Brewer, LaPrincess C.

Background: The American Heart Association recently published an updated algorithm for quantifying cardiovascular health (CVH)—the Life’s Essential 8 score. We quantified US levels of CVH using the new score. Methods: We included individuals ages 2 through 79 years (not pregnant or institutionalized) who were free of cardiovascular disease from the National Health and Nutrition Examination Surveys in 2013 through 2018. For all participants, we calculated the overall CVH score (range, 0 [lowest] to 100 [highest]), as well as the score for each component of diet, physical activity, nicotine exposure, sleep duration, body mass index, blood lipids, blood glucose, and blood pressure, using published American Heart Association definitions. Sample weights and design were incorporated in calculating prevalence estimates and standard errors using standard survey procedures. CVH scores were assessed across strata of age, sex, race and ethnicity, family income, and depression. Results: There were 23 409 participants, representing 201 728 000 adults and 74 435 000 children. The overall mean CVH score was 64.7 (95% CI, 63.9–65.6) among adults using all 8 metrics and 65.5 (95% CI, 64.4–66.6) for the 3 metrics available (diet, physical activity, and body mass index) among children and adolescents ages 2 through 19 years. For adults, there were significant differences in mean overall CVH scores by sex (women, 67.0; men, 62.5), age (range of mean values, 62.2–68.7), and racial and ethnic group (range, 59.7–68.5). Mean scores were lowest for diet, physical activity, and body mass index metrics. There were large differences in mean scores across demographic groups for diet (range, 23.8–47.7), nicotine exposure (range, 63.1–85.0), blood glucose (range, 65.7–88.1), and blood pressure (range, 49.5–84.0). In children, diet scores were low (mean 40.6) and were progressively lower in higher age groups (from 61.1 at ages 2 through 5 to 28.5 at ages 12 through 19); large differences were also noted in mean physical activity (range, 63.1–88.3) and body mass index (range, 74.4–89.4) scores by sociodemographic group. Conclusions: The new Life’s Essential 8 score helps identify large group and individual differences in CVH. Overall CVH in the US population remains well below optimal levels and there are both broad and targeted opportunities to monitor, preserve, and improve CVH across the life course in individuals and the population.

Background: Outcomes in heart failure with reduced ejection fraction (HFrEF) are influenced by access and adherence to guideline-directed medical therapy. Our objective was to study the association between annual household income and: (1) the odds of having a claim for sacubitril/valsartan among insured patients with HFrEF and (2) medication adherence (measured as the proportion of days covered). We hypothesized that lower annual household income is associated with decreased odds of having a claim for and adhering to sacubitril/valsartan. Methods: Using the Optum de-identified Clinformatics Data Mart, patients with HFrEF and ≥6 months of enrollment for follow-up (2016–2020) were included. Covariates included age, sex, race, ethnicity, educational attainment, US region, number of prescribed medications, and Elixhauser Comorbidity Index. Prescription for sacubitril/valsartan was defined by the presence of a claim within 6 months of HFrEF diagnosis. Adherence was defined as proportion of days covered ≥80%. We fit multivariable-adjusted logistic regression models and hierarchical logistic regression accounting for covariates. Results: Among 322 007 individuals with incident HFrEF, 135 282 had complete data for analysis. Of the patients eligible for sacubitril/valsartan, 4.7% (6372) had a claim within 6 months of HFrEF diagnosis. Following multivariable adjustment, individuals in the lowest annual income category (<$40 000) were significantly less likely (odds ratio, 0.83 [95% CI, 0.76–0.90]) to have a sacubitril/valsartan claim within 6 months of HFrEF diagnosis than those in the highest annual income category (≥$100 000). Annual income <$40 000 was associated with lower odds of proportion of days covered ≥80% compared with income ≥$100 000 (odds ratio, 0.70 [95% CI, 0.59–0.83]). Conclusions: Lower household income is associated with decreased likelihood of a sacubitril/valsartan claim and medication adherence within 6 months of HFrEF diagnosis, even after adjusting for sociodemographic and clinical factors. Future analyses are needed to identify additional social factors associated with delays in sacubitril/valsartan initiation and long-term adherence.

Background: Outcomes in heart failure with reduced ejection fraction (HFrEF), are influenced by access and adherence to guideline directed medical therapy. Objective: To study the association between median annual household income and: (1) odds of receiving sacubitril/valsartan, a novel angiotensin receptor/neprilysin inhibitor (ARNI) therapy among insured patients with heart failure with reduced ejection fraction (HFrEF) and (2) medication adherence (measured as the proportion of days covered (PDC)). Hypothesis: lower income is associated with lower odds of receiving and adhering to ARNI among patients with HFrEF. Methods: Using Optum’s deidentified Clinformatics® Data Mart, patients with ≥ 2 diagnoses of HFrEF and ≥ 6 months of enrollment for follow up (2016-2020) were included. Covariates included age, race, ethnicity, sex, educational attainment, household net worth, geographical region and Elixhauser comorbidity index. Prescription for ARNI was defined by presence of a claim within 180 days. Adherence was defined as PDC ≥80%. We fit multivariable-adjusted logistic regression models and hierarchical logistic regression accounting for covariates. We also assessed for race-income interaction. Results: Among 322007 individuals with HFrEF diagnosis, 136,613 had ≥6 months of complete data. Of the patients eligible for ARNI, only 5.4% (7409/136613) received a claim within 180 days of HFrEF diagnosis. After adjusting for social and clinical factors, the odds were elevated for ARNI claim within 180 days of HFrEF diagnosis (OR=1.38, 95% CI: 1.27, 1.49) for the highest income category (>$100K) compared with the lowest (<$40K). After adjustment, income <$40k) was associated with a 47% higher odds of PDC<80% compared with income >$100K. Conclusions: Higher patient income is associated with increased likelihood of an ARNI claim within 180 days of HFrEF diagnosis, even after adjusting for socioeconomic and clinical factors. Future analyses are needed to determine other social factors associated with delay in ARNI initiation and long-term adherence.

The high prevalence of uncontrolled hypertension in underserved populations is a major cause of health disparities in the United States and requires innovative health care delivery interventions. We conducted a systematic review of randomized controlled trials and comparative observational studies examining the effectiveness of contemporary systems change and quality improvement interventions aimed at improving blood pressure (BP) control published from 2010 to 2020. We included studies evaluating multicomponent practice improvement interventions conducted in the United States in community health centers. We identified 26 studies including 48 187 patients with hypertension with a high proportion of racial/ethnic minorities, low socioeconomic status, and a high burden of chronic illness. Multicomponent interventions led to an average reduction of 5 to 10 mm Hg in systolic BP. Four studies demonstrated the effectiveness of integrating pharmacists into community health centers for BP management and reduced cardiovascular disparities for at-risk populations. Five studies demonstrated the effectiveness of integrating community health workers into care workflows leading to reduction in BP and high patient satisfaction. Five studies used the electronic medical record as a tool for population management and showed only modest reduction in BP. One study demonstrated the effectiveness of incentivizing clinics with higher payments for uninsured and Medicaid patients meeting performance criteria. Very few studies evaluated treatment complications or medications side effects. Multicomponent quality improvement interventions instituted in community health centers are effective in lowering BP. Several components of the interventions were identified as being associated with higher efficacy.

Introduction: Compared to Whites, African-Americans (AAs) have 82% lower odds of meeting ideal levels for five or more cardiovascular (CV) health components that comprise the American Heart Association’s Life’s Simple 7, an evidenced-based metric of seven health promoting behaviors and biological factors that improve CV outcomes. Given expanding mobile technology use among AAs, mobile health (mHealth) interventions are promising avenues to promote CV health within this population. Hypothesis: An evidence-based, theory-informed, culturally relevant, community-based mHealth lifestyle intervention would improve CV health among AAs adults. Methods: Five predominately AA churches collaborated in a community-based participatory research approach to develop a 10-week CV health and wellness digital application-based program ( FAITH! App ). We enrolled AA adults [N=50, mean age 49.6 (SD 12.7), 70% women (35/50)] into a single group, 10-week intervention centered on the FAITH! App with adjunct in-person sessions. The FAITH! App included ten core video education modules from health professionals on CV health, interactive diet/physical activity self-monitoring and a sharing board. The primary outcome was change in individual CV health behaviors (body mass index, physical activity, diet, cigarette smoking) and biological factors (blood pressure (BP), total cholesterol, fasting glucose) from baseline to post-intervention at 28 weeks. Results: Participants were overall high CV risk at baseline (hypertensive [40% (20/50)] with poor/intermediate physical activity [79% (37/47)] and diet [72% (36/50)]). At 28 weeks, there were substantial improvements in CV health factors (systolic and diastolic BPs), CV health behaviors (diet, physical activity) and psychological/psychosocial variables to promote behavior change ( Table 1 ). Conclusions: This study supports the benefits of a culturally relevant, community-based mHealth lifestyle intervention to promote CV health among AAs with high cardiometabolic risk.

Introduction: Compared to other racial and ethnic groups, African Americans experience greater negative psychosocial factors (depression, stress), which are related to increased risk of cardiovascular disease (CVD). Little research has examined the association of positive psychosocial factors (optimism) with cardiovascular health in this population. Using the Jackson Heart Study (JHS) data, we examined the association of optimism with the American Heart Association Life’s Simple 7 TM (LS7), a measure of seven metrics that assesses a person’s cardiovascular health. Hypothesis: Higher levels of optimism are positively associated with individual LS7 metrics, and positively associated with the total LS7 score. Methods: We evaluated cross-sectional associations of optimism with each LS7 metric [cigarette smoking, physical activity, diet, body mass index (BMI), blood pressure, cholesterol, glucose] and with a composite LS7 score among 4,761 participants, 21-95 years old (women=3,070; men=1,691) enrolled in the JHS, a single-site, community-based cohort of African Americans residing in Jackson, MS. Optimism was measured in tertiles (low, moderate, high) to examine threshold effects. Each LS7 metric was classified as poor, intermediate, and ideal. LS7 metrics were also summed to create a total continuous score (0-13) categorized in tertiles (low, moderate, high). Multinomial logistic regression estimated the odds ratios (OR, 95% confidence interval-CI) of intermediate (vs. poor) and ideal (vs. poor) LS7 metric by levels of optimism. Multinomial regression also estimated the odds of moderate (vs. low) or high (vs. low) total LS7 score by optimism. Models adjusted for demographics, SES, and depressive symptoms. Results: Descriptive findings showed that participants who reported high optimism had ideal physical activity, nutrition, smoking, blood pressure, glucose and high total LS7 score (all p<0.01). After adjustment for age, sex, education, income, marital status, and insurance status, participants who reported high (vs. low) optimism had a 39% increased odds of having ideal (vs. poor) physical activity (OR 1.39; 95% CI 1.10-1.76) and a 33% increased odds of having ideal (vs. poor) smoking (OR 1.33; 95% CI 1.02-1.73). Participants who reported high (vs. low) optimism had a 34% greater odds of having a high (vs. low) total LS7 score (OR 1.34 95% CI 1.03-1.74) after full adjustment. Conclusion: Optimism is associated with ideal physical activity and ideal smoking, which is important for promoting cardiovascular health and reducing the risk of CVD among African Americans in this sample.

Background: Cardiovascular disease (CVD) remains the leading cause of death for African-American (AA) adults. There is a low prevalence of ideal cardiovascular health (CVH) (as defined by the American Heart Association’s Life’s Simple 7 TM (LS7)), especially diet, physical activity and obesity among AAs placing them at a disproportionately high risk for CVD. The identification of psychosocial stress that may influence ideal CVH could assist in the development of more effective behavior change interventions among AAs. Objectives: The aim of this study is to examine the associations of multidimensional stressors (chronic stress, minor stressors, and major life events - MLEs) with the LS7 components (classified as poor, intermediate and ideal) in AAs. We hypothesize that stress is negatively associated with the likelihood of achievement of intermediate/ideal levels of the LS7 components and LS7 composite score after adjusting for traditional socio-demographic factors. Methods: Using the Jackson Heart Study (JHS), a cohort of AAs based in Jackson, Mississippi (n=4383), we conducted a cross-sectional analysis of the association of stress measures with LS7 components (smoking, diet, physical activity, body mass index, blood pressure, total cholesterol and glucose). This association was measured using logistic regression which assessed the odds ratios (OR, 95% confidence interval (CI)) of the achievement of intermediate/ideal levels of CVH with progressive adjustment for demographic, socioeconomic, behavioral and biomedical factors. A composite LS7 score was calculated [range 0-14; categorized as 0 to 6 (poor), 7 to 8 (intermediate) and 9 to 14 (ideal)]. We also constructed a cumulative stress score as a summation of tertiles of each stress measure (range 3-9). Results: Fewer participants achieved intermediate or ideal CVH for the LS7 components including diet (39%), physical activity (51%) and BMI (47%). Higher chronic stress and minor stressors scores were associated a decreased likelihood of achievement of ideal/intermediate levels for smoking [OR 0.80; 95% CI 0.73-0.88 and OR 0.84; 95% CI 0.75-0.94, respectively). Higher MLE scores were associated decreased likelihood of achievement of ideal/intermediate levels for smoking (OR 0.84; 95% CI 0.76-0.92) and glucose (OR 0.90; 95% CI 0.82-0.98). Those with higher minor stressors and MLE scores were less likely to achieve intermediate or ideal LS7 composite score categories (OR 0.89; 95% CI 0.81-0.97 and OR 0.91; 95% CI 0.84-0.98, respectively). There was no statistically significant association between LS7 composite scores and cumulative stress scores. Conclusions: Our results suggest that key stress measures may contribute adversely to CVH among AAs. These findings provide support for future lifestyle interventions which integrate a focus on alleviating stressors in this high risk population to improve CVH.

The COVID-19 pandemic has disproportionately affected underserved and minority populations in the United States. This is partially attributable to limited access to diagnostic testing from deeply rooted structural inequities precipitating higher infection and mortality rates. We describe the process of establishing a drive-through collection site by leveraging an academic–community partnership between a medical institution and a federally qualified health center in Minnesota. Over 10 weeks, 2006 COVID-19 tests were provided to a socioeconomically disadvantaged population of racial/ethnic minorities and low-income essential workers.

Background: Deep learning algorithms derived in homogeneous populations may be poorly generalizable and have the potential to reflect, perpetuate, and even exacerbate racial/ethnic disparities in health and health care. In this study, we aimed to (1) assess whether the performance of a deep learning algorithm designed to detect low left ventricular ejection fraction using the 12-lead ECG varies by race/ethnicity and to (2) determine whether its performance is determined by the derivation population or by racial variation in the ECG. Methods: We performed a retrospective cohort analysis that included 97 829 patients with paired ECGs and echocardiograms. We tested the model performance by race/ethnicity for convolutional neural network designed to identify patients with a left ventricular ejection fraction ≤35% from the 12-lead ECG. Results: The convolutional neural network that was previously derived in a homogeneous population (derivation cohort, n=44 959; 96.2% non-Hispanic white) demonstrated consistent performance to detect low left ventricular ejection fraction across a range of racial/ethnic subgroups in a separate testing cohort (n=52 870): non-Hispanic white (n=44 524; area under the curve [AUC], 0.931), Asian (n=557; AUC, 0.961), black/African American (n=651; AUC, 0.937), Hispanic/Latino (n=331; AUC, 0.937), and American Indian/Native Alaskan (n=223; AUC, 0.938). In secondary analyses, a separate neural network was able to discern racial subgroup category (black/African American [AUC, 0.84], and white, non-Hispanic [AUC, 0.76] in a 5-class classifier), and a network trained only in non-Hispanic whites from the original derivation cohort performed similarly well across a range of racial/ethnic subgroups in the testing cohort with an AUC of at least 0.930 in all racial/ethnic subgroups. Conclusions: Our study demonstrates that while ECG characteristics vary by race, this did not impact the ability of a convolutional neural network to predict low left ventricular ejection fraction from the ECG. We recommend reporting of performance among diverse ethnic, racial, age, and sex groups for all new artificial intelligence tools to ensure responsible use of artificial intelligence in medicine.