Disparities in Premature Cardiac Death Among US Counties From 1999-2017: Temporal Trends and Key Drivers

The global estimate of premature cardiovascular mortality: a systematic review and meta-analysis of age-standardized mortality rate

BACKGROUND

Cardiovascular disease (CVD) is a significant cause of premature mortality worldwide, with a growing burden in recent years. Despite this, there is a lack of comprehensive meta-analyses that quantify the extent of premature CVD mortality. Study addressed this gap by estimating the pooled age-standardized mortality rate (ASMR) of premature CVD mortality.

METHODS

We conducted a systematic review of published CVD mortality studies that reported ASMR as an indicator for premature mortality measurement. All English articles published as of October 2022 were searched in four electronic databases: PubMed, Scopus, Web of Science (WoS), and the Cochrane Central Register of Controlled Trials (CENTRAL). We computed pooled estimates of ASMR using random-effects meta-analysis. We assessed heterogeneity from the selected studies using the I2 statistic. Subgroup analyses and meta regression analysis was performed based on sex, main CVD types, income country level, study time and age group. The analysis was performed using R software with the "meta" and "metafor" packages.

RESULTS

A total of 15 studies met the inclusion criteria. The estimated global ASMR for premature mortality from total CVD was 96.04 per 100,000 people (95% CI: 67.18, 137.31). Subgroup analysis by specific CVD types revealed a higher ASMR for ischemic heart disease (ASMR = 15.57, 95% CI: 11.27, 21.5) compared to stroke (ASMR = 12.36, 95% CI: 8.09, 18.91). Sex-specific differences were also observed, with higher ASMRs for males (37.50, 95% CI: 23.69, 59.37) than females (15.75, 95% CI: 9.61, 25.81). Middle-income countries had a significantly higher ASMR (90.58, 95% CI: 56.40, 145.48) compared to high-income countries (21.42, 95% CI: 15.63, 29.37). Stratifying by age group indicated that the age groups of 20-64 years and 30-74 years had a higher ASMR than the age group of 0-74 years. Our multivariable meta-regression model suggested significant differences in the adjusted ASMR estimates for all covariates except study time.

CONCLUSIONS

This meta-analysis synthesized a comprehensive estimate of the worldwide burden of premature CVD mortality. Our findings underscore the continued burden of premature CVD mortality, particularly in middle-income countries. Addressing this issue requires targeted interventions to mitigate the high risk of premature CVD mortality in these vulnerable populations.

Risk factors and geographic disparities in premature cardiovascular mortality in US counties: a machine learning approach

Disparities in premature cardiovascular mortality (PCVM) have been associated with socioeconomic, behavioral, and environmental risk factors. Understanding the "phenotypes", or combinations of characteristics associated with the highest risk of PCVM, and the geographic distributions of these phenotypes is critical to targeting PCVM interventions. This study applied the classification and regression tree (CART) to identify county phenotypes of PCVM and geographic information systems to examine the distributions of identified phenotypes. Random forest analysis was applied to evaluate the relative importance of risk factors associated with PCVM. The CART analysis identified seven county phenotypes of PCVM, where high-risk phenotypes were characterized by having greater percentages of people with lower income, higher physical inactivity, and higher food insecurity. These high-risk phenotypes were mostly concentrated in the Black Belt of the American South and the Appalachian region. The random forest analysis identified additional important risk factors associated with PCVM, including broadband access, smoking, receipt of Supplemental Nutrition Assistance Program benefits, and educational attainment. Our study demonstrates the use of machine learning approaches in characterizing community-level phenotypes of PCVM. Interventions to reduce PCVM should be tailored according to these phenotypes in corresponding geographic areas.

Mediterranean Diet and White Matter Hyperintensity Change over Time in Cognitively Intact Adults

Current evidence on the impact of Mediterranean diet (MeDi) on white matter hyperintensity (WMH) trajectory is scarce. This study aims to examine whether greater adherence to MeDi is associated with less accumulation of WMH. This population-based longitudinal study included 183 cognitively intact adults aged 20−80 years. The MeDi score was obtained from a self-reported food frequency questionnaire; WMH was assessed by 3T MRI. Multivariable linear regression was used to estimate the effect of MeDi on WMH change. Covariates included socio-demographic factors and brain markers. Moderation effects by age, gender, and race/ethnicity were examined, followed by stratification analyses. Among all participants, WMH increased from baseline to follow-up (mean difference [follow-up-baseline] [standard deviation] = 0.31 [0.48], p < 0.001). MeDi adherence was negatively associated with the increase in WMH (β = −0.014, 95% CI = −0.026−−0.001, p = 0.034), adjusting for all covariates. The association between MeDi and WMH change was moderated by age (young group = reference, p-interaction[middle-aged × MeDi] = 0.075, p-interaction[older × MeDi] = 0.037). The association between MeDi and WMH change was observed among the young group (β = −0.035, 95% CI = −0.058−−0.013, p = 0.003), but not among other age groups. Moderation effects by gender and race/ethnicity did not reach significance. Greater adherence to MeDi was associated with a lesser increase in WMH over time. Following a healthy diet, especially at younger age, may help to maintain a healthy brain.

Association of Socioeconomic Status With Ideal Cardiovascular Health in Black Men

Background

Black men are burdened by high cardiovascular risk and the highest all‐cause mortality rate in the United States. Socioeconomic status (SES) is associated with improved cardiovascular risk factors in majority populations, but there is a paucity of data in Black men.

Methods and Results

We examined the association of SES measures including educational attainment, annual income, employment status, and health insurance status with an ideal cardiovascular health (ICH) score, which included blood pressure, glucose, cholesterol, body mass index, physical activity, and smoking in African American Male Wellness Walks. Six metrics of ICH were categorized into a 3‐tiered ICH score 0 to 2, 3 to 4, and 5 to 6. Multinomial logistic regression modeling was performed to examine the association of SES measures with ICH scores adjusted for age. Among 1444 men, 7% attained 5 to 6 ICH metrics. Annual income <$20 000 was associated with a 56% lower odds of attaining 3 to 4 versus 0 to 2 ICH components compared with ≥$75 000 (P=0.016). Medicare and no insurance were associated with a 39% and 35% lower odds of 3 to 4 versus 0 to 2 ICH components, respectively, compared with private insurance (all P<0.05). Education and employment status were not associated with higher attainment of ICH in Black men.

Conclusions

Among community‐dwelling Black men, higher attainment of measures of SES showed mixed associations with greater attainment of ICH. The lack of association of higher levels of educational attainment and employment status with ICH suggests that in order to address the long–standing health inequities that affect Black men, strategies to increase attainment of cardiovascular health may need to address additional components beyond SES.

Association Between Patient-Clinician Relationships and Adherence to Antihypertensive Medications Among Black Adults: An Observational Study Design

Background We assessed the associations between patient-clinician relationships (communication and involvement in shared decision-making [SDM]) and adherence to antihypertensive medications. Methods and Results The 2010 to 2017 Medical Expenditure Panel Survey (MEPS) data were analyzed. A retrospective cohort study design was used to create a cohort of prevalent and new users of antihypertensive medications. We defined constructs of patient-clinician communication and involvement in SDM from patient responses to the standard questionnaires about satisfaction and access to care during the first year of surveys. Verified self-reported medication refill information collected during the second year of surveys was used to calculate medication refill adherence; adherence was defined as medication refill adherence ≥80%. Survey-weighted multivariable-adjusted logistic regression models were used to measure the odds ratio (OR) and 95% CI for the association between both patient-clinician constructs and adherence. Our analysis involved 2571 Black adult patients with hypertension (mean age of 58 years; SD, 14 years) who were either persistent (n=1788) or new users (n=783) of antihypertensive medications. Forty-five percent (n=1145) and 43% (n=1016) of the sample reported having high levels of communication and involvement in SDM, respectively. High, versus low, patient-clinician communication (OR, 1.38; 95% CI, 1.14-1.67) and involvement in SDM (OR, 1.32; 95% CI, 1.08-1.61) were both associated with adherence to antihypertensives after adjusting for multiple covariates. These associations persisted among a subgroup of new users of antihypertensive medications. Conclusions Patient-clinician communication and involvement in SDM are important predictors of optimal adherence to antihypertensive medication and should be targeted for improving adherence among Black adults with hypertension.

Socioeconomic Inequalities in Premature Cancer Mortality Among U.S. Counties During 1999 to 2018

BACKGROUND

This study investigated socioeconomic inequalities in premature cancer mortality by cancer types, and evaluated the associations between socioeconomic status (SES) and premature cancer mortality by cancer types.

METHODS

Using multiple databases, cancer mortality was linked to SES and other county characteristics. The outcome measure was cancer mortality among adults ages 25-64 years in 3,028 U.S. counties, from 1999 to 2018. Socioeconomic inequalities in mortality were calculated as a concentration index (CI) by income (annual median household income), educational attainment (% with bachelor's degree or higher), and unemployment rate. A hierarchical linear mixed model and dominance analyses were used to investigate SES associated with county-level mortality. The analyses were also conducted by cancer types.

RESULTS

CIs of SES factors varied by cancer types. Low-SES counties showed increasing trends in mortality, while high-SES counties showed decreasing trends. Socioeconomic inequalities in mortality among high-SES counties were larger than those among low-SES counties. SES explained 25.73% of the mortality. County-level cancer mortality was associated with income, educational attainment, and unemployment rate, at -0.24 [95% (CI): -0.36 to -0.12], -0.68 (95% CI: -0.87 to -0.50), and 1.50 (95% CI: 0.92-2.07) deaths per 100,000 population with one-unit SES factors increase, respectively, after controlling for health care environment and population health.

CONCLUSIONS

SES acts as a key driver of premature cancer mortality, and socioeconomic inequalities differ by cancer types.

IMPACT

Focused efforts that target socioeconomic drivers of mortalities and inequalities are warranted for designing cancer-prevention implementation strategies and control programs and policies for socioeconomically underprivileged groups.

Evaluation of Between-County Disparities in Premature Mortality Due to Stroke in the US

IMPORTANCE

Identifying the factors associated with premature stroke mortality and measuring between-county disparities may provide insight into how to reduce variations and achieve more equitable health outcomes.

OBJECTIVE

To examine the between-county disparities in premature stroke mortality in the US, investigate county-level factors associated with mortality, and describe differences in mortality disparities by place of death and stroke subtype.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cross-sectional study linked the mortality and demographic data of US counties from the Centers for Disease Control and Prevention WONDER database to county-level characteristics from multiple databases. The outcome measure was county-level age-adjusted stroke mortality among adults aged 25 to 64 years in 2637 US counties from 1999 to 2018. This study was conducted from April 1, 2019, to October 31, 2020. Generalized linear Poisson regressions were fitted to investigate 4 sets of factors associated with county-level mortality: demographic composition, socioeconomic status, health care and environmental features, and population health. The Theil index score was calculated to assess the mortality disparities.

MAIN OUTCOMES AND MEASURES

Stroke mortality was measured as the number of deaths attributed to stroke in the data set. Out-of-stroke-unit death was defined as any death occurring in outpatient or emergency departments or at the pretransport location. Five stroke subtypes were included in the analysis.

RESULTS

Although mortality did not change substantially from 1999 to 2018 (from 12.62 to 11.81 per 100 000 population), the proportion of deaths occurring out of the stroke unit increased from 23.56% (4328 of 18 369) to 34.57% (6978 of 20 188). A large percentage of stroke of an uncertain cause was reported, with most deaths (55.20%) occurring out of the stroke unit. In the county with the highest premature stroke mortality, the incidence was 20.78 times as high as that in the county with the lowest mortality (65.04 vs 3.13 deaths per 100 000 population). The highest between-county disparities were found for stroke of uncertain cause. For out-of-stroke-unit death, county-level mortality was largely associated with demographic composition (31.6%) and health care and environmental features (25.8%). For in-hospital death, 29.8% of county-level mortality was associated with population health and 28.7% was associated with demographic composition.

CONCLUSIONS AND RELEVANCE

These findings suggest that strategies addressing specific factors that underlie the mortality disparities among US counties, especially for out-of-stroke-unit death and stroke of uncertain cause, may be useful when tailored to the county-level context before implementing interventions for the neediest counties.

Disparities in Premature Cardiac Death Among US Counties From 1999-2017: Temporal Trends and Key Drivers

Background Disparities in premature cardiac death (PCD) might stagnate the progress toward the reduction of PCD in the United States and worldwide. We estimated disparities across US counties in PCD rates and investigated county-level factors related to the disparities. Methods and Results We used US mortality data for cause-of-death and demographic data from death certificates and county-level characteristics data from multiple databases. PCD was defined as any death that occurred at an age between 35 and 74 years with an underlying cause of death caused by cardiac disease based on International Classification of Diseases, Tenth Revision (ICD-10), codes. Of the 1 598 173 PCDs that occurred during 1999-2017, 60.9% were out of hospital. Although the PCD rates declined from 1999-2017, the proportion of out-of-hospital PCDs among all cardiac deaths increased from 58.3% to 61.5%. The geographic disparities in PCD rates across counties widened from 1999 (Theil index=0.10) to 2017 (Theil index=0.23), and within-state differences accounted for the majority of disparities (57.4% in 2017). The disparities in out-of-hospital PCD rates (and in-hospital PCD rates) associated with demographic composition were 36.51% (and 37.51%), socioeconomic features were 18.64% (and 18.36%), healthcare environment were 18.64% (and 13.90%), and population health status were 23.73% (and 30.23%). Conclusions Disparities in PCD rates exist across US counties, which may be related to the decelerated trend of decline in the rates among middle-aged adults. The slower declines in out-of-hospital rates warrants more precision targeting and sustained efforts to ensure progress at better levels of health (with lower PCD rates) against PCD.