Increasing use of systems science in cardiovascular disease prevention to understand how to address geographic health disparities in communities with a disproportionate burden of risk.

Objective: Marginalized communities shoulder a disproportionate burden of cardiovascular disease (CVD) driven by concentrated neighborhood social risk factors. We provide a case study of systems science application to address geographic CVD health disparities at the community level - informing the science of CVD health disparities research. Methods: We conducted a two-phased, multi-methods needs assessment in the Denver, Colorado area. Phase I consisted of a social network analysis to map a two-mode network of existing CVD prevention interventions and their implementing organizations. In Phase II, group model building (GMB) sessions with key community, public health, and healthcare provider stakeholders, were utilized to identify and visualize community factors contributing to disparities in CVD risk, producing a consensus-based causal loop diagram. Results: Between May 2021 and June 2022, we conducted 24 virtual, semi-structured interviews in Phase I to describe CVD prevention interventions, and 7 virtual GMB sessions in Phase II to describe experiences of disparities in CVD risk. For the purposes of this paper, we focus on a subset of results for both phases. In Phase I we identified 89 active CVD prevention interventions, 29 of which addressed tobacco use. In Phase II, causal loop diagrams revealed root causes of disparities in CVD risk. We provide an example of a causal loop diagram that focuses on the community prevalence of tobacco use, identifying stress as a key underlying factor driving disparities. The integration of findings from both phases highlighted the alignment and misalignment between quit tobacco intervention goals and how they are being experienced in marginalized communities. Conclusion: Systems science methods were useful to organize a large number of CVD prevention efforts, and evaluate the root causes of CVD health disparities in a high risk community. By integrating these two aspects, interventions may be reoriented to more effectively address the root causes of CVD health disparities.

Socioeconomic status and modification of atherosclerotic cardiovascular disease risk prediction: epidemiological analysis using data from the atherosclerosis risk in communities study.

OBJECTIVE: Examine whether the relationship between the pooled cohort equations (PCE) predicted 10-year risk for atherosclerotic cardiovascular disease (ASCVD) and absolute risk for ASCVD is modified by socioeconomic status (SES). DESIGN: Population-based longitudinal cohort study-Atherosclerosis Risk in Communities (ARIC)-investigating the development of cardiovascular disease across demographic subgroups. SETTING: Four communities in the USA-Forsyth County, North Carolina, Jackson, Mississippi, suburbs of Minneapolis, Minnesota and Washington County, Maryland. PARTICIPANTS: We identified 9782 ARIC men and women aged 54-73 without ASCVD at study visit 4 (1996-1998). PRIMARY OUTCOME MEASURES: Risk ratio (RR) differences in 10-year incident hospitalisations or death for ASCVD by SES and PCE predicted 10-year ASCVD risk categories to assess for risk modification. SES measures included educational attainment and census-tract neighbourhood deprivation using the Area Deprivation Index. PCE risk categories were 0%-5%, >5%-10%, >10%-15% and >15%. SES as a prognostic factor to estimate ASCVD absolute risk categories was further investigated as an interaction term with the PCE. RESULTS: ASCVD RRs for participants without a high school education (referent college educated) increased at higher PCE estimated risk categories and was consistently >1. Results indicate education is both a risk modifier and delineates populations at higher ASCVD risk independent of PCE. Neighbourhood deprivation did modify association but was less consistent in direction of effect. However, for participants residing in the most deprived neighbourhoods (referent least deprived neighbourhoods) with a PCE estimated risk >10%-15%, risk was significantly elevated (RR 1.65, 95% CI 1.05 to 2.59). Education and neighbourhood deprivation inclusion as an interaction term on the PCE risk score was statistically significant (likelihood ratio p≤0.0001). CONCLUSIONS: SES modifies the association between PCE estimated risk and absolute risk of ASCVD. SES added into ASCVD risk prediction models as an interaction term may improve our ability to predict absolute ASCVD risk among socially disadvantaged populations.

Relationship Between Social Vulnerability Indicators and Trial Participant Attrition: Findings From the HYVALUE Trial.

BACKGROUND: Social vulnerability indicators are associated with health care inequities and may similarly impede ongoing participation in research studies. We evaluated the association of social vulnerability indicators and research participant attrition in a trial focused on reducing health disparities. METHODS: Self-identified White or Black adults enrolled in the HYVALUE trial (Hypertension and VALUEs), a randomized trial testing a values-affirmation intervention on medication adherence, from February 2017 to September 2019 were included. The self-reported measures of social vulnerability indicators included: (1) Black race; (2) female gender; (3) no health insurance; (4) unemployment; (5) a high school diploma or less; and (6) financial-resource strain. Full attrition was defined as not completing at least one 3- or 6-month follow-up study visit. Log-binomial regression models adjusted for age, gender, race, medical comorbidities, and the other social vulnerability indicators to estimate the relative risk of each social vulnerability indicator with study attrition. RESULTS: Among 825 participants, the mean age was 63.3 years (±11.7 years), 60% were women, 54% were Black, and 97% reported at least one social vulnerability. Overall, 21% participants had full attrition after study enrollment. After adjustment for all other social vulnerabilities, only financial-resource strain remained consistently associated with full attrition (relative risk, 1.71 [95% CI, 1.28-2.29]). In a secondary analysis of partial attrition (completed only one follow-up visit), financial-resource strain (relative risk, 1.40 [95% CI, 1.09-1.81]) and being uninsured (relative risk, 1.54 [95% CI, 1.01-2.34]) were associated with partial attrition. CONCLUSIONS: In a trial aimed at reducing disparities in medication adherence, participants who reported financial-resource strain had a higher risk of participant attrition independent of race or gender. Our findings suggest that efforts to retain diverse populations in clinical trials should extend beyond race and gender to consider other social vulnerability indicators. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03028597.

Potential unrealized mortality benefit of glucagon-like peptide-1 receptor agonists and sodium-glucose co-transport-2 inhibitors: A report from the Veterans Health Administration Clinical Assessment, Reporting and Tracking program.

AIM: To assess the unrealized potential of glucagon-like peptide-1 receptor agonist (GLP-1RA) or sodium-glucose co-transport-2 inhibitor (SGLT2i) use to reduce mortality in veterans with type 2 diabetes (T2D), coronary artery disease (CAD), and other characteristics congruent with clinical trial cohorts that established the efficacy of these agents. METHODS: Veterans with T2D and CAD on angiography in 2014 who were untreated with either a GLP-1RA or a SGLT2i were assessed for key eligibility criteria of the LEADER (GLP-1RA) and EMPA-REG OUTCOME (SGLT2i) trials. Trial hazard ratios and 95% confidence intervals for all-cause death were applied to deaths observed in veterans through 2018 to estimate the potential benefit of GLP-1RA or SGLT2i use. RESULTS: Median observation was 4.3 years. Of 15 987 veterans with T2D and CAD, 1186 (7.4%) were excluded for GLP-1RA or SGLT2i treatment, and 1386 lacked glycated haemoglobin measurement. Of the remaining 13 415 patients, 4103 (30.1%) and 5313 (39.6%) fulfilled the key criteria for the LEADER and EMPA-REG OUTCOME trials, respectively. Death occurred in 1009 (24.6%) of LEADER-eligible patients and 1335 (25.1%) of EMPA-REG OUTCOME-eligible patients. Under treatment with liraglutide in LEADER-eligible veterans, a 3.5% (0.7%-6.2%) potential absolute mortality reduction, corresponding to 144 (28-253) fewer deaths (0.88 [0.17-1.56] per 100 person-years), might have been expected. Similarly, under treatment with empagliflozin in EMPA-REG OUTCOME-eligible veterans, a 7.9% (4.5%-10.8%) potential absolute mortality reduction, corresponding to 418 (230-573) fewer deaths (1.98 [1.14-2.72] per 100 person-years), might have been expected. CONCLUSIONS: This analysis indicates unrealized opportunities to reduce mortality in selected veterans with T2D and CAD via increased GLP-1RA and SGLT2i use.

Social Determinants of Health and Rates of Implantation for Patients Considering Destination Therapy Left Ventricular Assist Device.

BACKGROUND: A left ventricular assist device (LVAD) is a treatment option available to select patients with advanced heart failure. However, there are important social determinants of health that can play a role in determining patients' outcomes after device placement. METHODS AND RESULTS: We leveraged the DECIDE-LVAD Trial to assess social determinants of health-relationship status, household income, race/ethnicity, educational attainment, and health insurance-at the time of evaluation, and their association with rate of LVAD placement in the subsequent year. About a quarter of patients were unpartnered (i.e., single/divorced/widowed/separated; n = 55 [26%]). A similar proportion had a household income of less than $20,000 per year (n = 50 [24%]). Few patients were other race (n = 39 [18%]), had less than a high school education (n = 14 [6.6%]), or had Medicaid as their primary payor (n = 17 [8.4%]). LVAD implantation was significantly lower among patients who were unpartnered compared with patients who were married or partnered. LVAD implantation was not associated with income, race, educational attainment or insurance status. CONCLUSIONS: Our data from diverse LVAD centers at U.S. private and academic hospitals found that, among a broad sample of patients being evaluated for LVAD, married or partnered status was favorably associated with LVAD implantation, but other social determinants of health were not. Future research and policy changes should consider novel interventions for improving access to LVAD implantation for patients with inadequate social support.

Practice level factors associated with enhanced engagement with practice facilitators; findings from the heart health now study.

BACKGROUND: Practice facilitation is a promising strategy to enhance care processes and outcomes in primary care settings. It requires that practices and their facilitators engage as teams to drive improvement. In this analysis, we explored the practice and facilitator factors associated with greater team engagement at the mid-point of a 12-month practice facilitation intervention focused on implementing cardiovascular prevention activities in practice. Understanding factors associated with greater engagement with facilitators in practice-based quality improvement can assist practice facilitation programs with planning and resource allocation. METHODS: One hundred thirty-six ambulatory care small to medium sized primary care practices that participated in the EvidenceNow initiative's NC Cooperative, named Heart Health Now (HHN), fit the eligibility criteria for this analysis. We explored the practice and facilitator factors associated with greater team engagement at the mid-point of a 12-month intervention using a retrospective cohort design that included baseline survey data, monthly practice activity implementation data and information about facilitator's experience. Generalized linear mixed-effects models (GLMMs) identified variables associated with greater odds of team engagement using an ordinal scale for level of team engagement. RESULTS: Among our practice cohort, over half were clinician-owned and 27% were Federally Qualified Health Centers. The mean number of clinicians was 4.9 (SD 4.2) and approximately 40% of practices were in Medically Underserved Areas (MUA). GLMMs identified a best fit model. The Model presented as odd ratios and 95% confidence intervals suggests greater odds ratios of higher team engagement with greater practice QI leadership 17.31 (5.24-57.19), [0.00], and practice location in a MUA 7.25 (1.8-29.20), [0.005]. No facilitator characteristics were independently associated with greater engagement. CONCLUSIONS: Our analysis provides information for practice facilitation stakeholders to consider when considering which practices may be more amendable to embracing facilitation services.

Distribution of Cardiovascular Health by Individual- and Neighborhood-Level Socioeconomic Status: Findings From the Jackson Heart Study.

BACKGROUND: Data demonstrate a positive relationship between socioeconomic status (SES) and cardiovascular health (CVH). OBJECTIVE: To assess the association between individual- and neighborhood-level SES and CVH among participants of the JHS (Jackson Heart Study), a community-based cohort of African Americans in Jackson, Mississippi. METHODS: We included all JHS participants with complete SES and CVH information at the baseline study visit (n = 3,667). We characterized individual- and neighborhood-level SES according to income (primary analysis) and education (secondary analysis), respectively. The outcome of interest for these analyses was a CVH score, based on 7 modifiable behaviors and factors, summed to a total of 0 (worst) to 14 (best) points. We utilized generalized estimating equations to account for the clustering of participants within the same residential areas to estimate the linear association between SES and CVH. RESULTS: The median age of the participants was 55 years, and 64% were women. Nearly one-third of eligible participants had individual incomes <$20,000 and close to 40% lived in the lowest neighborhood income category (<$25,480). Adjusted for age, sex, and neighborhood SES, there was an average increase in CVH score of 0.31 points associated with each 1-category increase in individual income. Similarly, each 1-category increase in neighborhood SES was associated with a 0.19-point increase in CVH score. These patterns held for our secondary analyses, which used educational attainment in place of income. These data did not suggest a synergistic effect of individual- and neighborhood-level SES on CVH. CONCLUSIONS: Our findings suggest a potential causal pathway for disparities in CVH among vulnerable populations. These data can be useful to the JHS community to empower public health and clinical interventions and policies for the improvement of CVH.

Organizational Leadership and Adaptive Reserve in Blood Pressure Control: The Heart Health NOW Study.

PURPOSE: Our purpose was to assess whether a practice's adaptive reserve and high leadership capability in quality improvement are associated with population blood pressure control. METHODS: We divided practices into quartiles of blood pressure control performance and considered the top quartile as the benchmark for comparison. Using abstracted clinical data from electronic health records, we performed a cross-sectional study to assess the association of top quartile hypertension control and (1) the baseline practice adaptive reserve (PAR) scores and (2) baseline practice leadership scores, using modified Poisson regression models adjusting for practice-level characteristics. RESULTS: Among 181 practices, 46 were in the top quartile, which averaged 68% or better blood pressure control. Practices with higher PAR scores compared with lower PAR scores were not more likely to reside in the top quartile of performance (prevalence ratio [PR] = 1.92 for highest quartile; 95% CI, 0.9-4.1). Similarly, high quality improvement leadership capability compared with lower capability did not predict better blood pressure control performance (PR = 0.94; 95% CI, 0.57-1.56). Practices with higher proportions of commercially insured patients were more likely than practices with lower proportions of commercially insured patients to have top quartile performance (37% vs 26%, P =.002), whereas lower proportions of the uninsured (8% vs 14%, P =.055) were associated with better performance. CONCLUSIONS: Our findings show that adaptive reserve and leadership capability in quality improvement implementation are not statistically associated with achieving top quartile practice-level hypertension control at baseline in the Heart Health NOW project. Our findings, however, may be limited by a lack of patient-related factors and small sample size to preclude strong conclusions.