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

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

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

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

Social Determinants of Cardiovascular Risk, Subclinical Cardiovascular Disease, and Cardiovascular Events.

Background Although there is research on the impact of social determinants of health (SDOHs) on cardiovascular health, most existing evidence is based on individual SDOH components. We evaluated the impact of cumulative SDOH burden on cardiovascular risk factors, subclinical atherosclerosis, and incident cardiovascular disease events. Methods and Results We included 6479 participants from the MESA (Multi-Ethnic Study of Atherosclerosis). A weighted aggregate SDOH score representing the cumulative number of unfavorable SDOHs, identified from 14 components across 5 domains (economic stability, neighborhood and physical environment, community and social context, education, and health care system access) was calculated and divided into quartiles (quartile 4 being the least favorable). The impact of cumulative SDOH burden on cardiovascular risk factors (hypertension, diabetes, dyslipidemia, smoking, and obesity), systemic inflammation, subclinical atherosclerosis, and incident cardiovascular disease was evaluated. Increasing social disadvantage was associated with increased odds of all cardiovascular risk factors except dyslipidemia. Smoking was the risk factor most strongly associated with worse SDOH (odds ratio [OR], 2.67 for quartile 4 versus quartile 1 [95% CI, 2.13-3.34]). Participants within SDOH quartile 4 had 33% higher odds of increased high-sensitivity C-reactive protein (OR, 1.33 [95% CI, 1.11-1.60]) and 31% higher risk of all cardiovascular disease (hazard ratio, 1.31 [95% CI, 1.03-1.67]), yet no greater burden of subclinical atherosclerosis (OR, 1.01 [95% CI, 0.79-1.29]), when compared with those in quartile 1. Conclusions Increasing social disadvantage was associated with more prevalent cardiovascular risk factors, inflammation, and incident cardiovascular disease. These findings call for better identification of SDOHs in clinical practice and stronger measures to mitigate the higher SDOH burden among the socially disadvantaged to improve cardiovascular outcomes.

Favorable Neighborhood Walkability is Associated With Lower Burden of Cardiovascular Risk Factors Among Patients Within an Integrated Health System: The Houston Methodist Learning Health System Outpatient Registry.

This is the first study to investigate the relationship between neighborhood walkability and cardiovascular (CV) risk factors in the United States using a large population-based database. Cross-sectional study using data from 1.1 million patients over the age of 18 in the Houston Methodist Learning Health System Outpatient Registry (2016-2022). Using the 2019 WalkScore, patients were assigned to one of the 4 neighborhood walkability categories. The burden of CV risk factors (hypertension, diabetes, obesity, dyslipidemia, and smoking) was defined as poor, average, or optimal (>3, 1-2, 0 risk factors, respectively). We included 887,654 patients, of which 86% resided in the two least walkable neighborhoods. The prevalence of CV risk factors was significantly lower among participants in the most walkable neighborhoods irrespective of ASCVD status. After adjusting for age, sex, race/ethnicity, and socioeconomic factors, we found that adults living in the most walkable neighborhoods were more likely to have optimal CV risk profile than those in the least walkable ones (RRR 2.77, 95% CI 2.64-2.91). We observed an inverse association between neighborhood walkability and the burden of CV risk factors. These findings support multilevel health system stakeholder engagements and investments in walkable neighborhoods as a viable tool for mitigating the growing burden of modifiable CV risk factors.

The Impact of the Affordable Care Act on Disparities in Utilization of Cardiovascular Preventive Services by Socioeconomic Status.

Disparities in cardiovascular outcomes are persistent in our society. The objective was to track the trends before and after the passage of the Affordable Care Act in socioeconomic status (SES) disparities in utilization of cardiovascular disease (CVD) preventive services among nonelderly adults aged 18-64 years. This study used the National Health Interview Survey (2011-2017) to compare utilization of blood pressure, cholesterol, glycemic screening, and diet and smoking cessation advice over time between groups stratified by SES and race using difference-in-difference analysis. This study also measured the differences over time in specific vulnerable population subgroups (Hispanic, low-income and uninsured vs. White, middle-high-income, and insured). The study population included 176,961 surveyed individuals (mean age 40 [±13] years; 51% female; 67.7% non-Hispanic White) between 2011 and 2017, translating to 194.8 million nonelderly US adults per year. Most individuals were from high-income SES (40.0%), followed by middle-income (28.1%), low-income (13.6%), and lowest income SES (18.3%). The proportion of CVD preventive services increased over all SES categories through the study period. The biggest relative changes were seen among low-income individuals. The difference in blood pressure checks, cholesterol checks, and smoking cessation advise between high- and lowest income groups showed a statistically significant decrease at 5.2%, 4.8%, and 11.2%, respectively, between 2011 and 2017. The findings demonstrate a trend in reduction of CVD preventive care disparities between SES groups. However, a gap still exists, and this study highlights the need for continuous improvement to eliminate SES disparities.

Social Determinants of Health Among Non-Elderly Adults With Stroke in the United States.

OBJECTIVE: To examine the association of social determinants of health (SDOH) on prevalence of stroke in non-elderly adults (<65 years of age). METHODS: 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. RESULTS: The age-adjusted prevalence of stroke was 1.4% in the study population (n=123,631; 58.2% (n=71,956) in patients <45 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). CONCLUSION: 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.

Social Determinants of Suboptimal Cardiovascular Health Among Pregnant Women in the United States.

Background Suboptimal cardiovascular health (CVH) and social determinants of health (SDOH) have a significant impact on maternal morbidity and mortality. We aimed to evaluate the association of SDOH with suboptimal CVH among pregnant women in the United States. Methods and Results We examined cross-sectional data of pregnant women aged 18 to 49 years from the National Health Interview Survey (2013-2017). We ascertained optimal and suboptimal CVH based on the presence of 0 to 1 and ≥2 risk factors (hypertension, diabetes, hyperlipidemia, current smoking, obesity, and insufficient physical activity), respectively. We calculated an aggregate SDOH score representing 38 variables from 6 domains (economic stability; neighborhood, physical environment, and social cohesion; community and social context; food; education; and healthcare system) and divided into quartiles. We used Poisson regression model to evaluate the association of SDOH with suboptimal CVH and risk factors. Our study included 1433 pregnant women (28.8±5.5 years, 13% non-Hispanic Black). Overall, 38.4% (95% CI, 33.9-43.0) had suboptimal CVH versus 51.7% (95% CI, 47.0-56.3) among those in the fourth SDOH quartile. Risk ratios of suboptimal CVH, smoking, obesity, and insufficient physical activity were 2.05 (95% CI, 1.46-2.88), 8.37 (95% CI, 3.00-23.43), 1.54 (95% CI, 1.17-2.03), and 1.19 (95% CI, 1.01-1.42), respectively among those in the fourth SDOH quartile compared with the first quartile. Conclusions Over 50% of pregnant women with the highest SDOH burden had suboptimal CVH, highlighting the public health urgency for interventions in socially disadvantaged pregnant women with renewed strategies toward improving modifiable risk factors, especially smoking and insufficient physical activity.

Predictors of Long-term Opioid Use Following Lumbar Fusion Surgery.

STUDY DESIGN: A population-based retrospective cohort study. OBJECTIVE: The aim of this study was to examine risk factors for long-term opioid use following lumbar spinal fusion surgery in a nationally representative cohort of commercially insured adults. SUMMARY OF BACKGROUND DATA: Opioid prescription rates for the management of low back pain have more than doubled in the US over the past decade. Although opioids are commonly used for the management of pain following lumbar spinal fusion surgery, to date, no large-scale nationally representative studies have examined the risk factors for long-term opioid use following such surgical intervention. METHODS: Using one of the nation's largest commercial insurance databases, we conducted a retrospective cohort study of 8377 adults, aged 21 to 63 years, who underwent lumbar spinal fusion surgery between January 1, 2009, and December 31, 2012. Long-term opioid use was defined as ≥365 days of filled opioid prescriptions in the 24 months following lumbar fusion. Multivariable logistic regression was used to calculate adjusted odds ratios (ORs) and 95% confidence intervals for the risk of long-term opioid use following lumbar fusion. RESULTS: After adjusting for covariates, the following factors were associated with an increased risk of long-term opioid use following surgery: duration of opioid use in the year before lumbar surgery [Referent (0 days); Quartile 1 (1-22 days) OR = 2.27, 95% CI = 1.48-3.49; Quartile 2 (23-72 days): OR = 5.94, 95% CI = 4.00-8.83; Quartile 3: (73-250 days) OR = 25.31, 95% CI = 17.26-37.10; Quartile 4 (≥250 days) OR = 219.95, 95% CI = 148.53-325.71)], refusion surgery (OR = 1.32, 95% CI = 1.02-1.72), and diagnosis of depression (OR = 1.43, 95% CI = 1.18-1.74). Receipt of anterior fusion was associated with a modest decrease in the risk of long-term opioid use (OR = 0.79, 95% CI = 0.63-0.99). CONCLUSION: These findings may provide clinically relevant information to physicians, patients, and their families regarding the risk factors for opioid dependence following lumbar fusion surgery. LEVEL OF EVIDENCE: 3.