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

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

Unfavorable social determinants of health and mortality risk by cardiovascular disease status: Findings from a National Study of United States Adults.

BACKGROUND: The association between cumulative burden of unfavorable social determinants of health (SDoH) and all-cause mortality has not been assessed by atherosclerotic cardiovascular disease (ASCVD) status on a population level in the United States. METHODS: We assessed the association between cumulative social disadvantage and all-cause mortality by ASCVD status in the National Health Interview Survey, linked to the National Death Index. RESULTS: In models adjusted for established clinical risk factors, individuals experiencing the highest level of social disadvantage (SDoH-Q4) had over 1.5 (aHR = 1.55; 95%CI = 1.22, 1.96) and 2-fold (aHR = 2.21; 95% CI = 1.91, 2.56) fold increased risk of mortality relative to those with the most favorable social profile (SDoH-Q1), respectively for adults with and without ASCVD; those experiencing co-occurring ASCVD and high social disadvantage had up to four-fold higher risk of mortality (aHR = 3.81; 95%CI = 3.36, 4.32). CONCLUSIONS: These findings emphasize the importance of a healthcare model that prioritizes efforts to identify and address key social and environmental barriers to health and wellbeing, particularly in individuals experiencing the double jeopardy of clinical and social risk.

Social Phenotyping for Cardiovascular Risk Stratification in Electronic Health Registries.

PURPOSE OF REVIEW: Evaluation of social influences on cardiovascular care requires a comprehensive analysis encompassing economic, societal, and environmental factors. The increased utilization of electronic health registries provides a foundation for social phenotyping, yet standardization in methodology remains lacking. This review aimed to elucidate the primary approaches to social phenotyping for cardiovascular risk stratification through electronic health registries. RECENT FINDINGS: Social phenotyping in the context of cardiovascular risk stratification within electronic health registries can be separated into four principal approaches: place-based metrics, questionnaires, ICD Z-coding, and natural language processing. These methodologies vary in their complexity, advantages and limitations, and intended outcomes. Place-based metrics often rely on geospatial data to infer socioeconomic influences, while questionnaires may directly gather individual-level behavioral and social factors. Z-coding, a relatively new approach, can capture data directly related to social determinant of health domains in the clinical context. Natural language processing has been increasingly utilized to extract social influences from unstructured clinical narratives-offering nuanced insights for risk prediction models. Each method plays an important role in our understanding and approach to using social determinants data for improving population cardiovascular health. These four principal approaches to social phenotyping contribute to a more structured approach to social determinant of health research via electronic health registries, with a focus on cardiovascular risk stratification. Social phenotyping related research should prioritize refining predictive models for cardiovascular diseases and advancing health equity by integrating applied implementation science into public health strategies.

Association of cardiovascular risk profile with premature all-cause and cardiovascular mortality in US adults: findings from a national study.

OBJECTIVE: To assess the association between cardiovascular risk factor (CRF) profile and premature all-cause and cardiovascular disease (CVD) mortality among US adults (age < 65). METHODS: This study used data from the National Health Interview Survey from 2006 to 2014, linked to the National Death Index for non-elderly adults aged < 65 years. A composite CRF score (range = 0-6) was calculated, based on the presence or absence of six established cardiovascular risk factors: hypertension, diabetes, hypercholesterolemia, smoking, obesity, and insufficient physical activity. CRF profile was defined as "Poor" (≥ 3 risk factors), "Average" (1-2), or "Optimal" (0 risk factors). Age-adjusted mortality rates (AAMR) were reported across CRF profile categories, separately for all-cause and CVD mortality. Cox proportional hazard models were used to evaluate the association between CRF profile and all-cause and CVD mortality. RESULTS: Among 195,901 non-elderly individuals (mean age: 40.4 ± 13.0, 50% females and 70% Non-Hispanic (NH) White adults), 24.8% had optimal, 58.9% average, and 16.2% poor CRF profiles, respectively. Participants with poor CRF profile were more likely to be NH Black, have lower educational attainment and lower income compared to those with optimal CRF profile. All-cause and CVD mortality rates were three to four fold higher in individuals with poor CRF profile, compared to their optimal profile counterparts. Adults with poor CRF profile experienced 3.5-fold (aHR: 3.48 [95% CI: 2.96, 4.10]) and 5-fold (aHR: 4.76 [3.44, 6.60]) higher risk of all-cause and CVD mortality, respectively, compared to those with optimal profile. These results were consistent across age, sex, and race/ethnicity subgroups. CONCLUSIONS: In this population-based study, non-elderly adults with poor CRF profile had a three to five-fold higher risk of all-cause and CVD mortality, compared to those with optimal CRF profile. Targeted prevention efforts to achieve optimal cardiovascular risk profile are imperative to reduce the persistent burden of premature all-cause and CVD mortality in the US.

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

PURPOSE OF REVIEW: 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. RECENT FINDINGS: 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.

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

BACKGROUND: Evidence 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). METHODS: Using 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. RESULTS: The 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. CONCLUSIONS: Cumulative 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.

Low educational attainment is associated with higher all-cause and cardiovascular mortality in the United States adult population.

INTRODUCTION: Educational attainment is an important social determinant of health (SDOH) for cardiovascular disease (CVD). However, the association between educational attainment and all-cause and CVD mortality has not been longitudinally evaluated on a population-level in the US, especially in individuals with atherosclerotic cardiovascular disease (ASCVD). In this nationally representative study, we assessed the association between educational attainment and the risk of all-cause and cardiovascular (CVD) mortality in the general adult population and in adults with ASCVD in the US. METHODS: We used data from the 2006-2014 National Death Index-linked National Health Interview Survey for adults ≥ 18 years. We generated age-adjusted mortality rates (AAMR) by levels of educational attainment (< high school (HS), HS/General Education Development (GED), some college, and ≥ College) in the overall population and in adults with ASCVD. Cox proportional hazards models were used to examine the multivariable-adjusted associations between educational attainment and all-cause and CVD mortality. RESULTS: The sample comprised 210,853 participants (mean age 46.3), representing ~ 189 million adults annually, of which 8% had ASCVD. Overall, 14.7%, 27%, 20.3%, and 38% of the population had educational attainment < HS, HS/GED, Some College, and ≥ College, respectively. During a median follow-up of 4.5 years, all-cause age-adjusted mortality rates were 400.6 vs. 208.6 and 1446.7 vs. 984.0 for the total and ASCVD populations for < HS vs ≥ College education, respectively. CVD age adjusted mortality rates were 82.1 vs. 38.7 and 456.4 vs 279.5 for the total and ASCVD populations for < HS vs ≥ College education, respectively. In models adjusting for demographics and SDOH, < HS (reference = ≥ College) was associated with 40-50% increased risk of mortality in the total population and 20-40% increased risk of mortality in the ASCVD population, for both all-cause and CVD mortality. Further adjustment for traditional risk factors attenuated the associations but remained statistically significant for < HS in the overall population. Similar trends were seen across sociodemographic subgroups including age, sex, race/ethnicity, income, and insurance status. CONCLUSIONS: Lower educational attainment is independently associated with increased risk of all-cause and CVD mortality in both the total and ASCVD populations, with the highest risk observed for individuals with < HS education. Future efforts to understand persistent disparities in CVD and all-cause mortality should pay close attention to the role of education, and include educational attainment as an independent predictor in mortality risk prediction algorithms.

Social Vulnerability and Premature Cardiovascular Mortality Among US Counties, 2014 to 2018.

BACKGROUND: Substantial differences exist between United States counties with regards to premature (<65 years of age) cardiovascular disease (CVD) mortality. Whether underlying social vulnerabilities of counties influence premature CVD mortality is uncertain. METHODS: In this cross-sectional study (2014-2018), we linked county-level CDC/ATSDR SVI (Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry Social Vulnerability Index) data with county-level CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiological Research) mortality data. We calculated scores for overall SVI and its 4 subcomponents (ie, socioeconomic status; household composition and disability; minority status and language; and housing type and transportation) using 15 social attributes. Scores were presented as percentile rankings by county, further classified as quartiles on the basis of their distribution among all US counties (1st [least vulnerable] = 0 to 0.25; 4th [most vulnerable = 0.75 to 1.00]). We grouped age-adjusted mortality rates per 100 000 person-years for overall CVD and its subtypes (ischemic heart disease, stroke, hypertension, and heart failure) for nonelderly (<65 years of age) adults across SVI quartiles. RESULTS: Overall, the age-adjusted CVD mortality rate per 100 000 person-years was 47.0 (ischemic heart disease, 28.3; stroke, 7.9; hypertension, 8.4; and heart failure, 2.4). The largest concentration of counties with more social vulnerabilities and CVD mortality were clustered across the southwestern and southeastern parts of the United States. The age-adjusted CVD mortality rates increased in a stepwise manner from 1st to 4th SVI quartiles. Counties in the 4th SVI quartile had significantly higher mortality for CVD (rate ratio, 1.84 [95% CI, 1.43-2.36]), ischemic heart disease (1.52 [1.09-2.13]), stroke (2.03 [1.12-3.70]), hypertension (2.71 [1.54-4.75]), and heart failure (3.38 [1.32-8.61]) than those in the 1st SVI quartile. The relative risks varied considerably by demographic characteristics. For example, among all ethnicities/races, non-Hispanic Black adults in the 4th SVI quartile versus the 1st SVI quartile exclusively had significantly higher relative risks of stroke (1.65 [1.07-2.54]) and heart failure (2.42 [1.29-4.55]) mortality. Rural counties with more social vulnerabilities had 2- to 5-fold higher mortality attributable to CVD and subtypes. CONCLUSIONS: In this analysis, US counties with more social vulnerabilities had higher premature CVD mortality, varied by demographic characteristics and rurality. Focused public health interventions should address the socioeconomic disparities faced by underserved communities to curb the growing burden of premature CVD.

Delayed medical care due to transportation barriers among adults with atherosclerotic cardiovascular disease.

BACKGROUND: In patients with atherosclerotic cardiovascular disease (ASCVD), barriers related to transportation may impair access to care, with potential implications for prognosis. Although few studies have explored transportation barriers among patients with ASCVD, the correlates of delayed care due to transportation barriers have not been examined in this population. We aimed to examine this in U.S. patients with ASCVD using nationally representative data. METHODS: Using data from the 2009-2018 National Health Interview Survey, we estimated the self-reported prevalence of delayed medical care due to transportation barriers among adults with ASCVD, overall and by sociodemographic characteristics. Logistic regression was used to examine the association between various sociodemographic characteristics and delayed care due to transportation barriers. RESULTS: Among adults with ASCVD, 4.5% (95% CI; 4.2, 4.8) or ∼876,000 annually reported delayed care due to transportation barriers. Income (low-income: odds ratio [OR] 4.43, 95% CI [3.04, 6.46]; lowest-income: OR 6.35, 95% CI [4.36, 9.23]) and Medicaid insurance (OR 4.53; 95% CI [3.27, 6.29]) were strongly associated with delayed care due to transportation barriers. Additionally, younger individuals, women, non-Hispanic Black adults, and those from the U.S. South or Midwest, had higher odds of reporting delayed care due to transportation barriers. CONCLUSIONS: Approximately 5% of adults with ASCVD experience delayed care due to transportation barriers. Vulnerable groups include young adults, women, low-income people, and those with public/no insurance. Future studies should analyze the feasibility and potential benefits of interventions such as use of telehealth, mobile clinics, and provision of transportation among patients with ASCVD in the U.S.

Disparities in Influenza Vaccination Coverage and Associated Factors Among Adults with Cardiovascular Disease, United States, 2011-2020.

INTRODUCTION: Influenza vaccination can reduce the incidence of cardiovascular disease (CVD) in the US. However, differences in state-level trends in CVD and sociodemographic and health care characteristics of adults with CVD have not yet been studied. METHODS: In this repeated cross-sectional study, we extracted 476,227 records of adults with a self-reported history of CVD from the Behavioral Risk Factor Surveillance System from January 2011 through December 2020. We calculated the prevalence and likelihood of annual influenza vaccination by sociodemographic characteristics, health care characteristics, and CVD risk factors. Additionally, we examined annual trends of influenza vaccination by geographic location. RESULTS: The annual age-adjusted influenza vaccination rate among adults with CVD increased from 38.6% (2011) to 44.3% (2020), with an annual average percentage change of 1.1%. Adults who were aged 18 to 44 years, male, non-Hispanic Black/African American, or Hispanic, or had less than a high school diploma, annual household income less than $50,000, and no health insurance had a lower prevalence of vaccination. The odds of vaccination were lower among non-Hispanic Black/African American (adjusted odds ratio, 0.73; 95% CI, 0.70-0.77) and non-Hispanic American Indian/Alaska Native (adjusted odds ratio, 0.86; 95% CI, 0.75-0.98) compared with non-Hispanic White adults. Only 16 states achieved a vaccination rate of 50%; no state achieved the Healthy People 2020 goal of 70%. Nonmedical settings (supermarkets, drug stores) gained popularity (19.2% in 2011 to 28.5% in 2018) as a vaccination setting. CONCLUSION: Influenza vaccination among adults with CVD improved marginally during the past decade but is far behind the targeted national goals. Addressing existing disparities requires attention to the role of social determinants of health in determining access to vaccination, particularly among young people, racial and ethnic minority populations, people who lack health insurance, and people with comorbidities.

Race and Ethnicity and Cardiometabolic Risk Profile: Disparities Across Income and Health Insurance in a National Sample of US Adults.

CONTEXT: Income and health insurance are important social determinants of cardiovascular disease (CVD) and may explain much racial/ethnic variation in CVD burden. However, racial/ethnic disparities in cumulative cardiometabolic (CMB) risk profile by insurance type and income level have not been studied on a national scale. OBJECTIVES: To test the hypothesis that racial/ethnic minorities experience greater CMB burden at each income level and insurance type than non-Hispanic Whites (NHW). SETTING: This study used nationally representative data from the National Health Interview Survey (NHIS). DESIGN: Observational (cross-sectional). PARTICIPANTS: In total, 134661 (weighted N = 197780611) adults, 18 years or older, from the 2013-2017 NHIS. PRIMARY OUTCOME: CMB risk profile. INTERVENTION/ANALYSIS: Age-adjusted prevalence of optimal, average, and poor CMB risk profile-defined respectively as self-report of 0, 1-2, and 3 or more risk factors of diabetes, hypertension, obesity, or hypercholesterolemia-was examined for NHW, non-Hispanic Blacks (NHB), and Hispanics. Multivariable ordinal logistic regression models were used to test the association between race and ethnicity and CMB profile overall and separately by household income level and insurance type. RESULTS: Overall, 15% of NHB and 11% of Hispanics experienced poor CMB risk profile, compared with 9% for NHW. In fully adjusted models, NHB and Hispanics, respectively had nearly 25%-90% and 10%-30% increased odds of poor CMB profile across insurance types and 45%-60% and 15%-30% increased odds of poor CMB profile across income levels, relative to NHW. The observed disparities were widest for the Medicare group (NHB: OR = 1.90; Hispanics: OR = 1.31) and highest-income level (NHB: OR = 1.62). CONCLUSIONS: Racial/ethnic minorities experience poor CMB profile at each level of income and insurance. These findings point to the need for greater investigation of unmeasured determinants of minority cardiovascular (CV) health, including structural racism and implicit bias in CV care.

Financial Hardship Among Nonelderly Adults With CKD in the United States.

RATIONALE & OBJECTIVE: The burden of financial hardship among individuals with chronic kidney disease (CKD) has not been extensively studied. Therefore, we describe the scope and determinants of financial hardship among a nationally representative sample of adults with CKD. STUDY DESIGN: Cross-sectional. SETTING & PARTICIPANTS: Nonelderly adults with CKD from the 2014-2018 National Health Interview Survey. EXPOSURE: Sociodemographic and clinical characteristics. OUTCOME: Financial hardship based on medical bills and consequences of financial hardship (high financial distress, food insecurity, cost-related medication nonadherence, delayed/forgone care due to cost). Financial hardship was categorized into 3 levels: no financial hardship, financial hardship but able to pay bills, and unable to pay bills at all. Financial hardship was then modeled in 2 different ways: (1) any financial hardship (regardless of ability to pay) versus no financial hardship and (2) inability to pay bills versus no financial hardship and financial hardship but able to pay bills. ANALYTICAL APPROACH: Nationally representative estimates of financial hardship from medical bills were computed. Multivariable logistic regression models were used to examine the associations of sociodemographic and clinical factors with the outcomes of financial hardship based on medical bills. RESULTS: A total 1,425 individuals, representing approximately 2.1 million Americans, reported a diagnosis of CKD within the past year, of whom 46.9% (95% CI, 43.7%-50.2%) reported experiencing financial hardship from medical bills; 20.9% (95% CI, 18.5%-23.6%) reported inability to pay medical bills at all. Lack of insurance was the strongest determinant of financial hardship in this population (odds ratio, 4.06 [95% CI, 2.18-7.56]). LIMITATIONS: Self-reported nature of CKD diagnosis. CONCLUSIONS: Approximately half the nonelderly US population with CKD experiences financial hardship from medical bills that is associated strongly with lack of insurance. Evidence-based clinical and policy interventions are needed to address these hardships.

Social Determinants of Health and Cardiovascular Disease: Current State and Future Directions Towards Healthcare Equity.

PURPOSE OF REVIEW: We sought to examine the role of social and environmental conditions that determine an individual's behaviors and risk of disease-collectively known as social determinants of health (SDOH)-in shaping cardiovascular (CV) health of the population and giving rise to disparities in risk factors, outcomes, and clinical care for cardiovascular disease (CVD), the leading cause of death in the United States (US). RECENT FINDINGS: Traditional CV risk factors have been extensively targeted in existing CVD prevention and management paradigms, often with little attention to SDOH. Limited evidence suggests an association between individual SDOH (e.g., income, education) and CVD. However, inequities in CVD care, risk factors, and outcomes have not been studied using a broad SDOH framework. We examined existing evidence of the association between SDOH-organized into 6 domains, including economic stability, education, food, neighborhood and physical environment, healthcare system, and community and social context-and CVD. Greater social adversity, defined by adverse SDOH, was linked to higher burden of CVD risk factors and poor outcomes, such as stroke, myocardial infarction (MI), coronary heart disease, heart failure, and mortality. Conversely, favorable social conditions had protective effects on CVD. Upstream SDOH interact across domains to produce cumulative downstream effects on CV health, via multiple physiologic and behavioral pathways. SDOH are major drivers of sociodemographic disparities in CVD, with a disproportionate impact on socially disadvantaged populations. Efforts to achieve health equity should take into account the structural, institutional, and environmental barriers to optimum CV health in marginalized populations. In this review, we highlight major knowledge gaps for each SDOH domain and propose a set of actionable recommendations to inform CVD care, ensure equitable distribution of healthcare resources, and reduce observed disparities.

Testosterone replacement therapy and hospitalization rates in men with COPD.

Testosterone deficiency is common in men with chronic obstructive pulmonary disease (COPD) and may exacerbate their condition. Research suggests that testosterone replacement therapy (TRT) may have a beneficial effect on respiratory outcomes in men with COPD. To date, however, no large-scale nationally representative studies have examined this association. The objective of the study was to assess whether TRT reduced the risk of respiratory hospitalizations in middle-aged and older men with COPD. We conducted two retrospective cohort studies. First, using the Clinformatics Data Mart-a database of one of the largest commercially insured populations in the United States-we examined 450 men, aged 40-63 years, with COPD who initiated TRT between 2005 and 2014. Second, using the national 5% Medicare database, we examined 253 men, aged ≥66 years, with COPD who initiated TRT between 2008 and 2013. We used difference-in-differences (DID) statistical modeling to compare pre- versus post-respiratory hospitalization rates in TRT users versus matched TRT nonusers over a parallel time period. DID analyses showed that TRT users had a greater relative decrease in respiratory hospitalizations compared with nonusers. Specifically, middle-aged TRT users had a 4.2% greater decrease in respiratory hospitalizations compared with nonusers (-2.4 decrease vs. 1.8 increase; p = 0.03); and older TRT users had a 9.1% greater decrease in respiratory hospitalizations compared with nonusers (-0.8 decrease vs. 8.3 increase; p = 0.04). These findings suggest that TRT may slow disease progression in patients with COPD. Future studies should examine this association in larger cohorts of patients, with particular attention to specific biological pathways.

Association of Obesity With Psychological Distress in Young Adults: Patterns by Sex and Race or Ethnicity.

Background: Recent studies have emphasized the intricate relationship between obesity and psychological distress, unraveling the complex interplay of biological, psychological, and sociocultural factors. However, a conspicuous knowledge gap persists in understanding the association between obesity severity and psychological distress, particularly in young adults, marked by limited empirical data. Objectives: This study comprehensively investigates the link between obesity and psychological distress among young adults, emphasizing potential variations based on gender and race or ethnicity. Addressing this gap is crucial for informing targeted interventions and understanding the nuanced impact of obesity on mental health in this demographic. Methods: Utilizing data from the 2013 to 2018 National Health Interview Survey, individuals aged 18 to 26 years were analyzed. Body mass index served as the primary exposure variable, with the Kessler Psychological Distress Scale assessing the primary outcome. Fully-adjusted ordinal regression models were employed for analyses. Results: Among the 20,954 participants included in this study, representing 35,564,990 adults, 27% were overweight and 24% had obesity. In class III obesity, individuals experienced 1.4 times more psychological distress than those with normal weight (OR: 1.393; 95% CI: 1.181-1.644; P < 0.001). Subgroup analyses revealed consistent trends in non-Hispanic White (OR: 1.615; 95% CI: 1.283-2.032; P < 0.001) and female participants (OR: 1.408; 95% CI: 1.408-2.096; P < 0.001). Conclusions: This study underscores the association between obesity and psychological distress in young adults, notably impacting non-Hispanic White and female populations. The findings bear significant implications for shaping future health policies, addressing the mental health crisis, and mitigating the increasing prevalence of obesity among young U.S. adults.

Race, Social Determinants of Health, and Risk of All-Cause and Cardiovascular Mortality in the United States.

OBJECTIVE: To examine the independent and interdependent effects of race and social determinants of health (SDoH) and risk of all-cause and cardiovascular disease (CVD) mortality in the US. DATA SOURCE/STUDY DESIGN: Secondary analysis of pooled data for 252,218 participants of the 2006-2018 National Health Interview Survey, linked to the National Death Index. METHODS: Age-adjusted mortality rates (AAMR) were reported for non-Hispanic White (NHW) and non-Hispanic Black (NHB) individuals overall, and by quintiles of SDoH burden, with higher quintiles representing higher cumulative social disadvantage (SDoH-Qx). Survival analysis was used to examine the association between race, SDoH-Qx, and all-cause and CVD mortality. FINDINGS: AAMRs for all-cause and CVD mortality were higher for NHB and considerably higher at higher levels of SDoH-Qx, however, with similar mortality rates at any given level of SDoH-Qx. In multivariable models, NHB experienced 20-25% higher mortality risk relative to NHW (aHR = 1.20-1.26); however, no association was observed after adjusting for SDoH. In contrast, higher SDoH burden was associated with up to nearly threefold increased risk of all-cause (aHR, Q5 vs Q1 = 2.81) and CVD mortality (aHR, Q5 vs Q1 = 2.90); the SDoH effect was observed similarly for NHB (aHR, Q5:all-cause mortality = 2.38; CVD mortality = 2.58) and NHW (aHR, Q5:all-cause mortality = 2.87; CVD mortality = 2.93) subgroups. SDoH burden mediated 40-60% of the association between NHB race and mortality. CONCLUSIONS: These findings highlight the critical role of SDoH as upstream drivers of racial inequities in all-cause and CVD mortality. Population level interventions focused on addressing adverse SDoH experienced by NHB individuals may help mitigate persistent disparities in mortality in the US.

Unfavorable social determinants of health and risk of mortality in adults with diabetes: findings from the National Health Interview Survey.

INTRODUCTION: Understanding the role of social determinants of health as predictors of mortality in adults with diabetes may help improve health outcomes in this high-risk population. Using population-based, nationally representative data, this study investigated the cumulative effect of unfavorable social determinants on all-cause mortality in adults with diabetes. RESEARCH DESIGN AND METHODS: We used data from the 2013-2018 National Health Interview Survey, linked to the National Death Index through 2019, for mortality ascertainment. A total of 47 individual social determinants of health were used to categorize participants in quartiles denoting increasing levels of social disadvantage. Poisson regression was used to report age-adjusted mortality rates across increasing social burden. Multivariable Cox proportional hazards models were used to assess the association between cumulative social disadvantage and all-cause mortality in adults with diabetes, adjusting for traditional risk factors. RESULTS: The final sample comprised 182 445 adults, of whom 20 079 had diabetes. In the diabetes population, mortality rate increased from 1052.7 per 100 000 person-years in the first quartile (Q1) to 2073.1 in the fourth quartile (Q4). In multivariable models, individuals in Q4 experienced up to twofold higher mortality risk relative to those in Q1. This effect was observed similarly across gender and racial/ethnic subgroups, although with a relatively stronger association for non-Hispanic white participants compared with non-Hispanic black and Hispanic subpopulations. CONCLUSIONS: Cumulative social disadvantage in individuals with diabetes is associated with over twofold higher risk of mortality, independent of established risk factors. Our findings call for action to screen for unfavorable social determinants and design novel interventions to mitigate the risk of mortality in this high-risk population.

Social Vulnerability Index and Cardiovascular Disease Care Continuum: A Scoping Review.

Background: Social vulnerability index (SVI) estimates the vulnerability of communities to disasters, encompassing 4 separate domains (socioeconomic, household composition and disability, minority status and language, and housing and transportation). The SVI has been linked with risk and outcomes of cardiovascular disease (CVD). Objectives: This scoping review explored the literature between the SVI and CVD continuum, with a goal to identify gaps in understanding the impact of the SVI on CVD and to elucidate future research opportunities. Methods: We systematically searched 7 databases from inception to May 19, 2023, for articles that explored the relationship between the SVI and CVD care continuum, including prevention, diagnosis and prevalence, treatment, and health outcomes. Extracted data included SVI ranking type, populations, outcomes, and quality of studies. Results: Twelve studies evaluated the impact of SVI on the CVD continuum. Five studies explored mortality outcomes, 3 studies explored CVD risk factor prevalence, 4 studies explored CVD prevalence, 1 study explored access to health care in those with CVD, 1 study explored the use of cardiac rehabilitation services, and 1 study explored heart failure readmission rates, all of which revealed statistically significant associations with SVI. All studies included the SVI aggregate percentile ranking, while 5 studies focused on individual thematic components. We identified gaps in understanding the SVI's impact on CVD care continuum, particularly regarding CVD prevention and early detection. Conclusions: This review provides a comprehensive understanding of the SVI's application in assessing various aspects of the CVD care continuum and highlights potential avenues for future research.

Houston Methodist cardiovascular learning health system (CVD-LHS) registry: Methods for development and implementation of an automated electronic medical record-based registry using an informatics framework approach.

Objectives: To investigate the potential value and feasibility of creating a listing system-wide registry of patients with at-risk and established Atherosclerotic Cardiovascular Disease (ASCVD) within a large healthcare system using automated data extraction methods to systematically identify burden, determinants, and the spectrum of at-risk patients to inform population health management. Additionally, the Houston Methodist Cardiovascular Disease Learning Health System (HM CVD-LHS) registry intends to create high-quality data-driven analytical insights to assess, track, and promote cardiovascular research and care. Methods: We conducted a retrospective multi-center, cohort analysis of adult patients who were seen in the outpatient settings of a large healthcare system between June 2016 - December 2022 to create an EMR-based registry. A common framework was developed to automatically extract clinical data from the EMR and then integrate it with the social determinants of health information retrieved from external sources. Microsoft's SQL Server Management Studio was used for creating multiple Extract-Transform-Load scripts and stored procedures for collecting, cleaning, storing, monitoring, reviewing, auto-updating, validating, and reporting the data based on the registry goals. Results: A real-time, programmatically deidentified, auto-updated EMR-based HM CVD-LHS registry was developed with ∼450 variables stored in multiple tables each containing information related to patient's demographics, encounters, diagnoses, vitals, labs, medication use, and comorbidities. Out of 1,171,768 adult individuals in the registry, 113,022 (9.6%) ASCVD patients were identified between June 2016 and December 2022 (mean age was 69.2 ± 12.2 years, with 55% Men and 15% Black individuals). Further, multi-level groupings of patients with laboratory test results and medication use have been analyzed for evaluating the outcomes of interest. Conclusions: HM CVD-LHS registry database was developed successfully providing the listing registry of patients with established ASCVD and those at risk. This approach empowers knowledge inference and provides support for efforts to move away from manual patient chart abstraction by suggesting that a common registry framework with a concurrent design of data collection tools and reporting rapidly extracting useful structured clinical data from EMRs for creating patient or specialty population registries.

Multidimensional Poverty and Risk of Atherosclerotic Cardiovascular Disease: A U.S. National Study.

Background: Poverty is associated with atherosclerotic cardiovascular disease (ASCVD). While poverty can be evaluated using income, a unidimensional poverty metric inadequately captures socioeconomic adversity. Objectives: The aim of the study was to examine the association between a multidimensional poverty measure and ASCVD. Methods: Survey data from the National Health Interview Survey was analyzed. Four poverty dimensions were used: income, education, self-reported health, and health insurance status. A weighted deprivation score (c i ) was calculated for each person. The multidimensional poverty index was computed for various cutoffs, k, for total population, and by ASCVD status. The association between multidimensional poverty and ASCVD was examined using Poisson regression. Area under receiver operator characteristics curve analysis was performed to compare the multidimensional poverty measure with the income poverty measure as a classification tool for ASCVD. Results: Among the 328,164 participants, 55.0% were females, the mean age was 46.3 years, 63.1% were non-Hispanic Whites, and 14.1% were non-Hispanic Blacks. Participants with ASCVD (7.95%) experienced greater deprivation at each multidimensional poverty cutoff, k, compared to those without ASCVD. In adjusted models, higher burden of multidimensional poverty was associated with up to 2.4-fold increased prevalence of ASCVD (c i  = 0.25, adjusted prevalence ratio [aPR] = 1.66, P < 0.001; c i  = 0.50, aPR = 1.99; c i  = 0.75, aPR = 2.29; P < 0.001; c i  = 1.00, aPR = 2.38, P < 0.001). Multidimensional poverty exhibited modestly higher discriminant validity, compared to income poverty (area under receiver operator characteristics = 0.62 vs 0.58). Conclusions: There is an association between the multidimensional poverty and ASCVD. Multidimensional poverty index demonstrates slightly better discriminatory power than income alone. Future validation studies are warranted to redefine poverty's role in health outcomes.