Social Vulnerability and Sickle Cell Disease Mortality in the US.

Importance: Social determinants of health (SDOH) influence health outcomes, including those of sickle cell disease (SCD), despite advancements in treatments like disease-modifying therapies. Objective: To investigate the association of SDOH with SCD mortality rates from 2016 to 2020. Design, Setting, and Participants: This cross-sectional study combined county-level data from the Centers for Disease Control and Prevention and Agency for Toxic Substances and Disease Registry Social Vulnerability Index (SVI) with SCD mortality data from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database from January 1, 2016, to December 31, 2020. US counties were divided into 4 quartile (Q) models according to their SVI scores. Deaths from SCD in the US among patients of all ages were included. Data analysis occurred from March to April 2024. Exposure: SVI score. Main Outcomes and Measures: Age-adjusted mortality rates (AAMRs) per 1 000 000 individuals were measured. Rate ratios (RRs) were obtained by comparing county-specific AAMRs of SVI-Q4 with SVI-Q1. Results: From 2016 to 2020, among a total population of 1 633 737 771 individuals, there were 2635 deaths from SCD (1289 male [49.1%] and 1336 female [50.9%]). There were 1480 deaths in Q4, 687 deaths in Q3, 344 deaths in Q2, and 114 deaths in Q1. Higher SVI was associated with 2.11 excess deaths per 1 000 000 individuals (RR, 4.90; 95% CI, 4.81-5.00). Similar trends were seen for both males (RR, 4.56; 95% CI, 4.44-4.69) and females (RR, 5.85; 95% CI, 5.68-6.03). Middle-aged patients with SCD had the highest mortality rate in Q4, with 3.45 excess deaths per 1 000 000 individuals (RR, 4.97; 95% CI, 4.85-5.09). Higher SVI was associated with 2.29 excess deaths per 1 000 000 individuals in African American individuals with SCD (RR, 1.24; 95% CI, 1.22-1.27]). In White individuals with SCD, higher SVI was associated with 0.12 excess deaths per 1 000 000 individuals (RR not available due to unreliable data in Q1). When stratifying by census region, the highest level of SCD-related mortality was in the Northeast, with higher SVI associated with 3.16 excess deaths per 1 000 000 individuals (RR, 8.02; 95% CI, 7.66-8.40). Conclusions: In this cross-sectional study of the association of SVI with SCD mortality rates, higher SVI was associated with higher SCD mortality across US counties. These findings underscore the importance of addressing social determinants of health to improve mortality outcomes among patients with SCD.

Associations between Minority Health Social Vulnerability Index Scores, Rurality, and Histoplasmosis Incidence, 8 US States.

To explore associations between histoplasmosis and race and ethnicity, socioeconomic status, and rurality, we conducted an in-depth analysis of social determinants of health and histoplasmosis in 8 US states. Using the Minority Health Social Vulnerability Index (MH SVI), we analyzed county-level histoplasmosis incidence (cases/100,000 population) from the 8 states by applying generalized linear mixed hurdle models. We found that histoplasmosis incidence was higher in counties with limited healthcare infrastructure and access as measured by the MH SVI and in more rural counties. Other social determinants of health measured by the MH SVI tool either were not significantly or were inconsistently associated with histoplasmosis incidence. Increased awareness of histoplasmosis, more accessible diagnostic tests, and investment in rural health services could address histoplasmosis-related health disparities.

Association between social vulnerability factors and homicide and suicide rates - United States, 2016 - 2020.

BACKGROUND: Differences in social and environmental factors contribute to disparities in fatal injury rates. This study assessed the relationship between social vulnerability and homicide and suicide rates across United States counties. METHODS: County-level age-adjusted homicide and suicide rates for 2016-2020 were linked with data from the Centers for Disease Control and Prevention's 2020 Social Vulnerability Index (SVI), a dataset identifying socially vulnerable communities. We conducted negative binomial regressions to examine the association between SVI and homicide and suicide rates, overall and by Census region/division. We mapped county-level data for SVI and homicide and suicide rates in bivariate choropleth maps. RESULTS: Overall SVI was associated with homicide rates across U.S. counties. While no association was found for overall SVI and suicide rates, Socioeconomic Status and Racial & Ethnic Minority Status domains were associated. The geographic distribution of SVI and homicide and suicide rates varied spatially; notably, counties in the South had the greatest levels of social vulnerability and greatest homicide rates. CONCLUSIONS: Our findings demonstrate county-level social vulnerability is associated with homicide rates but may be more nuanced for suicide rates. A modified SVI for injury should include additional social and structural determinants and exclude variables not applicable to injuries. PRACTICAL APPLICATIONS: This study combines the SVI with homicide and suicide data, enabling researchers to examine related social and environmental factors. Modifying the SVI to include relevant predictors could improve injury prevention strategies by prioritizing efforts in areas with high social vulnerability.

COVID-19 Mortality Disparities Among Socially Vulnerable Medicare Beneficiaries Associated With the Quality of Nurse Work Environments in U.S. Hospitals.

COVID-19 mortality disparities for socially vulnerable patients, including individuals facing higher levels of poverty, housing insecurity, and limited transportation, have been linked to the quality of hospitals where they received care. Few studies have examined the specific aspects of hospitals, such as nursing care quality, that may underlie disparate outcomes. Recent studies suggest that nursing resources in the pre-pandemic period were associated with mortality during the COVID-19 public health emergency. In this study, we examined the association between social vulnerability, the nurse work environment, and inpatient mortality among Medicare beneficiaries hospitalized with COVID-19. A cross-sectional analysis was conducted of linked survey data collected from nurses working in New York and Illinois, Medicare claims, American Hospital Association Annual Survey data, and the Social Vulnerability Index (SVI). Higher mortality rates were observed among patients in the highest quartile of social vulnerability compared to the lowest (6870 [25.8%] vs 5019 [19.1%]; P < .001). Using multivariable regression modeling, a statistically significant interaction was found between the highest SVI quartile and the nurse work environment (OR, 0.86; 95% CI, 0.76-0.98; P < .05), implying that the effect of a higher quality nurse work environment on mortality was decidedly greater for patients in the highest quartile (odds ratio = 0.86 × 0.94 = 0.80) compared to patients in the lowest quartile (OR, 0.94). Post-hoc analyses demonstrated that hundreds of COVID-19 related deaths among the most socially vulnerable patients may have been avoided if all hospitals had a high-quality nurse work environment. Strengthening the quality of nurse work environments may help to reduce health disparities and should be considered in public health emergency planning, specifically in hospitals serving socially vulnerable communities.

Social Vulnerability May Underlie Racial Disparities in Peripartum Cardiomyopathy Outcomes.

Objective: Black patients have disproportionately more cases of peripartum cardiomyopathy (PPCM) and more severe disease. To better understand these disparities, we examined the geographic distribution of patients with PPCM by race and evaluated associations between race and social vulnerability. We hypothesized that Black patients with PPCM are more likely than White patients to live in socially vulnerable communities. Study Design: A retrospective cohort study of patients with PPCM defined by the National Institutes of Health, National Heart, Lung, and Blood Institute was conducted at a single center from January 2000 to November 2017. The US census tract for each patient was identified, and social vulnerability was assessed using the Centers for Disease Control and Prevention Social Vulnerability Index (SVI). Higher SVI values represent a more vulnerable community. SVI and select subcomponents were compared by self-reported race. Results: Among 90 patients with PPCM (47 White, 43 Black), the ejection fraction at diagnosis was similar between groups, although Black patients were more likely to have an ejection fraction of ≤40% at 6 to 12 months postpartum. Black race was associated with living in areas of greater social vulnerability; mean SVI was significantly higher among Black individuals than among White individuals (.56 versus .33, P=.0003). Black patients lived in areas with more people living in poverty, higher unemployment, and more single-parent households. Conclusion: Black patients with PPCM were more likely to have persistent left ventricular dysfunction and live in areas of greater social vulnerability. Strategies to achieve equitable social determinants of health are needed to improve health outcomes in Black patients with PPCM.

Using Social Vulnerability Indices to Predict Priority Areas for Prevention of Sudden Unexpected Infant Death in Cook County, IL: Cross-Sectional Study.

Background: The incidence of sudden unexpected infant death (SUID) in the United States has persisted at roughly the same level since the mid-2000s, despite intensive prevention efforts around safe sleep. Disparities in outcomes across racial and socioeconomic lines also persist. These disparities are reflected in the spatial distribution of cases across neighborhoods. Strategies for prevention should be targeted precisely in space and time to further reduce SUID and correct disparities. Objective: We sought to aid neighborhood-level prevention efforts by characterizing communities where SUID occurred in Cook County, IL, from 2015 to 2019 and predicting where it would occur in 2021-2025 using a semiautomated, reproducible workflow based on open-source software and data. Methods: This cross-sectional retrospective study queried geocoded medical examiner data from 2015-2019 to identify SUID cases in Cook County, IL, and aggregated them to "communities" as the unit of analysis. We compared demographic factors in communities affected by SUID versus those unaffected using Wilcoxon rank sum statistical testing. We used social vulnerability indicators from 2014 to train a negative binomial prediction model for SUID case counts in each given community for 2015-2019. We applied indicators from 2020 to the trained model to make predictions for 2021-2025. Results: Validation of our query of medical examiner data produced 325 finalized cases with a sensitivity of 95% (95% CI 93%-97%) and a specificity of 98% (95% CI 94%-100%). Case counts at the community level ranged from a minimum of 0 to a maximum of 17. A map of SUID case counts showed clusters of communities in the south and west regions of the county. All communities with the highest case counts were located within Chicago city limits. Communities affected by SUID exhibited lower median proportions of non-Hispanic White residents at 17% versus 60% (P<.001) and higher median proportions of non-Hispanic Black residents at 32% versus 3% (P<.001). Our predictive model showed moderate accuracy when assessed on the training data (Nagelkerke R2=70.2% and RMSE=17.49). It predicted Austin (17 cases), Englewood (14 cases), Auburn Gresham (12 cases), Chicago Lawn (12 cases), and South Shore (11 cases) would have the largest case counts between 2021 and 2025. Conclusions: Sharp racial and socioeconomic disparities in SUID incidence persisted within Cook County from 2015 to 2019. Our predictive model and maps identify precise regions within the county for local health departments to target for intervention. Other jurisdictions can adapt our coding workflows and data sources to predict which of their own communities will be most affected by SUID.

Social Vulnerabilities Among Hired Migrant and Seasonal Farmworkers During COVID-19: The Need for Employment-Based Indicators.

OBJECTIVES: This study aimed to explore farmworkers' experiences of social vulnerability during the peak period of the COVID-19 pandemic. METHODS: Telephone surveys of 63 migrant and seasonal farmworkers across three major agricultural areas in Florida were conducted. The survey, designed and disseminated with critical support from a statewide farmworker membership and advocacy organization, included items related to social and occupational precarity and a suite of demographic conditions, including specific employment-based indicators and categories. Data were analyzed with SPSS using a series of statistical significance tests including Pearson's Chi-Square, Fisher's Exact, T-tests, and Mann-Whitney U. An open-ended question regarding employment precarity was also analyzed for frequencies of responses pertaining to a set of descriptive categories. RESULTS: Survey findings demonstrated a high degree of social vulnerability among the farmworker sample, with notable variation in the type and severity of vulnerability and risk exposure across employment-based indicators and occupational categories. For example, a cross-industry comparison between vegetable field workers and greenhouse nursery workers revealed a disparity in COVID-exposure risk through commuting characteristics, as 43% of vegetable field workers used shared, employer-provided transport, while 68% of nursery workers used personal vehicles. CONCLUSION: While previous research has broadly established the extreme precarity of migrant and seasonal farmworkers during the peak COVID-19 period, the variability of experience, exposure to risk, and social vulnerability between farmworkers representing distinct employment-based indicators and occupational categories demonstrated in this study contributes to widening awareness of the importance of assessing farmworker experiences at a more granular level. In addition to delineating social vulnerability across key demographic categories, cross-industry comparisons between farmworkers revealed significant discrepancies in risk and vulnerability to COVID-19. Future research that further explores this variability may reveal opportunities to improve disaster-relief planning and mitigate social vulnerability in future disaster scenarios. The importance of surveying the vulnerability of worker populations, aside from geographic communities, is highlighted.

Social Vulnerability and Prevalence and Treatment for Mental Health and Substance Use Disorders.

Importance: Community-level social vulnerability (SV) is associated with physical illness and premature mortality. Its association with mental health (MH) and substance use disorders (SUDs) needs further study. Objective: To study associations of SV with clinical diagnoses of MH disorders, SUDs, and related treatments in the US noninstitutionalized population of adults aged 18 years and older. Design, Setting, and Participants: A survey of adults in a national sample of US households between October 2020 and October 2022. Participants drawn from a multistage, clustered, and stratified area probability sample of US households were included, excluding adults older than 65 years because of the difficulty of differentiating mental disorders from symptoms of dementia. The sample also included adults living in prisons, state psychiatric hospitals, and homeless shelters who were excluded from the sample of US households used in these analyses. Each sample household was sent a letter explaining the study and offering the option to complete the household roster online, by phone, or by email. Of the 12 906 adults selected for clinical interviewing in the household sample, 4674 completed clinical interviews. Main Outcomes and Measures: Main outcomes were Structured Clinical Interview for DSM-5 past-year diagnoses of MH disorders and SUDs and responses to survey questions regarding treatment received. The Social Vulnerability Metric (SVM) and the Area Deprivation Index (ADI) were used to determine SV at the residential zip code level. Results: The analysis involved 4674 participants (2904 [62.13%] female and 1770 [37.87%] male; mean [SD] age, 41.51 [13.41] years). Controlling for measured confounders, the SVM was significantly associated with diagnoses of schizophrenia spectrum disorder (SSD; adjusted odds ratio [aOR], 17.22; 95% CI, 3.05-97.29), opioid use disorder (OUD; aOR, 9.47; 95% CI, 2.30-39.02), stimulant use disorder (aOR, 6.60; 95% CI, 2.01-21.67), bipolar I disorder (aOR, 2.39; 95% CI, 1.19-4.80), posttraumatic stress disorder (aOR, 1.63; 95% CI, 1.06-2.50), and any MH disorder (aOR, 1.44; 95% CI, 1.14-1.83), but not major depressive disorder (MDD), generalized anxiety disorder (GAD), or any SUD. Results were similar for the ADI but generally of lower magnitude (SSD aOR, 11.38; 95% CI, 1.61-80.58; OUD aOR, 2.05; 95% CI, 0.30-14.10; stimulant use disorder aOR, 2.18; 95% CI, 0.52-9.18). Among participants with SSDs, SV was associated with reduced MH treatment (aOR, 0.001; 95% CI, 0.00-0.18) and reduced SUD treatment in participants with OUD or stimulant use disorder (aOR, 0.24; 95% CI, 0.02-2.80). Conclusions and Relevance: In contrast to previous studies using nonclinical symptom-based survey data, we found no association between SV and GAD or MDD. By contrast, there were associations of SV with prevalence of SSD, stimulant use disorder, and OUD with corresponding decreases in treatment. These results suggest that the SVM might assist in developing more comprehensive care models that integrate medical and social care for MH disorders and SUDs.

Social vulnerability and surgery outcomes: a cross-sectional analysis.

BACKGROUND: Post-operative complications present a challenge to the healthcare system due to the high unpredictability of their incidence. Socioeconomic conditions have been established as social determinants of health. However, their contribution relating to postoperative complications is still unclear as it can be heterogeneous based on community, type of surgical services, and sex and gender. Uncovering these relations can enable improved public health policy to reduce such complications. METHODS: In this study, we conducted a large population cross-sectional analysis of social vulnerability and the odds of various post-surgical complications. We collected electronic health records data from over 50,000 surgeries that happened between 2012 and 2018 at a quaternary health center in St. Louis, Missouri, United States and the corresponding zip code of the patients. We built statistical logistic regression models of postsurgical complications with the social vulnerability index of the tract consisting of the zip codes of the patient as the independent variable along with sex and race interaction. RESULTS: Our sample from the St. Louis area exhibited high variance in social vulnerability with notable rapid increase in vulnerability from the south west to the north of the Mississippi river indicating high levels of inequality. Our sample had more females than males, and females had slightly higher social vulnerability index. Postoperative complication incidence ranged from 0.75% to 41% with lower incidence rate among females. We found that social vulnerability was associated with abnormal heart rhythm with socioeconomic status and housing status being the main association factors. We also found associations of the interaction of social vulnerability and female sex with an increase in odds of heart attack and surgical wound infection. Those associations disappeared when controlling for general health and comorbidities. CONCLUSIONS: Our results indicate that social vulnerability measures such as socioeconomic status and housing conditions could affect postsurgical outcomes through preoperative health. This suggests that the domains of preventive medicine and public health should place social vulnerability as a priority to achieve better health outcomes of surgical interventions.

Family structure and social vulnerability as risk factors for traumatic dental injuries in children and adolescents: a systematic review and meta-analysis.

OBJECTIVE: To investigate the associations between family structure and social vulnerability with TDIs in children and adolescents. METHODS: An electronic search was conducted in seven databases (PubMed, Scopus, LILACS, Embase, Web of Science, ProQuest, and Google Scholar) to retrieve observational studies that evaluated the prevalence of TDIs. The risk of bias was assessed using the JBI Critical Appraisal Tools. Meta-analyses were also conducted using odds ratios (ORs) and 95% confidence intervals (CIs). The certainty of evidence was evaluated using the GRADE approach. RESULTS: Out of 7,424 records, seventeen articles were included (n = 18,806 children and adolescents aged between 0 and 19 years). Only two studies had a low risk of bias. Children and adolescents from nonnuclear families were more likely to suffer from TDIs (OR: 1.39; 95% CI: 1.17; 1.66). On the other hand, the level of social vulnerability did not show a positive association with TDIs (OR - 1.21; 95% CI: 1.00; 1.47). The GRADE approach assessed the certainty of evidence as low. CONCLUSION: Despite the uncertainty of the evidence, children and adolescents from nonnuclear families are more likely to have TDIs than are those from nuclear families. On the other hand, social vulnerability does not seem to be associated with episodes of TDIs in children and adolescents. CLINICAL RELEVANCE: Through knowledge of the risk factors for TDIs, it is possible to develop public policies for their prevention.