Social Determinants Of Health Domains Research Articles

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 and Cancer Pain in the US: Scoping Review.

Social determinants of health (SDOH) are structural factors that yield health inequities. Within the context of cancer, these inequities include screening rates and survival rates, as well as higher symptom burden during and after treatment. While pain is one of the most frequently reported symptoms, the relationship between SDOHs and cancer pain is not well understood. The purpose of this study is to describe and synthesize the published research that has evaluated the relationships between SDOH and cancer pain. A systematic search of PubMed, CINAHL, and Embase was conducted to identify studies in which cancer pain and SDOH were described. In all, 20 studies met the inclusion criteria. In total, 14 studies reported a primary aim related to SDOH and cancer pain. Demographic variables including education or income were used most frequently. Six specific measurements were utilized to measure SDOH, such as the acculturation scale, the composite measure of zip codes for poverty level and blight prevalence, or the segregation index. Among the five domains of SDOH based on Healthy People 2030, social and community was the most studied, followed by economic stability, and education access and quality. The neighborhood and built environment domain was the least studied. Despite increasing attention to SDOH, the majority of published studies use single-dimension variables derived from demographic data to evaluate the relationships between SDOH and cancer pain. Future research is needed to explore the intersectionality of SDOH domains and their impact on cancer pain. Additionally, intervention studies should be conducted to address existing disparities and to reduce the incidence and impact of cancer pain.

Categorizing Sports-Related Concussion Disparities by Key Domains of Social Determinants of Health.

To explore recently published data on disparities in concussion and best categorize these data into domains of social determinants of health (SDOH). Disparities in concussion cover a range of SDOH domains. Questions on disparities in concussion remain. Interventions to reduce these disparities and inequities are needed. Social determinants of health may play a significant role in disparities and inequities in sports related concussion. There is interplay and overlap in SDOH domains that affect concussion outcomes. It is possible that an increase in SDOH may affect concussion disparities by moderated mediation; however, further data is needed to validate this potential effect. Moreover, attention to SDOH domains in sports related concussion may provide insight on intervention targets to ameliorate disparities in sports related concussion.

Contribution of individual and cumulative social determinants of health underlying gender disparities in periodontitis in a representative US population: A cross-sectional NHANES study.

To examine the impact of both individual and cumulative social determinants of health (SDoH) on the likelihood of developing periodontitis, while also exploring any gender disparities in this relationship. Data of self-reported SDoH domains and sub-items based on Healthy People 2030 were obtained from the U.S. National Health and Nutrition Examination Surveys between 1999 and 2014. Logistic regression models, weighted by survey responses, were used to examine the relationship between SDoH (including eight sub-items and the cumulative number of unfavourable SDoH) and periodontitis. The results were further analysed by gender. A total of 18,075 participants (8867 males and 9208 females) were included in the main analysis, of which 5814 (32.2%) had periodontitis. The study found that certain unfavourable SDoH were individually associated with higher odds of periodontitis, and the cumulative number of unfavourable SDoH was positively linked to the odds of developing periodontitis. Furthermore, males exposed to more unfavourable SDoH appeared to be more susceptible to developing periodontitis than females. The findings suggest that unfavourable SDoH, especially when they accumulate, are associated with an increased odds of periodontitis and contribute to gender disparities within the U.S.

Associations of social determinants of health and childhood obesity: a cross-sectional analysis of the 2021 National Survey of Children's Health.

Childhood obesity is a growing health problem in the United States, with those affected having an increased likelihood of developing chronic diseases at a younger age. Social determinants of health (SDOH) are known to influence overall health. Families who are of low socioeconomic status (SES) have also been shown to be more likely to experience food insecurity. Our primary objective was to utilize the National Survey of Children's Health (NSCH) 2021 data to determine the current associations between childhood obesity and SDOH. Secondarily, we estimated the prevalence of select SDOH among children with obesity. We conducted a cross-sectional analysis of 2021 NSCH to extract data related to the SDOH domains. We extracted sociodemographic variables to utilize as controls and constructed logistic regression models to determine associations, via odds ratios, between SDOH and childhood obesity. Within the binary regression models, children with obesity (≥95th percentile) were more likely than children without obesity to experience SDOH in all domains. After controlling for sociodemographic variables, children with obesity were significantly more likely to experience food insecurity when compared to children without obesity (adjusted odds ratio [AOR]=1.39; 95 % confidence interval [CI]: 1.13-1.17). In line with the current American Academy of Pediatrics (AAP) Clinical Practice Guidelines (CPG), improving policies for nutrition programs and addressing the lack of access to nutritious foods may alleviate some food insecurity. Ensuring that children have access to sufficient nutritious foods is critical in addressing childhood obesity and thus decreasing risk of chronic disease.

Evidence gaps among systematic reviews examining the relationship of race, ethnicity, and social determinants of health with adult inpatient quality measures

Abstract Background: The field of healthcare epidemiology is increasingly focused on identifying, characterizing, and addressing social determinants of health (SDOH) to address inequities in healthcare quality. To identify evidence gaps, we examined recent systematic reviews examining the association of race, ethnicity, and SDOH with inpatient quality measures. Methods: We searched Medline via OVID for English language systematic reviews from 2010 to 2022 addressing race, ethnicity, or SDOH domains and inpatient quality measures in adults using specific topic questions. We imported all citations to Covidence (www.covidence.org, Veritas Health Innovation) and removed duplicates. Two blinded reviewers assessed all articles for inclusion in 2 phases: title/abstract, then full-text review. Discrepancies were resolved by a third reviewer. Results: Of 472 systematic reviews identified, 39 were included. Of these, 23 examined all-cause mortality; 6 examined 30-day readmission rates; 4 examined length of stay, 4 examined falls, 2 examined surgical site infections (SSIs) and one review examined risk of venous thromboembolism. The most evaluated SDOH measures were sex (n = 9), income and/or employment status (n = 9), age (n = 6), race and ethnicity (n = 6), and education (n = 5). No systematic reviews assessed medication use errors or healthcare-associated infections. We found very limited assessment of other SDOH measures such as economic stability, neighborhood, and health system access. Conclusion: A limited number of systematic reviews have examined the association of race, ethnicity and SDOH measures with inpatient quality measures, and existing reviews highlight wide variability in reporting. Future systematic evaluations of SDOH measures are needed to better understand the relationships with inpatient quality measures.

Centering Health Equity in the Implementation of the Hospital Incident Command System: A Qualitative Case Comparison Study.

Disasters exacerbate inequities in health care. Health systems use the Hospital Incident Command System (HICS) to plan and coordinate their disaster response. This study examines how 2 health systems prioritized equity in implementing the Hospital Incident Command System (HICS) during the coronavirus disease 2019 (COVID-19) pandemic and identifies factors that influenced implementation. This is a qualitative case comparison study, involving semi-structured interviews with 29 individuals from 2 US academic health systems. Strategies for promoting health equity were categorized by social determinants of health. The Consolidated Framework for Implementation Research (CFIR) guided analysis using a hybrid inductive-deductive approach. The health systems used various strategies to incorporate health equity throughout implementation, addressing all 5 social determinants of health domains. Facilitators included HICS principles, external partnerships, community relationships, senior leadership, health equity experts and networks, champions, equity-stratified data, teaming, and a culture of health equity. Barriers encompassed clarity of the equity representative role, role ambiguity for equity representatives, tokenism, competing priorities, insufficient resource allocation, and lack of preparedness. These findings elucidate how health systems centered equity during HICS implementation. Health systems and regulatory bodies can use these findings as a foundation to revise the HICS and move toward a more equitable disaster response.

Exploring patient's perspective of barriers to diabetic medication adherence in Jazan, Saudi Arabia, using the social determinants of health model.

Type 2 diabetes mellitus is usually associated with long-term macrovascular and microvascular complications that negatively impact the patient's quality of life and add economic burden to the healthcare system. Understanding patients' perspectives on medication nonadherence is essential for planning the appropriate methods and strategies to improve medication adherence among patients with uncontrolled diabetes. Therefore, this study aims to explore patients' perceptions of the barriers to medication adherence through the Social Health determinants framework. After obtaining ethical approval, qualitative face-to-face interviews with a sample of patients with type 2 diabetes mellitus (uncontrolled diabetes) were conducted. Interviews were audio-recorded, and then the data were analyzed using thematic analysis to identify essential themes related to the patient's views. Fifteen patients with type 2 diabetes mellitus were interviewed. Potential barriers to antidiabetic medications were identified and categorized based on the Social Determinants of Health domains. The patient's health perceptions and behaviors were found to positively or negatively impact medication adherence. Beliefs toward antidiabetic medications, polypharmacy, medication-related problems, and the relationship between patients and their healthcare providers that related to healthcare access and quality domains were also reported as potential barriers to medications. Financial constraints, social stigma, and family support were other social health determinants factors that were found to have either positive or negative impacts on adherence. Nevertheless, using mobile health applications was suggested to facilitate medication adherence. Social Determinants of Health, such as education about type 2 diabetes mellitus, quality and access to healthcare, and social stigma and support, might significantly affect medication adherence among type 2 diabetes mellitus patients. This study's findings can aid the development of suitable patient-specific tools and strategies to enhance medication adherence.

Hospital use of common Z-codes for Medicare fee-for-service beneficiaries, 2017-2021.

Recognizing the impact of the social determinants of health (SDOH) on health outcomes, in 2016, the Centers for Medicare and Medicaid Services recommended the use of International Classification of Diseases, 10th Revision (ICD-10), Z-codes to capture patients' health-related social needs. We examined changes in Z-code utilization to document health-related social needs for Medicare fee-for-service recipients among US hospitals between 2017 and 2021 across 5 common SDOH domains. We found that, while 56.9% of hospitals had at least 1 Z-code recorded in at least 1 patient per year, apart from those referring to housing needs, rates of Z-code adoption were low. Additionally, hospitals that were general medical, part of a teaching institution, affiliated with larger health systems, and of medium to large size had greater odds of utilizing Z-codes. Findings from this study highlight the need for continued efforts in promoting the consistent use of standardized SDOH capturing methods like Z-code documentation, such as provider training.

Joint Modeling of Social Determinants and Clinical Factors to Define Subphenotypes in Out-of-Hospital Cardiac Arrest Survival: Cluster Analysis.

Machine learning clustering offers an unbiased approach to better understand the interactions of complex social and clinical variables via integrative subphenotypes, an approach not studied in out-of-hospital cardiac arrest (OHCA). We conducted a cluster analysis for a cohort of OHCA survivors to examine the association of clinical and social factors for mortality at 1 year. We used a retrospective observational OHCA cohort identified from Medicare claims data, including area-level social determinants of health (SDOH) features and hospital-level data sets. We applied k-means clustering algorithms to identify subphenotypes of beneficiaries who had survived an OHCA and examined associations of outcomes by subphenotype. We identified 27,028 unique beneficiaries who survived to discharge after OHCA. We derived 4 distinct subphenotypes. Subphenotype 1 included a distribution of more urban, female, and Black beneficiaries with the least robust area-level SDOH measures and the highest 1-year mortality (2375/4417, 53.8%). Subphenotype 2 was characterized by a greater distribution of male, White beneficiaries and had the strongest zip code-level SDOH measures, with 1-year mortality at 49.9% (4577/9165). Subphenotype 3 had the highest rates of cardiac catheterization at 34.7% (1342/3866) and the greatest distribution with a driving distance to the index OHCA hospital from their primary residence >16.1 km at 85.4% (8179/9580); more were also discharged to a skilled nursing facility after index hospitalization. Subphenotype 4 had moderate median household income at US $51,659.50 (IQR US $41,295 to $67,081) and moderate to high median unemployment at 5.5% (IQR 4.2%-7.1%), with the lowest 1-year mortality (1207/3866, 31.2%). Joint modeling of these features demonstrated an increased hazard of death for subphenotypes 1 to 3 but not for subphenotype 4 when compared to reference. We identified 4 distinct subphenotypes with differences in outcomes by clinical and area-level SDOH features for OHCA. Further work is needed to determine if individual or other SDOH domains are specifically tied to long-term survival after OHCA.

Physical Inactivity and Social Determinants of Health Among Older Adults with Mild Cognitive Impairment and Dementia

AbstractBackgroundPhysical activity can improve the physical health of people living with mild cognitive impairment (MCI) and dementia and may have cognitive benefits. Identifying modifiable social factors inhibiting physical activity among this group is important. We examined the relationship between reported physical activity levels and social determinants of health (SDOH) in a population of older adults living with MCI or dementia.MethodWe included people with a diagnosis of MCI or dementia, age 55 years and older, who were empaneled to Community Internal Medicine at Mayo Clinic (Rochester, Minnesota), had a clinic visit between June 1, 2019 and June 30, 2021 and had completed a SDOH questionnaire. We focused on 8 SDOH domains: education, depression, alcohol use, stress, financial resource strain, social connections, food insecurity and transportation needs. Self‐reported activity levels were categorized as inactive (0 minutes of exercise per week), insufficiently active (10‐140 minutes per week) or sufficiently active (≥150 minutes per week). SDOH domains were compared according to physical activity level using χ2 tests and multinomial logistic regression.ResultA total of 3224 persons with MCI (n = 1371) or dementia (n = 1853) who had completed questions on physical activity were included. Of these, 1936 (60%) were characterized as physically inactive and 837 (26%) insufficiently active. Characteristics associated with an increased likelihood of physical inactivity were older age, female sex, obesity, lower education, dementia diagnosis, depression risk and increased social isolation (all p<0.001).ConclusionPhysical inactivity is common among people living with MCI and dementia. Physical activity levels may be influenced by many modifiable factors, highlighting potential areas for intervention in this population.

Polysocial Risk Scores: Implications for Cardiovascular Disease Risk Assessment and Management.

To review current evidence, discuss key knowledge gaps and identify opportunities for development, validation and application of polysocial risk scores (pSRS) for cardiovascular disease (CVD) risk prediction and population cardiovascular health management. Limited existing evidence suggests that pSRS are promising tools to capture cumulative social determinants of health (SDOH) burden and improve CVD risk prediction beyond traditional risk factors. However, available tools lack generalizability, are cross-sectional in nature or do not assess social risk holistically across SDOH domains. Available SDOH and clinical risk factor data in large population-based databases are under-utilized for pSRS development. Recent advances in machine learning and artificial intelligence present unprecedented opportunities for SDOH integration and assessment in real-world data, with implications for pSRS development and validation for both clinical and healthcare utilization outcomes. pSRS presents unique opportunities to potentially improve traditional "clinical" models of CVD risk prediction. Future efforts should focus on fully utilizing available SDOH data in large epidemiological databases, testing pSRS efficacy in diverse population subgroups, and integrating pSRS into real-world clinical decision support systems to inform clinical care and advance cardiovascular health equity.

Exploring social determinants of health and physical activity levels in older adults living with mild cognitive impairment and dementia in the Upper Midwest of the United States

BackgroundPhysical activity can improve physical health for people living with mild cognitive impairment (MCI) and dementia and may have cognitive benefits. Identifying modifiable social factors inhibiting physical activity among this group is needed. We sought to examine the relationship between reported physical activity levels and social determinants of health (SDOH) in a population of older adults living with MCI or dementia. MethodsThis descriptive study included people with a diagnosis of MCI or dementia followed by Community Internal Medicine at Mayo Clinic (Rochester, Minnesota, United States), aged over 55 years, who had a clinic visit between June 1, 2019 and June 30, 2021 and had completed a SDOH questionnaire. We focused on 8 SDOH domains: education, depression, alcohol use, stress, financial resource strain, social connections, food insecurity, and transportation needs. Data were analyzed based on physical activity level (inactive, insufficiently active, sufficiently active). SDOH domains were compared according to physical activity level using the χ2 test and multinomial logistic regression. ResultsA total of 3224 persons with MCI (n = 1371) or dementia (n = 1853) who had completed questions on physical activity were included. Of these, 1936 (60%) were characterized as physically inactive and 837 (26%) insufficiently active. Characteristics associated with an increased likelihood of physical inactivity were older age, female sex, obesity, lower education, dementia diagnosis, screening positive for depression and increased social isolation (p < 0.001). ConclusionsPhysical inactivity is common among people living with MCI and dementia. Physical activity levels may be influenced by many factors, highlighting potential areas for intervention.

Shortcomings and disparities in contraception counseling and use by hypertensive individuals at risk for unintended pregnancy: a comparative analysis of the National Survey of Family Growth

BackgroundHypertension is a leading cause of adverse pregnancy outcomes. These outcomes disproportionately affect Black individuals. Reproductive life planning that includes patient-centered contraception counseling could mitigate the impact of unintended pregnancy. ObjectiveThe primary objective of the study is to compare contraception counseling and use among hypertensive and non-hypertensive individuals at risk for unintended pregnancy. Our secondary objectives are 1) to evaluate the effect of race on the probability of counseling and the use of contraception and 2) to evaluate the methods used by individuals with hypertension. MethodsData from the 2015-2017 and 2017-2019 National Survey of Family Growth Female Respondent Files were used to analyze whether individuals who reported being informed of having high blood pressure within the prior 12 months received counseling about contraception or received a contraceptive method. Covariates considered in the analysis included age, race, parity, educational attainment, body mass index, smoking, diabetes, and experience with social determinants of health (SDH). The SDH covariate was based on reported experiences within five SDH domains: food security, housing stability, financial security, transportation access, and childcare needs. Linear probability models were employed to estimate the adjusted probability of receiving counseling and the use of a contraceptive. Using difference in difference analyses, we compared the change in counseling and use between hypertensive and non-hypertensive respondents by race, relative to White respondents. ResultsOf the 8,625 subjects analyzed, 771 (9%) were hypertensive. Contraception counseling was received by 26.2% (95%CI 20.4-31.9) of hypertensive individuals and 20.7% (95%CI 19.3-22.2) of non-hypertensive individuals. Contraception use was reported by 39.8% (95% CI 33.2-46.5) of hypertensive and 35.3% (95%CI 33.3-37.2) of non-hypertensive individuals. The linear probability model adjusting for age, parity, education attainment, body mass index, smoking, diabetes and SDH indicated that hypertensive individuals were 8 percentage points (95%CI 3, 18 percentage points). more likely to receive counseling and 9 percentage points (95%CI 3, 16 percentage points) more likely to receive contraception. Hypertensive Black individuals did not receive more counseling or use more contraceptives compared to non-hypertensive Black women. The lack of difference in counseling when hypertension is present is 13 percent less than the change we observed for White respondents when hypertension was present (p=0.01). The most frequently used contraceptive method among hypertensive individuals was combined oral contraceptive pills (COCs) [54.0% (95%CI 44.3-63.5%)]. ConclusionsDespite a higher likelihood of receiving contraception counseling and using contraception among hypertensive individuals at risk for unintended pregnancy, two-thirds of this population did not receive contraception counseling, and less than 40% used any contraceptive method. Furthermore, unlike for White individuals, Black individuals with hypertension did not receive more contraception care than non-hypertensive Black individuals. Of all those who used contraception, half relied on a method classified as Center for Disease Control Medical Eligibility Criteria Category 3. These findings highlight a substantial unmet need for safe and accessible contraception options for hypertensive individuals at risk for unintended pregnancy, emphasizing the importance of targeted interventions to improve contraceptive care and counseling in this population.

Social Determinants of Intrinsic Capacity: A National Cohort Study

IntroductionIntrinsic capacity (IC), a composite of physical and mental capacities, is a marker of healthy aging. Social determinants of health (SDOH), namely the economic and social environments across a lifespan, are the most fundamental factors influencing health outcomes and health disparities. However, there is limited evidence on the influence of the individual and combined burden of the SDOH on IC. MethodsData were obtained from the China Health and Retirement Longitudinal Study (2011-2015), and data analysis was conducted in 2023. Linear mixed-effect regression was employed to investigate the association between SDOH and IC in a longitudinal analysis. ResultsThis study comprised 7669 participants (mean [SD] age, 68.5 [7.1] years; 49.8% female; mean [SD] IC, 7.2 [1.6]). In the longitudinal analysis, all five SDOH domains were independently and significantly associated with IC. The absence of social association within the social and community context domain exhibited the weakest association with IC (β: -0.11 [95% confidence interval (CI) -0.20, -0.02]), while illiteracy within the education access and quality domain demonstrated the strongest association with IC (β: -0.51 [95% CI -0.60, -0.42]). Furthermore, the adverse effects of SDOH on IC became more distinguishable with the cumulative number of SDOH variables (coefficient for 2 SDOH, -0.41 [-0.64, -0.19]; 3 SDOH, -0.70 [-0.93, -0.48]; ≥4 SDOH, -1.10 [-1.33, -0.88]) compared with those without any SDOH. ConclusionsCertain SDOH levels were significantly and negatively associated with IC. Targeted interventions may be needed to improve SDOH in individuals at high risk of poor IC.

Development and Testing of a Mobile App to Collect Social Determinants of Health Data in Cancer Settings: Interview Study.

Social determinants of health (SDOH) such as lack of basic resources, housing, transportation, and social isolation play an important role for patients on the cancer care continuum. Health systems' current technological solutions for identifying and managing patients' SDOH data largely focus on information recorded in the electronic health record by providers, which is often inaccessible to patients to contribute to or modify. We developed and tested a patient-centric SDOH screening tool designed for use on patients' personal mobile phone that preserves patient privacy and confidentiality, collects information about the unmet social needs of patients with cancer, and communicates them to the provider. We interviewed 22 patients with cancer, oncologists, and social workers associated with a US-based comprehensive cancer center to better understand how patients' SDOH information is collected and reported. After triangulating data obtained from thematic analysis of interviews, an environmental scan, and a literature search of validated tools to collect SDOH data, we developed an SDOH screening tool mobile app and conducted a pilot study of 16 dyadic pairs of patients and cancer care team members at the same cancer center. We collected patient SDOH data using 36 survey items covering 7 SDOH domains and used validated scales and follow-up interviews to assess the app's usability and acceptability among patients and cancer care team members. Formative interviews with patients and care team members revealed that transportation, financial challenges, food insecurity, and low health literacy were common SDOH challenges and that a mobile app that collected those data, shared those data with care team members, and offered supportive resources could be useful and valuable. In the pilot study, 25% (4/16) of app-using patients reported having at least one of the abovementioned social needs; the most common social need was social isolation (7/16, 44%). Patients rated the mobile app as easy to use, accurately capturing their SDOH, and preserving their privacy but suggested that the app could be more helpful by connecting patients to actual resources. Providers reported high acceptability and usability of the app. Use of a brief, patient-centric, mobile app-based SDOH screening tool can effectively capture SDOH of patients with cancer for care team members in a way that preserves patient privacy and that is acceptable and usable for patients and care team members. However, only collecting SDOH information is not sufficient; usefulness can be increased by connecting patients directly to resources to address their unmet social needs.

An observational, sequential analysis of the relationship between local economic distress and inequities in health outcomes, clinical care, health behaviors, and social determinants of health

BackgroundSocioeconomic status has long been associated with population health and health outcomes. While ameliorating social determinants of health may improve health, identifying and targeting areas where feasible interventions are most needed would help improve health equity. We sought to identify inequities in health and social determinants of health (SDOH) associated with local economic distress at the county-level.MethodsFor 3,131 counties in the 50 US states and Washington, DC (wherein approximately 325,711,203 people lived in 2019), we conducted a retrospective analysis of county-level data collected from County Health Rankings in two periods (centering around 2015 and 2019). We used ANOVA to compare thirty-three measures across five health and SDOH domains (Health Outcomes, Clinical Care, Health Behaviors, Physical Environment, and Social and Economic Factors) that were available in both periods, changes in measures between periods, and ratios of measures for the least to most prosperous counties across county-level prosperity quintiles, based on the Economic Innovation Group’s 2015–2019 Distressed Community Index Scores.ResultsWith seven exceptions, in both periods, we found a worsening of values with each progression from more to less prosperous counties, with least prosperous counties having the worst values (ANOVA p < 0.001 for all measures). Between 2015 and 2019, all except six measures progressively worsened when comparing higher to lower prosperity quintiles, and gaps between the least and most prosperous counties generally widened.ConclusionsIn the late 2010s, the least prosperous US counties overwhelmingly had worse values in measures of Health Outcomes, Clinical Care, Health Behaviors, the Physical Environment, and Social and Economic Factors than more prosperous counties. Between 2015 and 2019, for most measures, inequities between the least and most prosperous counties widened. Our findings suggest that local economic prosperity may serve as a proxy for health and SDOH status of the community. Policymakers and leaders in public and private sectors might use long-term, targeted economic stimuli in low prosperity counties to generate local, community health benefits for vulnerable populations. Doing so could sustainably improve health; not doing so will continue to generate poor health outcomes and ever-widening economic disparities.

Cumulative social disadvantage and health-related quality of life: national health interview survey 2013–2017

BackgroundEvidence for the association between social determinants of health (SDoH) and health-related quality of life (HRQoL) is largely based on single SDoH measures, with limited evaluation of cumulative social disadvantage. We examined the association between cumulative social disadvantage and the Health and Activity Limitation Index (HALex).MethodsUsing adult data from the National Health Interview Survey (2013–2017), we created a cumulative disadvantage index by aggregating 47 deprivations across 6 SDoH domains. Respondents were ranked using cumulative SDoH index quartiles (SDoH-Q1 to Q4), with higher quartile groups being more disadvantaged. We used two-part models for continuous HALex scores and logistic regression for poor HALex (< 20th percentile score) to examine HALex differences associated with cumulative disadvantage. Lower HALex scores implied poorer HRQoL performance.ResultsThe study sample included 156,182 respondents, representing 232.8 million adults in the United States (mean age 46 years; 51.7% women). The mean HALex score was 0.85 and 17.7% had poor HALex. Higher SDoH quartile groups had poorer HALex performance (lower scores and increased prevalence of poor HALex). A unit increase in SDoH index was associated with − 0.010 (95% CI [-0.011, -0.010]) difference in HALex score and 20% higher odds of poor HALex (odds ratio, OR = 1.20; 95% CI [1.19, 1.21]). Relative to SDoH-Q1, SDoH-Q4 was associated with HALex score difference of -0.086 (95% CI [-0.089, -0.083]) and OR = 5.32 (95% CI [4.97, 5.70]) for poor HALex. Despite a higher burden of cumulative social disadvantage, Hispanics had a weaker SDoH-HALex association than their non-Hispanic White counterparts.ConclusionsCumulative social disadvantage was associated with poorer HALex performance in an incremental fashion. Innovations to incorporate SDoH-screening tools into clinical decision systems must continue in order to accurately identify socially vulnerable groups in need of both clinical risk mitigation and social support. To maximize health returns, policies can be tailored through community partnerships to address systemic barriers that exist within distinct sociodemographic groups, as well as demographic differences in health perception and healthcare experience.

Disparities in Lupus and the Role of Social Determinants of Health: Current State of Knowledge and Directions for Future Research.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease. The complex relationships between race and ethnicity and social determinants of health (SDOH) in influencing SLE and its course are increasingly appreciated. Multiple SDOH have been strongly associated with lupus incidence and outcomes and contribute to health disparities in lupus. Measures of socioeconomic status, including economic instability, poverty, unemployment, and food insecurity, as well as features of the neighborhood and built environment, including lack of safe and affordable housing, crime, stress, racial segregation, and discrimination, are associated with race and ethnicity in the US and are risk factors for poor outcomes in lupus. In this scientific statement, we aimed to summarize current evidence on the role of SDOH in relation to racial and ethnic disparities in SLE and SLE outcomes, primarily as experienced in the U.S. Lupus Foundation of America's Health Disparities Advisory Panel, comprising 10 health disparity experts, including academic researchers and patients, who met 12 times over the course of 18 months in assembling and reviewing the data for this study. Sources included articles published from 2011 to 2023 in PubMed, Centers for Disease Control and Prevention data, and bibliographies and recommendations. Search terms included lupus, race, ethnicity, and SDOH domains. Data were extracted and synthesized into this scientific statement. Poorer neighborhoods correlate with increased damage, reduced care, and stress-induced lupus flares. Large disparities in health care affordability, accessibility, and acceptability exist in the US, varying by region, insurance status, and racial and minority groups. Preliminary interventions targeted social support, depression, and shared-decision-making, but more research and intervention implementation and evaluation are needed. Disparities in lupus across racial and ethnic groups in the US are driven by SDOH, some of which are more easily remediable than others. A multidimensional and multidisciplinary approach involving various stakeholder groups is needed to address these complex challenges, address these diminish disparities, and improve outcomes.

Social Determinants of Health in Women With Heart Failure: Prospective Observational Cohort Study

ObjectiveThe social determinants of health (SDoH) account for 80%-90% of modifiable contributors to health outcomes for chronic diseases such as heart failure. Knowledge gaps exist on how SDoH influences hospitalization rates in women with heart failure. Our aim was to evaluate the relationship between the baseline SDoH status of women with heart failure with subsequent all-cause and cardiovascular hospitalization. MethodsThis is a prospective observational longitudinal cohort study of women diagnosed with heart failure with 6-month follow-up. The subjects completed SDoH assessment by the Institute of Medicine. Monthly follow-ups were performed to assess for hospitalization events. ResultsA total of 92 patients with at least 1 follow-up clinic visit were included. The mean age was 66 ± 15 years and 80% had nonischemic cardiomyopathy as the etiology of heart failure. New York Heart Association (NYHA) Classifications I-II were the most common (n = 66, 71.8%). In total, 51 patients (55.4%) had overall high-risk SDoH (4 or more SDoH domains at risk). By the 6-month follow-up, 22 (23.9%) patients were hospitalized for any cause; 8 patients (8.7%) were hospitalized for cardiovascular causes. There were no deaths. In multivariate logistic regression analysis, the high-risk SDoH group had a higher odds ratio for all-cause hospitalization (OR 5.31, 95% CI 1.59-17.73). In addition, Kansas City Cardiomyopathy Questionnaire 12-item (KCCQ-12) scores, surrogate for quality of life, were worse in the high-risk SDoH group. ConclusionSDoH adversely impacts hospitalizations and quality of life in women with heart failure. Future efforts for screening and interventions should evaluate the SDoH at all levels, including the individual health care provider, institutional, and national levels.