerability index and other county-level characteristics.

Mitigating tobacco-related disparities in the Appalachian region and rural areas is crucial. This study seeks to gauge cigarette smoking prevalence in Virginia counties, uncover rurality and Appalachian-linked disparities, and explore local drivers of these gaps. A 2011-2019 Virginia BRFSS data were used to estimate county-level cigarette smoking rates in adults aged 18 or older. Counties were categorized as urban/rural and Appalachian/non-Appalachian, with a focus on rural-Appalachian. Disparities in cigarette smoking rates and associated factors were analyzed via the Blinder-Oaxaca decomposition method. The study assessed 4 dimensions of the Centers for Disease Control and Prevention's social vulnerability index (SVI): socioeconomic, minority status, household composition, and housing. Additionally, county-specific factors such as tobacco agriculture, physician availability, coal mining, and tobacco retailer density were examined. Rural areas exhibited a 6.18% higher cigarette smoking prevalence compared to urban areas (P<.001). SVI dimensions accounted for 53.2% of the disparity, county features explained 16.4%, and 30.4% remained unexplained. Appalachian areas had a 6.79% higher cigarette smoking prevalence than non-Appalachian areas (P<.001). SVI dimensions explained 51.4% of the disparity, county features accounted for 21.8%, leaving 26.8% unexplained. Rural-Appalachian areas showed a 7.8% higher cigarette smoking prevalence (P<.001). SVI dimensions contributed to 51.7% of the disparity, county features explained 9.6%, and 38.7% remained unexplained. Substantial disparities in cigarette smoking prevalence exist in underserved areas of Virginia, including rural, Appalachian, and rural-Appalachian regions. While SVI dimensions, physician availability, tobacco agriculture, and coal mining contribute, yet notable gaps remain unexplained. Targeted interventions must tackle unique challenges in disadvantaged areas to reduce smoking and promote health equity.

Associations of neighborhood sociodemographic environment with mortality and circulating metabolites among low-income black and white adults living in the southeastern United States

BackgroundResiding in a disadvantaged neighborhood has been linked to increased mortality. However, the impact of residential segregation and social vulnerability on cause-specific mortality is understudied. Additionally, the circulating metabolic correlates of neighborhood sociodemographic environment remain unexplored. Therefore, we examined multiple neighborhood sociodemographic metrics, i.e., neighborhood deprivation index (NDI), residential segregation index (RSI), and social vulnerability index (SVI), with all-cause and cardiovascular disease (CVD) and cancer-specific mortality and circulating metabolites in the Southern Community Cohort Study (SCCS).MethodsThe SCCS is a prospective cohort of primarily low-income adults aged 40–79, enrolled from the southeastern United States during 2002–2009. This analysis included self-reported Black/African American or non-Hispanic White participants and excluded those who died or were lost to follow-up ≤ 1 year. Untargeted metabolite profiling was performed using baseline plasma samples in a subset of SCCS participants.ResultsAmong 79,631 participants, 23,356 deaths (7214 from CVD and 5394 from cancer) were documented over a median 15-year follow-up. Higher NDI, RSI, and SVI were associated with increased all-cause, CVD, and cancer mortality, independent of standard clinical and sociodemographic risk factors and consistent between racial groups (standardized HRs among all participants were 1.07 to 1.20 in age/sex/race-adjusted model and 1.04 to 1.08 after comprehensive adjustment; all P < 0.05/3 except for cancer mortality after comprehensive adjustment). The standard risk factors explained < 40% of the variations in NDI/RSI/SVI and mediated < 70% of their associations with mortality. Among 1110 circulating metabolites measured in 1688 participants, 134 and 27 metabolites were associated with NDI and RSI (all FDR < 0.05) and mediated 61.7% and 21.2% of the NDI/RSI-mortality association, respectively. Adding those metabolites to standard risk factors increased the mediation proportion from 38.4 to 87.9% and 25.8 to 42.6% for the NDI/RSI-mortality association, respectively.ConclusionsAmong low-income Black/African American adults and non-Hispanic White adults living in the southeastern United States, a disadvantaged neighborhood sociodemographic environment was associated with increased all-cause and CVD and cancer-specific mortality beyond standard risk factors. Circulating metabolites may unveil biological pathways underlying the health effect of neighborhood sociodemographic environment. More public health efforts should be devoted to reducing neighborhood environment-related health disparities, especially for low-income individuals.

QOL-18. THE MODERATING ROLE OF SOCIAL VULNERABILITY IN THE RELATIONSHIP OF MATERNAL CAREGIVER CONDITION MANAGEMENT ABILITY AND TRANSITION READINESS OF THEIR YOUNG ADULT SURVIVORS OF PEDIATRIC BRAIN TUMORS

Abstract BACKGROUND The transition into adulthood is a particularly vulnerable time for young adult survivors of pediatric brain tumors (YAS) due to tumor/treatment-related late effects. Reduced supportive resource access and social determinants of health (SDH) can exacerbate challenges, impacting caregiver condition management ability (CMA) and YAS transition readiness. This study’s aim was to evaluate the relationship between YAS cognitive late effects, caregiver CMA, and YAS transition readiness, and the moderating role of SDH for YAS and caregivers with condition-focused family management. METHODS Fifty-three maternal caregivers (93% white, 98% non-Hispanic) of YAS (Mage=22) reporting low CMA completed the Transition Readiness Assessment Questionnaire (TRAQ; 5 subdomains) and rated YAS cognitive late effect severity. Medical experts scored 1) cognitive medical sequelae (0-6 scale), and 2) the Pediatric Neuro-Oncology Rating of Treatment Intensity. Social Vulnerability Index (SVI) measured cumulative SDH using 16 factors across US Census residential zip code data. Pearson correlations and moderated mediation analyses in Process Macro were used. RESULTS Caregiver ratings were associated with overall transition readiness (r=-.38, p=.005), cognitive medical sequelae (r=.53, p&amp;lt;.001), and treatment intensity (r=.28, p=.039). Expert ratings were not related to transition readiness (ps&amp;gt;.05); therefore, only caregiver ratings were used in moderated mediation models. For overall transition readiness, managing medications, appointment keeping, talking with providers, and managing daily activities, the direct effects of caregiver ratings (ps&amp;gt;.05) and indexes of moderated mediation via CMA (ps&amp;gt;.05) were not significant. For tracking health issues, the direct effect of caregiver ratings (p=.085) was not significant, but the index of moderated mediation was significant (95%CI=.026;.315). CONCLUSIONS Only caregiver cognitive late effect ratings were helpful in explaining YAS overall transition readiness. The role of social vulnerability in CMA and transition readiness warrants further exploration. Empirically based transition readiness YAS programs targeting access to resources for families with more social vulnerability are needed.

EPH183 The Association Between the Minority Health Social Vulnerability Index and Pneumococcal Disease Incidence Among Medicare Beneficiaries (2016-2019)

EPH183 The Association Between the Minority Health Social Vulnerability Index and Pneumococcal Disease Incidence Among Medicare Beneficiaries (2016-2019)

Medicaid expansion in California and breast cancer incidence across neighborhoods with varying social vulnerabilities.

To investigate changes in breast cancer incidence rates associated with Medicaid expansion in California. We extracted yearly census tract-level population counts and cases of breast cancer diagnosed among women aged between 20 and 64years in California during years 2010-2017. Census tracts were classified into low, medium and high groups according to their social vulnerability index (SVI). Using a difference-in-difference (DID) approach with Poisson regression models, we estimated the incidence rate, incidence rate ratio (IRR) during the pre- (2010-2013) and post-expansion periods (2014-2017), and the relative IRR (DID estimates) across three groups of neighborhoods. Prior to the Medicaid expansion, the overall incidence rate was 93.61, 122.03, and 151.12 cases per 100,000 persons among tracts with high, medium, and low-SVI, respectively; and was 96.49, 122.07, and 151.66 cases per 100,000 persons during the post-expansion period, respectively. The IRR between high and low vulnerability neighborhoods was 0.62 and 0.64 in the pre- and post-expansion period, respectively, and the relative IRR was 1.03 (95% CI 1.00 to 1.06, p = 0.026). In addition, significant DID estimate was only found for localized breast cancer (relative IRR = 1.05; 95% CI, 1.01 to 1.09, p = 0.049) between high and low-SVI neighborhoods, not for regional and distant cancer stage. The Medicaid expansion had differential impact on breast cancer incidence across neighborhoods in California, with the most pronounced increase found for localized cancer stage in high-SVI neighborhoods. Significant pre-post change was only found for localized breast cancer between high and low-SVI neighborhoods.

The Legacy of Redlining: Increasing Childhood Asthma Disparities Through Neighborhood Poverty.

Identifying the root causes of racial disparities in childhood asthma is critical for health equity. To determine if the 1930's racist policy of redlining led to present-day disparities in childhood asthma by increasing community-level poverty and decreasing neighborhood socioeconomic position (SEP). We categorized census tracts at birth of participants from the Children's Respiratory and Environmental Workgroup birth cohort consortium into A, B, C, or D categories as defined by the Home Owners Loan Corporation (HOLC), with D being the highest perceived risk. Surrogates of present-day neighborhood-level SEP were determined for each tract including the percentage of low-income households, the CDC's social vulnerability index (SVI), and other tract-level variables. We performed causal mediation analysis, which, under the assumption of no unmeasured confounding, estimates the direct and mediated pathways by which redlining may cause asthma disparities through census tract-level mediators adjusting for individual-level covariates. Of 4,849 children, the cumulative incidence of asthma through age 11 was 26.6% and 13.2% resided in census tracts with a HOLC grade of D. In mediation analyses, residing in grade D tracts (aOR = 1.03 [95%CI 1.01,1.05]) was significantly associated with childhood asthma, with 79% of this increased risk mediated by percentage of low-income households; results were similar for SVI and other tract-level variables. The historical structural racist policy of redlining led to present-day asthma disparities in part through decreased neighborhood SEP. Policies aimed at reversing the effects of structural racism should be considered to create more just, equitable, and healthy communities.