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Cardiovascular disease (CVD) is the leading cause of death in the world and is largely preventable. An increasing amount of evidence suggests that annual influenza vaccination reduces CVD-related morbidity and mortality. Despite various clinical guidelines recommending annual influenza vaccination for the general population for influenza-like illness risk reduction, with a particular emphasis on people with CVD, vaccination rates fall consistently below the goal established by the World Health Organization. This review outlines the importance of influenza vaccination, mechanisms of cardiovascular events in influenza, summarizing the available literature on the effects of influenza vaccine in CVD and the benefits of influenza vaccine during the COVID-19 pandemic.

The extent to which cumulative social disadvantage-defined as aggregate social risk resulting from multiple co-occurring adverse social determinants of health (SDOH)-affects the risk of all-cause mortality, independent of demographic and clinical risk factors, is not well understood. The objective of this study was to examine the association between cumulative social disadvantage, measured using a comprehensive 47-factor SDOH framework, and mortality in a nationally representative sample of adults in the United States. The authors conducted secondary analysis of pooled data for 63,540 adult participants of the 2013-2015 National Death Index-linked National Health Interview Survey. Age-adjusted mortality rates (AAMRs) were reported by quintiles of aggregate SDOH burden, with higher quintiles denoting greater social disadvantage. Cox proportional hazards models were used to examine the association between cumulative social disadvantage and risk of all-cause mortality. AAMR increased significantly with greater SDOH burden, ranging from 631 per 100,000 person-years (PYs) for participants in SDOH-Q1 to 1490 per 100,000 PYs for those in SDOH-Q5. In regression models adjusted for demographics, being in SDOH-Q5 was associated with 2.5-fold higher risk of mortality, relative to Q1 (adjusted hazard ratio [aHR] = 2.57 [95% confidence interval, CI = 1.94-3.41]); the observed association persisted after adjusting for comorbidities, with over 2-fold increased risk of mortality for SDOH-Q5 versus Q1 (aHR = 2.02 [95% CI = 1.52-2.67]). These findings indicate that cumulative social disadvantage is associated with increased risk of all-cause mortality, independent of demographic and clinical factors. Population level interventions focused on improving individuals' social, economic, and environmental conditions may help reduce the burden of mortality and mitigate persistent disparities.

Heart failure (HF) poses a substantial economic burden on the United States (US) health care system. In contrast, little is known about the financial challenges faced by patients with HF. In this study, we examined the scope and sociodemographic predictors of subjective financial hardship due to medical bills incurred by patients with HF.In the Medical Expenditure Panel Survey (MEPS; years 2014--2018), a US nationally representative database, we identified all patients who reported having HF. Any subjective financial hardship due to medical bills was assessed based on patients' reporting either themselves or their families (1) having difficulties paying medical bills in the past 12 months, (2) paying bills late or (3) being unable to pay bills at all. Logistic regression was used to evaluate independent predictors of financial hardship among patients with HF. All analyses took into consideration the survey's complex design.A total of 116,563 MEPS participants were included in the analysis, of whom 858 (0.7%) had diagnoses of HF, representing 1.8 million (95% CI 1.6-2.0) patients annually. Overall, 33% (95% CI 29%-38%) reported any financial hardship due to medical bills, and 13.2% were not able to pay bills at all. Age ≤ 65 years and lower educational attainment were independently associated with higher odds of subjective financial hardship due to medical bills.Subjective financial hardship is a prevalent issue for patients with HF in the US, particularly those who are younger and have lower educational attainment. There is a need for policies that reduce out-of-pocket costs for the care of HF, an enhanced identification of this phenomenon in the clinical setting, and approaches to help minimize financial toxicity in patients with HF while ensuring optimal quality of care.

Access to health care is affected by social determinants of health. The social vulnerability index encompasses multiple social determinants of health simultaneously and may therefore be associated with healthcare access.Cross-sectional data were used from the 2016‒2019 Behavioral Risk Factor Surveillance System, a nationally representative U.S. telephone-based survey of adults aged ≥18 years. State-level social vulnerability index was derived using county-level social vulnerability index estimates from the Centers for Disease Control and Prevention Agency for Toxic Substances and Disease Registry. Analyses were performed in October 2021. Social vulnerability index was ranked according to percentiles, which were divided into tertiles: Tertile 1 (0.10-0.32), Tertile 2 (0.33-0.53), and Tertile 3 (0.54-0.90).In multivariable-adjusted models comparing U.S. states in Tertile 3 with those in Tertile 1 of social vulnerability index, there was a higher prevalence of absence of healthcare coverage (OR=1.39 [95% CI=1.22, 1.58]), absence of primary care provider (OR=1.34 [95% CI=1.22, 1.48]),1-year duration since last routine checkup (OR=1.18 [95% CI=1.10, 1.27]), inability to see a doctor because of cost (OR=1.38 [95% CI=1.23, 1.54]), and the composite variable of any difficulty in accessing healthcare (OR=1.15 [95% CI=1.08, 1.22]).State-level social vulnerability is associated with several measures related to healthcare access. These results can help to identify targeted interventions to improve access to health care in U.S. states with high social vulnerability index burden.

Dementia and cardiovascular diseases contribute to a significant disability and healthcare utilization in the elderly.The in-hospital treatment patterns and outcomes of heart failure (HF) and acute myocardial infarction (AMI) are not well-studied in this population.We used the National Inpatient Sample database to identify AMI and HF hospitalizations in adults ≥65 years between 2016 and 2018.A total of 2,466,369 HF hospitalizations (277,900 with dementia [11.3%]) and 1,094,155 AMI hospitalizations (100,365 with dementia [9.2%]) were identified. Patients with dementia were older (mean age 83.8 vs 78.6 years for HF, and 83.0 vs 75.8 years for AMI) with female predominance (59.0% for HF and 56.0% for AMI) than those without dementia. In adjusted analysis, patients with dementia had higher in-hospital mortality (HF 4.7% vs 3.1%, aOR 1.33 [1.27-1.39] and AMI 9.9% vs 5.9%, aOR 1.23 [1.17-1.30]), p0.001) and lower mechanical circulatory support utilization. Patients with AMI and dementia were less likely to receive revascularization (including percutaneous coronary intervention, coronary artery bypass grafting, and thrombolysis), vasopressors, and invasive mechanical ventilation. They had a longer mean length of stay (LOS) (5.5 vs 5.3 days for HF and 5.1 vs 4.8 days for AMI, p0.001 for both), a lower inflation-adjusted cost of care for AMI ($15,486 vs $23,215, p0.001), and higher rates of transfer to rehabilitation facilities.Patients with dementia admitted for HF or AMI had higher in-hospital mortality, a longer LOS, and were less likely to receive aggressive revascularization interventions after AMI.

The aim of this study was to assess trends in heart failure (HF) hospitalizations among young adults.Data are limited regarding clinical characteristics and outcomes of young adults hospitalized for HF.The National Inpatient Sample database was analyzed to identify adults aged 18 to 45 years who were hospitalized for HF between 2004 and 2018.In total, 767,180 weighted hospitalizations for HF in young adults were identified, equivalent to 4.32 (95% CI: 4.31-4.33) per 10,000 person-years. Overall HF hospitalizations per 10,000 U.S. population of young adults decreased from 2.43 in 2004 to 1.82 in 2012, followed by an increase to 2.51 in 2018. Black adults (50.1%) had a significantly higher proportion of HF hospitalizations compared with White (31.9%) and Hispanic adults (12.2%) throughout the study period. Nearly half of patients (45.8%) lived in zip codes in the lowest quartile of national household income. Overall, in-hospital mortality was 1.3%, which decreased over time; this trend was consistent by sex and race. The overall mean LOS (5.2 days) remained stable over time, while the mean inflation-adjusted cost increased from $12,449 in 2004 to $16,786 in 2018, with significant overall differences by race and sex.This longitudinal examination of U.S. clinical practice revealed that HF hospitalizations among young adults have increased since 2013. Approximately half of these patients are Black and reside in zip codes in the lowest quartile of national household income. Temporal trends showed decreased in-hospital mortality, stable adjusted lengths of stay, and increased inflation-adjusted costs, with significant racial differences in hospitalization rates.

BackgroundWhether intraprocedural changes in left atrial pressure and Doppler Echocardiographic parameters are synergistic in predicting outcomes after mitral transcatheter edge-to-edge repair (TEER) is not currently known. We sought to evaluate real-time changes in invasive hemodynamics and non-invasive Doppler to develop intraprocedural profiles and assess their impact on clinical outcomes after TEER for MR.MethodsIntraprocedural changes in hemodynamics and Doppler flow with transesophageal echocardiography were assessed in 181 patients with significant MR (51.9% primary MR) undergoing TEER between 2014 and 2022. Independent predictors of the primary composite endpoint of 1-year mortality and heart failure hospitalization (HFH) were identified using multivariable Cox-regression. With receiver operating characteristic curve-derived thresholds for the predictors of the primary end-point, patients were stratified into hemodynamic profiles based on the number of predictors present, and their impact on outcomes was examined.ResultsMedian follow-up was 21.3 months (IQR:11.3-36.5), with 1-year mortality and HFH rates of 19.3% and 12.7%, respectively. Residual mean left atrial pressure (mLAP) [HR=1.073/mmHg (1.03-1.12)], a lesser degree of MR reduction [HR=0.65/grade (0.45-0.93)], and lesser increment in PV systolic time velocity integral (S-VTI) [HR=0.95/cm (0.91-0.99)] were independent predictors of 1-year mortality/HFH. MR reduction by 15mmHg (43.6%) were the most predictive thresholds. Optimal profile (0 predictors), Mixed (1 predictor) and Poor profile (≥2 predictors) were present in 28.7%, 39.2% and 32.0% of cases respectively. Two-year cumulative event-free survival was 60.1% overall, and higher in patients with optimal profile compared to mixed/poor groups (84.7% vs 55.5% vs 43.3%, P5mmHg [HR=2.32 (1.17-4.61)].ConclusionIntraprocedural hemodynamic profiling integrating changes in invasive hemodynamics and non-invasive doppler provide prognostic information in patients undergoing TEER and may provide real-time intraprocedural guidance to optimize long-term clinical outcomes.

To examine the association of social determinants of health (SDOH) on prevalence of stroke in non-elderly adults (65 years of age).We used the National Health Interview Survey (2013-2017) database. The study population was stratified into younger (45 years of age) and middle age (45 to 64 years of age) adults. For each individual, an SDOH aggregate score was calculated representing the cumulative number of individual unfavorable SDOH (present vs absent), identified from 39 subcomponents across five domains (economic stability, neighborhood, community and social context, food, education, and health care system access) and divided into quartiles (quartile 1, most favorable; quartile 4, most unfavorable). Multivariable models tested the association between SDOH score quartiles and stroke.The age-adjusted prevalence of stroke was 1.4% in the study population (n=123,631; 58.2% (n=71,956) in patients45 years of age). Young adults reported approximately 20% of all strokes. Participants with stroke had unfavorable responses to 36 of 39 SDOH; nearly half (48%) of all strokes were reported by participants in the highest SDOH score quartile. A stepwise increase in age-adjusted stroke prevalence was observed across increasing quartiles of SDOH (first, 0.6%; second, 0.9%; third, 1.4%; and fourth, 2.9%). After accounting for demographics and cardiovascular disease risk factors, participants in the fourth vs first quartile had higher odds of stroke (odds ratio, 2.78; 95% CI, 2.25 to 3.45).Nearly half of all non-elderly individuals with stroke have an unfavorable SDOH profile. Standardized assessment of SDOH risk burden may inform targeted strategies to mitigate disparities in stroke burden and outcomes in this population.

To determine the trends in hospitalizations for heart failure (HF), acute myocardial infarction (AMI), and stroke in the United States (US).A retrospective analysis of the National Inpatient Sample weighted data between January 1, 2004 and December 31, 2018 which included hospitalized adults ≥18 years with a primary discharge diagnosis of HF, AMI, or stroke using International Classification of Diseases-9/10 administrative codes. Main outcomes were hospitalization for HF, AMI, and stroke per 1000 United States adults, length of stay, and in-hospital mortality. There were 33.4 million hospitalizations for HF, AMI, and stroke, with most being for HF (48%). After the initial decline in HF hospitalizations (5.3 hospitalizations/1000 US adults in 2004 to 4 hospitalizations/1000 US adults in 2013, P.001), there was a progressive increase in HF hospitalizations between 2013 and 2018 (4.0 hospitalizations/1000 US adults in 2013 to 4.9 hospitalizations/1000 US adults in 2018; P .001). Hospitalization for AMI decreased (3.1 hospitalizations/1000 US adults in 2004 to 2.5 hospitalizations/1000 US adults in 2010, P.001) and remained stable between 2010 and 2018. There was no significant change for hospitalization for stroke between 2004 and 2011 (2.3 hospitalizations/1000 US adults in 2004 vs 2.3 hospitalizations per 1000 US adults in 2011, P = .614); however, there was a small but significant increase in hospitalization for stroke after 2011 that reached 2.5 hospitalizations/1000 US adults in 2018. Adjusted length of stay and in-hospital mortality decreased for HF, AMI, and stroke hospitalizations.In contrast to the trend of AMI and stroke hospitalizations, a progressive increase in hospitalizations for HF has occurred since 2013. From 2004 to 2018, in-hospital mortality has decreased for HF, AMI, and stroke hospitalizations.

The association of repeat revascularization after percutaneous coronary intervention (PCI) with mortality is uncertain. To assess the association of repeat revascularization after PCI with mortality in patients with coronary artery disease (CAD). We identified randomized controlled trials comparing PCI with coronary artery bypass graft (CABG) or optimal medical therapy (OMT) using electronic databases through January 1, 2022. We performed a random-effects meta-regression between repeat revascularization rates after PCI (absolute risk difference [%] between PCI and CABG or OMT) with the relative risks (RR) of mortality. We assessed surrogacy of repeat revascularization for mortality using the coefficient of determination (R2), with threshold of 0.80. In 33 trials (21,735 patients), at median follow-up of 4 (2-7) years, repeat revascularization was higher after PCI than CABG [RR: 2.45 (95% confidence interval, 1.99-3.03)], but lower vs OMT [RR: 0.64 (0.46-0.88)]. Overall, meta-regression showed that repeat revascularization rates after PCI had no significant association with all-cause mortality [RR: 1.01 (0.99-1.02); R2=0.10) or cardiovascular mortality [RR: 1.01 (CI: 0.99-1.03); R2=0.09]. In PCI vs CABG (R2=0.0) or PCI vs OMT trials (R2=0.28), repeat revascularization did not meet the threshold for surrogacy for all-cause or cardiovascular mortality (R2=0.0). We observed concordant results for subgroup analyses (enrollment time, follow-up, sample size, risk of bias, stent types, and coronary artery disease), and multivariable analysis adjusted for demographics, comorbidities, risk of bias, MI, and follow-up duration. In summary, this meta-regression did not establish repeat revascularization after PCI as a surrogate for all-cause or cardiovascular mortality.

Objective: Limited data exist around the receipt of palliative care (PC) in patients hospitalized with common chronic conditions. We studied the independent predictors, temporal trends in rates of PC utilization in patients hospitalized with acute exacerbation of common chronic diseases. Methods: Population-based cohort study of all hospitalizations with an acute exacerbation of heart disease (HD), cerebrovascular accident (CVA), cancer (CA), and chronic lower respiratory disease (CLRD). Patients aged ≥18 years or older between January 1, 2004, and December 31, 2017, referred for inpatient PC were extracted from the National Inpatient Sample. Poisson regression analyses were used to estimate temporal trends. Results: Between 2004 and 2017, of 91,877,531 hospitalizations, 55.2%, 13.9%, 17.2%, and 13.8% hospitalizations were related to HD, CVA, CA, and CLRD, respectively. There was a temporal increase in the uptake of PC across all disease groups. Age-adjusted estimated rates of PC per 100,000 hospitalizations/year were highest for CA (2308 (95% CI 2249–2366) to 10,794 (95% CI 10,652–10,936)), whereas the CLRD cohort had the lowest rates of PC referrals (255 (95% CI 231–278) to 1882 (95% CI 1821–1943)) between 2004 and 2017, respectively. In the subgroup analysis of patients who died during hospitalization, the CVA group had the highest uptake of PC per 100,000 hospitalizations/year (4979 (95% CI 4918–5040)) followed by CA (4241 (95% CI 4189–4292)), HD (3250 (95% CI 3211–3289)) and CLRD (3248 (95% CI 3162–3405)). Conclusion: PC service utilization is increasing but remains disparate, particularly in patients that die during hospital admission from common chronic conditions. These findings highlight the need to develop a multidisciplinary, patient-centered approach to improve access to PC services in these patients.

Background: Substantial differences exist between United States counties with regards to premature ( 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 ( 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.

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.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.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.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.

Racial and social disparities exist in outcomes related to cancer and cardiovascular disease (CVD).The aim of this cross-sectional study was to study the impact of social vulnerability on mortality attributed to comorbid cancer and CVD.The Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database (2015-2019) was used to obtain county-level mortality data attributed to cancer, CVD, and comorbid cancer and CVD. County-level social vulnerability index (SVI) data (2014-2018) were obtained from the CDC's Agency for Toxic Substances and Disease Registry. SVI percentiles were generated for each county and aggregated to form SVI quartiles. Age-adjusted mortality rates (AAMRs) were estimated and compared across SVI quartiles to assess the impact of social vulnerability on mortality related to cancer, CVD, and comorbid cancer and CVD.The AAMR for comorbid cancer and CVD was 47.75 (95% CI: 47.66-47.85) per 100,000 person-years, with higher mortality in counties with greater social vulnerability. AAMRs for cancer and CVD were also significantly greater in counties with the highest SVIs. However, the proportional increase in mortality between the highest and lowest SVI counties was greater for comorbid cancer and CVD than for either cancer or CVD alone. Adults&nbsp

Background Despite improvements in the management and prevention of stroke, increasing hospitalizations for stroke and stagnant mortality rates have been described in young adults. However, there is a paucity of contemporary national mortality estimates in young adults. Methods and Results Trends in mortality related to stroke in young adults (aged 25–64 years) were assessed using the Centers for Disease Control and Prevention Wide‐Ranging Online Data for Epidemiologic Research database. Age‐adjusted mortality rates per 100 000 people with associated annual percentage change were calculated. Joinpoint regression was used to assess the trends in the overall sample and different demographic (sex, race and ethnicity, and age) and geographical (state, urban‐rural, and regional) subgroups. Between 1999 and 2019, a total of 566 916 stroke‐related deaths occurred among young adults. After the initial decline in mortality in the overall population, age‐adjusted mortality rate increased from 2013 to 2019 with an associated annual percentage change of 1.5 (95% CI, 1.1–2.0). Mortality rates were higher in men versus women and in non‐Hispanic Black people versus individuals of other races and ethnicities. Non‐Hispanic American Indian or Alaskan Native people had a marked increase in stroke‐related mortality (annual percentage change 2010–2019: 3.3). Furthermore, rural (nonmetropolitan) counties experienced the greatest increase in mortality (annual percentage change 2012–2019: 3.1) compared with urban (metropolitan) counties. Conclusions Following the initial decline in stroke‐related mortality, young adults have experienced increasing mortality rates from 2013 to 2019, with considerable differences across demographic groups and regions.

Identifying Asian subgroups with higher risk of premature coronary heart disease (CHD) can help implement targeted strategies to prevent future CHD events. We conducted this National Health Interview Survey study from 2006 to 2015 among participants with history of CHD to compare the risk of premature CHD (65 for women and55 years old for men) across Whites, Chinese, Asian Indians, Filipinos, and "other Asians" (Japanese, Korean, and Vietnamese individuals) using univariate and multi-variable logistic regression models. A total of 17,266 participants with history of CHD (mean age, 66.0 ± 0.2; 39% women) were included. Risk of premature CHD was higher among Asian Indians (OR = 1.77, 1.05-2.97) and "other Asians" (OR = 1.68, 1.17-2.42) than Whites adults. Compared with Chinese, the risk of premature CHD was significantly higher for Asian Indians in the unadjusted models (OR = 2.72, 1.19-6.3). "Other Asians" exhibited significantly higher risk in crude (OR = 2.88, 1.32-6.27) and adjusted models (aOR = 2.29, 1.01-5.18). Among younger adults (50 years) with CHD, Asian Indian adults (aOR = 2.43, 1.26-4.70) and other Asian adults (aOR = 1.86, 1.14-3.02) showed higher odds of premature CHD compared with White adults. The risk of premature CHD varies across Asian populations. More studies with an adequate sampling of Asian subgroups are needed to identify the risk and determinants of premature CHD.

Background Social and environmental factors play an important role in the rising health care burden of cardiovascular disease. The Centers for Disease Control and Prevention developed the Social Vulnerability Index (SVI) from US census data as a tool for public health officials to identify communities in need of support in the setting of a hazardous event. SVI (ranging from a least vulnerable score of 0 to a most vulnerable score of 1) ranks communities on 15 social factors including unemployment, minoritized groups status, and disability, and groups them under 4 broad themes: socioeconomic status, housing and transportation, minoritized groups, and household composition. We sought to assess the association of SVI with self‐reported prevalent cardiovascular comorbidities and atherosclerotic cardiovascular disease (ASCVD). Methods and Results We performed a retrospective cohort analysis of adults (≥18 years) in the Behavioral Risk Factor Surveillance System 2016 to 2019. Data regarding self‐reported prevalent cardiovascular comorbidities (including diabetes, hypertension, hyperlipidemia, smoking, substance use), and ASCVD was captured using participants' response to a structured telephonic interview. We divided states on the basis of the tertile of SVI (first—participant lives in the least vulnerable group of states, 0–0.32; to third—participant lives in the most vulnerable group of states, 0.54–1.0). Multivariable logistic regression models adjusting for age, race and ethnicity, sex, employment, income, health care coverage, and association with federal poverty line were constructed to assess the association of SVI with cardiovascular comorbidities. Our study sample consisted of 1 745 999 participants ≥18 years of age. States in the highest (third) tertile of social vulnerability had predominantly Black and Hispanic adults, lower levels of education, lower income, higher rates of unemployment, and higher rates of prevalent comorbidities including hypertension, diabetes, chronic kidney disease, hyperlipidemia, substance use, and ASCVD. In multivariable logistic regression models, individuals living in states in the third tertile of SVI had higher odds of having hypertension (odds ratio (OR), 1.14 [95% CI, 1.11–1.17]), diabetes (OR, 1.12 [95% CI, 1.09–1.15]), hyperlipidemia (OR, 1.09 [95% CI, 1.06–1.12]), chronic kidney disease (OR, 1.17 [95% CI, 1.12–1.23]), smoking (OR, 1.05 [95% CI, 1.03–1.07]), and ASCVD (OR, 1.15 [95% CI, 1.12–1.19]), compared with those living in the first tertile of SVI. Conclusions SVI varies across the US states and is associated with prevalent cardiovascular comorbidities and ASCVD, independent of age, race and ethnicity, sex, employment, income, and health care coverage. SVI may be a useful assessment tool for health policy makers and health systems researchers examining multilevel influences on cardiovascular‐related health behaviors and identifying communities for targeted interventions pertaining to social determinants of health.

ObjectiveTo compare the impact of ezetimibe and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors on cardiovascular outcomes in adults taking maximally tolerated statin therapy or who are statin intolerant.DesignNetwork meta-analysis.Data sourcesMedline, EMBASE, and Cochrane Library up to 31 December 2020.Eligibility criteria for selecting studiesRandomised controlled trials of ezetimibe and PCSK9 inhibitors with ≥500 patients and follow-up of ≥6 months.Main outcome measuresWe performed frequentist fixed-effects network meta-analysis and GRADE (grading of recommendations, assessment, development, and evaluation) to assess certainty of evidence. Results included relative risks (RR) and absolute risks per 1000 patients treated for five years for non-fatal myocardial infarction (MI), non-fatal stroke, all-cause mortality, and cardiovascular mortality. We estimated absolute risk differences assuming constant RR (estimated from network meta-analysis) across different baseline therapies and cardiovascular risk thresholds; the PREDICT risk calculator estimated cardiovascular risk in primary and secondary prevention. Patients were categorised at low to very high cardiovascular risk. A guideline panel and systematic review authors established the minimal important differences (MID) of 12 per 1000 for MI and 10 per 1000 for stroke.ResultsWe identified 14 trials assessing ezetimibe and PCSK9 inhibitors among 83 660 adults using statins. Adding ezetimibe to statins reduced MI (RR 0.87 (95% confidence interval 0.80 to 0.94)) and stroke (RR 0.82 (0.71 to 0.96)) but not all-cause mortality (RR 0.99 (0.92 to 1.06)) or cardiovascular mortality (RR 0.97 (0.87 to 1.09)). Similarly, adding PCSK9 inhibitor to statins reduced MI (0.81 (0.76 to 0.87)) and stroke (0.74 (0.64 to 0.85)) but not all-cause (0.95 (0.87 to 1.03)) or cardiovascular mortality (0.95 (0.87 to 1.03)). Among adults with very high cardiovascular risk, adding PCSK9 inhibitor was likely to reduce MI (16 per 1000) and stroke (21 per 1000) (moderate to high certainty); whereas adding ezetimibe was likely to reduce stroke (14 per 1000), but the reduction of MI (11 per 1000) (moderate certainty) did not reach MID. Adding ezetimibe to PCSK9 inhibitor and statin may reduce stroke (11 per 1000), but the reduction of MI (9 per 1000) (low certainty) did not reach MID. Adding PCSK9 inhibitors to statins and ezetimibe may reduce MI (14 per 1000) and stroke (17 per 1000) (low certainty). Among adults with high cardiovascular risk, adding PCSK9 inhibitor probably reduced MI (12 per 1000) and stroke (16 per 1000) (moderate certainty); adding ezetimibe probably reduced stroke (11 per 1000), but the reduction in MI did not achieve MID (8 per 1000) (moderate certainty). Adding ezetimibe to PCSK9 inhibitor and statins did not reduce outcomes beyond MID, while adding PCSK9 inhibitor to ezetimibe and statins may reduce stroke (13 per 1000). These effects were consistent in statin-intolerant patients. Among moderate and low cardiovascular risk groups, adding PCSK9 inhibitor or ezetimibe to statins yielded little or no benefit for MI and stroke.ConclusionsEzetimibe or PCSK9 inhibitors may reduce non-fatal MI and stroke in adults at very high or high cardiovascular risk who are receiving maximally tolerated statin therapy or are statin-intolerant, but not in those with moderate and low cardiovascular risk.

116 Background: The impact of socioeconomic status on genitourinary (GU) cancer mortality in the United States (US) is unclear. Hence, we evaluated the association of the socioeconomic status with GU cancer mortality across the US counties. Methods: County-level age-adjusted mortality rates (AAMR) per 100,000 person-years (PY) for populations diagnosed with GU cancers were abstracted from the wide-ranging online data for epidemiological research (WONDER) database. The agency for toxic substances and disease registry (ATSDR) was queried to obtain county-level social vulnerability indices from 2014-2018. Percentile ranking scores (PRS: ranging from 0-1) were computed for each US county and further categorized into quartiles (Q: 1st: 0-0.25 [least vulnerable]; 4th: 0.75-1.00 [most vulnerable]). AAMRs were then linked with quartile rankings. A population-weighted, Poisson regression analysis was conducted to compute rate ratios (RR) of AAMRs between 4th and 1st Q with the corresponding 95% confidence intervals (CI). Results: A total 3142 US counties were included in this analysis. The AAMR for GU cancers was 22.6 overall deaths (OD) and 4.20 premature deaths (PD; defined as death at age st Q to the 4th Q (OD: 21.6 vs 24.1; PD: 3.48 vs 5.19). In terms of OD by specific GU cancers, significantly higher AAMRs were observed in the 4th Q compared to the 1st Q for patients with prostate cancer (RR; 1.19 [95% CI;1.14-1.24]), and renal cell carcinoma (RCC; 1.12 [1.04-1.21]) but not for those with lower urothelial tract cancers (0.92 [0.87-0.96]). Among subgroups, non-Hispanic Blacks (1.19 [1.07-1.33]), and Hispanics (1.28 [1.08-1.51]) with prostate cancer and men with RCC (1.11; 1.03-1.19) in the 4th Q experienced significantly higher overall mortality when compared to those in the 1st Q. With regards to PD, significantly higher AAMRs were observed in the 4th Q vs 1st Q for patients with prostate cancer (1.54 [1.34-1.77]), and RCC (1.28 [1.12-1.45]). Consistently, men with RCC in the 4th Q also experienced higher premature mortality when compared to the 1st Q. Sparsity of mortality data among different ethnic/racial subgroups across the US counties precluded any formal assessment of disparity by specific GU cancers. A sensitivity analysis, conducted using the weighted linear regression approach, showed consistent results. Conclusions: Population level data suggest that socially vulnerable populations, especially Non-Hispanic Black and Hispanic men with prostate cancer, and men with renal cell carcinoma may be at an increased risk of cancer-related mortality. Hence, there is a dire need to address this mortality gap across different socioeconomic subgroups to ensure health-care equity. Investigations at the patient level are required to further ascertain these findings.

499 Background: The impact of socioeconomic status on gastrointestinal (GI) cancer mortality in the United States (US) is not well-established. We hypothesized that socially vulnerable populations have disproportionately higher mortality rates. Hence, we assessed the association of the social vulnerability index (SVI) with GI cancer mortality across US counties. Methods: Social vulnerability indices were obtained from the agency for toxic substances and disease registry (ATSDR) from 2014-2018 to compute percentile ranking scores (PRS: ranging from 0-1) for each US county. PRS were further categorized into quartiles (Q: 1st: 0-0.25 [least vulnerable]; 4th:0.75-1.00 [most vulnerable]). The wide-ranging online data for epidemiological research (WONDER) database was queried to abstract county-level age-adjusted mortality rates (AAMR) per 100,000 person-years (PY) for populations diagnosed with GI cancers. AAMRs were then linked with quartile rankings. Rate ratios (RR) of AAMRs between 4th and 1st Q were subsequently estimated with 95% confidence intervals using population-weighted, Poisson regression. Results: A total of 3142 counties were included in this analysis. The AAMR for overall deaths (OD) and premature deaths (PD; defined as death at age st Q to 4th Q (OD: 49.2 vs 59.3; PD: 14.1 vs 21.3). This stepwise increase in AAMR over the quartiles was consistent across gender, different racial/ethnic subgroups, and rural/urban categories of counties. The AAMRs for OD were significantly higher in the 4th Q as compared to the 1st Q for gastric (RR: 1.67 [95% CI, 1.51-1.86]), hepatocellular including intrahepatic biliary (1.52 [1.45-1.61]), colorectal (1.21 [1.16-1.26]) and biliary (1.17 [1.06-1.28]) cancer. Similarly, significantly higher AAMRs for PD were observed in 4th Q vs1st Q for gastric (1.81 [1.60-2.05]), hepatocellular including intrahepatic biliary (1.78 [1.58-2.00]), biliary (1.64 [1.35-1.99]), colorectal (1.29 [1.21-1.39]) and pancreatic (1.16 [1.07-1.25]) cancer. However, no significant differences were observed for esophageal and small intestinal cancers. Men with gastric (1.58 [1.41-1.78]) and hepatocellular cancer (1.54 [1.43-1.66]), non-Hispanic Black population (1.54 [1.31-1.80]) with hepatocellular cancer, and Hispanic population with colorectal cancer (1.50 [1.31-1.72]) were observed to have higher overall mortality in the 4th Q compared to the 1st Q. The findings were similar for premature mortality. Conclusions: Population-level data suggests that the US counties with higher socio-economic adversities may be at an increased risk of GI cancer-related mortality. Investigations using patient-level data are required to probe the impact of socioeconomic vulnerabilities on cancer-related mortality.

Race-based differences in clinical outcomes have been well described in type 1 myocardial infarction. However, type 2 myocardial infarction (T2MI) is more common in contemporary practice, with scarce data regarding racial differences in outcomes. The National Inpatient Sample Database October 2017-December 2018 was queried for hospitalizations with T2MI. Complex samples multivariable logistic and linear regression models were used to determine the association between T2MI and outcomes (in-hospital mortality, length of stay [LOS], hospital costs, and discharge to facility among different racial groups (White, Black, Hispanic, and Other-races/ethnicities [Native American, Asian or Pacific Islander and others]). A total of 294,540 hospitalizations [209,565 (71.2%) White patients, 47,105 (16%) Black patients, 22,115 (7.5%) Hispanic patients, and 15,755 (5.3%) Other-races/ethnicities patients] carrying a primary or secondary diagnosis of T2MI were included in this analysis. Compared to White patients with T2MI; Other-races/ethnicities patients were associated with higher in-hospital mortality (adjusted odds ratio [aOR] 1.17; 95% confidence interval [CI]1.03-1.33; P = 0.016), and longer LOS. Hospital costs were higher for Hispanic and Other-races/ethnicities patients compared to White patients with T2MI. Further, all the racial/ethnicity groups were less likely to be discharged to facility compared to White patients. Although Black and Hispanic patients with T2MI have similar in-hospital mortality compared with White patients, other racial minorities have higher in-hospital mortality among patients with T2MI compared to White patients. Furthermore, White patients were more likely to be discharged to a facility. Further prospective investigations of the impact of racial differences on T2MI-related in-hospital mortality and disposition are warranted.

Background: Stroke is increasing among the non-elderly adults ( Methods: Using the National Health Interview Survey (NHIS) database from 2012 to 2018, we examined the association of traditional risk factors (hypertension, diabetes, hypercholesterolemia, smoking, obesity, and insufficient physical activity), sociodemographic, cardiovascular risk factor (CRF) profile (CRF range: Optimal (0-1 cardiovascular risk factors) to Poor (≥ 4 cardiovascular risk factors)), family income (high to low based on income as percentage of poverty limit), and educational attainment (categorized as some college degree or higher vs high school (HS) degree/GED or less) with stroke in the young (18-44 years) and middle-aged (45-64 years) adults. Results: Among 168,862 non-elderly adults (55% in young adults) included in this study, the prevalence of stroke was 1.83% among the non-elderly which translates to roughly 3.1 million adults. Of these, 598 and 2,509 were young- and middle-aged adults, translating to 624,000 and 2.5 million US adults, respectively. Adults with low family income, lesser education, and who were black were more likely to have stroke. The majority of young adults without stroke had an optimal CRF profile (65%) with only 3.5% having a poor profile. In contrast, 17.7% of middle-aged adults had a poor CRF profile. Lower income status coupled with a poor CRF profile increased the odds of stroke in both young (adjusted [a]OR: 3.12 [2.12-4.59]) and middle-aged (aOR: 2.31 [1.97-2.72]) adults when compared to those with average or optimal CRF profiles. Conclusions: This national survey of non-elderly US adults showed that poor CRF profiles led to higher odds of stroke compared to optimal profiles. Additionally, low income and education, factors contributing to SES, and race/ethnicity contributed to worsening stroke odds.

Introduction: Area Deprivation Index (ADI), a proxy measure for neighbourhood socioeconomic context, is informative for prioritizing limited resources in improving health outcomes. With emerging therapeutic options to improve cardiometabolic health among individuals with morbid obesity, whether available measures, such as ADI, for integrated health systems can identify this subpopulation at risk is unknown. Methods: This cross-sectional study analyzed data from 865,995 adult patients in the Houston Methodist Outpatient Learning Health System Registry between June 1 st , 2016 and July 20 th , 2021. Using University of Wisconsin-Madison School of Medicine’s ADI dataset, each patient was assigned an ADI rank according to the census block group of their geocoded residential address. BMI was calculated based on recorded height and weight. Patients with non-geocoded addresses (n=9 855), missing and abnormal BMI values (n=107 037) were excluded. Multinomial logistic regression models were used to examine the association between ADI and morbid obesity (BMI≥40 kg/m 2 ). Results: A total of 751,174 adults with an ADI ranking were included in the analysis. Overall, the prevalence of morbid obesity was 6.9% (n=51,609). The age-adjusted prevalence of morbid obesity increased across worsening neighborhood deprivation in overall population and across racial/ethnic subgroups (Figure 1). Each ADI rank increase in neighborhood disadvantage was associated with an unadjusted odds ratio (OR) of 1.022 (95% CI, 1.022-1.023) for morbid obesity compared to normal weight. After adjusting for age, sex and race/ethnicity, we found a statistically significant association of worst vs least level of neighborhood deprivation with patients with morbid obesity compared to normal weight (aOR, 3.75; 95% CI, 3.60-3.89). Conclusion: The study highlights utility of census-based measures to identify patients living in socioeconomically deprived areas for comprehensive morbid obesity management strategies.

We analyzed the association between social vulnerability index (SVI) and healthcare access among patients with atherosclerotic cardiovascular disease (ASCVD). Using cross-sectional data from the Behavioral Risk Factor Surveillance System 2016 to 2019, we identified measures related to healthcare access in individuals with ASCVD, which included healthcare coverage, presence of primary care clinician, duration since last routine checkup, delay in access to healthcare, inability to see doctor because of cost, and cost-related medication nonadherence. We analyzed the association of state-level SVI (higher SVI denotes higher social vulnerability) and healthcare access using multivariable-adjusted logistic regression models. The study population comprised 203,347 individuals aged 18 years or older who reported a history of ASCVD. In a multivariable-adjusted analysis, prevalence odds ratios (95% confidence interval) for participants residing in states in the third tertile of SVI compared with those in the first tertile (used as reference) were as follows: absence of healthcare coverage = 1.03 (0.85 to 1.24), absence of primary care clinician = 1.33 (1.12 to 1.58),gt;1 year since last routine checkup = 1.09 (0.96 to 1.23), delay in access to healthcare = 1.39 (1.18, 1.63), inability to see a doctor because of cost = 1.21 (1.06 to 1.40), and cost-related medication nonadherence = 1.10 (0.83 to 1.47). In conclusion, SVI is associated with healthcare access in those with pre-existing ASCVD. Due to the ability of SVI to simultaneously and holistically capture many of the factors of social determinants of health, SVI can be a useful measure for identifying high-risk populations.