Background: The American Heart Association (AHA) 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 non-pregnant, non-institutionalized individuals ages 2 through 79 years who were free of cardiovascular disease from the National Health and Nutrition Examination Surveys in 2013-2018. 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 (PA), nicotine exposure, sleep duration, body mass index (BMI), blood lipids, blood glucose, and blood pressure (BP), using published AHA 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/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% confidence interval [CI], 63.9-65.6) among adults using all 8 metrics, and it was 65.5 (95% CI, 64.4-66.6) for the 3 metrics available (diet, PA, and BMI) among children/adolescents ages 2 through 19 years. For adults, there were significant differences in mean overall CVH scores by sex (women: 67.0 vs. men: 62.5), age (range of mean values 62.2-68.7), and racial/ethnic group (range 59.7-68.5). Mean scores were lowest for diet, PA, and BMI 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 BP (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 2-5 to 28.5 at ages 12-19); large differences were also noted in mean PA (range 63.1-88.3) and BMI (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 both individuals and the population.

Background: Substantial differences exist between United States counties with regards to premature (<65 years of age) cardiovascular disease (CVD) mortality. Whether underlying social vulnerabilities of counties influence premature CVD mortality is uncertain. Methods: In this cross-sectional study (2014–2018), we linked county-level CDC/ATSDR SVI (Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry Social Vulnerability Index) data with county-level CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiological Research) mortality data. We calculated scores for overall SVI and its 4 subcomponents (ie, socioeconomic status; household composition and disability; minority status and language; and housing type and transportation) using 15 social attributes. Scores were presented as percentile rankings by county, further classified as quartiles on the basis of their distribution among all US counties (1st [least vulnerable] = 0 to 0.25; 4th [most vulnerable = 0.75 to 1.00]). We grouped age-adjusted mortality rates per 100 000 person-years for overall CVD and its subtypes (ischemic heart disease, stroke, hypertension, and heart failure) for nonelderly (<65 years of age) adults across SVI quartiles. Results: Overall, the age-adjusted CVD mortality rate per 100 000 person-years was 47.0 (ischemic heart disease, 28.3; stroke, 7.9; hypertension, 8.4; and heart failure, 2.4). The largest concentration of counties with more social vulnerabilities and CVD mortality were clustered across the southwestern and southeastern parts of the United States. The age-adjusted CVD mortality rates increased in a stepwise manner from 1st to 4th SVI quartiles. Counties in the 4th SVI quartile had significantly higher mortality for CVD (rate ratio, 1.84 [95% CI, 1.43–2.36]), ischemic heart disease (1.52 [1.09–2.13]), stroke (2.03 [1.12–3.70]), hypertension (2.71 [1.54–4.75]), and heart failure (3.38 [1.32–8.61]) than those in the 1st SVI quartile. The relative risks varied considerably by demographic characteristics. For example, among all ethnicities/races, non-Hispanic Black adults in the 4th SVI quartile versus the 1st SVI quartile exclusively had significantly higher relative risks of stroke (1.65 [1.07–2.54]) and heart failure (2.42 [1.29–4.55]) mortality. Rural counties with more social vulnerabilities had 2- to 5-fold higher mortality attributable to CVD and subtypes. Conclusions: In this analysis, US counties with more social vulnerabilities had higher premature CVD mortality, varied by demographic characteristics and rurality. Focused public health interventions should address the socioeconomic disparities faced by underserved communities to curb the growing burden of premature CVD.

Background: Depression is a nontraditional risk factor for cardiovascular disease (CVD). Data on the association of depression and poor mental health with CVD and suboptimal cardiovascular health (CVH) among young adults are limited. Methods and Results: We used data from 593 616 young adults (aged 18–49 years) from the 2017 to 2020 Behavioral Risk Factor Surveillance System, a nationally representative survey of noninstitutionalized US adults. Exposures were self‐reported depression and poor mental health days (PMHDs; categorized as 0, 1–13, and 14–30 days of poor mental health in the past 30 days). Outcomes were self‐reported CVD (composite of myocardial infarction, angina, or stroke) and suboptimal CVH (≥2 cardiovascular risk factors: hypertension, hypercholesterolemia, overweight/obesity, smoking, diabetes, physical inactivity, and inadequate fruit and vegetable intake). Using logistic regression, we investigated the association of depression and PMHDs with CVD and suboptimal CVH, adjusting for sociodemographic factors (and cardiovascular risk factors for the CVD outcome). Of the 593 616 participants (mean age, 34.7±9.0 years), the weighted prevalence of depression was 19.6% (95% CI, 19.4–19.8), and the weighted prevalence of CVD was 2.5% (95% CI, 2.4–2.6). People with depression had higher odds of CVD than those without depression (odds ratio [OR], 2.32 [95% CI, 2.13–2.51]). There was a graded association of PMHDs with CVD. Compared with individuals with 0 PMHDs, the odds of CVD in those with 1 to 13 PMHDs and 14 to 30 PHMDs were 1.48 (95% CI, 1.34–1.62) and 2.29 (95% CI, 2.08–2.51), respectively, after adjusting for sociodemographic and cardiovascular risk factors. The associations did not differ significantly by sex or urban/rural status. Individuals with depression had higher odds of suboptimal CVH (OR, 1.79 [95% CI, 1.65–1.95]) compared with those without depression, with a similar graded relationship between PMHDs and suboptimal CVH. Conclusions: Depression and poor mental health are associated with premature CVD and suboptimal CVH among young adults. Although this association is likely bidirectional, prioritizing mental health may help reduce CVD risk and improve CVH in young adults.