Magnani, Jared W.

Background Studies have demonstrated neighborhood structural inequities are associated with cardiovascular outcomes among breast cancer survivors. We investigated the associations between bias in mortgage lending practices (contemporary redlining and racial lending bias) and cardiovascular outcomes in women with breast cancer. Methods Using the SEER (Surveillance, Epidemiology, and End Results)–Medicare database, we identified 51 007 Black and White women diagnosed with breast cancer between 2010 and 2014 with follow‐up through 2020. We used Home Mortgage Disclosure Act data to calculate census‐tract contemporary redlining index and racial lending bias index, and assessed indices continuously and categorically (low, moderate, or high). We used Cox proportional hazards regression to estimate multivariable‐adjusted, cause‐specific hazard ratios (HRs) for major adverse cardiovascular events, ischemic heart disease, heart failure, stroke, and cardiovascular death. Results In the overall population, a 10%‐unit increase in redlining was associated with increased risk of major adverse cardiovascular events (HR, 1.04 [95% CI, 1.02–1.06]). Among Black women, those in high redlining neighborhoods had an increased heart failure risk compared with those in low redlining neighborhoods (HR, 1.22 [95% CI, 1.05–1.41]). Similarly, White women in high redlining neighborhoods had an increased risk of ischemic heart disease (HR, 1.23 [95% CI, 1.15–1.30]) and stroke (HR, 1.09 [95% CI, 1.03–1.16]). Black women in high racial lending bias neighborhoods had reduced cardiovascular mortality risk compared with those in low racial lending bias neighborhoods (HR, 0.69 [95% CI, 0.54–0.90]). Conclusions We identified associations between contemporary redlining and cardiovascular outcomes among breast cancer survivors. High racial lending bias was associated with reduced cardiovascular mortality risk among Black women. Bias in mortgage lending practices may serve as a structural driver of cardiovascular disparities.

ImportanceThere are consistent data demonstrating that socioeconomic disadvantage is associated with risk of premature mortality, but research on the relationship between neighborhood socioeconomic factors and premature mortality is limited. Most studies evaluating the association between neighborhood socioeconomic status (SES) and mortality have used a single assessment of SES during middle to older adulthood, thereby not considering the contribution of early life neighborhood SES.ObjectiveTo investigate the association of life course neighborhood SES and premature mortality.Design, Setting, and ParticipantsThis cohort study included Black and White participants of the multicenter Atherosclerosis Risk in Communities Study, a multicenter study conducted in 4 US communities: Washington County, Maryland; Forsyth County, North Carolina; Jackson, Mississippi; and the northwestern suburbs of Minneapolis, Minnesota. Participants were followed up for a mean (SD) of 18.8 (5.7) years (1996-2020). Statistical analysis was performed from March 2023 through May 2024.ExposureParticipants’ residential addresses during childhood, young adulthood, and middle adulthood were linked with US Census–based socioeconomic indicators to create summary neighborhood SES scores for each of these life epochs. Neighborhood SES scores were categorized into distribution-based tertiles.Main Outcomes and MeasuresPremature death was defined as all-cause mortality occurring before age 75 years. Multivariable-adjusted Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs.ResultsAmong 12 610 study participants, the mean (SD) age at baseline was 62.6 (5.6) years; 3181 (25.2%) were Black and 9429 (74.8%) were White; and 7222 (57.3%) were women. The lowest, compared with the highest tertile, of neighborhood SES score in middle adulthood was associated with higher risk of premature mortality (HR, 1.28; 95% CI, 1.07-1.54). Similar associations were observed for neighborhood SES in young adulthood among women (HR, 1.25; 95% CI, 1.00-1.56) and neighborhood SES in childhood among White participants (HR, 1.25; 95% CI, 1.01-1.56). Participants whose neighborhood SES remained low from young to middle adulthood had an increased premature mortality risk compared with those whose neighborhood SES remained high (HR, 1.25; 95% CI, 1.05-1.49).Conclusions and RelevanceIn this study, low neighborhood SES was associated with premature mortality. The risk of premature mortality was greatest among individuals experiencing persistently low neighborhood SES from young to middle adulthood. Place-based interventions that target neighborhood social determinants of health should be designed from a life course perspective that accounts for early-life socioeconomic inequality.

Moritz F Sinner, 2012 Finalist and Presenting Author

Importance Only modest attention has been paid to the contributions of social determinants of health to atrial fibrillation (AF) risk factors, diagnosis, symptoms, management, and outcomes. The diagnosis of AF provides unique challenges exacerbated by the arrhythmia’s often paroxysmal nature and individuals’ disparate access to health care and technologies that facilitate detection. Social determinants of health affect access to care and management decisions for AF, increasing the likelihood of adverse outcomes among individuals who experience systemic disadvantages. Developing effective approaches to address modifiable social determinants of health requires research to eliminate the substantive inequities in health care delivery and outcomes in AF. Observations The National Heart, Lung, and Blood Institute convened an expert panel to identify major knowledge gaps and research opportunities in the field of social determinants of AF. The workshop addressed the following social determinants: (1) socioeconomic status and access to care; (2) health literacy; (3) race, ethnicity, and racism; (4) sex and gender; (5) shared decision-making in systemically disadvantaged populations; and (6) place, including rurality, neighborhood, and community. Many individuals with AF have multiple adverse social determinants, which may cluster in the individual and in systemically disadvantaged places (eg, rural locations, urban neighborhoods). Cumulative disadvantages may accumulate over the life course and contribute to inequities in the diagnosis, management, and outcomes in AF. Conclusions and Relevance Workshop participants identified multiple critical research questions and approaches to catalyze social determinants of health research that address the distinctive aspects of AF. The long-term aspiration of this work is to eradicate the substantive inequities in AF diagnosis, management, and outcomes across populations.

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.

Background Social determinants of health are relevant to cardiovascular outcomes but have had limited examination in atrial fibrillation (AF). Objectives The purpose of this study was to examine the association of annual household income and cardiovascular outcomes in individuals with AF. Methods We analysed administrative claims for individuals with AF from 2009 to 2015 captured by a health claims database. We categorised estimates of annual household income as <$40 000; $40–$59 999; $60–$74 999; $75–$99 999; and ≥$100 000. Covariates included demographics, education, cardiovascular disease risk factors, comorbid conditions and anticoagulation. We examined event rates by income category and in multivariable-adjusted models in reference to the highest income category (≥$100 000). Results Our analysis included 336 736 individuals (age 72.7±11.9 years; 44.5% women; 82.6% white, 8.4% black, 7.0% Hispanic and 2.1% Asian) with AF followed for median (25th and 75th percentile) of 1.5 (95% CI 0.6 to 3.0) years. We observed an inverse association between income and heart failure and myocardial infarction (MI) with evidence of progressive risk across decreased income categories. Individuals with household income <$40 000 had the greatest risk for heart failure (HR 1.17; 95% CI 1.05 to 1.30) and MI (HR 1.18; 95% CI 0.98 to 1.41) compared with those with income ≥$100 000. Conclusions We identified an association between lower household income and adverse outcomes in a large cohort of individuals with AF. Our findings support consideration of income in the evaluation of cardiovascular risk in individuals with AF.

Background Tools for the prediction of atrial fibrillation ( AF ) may identify high‐risk individuals more likely to benefit from preventive interventions and serve as a benchmark to test novel putative risk factors. Methods and Results Individual‐level data from 3 large cohorts in the U nited S tates (Atherosclerosis Risk in Communities [ ARIC ] study, the Cardiovascular Health Study [ CHS ], and the Framingham Heart Study [ FHS ]), including 18 556 men and women aged 46 to 94 years (19% A frican A mericans, 81% whites) were pooled to derive predictive models for AF using clinical variables. Validation of the derived models was performed in 7672 participants from the Age, Gene and Environment—Reykjavik study ( AGES ) and the Rotterdam Study ( RS ). The analysis included 1186 incident AF cases in the derivation cohorts and 585 in the validation cohorts. A simple 5‐year predictive model including the variables age, race, height, weight, systolic and diastolic blood pressure, current smoking, use of antihypertensive medication, diabetes, and history of myocardial infarction and heart failure had good discrimination (C‐statistic, 0.765; 95% CI , 0.748 to 0.781). Addition of variables from the electrocardiogram did not improve the overall model discrimination (C‐statistic, 0.767; 95% CI , 0.750 to 0.783; categorical net reclassification improvement, −0.0032; 95% CI , −0.0178 to 0.0113). In the validation cohorts, discrimination was acceptable ( AGES C‐statistic, 0.664; 95% CI , 0.632 to 0.697 and RS C‐statistic, 0.705; 95% CI , 0.664 to 0.747) and calibration was adequate. Conclusion A risk model including variables readily available in primary care settings adequately predicted AF in diverse populations from the U nited S tates and E urope.