Association of Cardiovascular Health in Young Adulthood with Long-Term Blood Pressure Trajectories.

BACKGROUND: Cardiovascular health (CVH) in young adulthood (YA) has been associated with cardiovascular outcomes in older age. However, little is known about the relationship between YA CVH and mid-life BP trajectories. METHODS: Baseline CVH (defined by 7 of AHA's Life's Essential 8 [LE8] metrics, excluding BP) was measured in YA with individual metrics scored and averaged as a composite LE8 score. Categorical CVH status was defined as high, moderate, and low. Latent class analysis was used to identify trajectories of mid-BP (mean of SBP and DBP) from average ages 35 to 55 years. Multinomial logistic regression was used to estimate the association of YA CVH status (continuously and categorically) with mid-life BP trajectory group membership. RESULTS: There were 3,688 participants from the Coronary Artery Risk Development in Young Adults (CARDIA) study in YA with follow-up data for mid-life BP trajectories. We observed 3 BP trajectory groups, labeled as Persistently-Low, Middle, and High-Increasing. On average, each 10-points higher baseline LE8 score (mean [SD] of 73.5 [13.1]) in YA was associated with adjusted odds ratios of 0.78 (95% CI, 0.72-0.84) for membership in the Middle and 0.65 (0.57-0.73) for membership in the High-Increasing trajectory groups. Compared with categorical low CVH status at baseline, those with high CVH were significantly less likely to be in the Middle and High-Increasing BP trajectory groups. CONCLUSIONS: Moderate or low CVH status in YA is associated with elevated mid-life BP trajectory. These data suggest that young adult CVH promotion may be important for primordial prevention of hypertension.

Association Between Life's Essential 8 Cardiovascular Health Metrics With Cardiovascular Events in the Cardiovascular Disease Lifetime Risk Pooling Project.

BACKGROUND: The American Heart Association recently launched updated cardiovascular health metrics, termed Life's Essential 8 (LE8). Compared with Life's Simple 7 (LS7), the new approach added sleep health as an eighth metric and updated the remaining 7 health factors and behaviors. The association of the updated LE8 score with long-term cardiovascular disease (CVD) outcomes and death is unknown. METHODS: We pooled individual-level data from 6 contemporary US-based cohorts from the Cardiovascular Lifetime Risk Pooling Project. Total LE8 score (0-100 points), LE8 score without sleep (0-100 points), and prior LS7 scores (0-14 points) were calculated separately. We used multivariable-adjusted Cox models to evaluate the association of LE8 with CVD, CVD subtypes, and all-cause mortality among younger, middle, and older adult participants. Net reclassification improvement analysis was used to measure the improvement in CVD risk classification with the addition of LS7 and LE8 recategorization based on score quartile rankings. RESULTS: Our sample consisted of 32 896 US adults (7836 [23.8%] Black; 14 941 [45.4%] men) followed for 642 000 person-years, of whom 9391 developed CVD events. Each 10-point higher overall LE8 score was associated with lower risk by 22% to 40% for CVD, 24% to 43% for congenital heart disease, 17% to 34% for stroke, 23% to 38% for heart failure, and 17% to 21% for all causes of mortality events across age strata. LE8 score provided more granular differentiation of the related CVD risk than LS7. Overall, 19.5% and 15.5% of the study participants were recategorized upward and downward based on LE8 versus LS7 categories, respectively, and the recategorization was significantly associated with CVD risk in addition to LS7 score. The addition of recategorization between LE8 and LS7 categories improved CVD risk reclassification across age groups (clinical net reclassification improvement, 0.06-0.12; P<0.01). CONCLUSIONS: These findings support the improved utility of the LE8 algorithm for assessing overall cardiovascular health and future CVD risk.

Incorporating longitudinal history of risk factors into atherosclerotic cardiovascular disease risk prediction using deep learning.

It is increasingly clear that longitudinal risk factor levels and trajectories are related to risk for atherosclerotic cardiovascular disease (ASCVD) above and beyond single measures. Currently used in clinical care, the Pooled Cohort Equations (PCE) are based on regression methods that predict ASCVD risk based on cross-sectional risk factor levels. Deep learning (DL) models have been developed to incorporate longitudinal data for risk prediction but its benefit for ASCVD risk prediction relative to the traditional Pooled Cohort Equations (PCE) remain unknown. Our study included 15,565 participants from four cardiovascular disease cohorts free of baseline ASCVD who were followed for adjudicated ASCVD. Ten-year ASCVD risk was calculated in the training set using our benchmark, the PCE, and a longitudinal DL model, Dynamic-DeepHit. Predictors included those incorporated in the PCE: sex, race, age, total cholesterol, high density lipid cholesterol, systolic and diastolic blood pressure, diabetes, hypertension treatment and smoking. The discrimination and calibration performance of the two models were evaluated in an overall hold-out testing dataset. Of the 15,565 participants in our dataset, 2170 (13.9%) developed ASCVD. The performance of the longitudinal DL model that incorporated 8 years of longitudinal risk factor data improved upon that of the PCE [AUROC: 0.815 (CI 0.782-0.844) vs 0.792 (CI 0.760-0.825)] and the net reclassification index was 0.385. The brier score for the DL model was 0.0514 compared with 0.0542 in the PCE. Incorporating longitudinal risk factors in ASCVD risk prediction using DL can improve model discrimination and calibration.

Educational Attainment and Lifetime Risk of Cardiovascular Disease.

Importance: Education is a social determinant of health. Quantifying its association with lifetime cardiovascular disease (CVD) risk has public health importance. Objective: To calculate lifetime risk estimates of incident CVD and CVD subtypes and estimate years lived with and without CVD by education. Design, Setting, and Participants: Included community-based cohort studies with adjudicated cardiovascular events used pooled individual-level data from 1985 to 2015 of 6 prospective cohort studies. The study team assessed the association between education and lifetime CVD risk with modified Kaplan-Meier and Cox models accounting for competing risk of noncardiovascular death. The study team estimated years lived with and without CVD by education with the Irwin restricted mean and the utility of adding educational attainment to CVD risk assessment. Participants (baseline 40 to 59 years old and 60 to 79 years old) were without CVD at baseline and had complete education, cardiovascular risk factors, and prospective CVD outcomes data. Data were analyzed from January 2022 to September 2022. Exposures: Educational attainment (less than high school, high school completion, some college, or college graduate). Main outcome and measures: Cardiovascular events (fatal and nonfatal coronary heart disease, heart failure, and stroke; CVD-related deaths; and total CVD encompassing any of these events). Results: There were 40 998 participants (23 305 female [56.2%]) with a mean (SD) age of 58.1 (9.7) years for males and 58.3 (9.9) years for females. Compared with college graduates, those with less than high school or high school completion had higher lifetime CVD risks. Among middle-aged men, the competing hazard ratios (HRs) for a CVD event were 1.58 (95% CI, 1.38-1.80), 1.30 (95% CI, 1.10-1.46), and 1.16 (95% CI, 1.00-1.34) in those with less than high school, high school, and some college, respectively, compared with those with college completion. Among women, these competing HRs were 1.70 (95% CI, 1.49-1.95), 1.19 (95% CI, 1.05-1.35), and 0.98 (95% CI, 0.83-1.15). Individuals with higher education had longer duration of life prior to incident CVD. Education provided limited contribution toward enhancing CVD risk prediction. Conclusions and relevance: Lower education was associated with lifetime CVD risk across adulthood; higher education translated to healthy longevity. Educational policy initiatives may associate with long-term health benefits.

Incorporating longitudinal history of risk factors into atherosclerotic cardiovascular disease risk prediction using deep learning.

Background: It is increasingly clear that longitudinal risk factor levels and trajectories are related to risk for atherosclerotic cardiovascular disease (ASCVD) above and beyond single measures. Currently used in clinical care, the Pooled Cohort Equations (PCE) are based on regression methods that predict ASCVD risk based on cross-sectional risk factor levels. Deep learning (DL) models have been developed to incorporate longitudinal data for risk prediction but its benefit for ASCVD risk prediction relative to the traditional Pooled Cohort Equations (PCE) remain unknown. Objective: To develop a ASCVD risk prediction model that incorporates longitudinal risk factors using deep learning. Methods: Our study included 15,565 participants from four cardiovascular disease cohorts free of baseline ASCVD who were followed for adjudicated ASCVD. Ten-year ASCVD risk was calculated in the training set using our benchmark, the PCE, and a longitudinal DL model, Dynamic-DeepHit. Predictors included those incorporated in the PCE: sex, race, age, total cholesterol, high density lipid cholesterol, systolic and diastolic blood pressure, diabetes, hypertension treatment and smoking. The discrimination and calibration performance of the two models were evaluated in an overall hold-out testing dataset. Results: Of the 15,565 participants in our dataset, 2,170 (13.9%) developed ASCVD. The performance of the longitudinal DL model that incorporated 8 years of longitudinal risk factor data improved upon that of the PCE [AUROC: 0.815 (CI: 0.782-0.844) vs 0.792 (CI: 0.760-0.825)] and the net reclassification index was 0.385. The brier score for the DL model was 0.0514 compared with 0.0542 in the PCE. Conclusion: Incorporating longitudinal risk factors in ASCVD risk prediction using DL can improve model discrimination and calibration.

Longitudinal trajectories of branched chain amino acids through young adulthood and diabetes in later life.

BACKGROUNDElevated circulating branched chain amino acids (BCAAs), measured at a single time point in middle life, are strongly associated with an increased risk of developing type 2 diabetes mellitus (DM). However, the longitudinal patterns of change in BCAAs through young adulthood and their association with DM in later life are unknown.METHODSWe serially measured BCAAs over 28 years in the Coronary Artery Risk Development in Young Adults (CARDIA) study, a prospective cohort of apparently healthy Black and White young adults at baseline. Trajectories of circulating BCAA concentrations from years 2-30 (for prevalent DM) or years 2-20 (for incident DM) were determined by latent class modeling.RESULTSAmong 3,081 apparently healthy young adults, trajectory analysis from years 2-30 revealed 3 distinct BCAA trajectory groups: low-stable (n = 1,427), moderate-stable (n = 1,384), and high-increasing (n = 270) groups. Male sex, higher body mass index, and higher atherogenic lipid fractions were more common in the moderate-stable and high-increasing groups. Higher risk of prevalent DM was associated with the moderate-stable (OR = 2.59, 95% CI: 1.90-3.55) and high-increasing (OR = 6.03, 95% CI: 3.86-9.43) BCAA trajectory groups in adjusted models. A separate trajectory group analysis from years 2-20 for incident DM after year 20 showed that moderate-stable and high-increasing trajectory groups were also significantly associated with higher risk of incident DM, after adjustment for clinical variables and glucose levels.CONCLUSIONBCAA levels track over a 28-year span in most young adults, but serial clinical metabolomic measurements identify subpopulations with rising levels associated with high risk of DM in later life.FUNDINGThis research was supported by the NIH, under grants R01 HL146844 (JTW) and T32 HL069771 (MRC). The CARDIA study is conducted and supported by the NIH National Heart, Lung, and Blood Institute in collaboration with the University of Alabama at Birmingham (HHSN268201800005I and HHSN268201800007I), Northwestern University (HHSN268201800003I), the University of Minnesota (HHSN268201800006I), and Kaiser Foundation Research Institute (HHSN268201800004I).

Joint effect of highly-sensitive cardiac troponin T and ankle-brachial index on incident cardiovascular events: The MESA and CHS.

Background: Elevated highly-sensitive cardiac troponin-T (hs-cTnT≥14 ng/L) and low ankle-brachial index (ABI<0.9) are risk factors for atherosclerotic cardiovascular diseases (ASCVD) but their joint effect on the risk of ASCVD events is unknown. Methods: We used data from the two population-based cohort studies, the Multi-Ethnic study of Atherosclerosis (MESA) and Cardiovascular Heart Study (CHS) among 10,897 participants free of CVD events at baseline (mean age 66.3 years, 44.7% males). Incident ASCVD was defined as CHD (fatal/non-fatal MI or revascularization), transient ischemic attack, or stroke,. Hazard ratio (HR) and 95% CI was calculated from a Cox regression model. Interaction on the additive scale was assessed using relative excess risk due to interaction (RERI) and interaction on the multiplicative scale was assessed by Likelihood ratio (LR) test. Results: At baseline (2000-2002 for MESA and 1989-1990 for CHS), 10.2% of participants had elevated hs-cTnT and 7.5% had low ABI. During a median follow-up of 13.6 years (interquartile range, 7.5-14.7 years), there were 2590 incident ASCVD and 1542 incident CHD events. The hazard of CHD and ASCVD was higher in participants with both elevated hs-cTnT and low ABI [HR(95% CI): CHD: 2.04 (1.45, 2.88), ASCVD: 2.05 (1.58, 2.66)] than those with only elevated hs-cTnT [CHD: 1.65 (1.37, 1.99), ASCVD: 1.67 (1.44, 1.99)] or only low ABI [CHD: 1.87 (1.52, 2.31), ASCVD: 1.67 (1.42, 1.97)]. Antagonistic multiplicative interaction was observed for CHD (LR test p-value=0.042) but not for ASCVD (LR test p-value =0.08). No significant additive interaction was detected for CHD and ASCVD (RERI p-value ≥0.23). Conclusion: The observed joint effect of elevated cTnT and low ABI on ASCVD risk was smaller (i.e., antagonistic interaction) than that expected by the combined independent effects of each risk factor.

Comparison of State-of-the-Art Neural Network Survival Models with the Pooled Cohort Equations for Cardiovascular Disease Risk Prediction.

BACKGROUND: The Pooled Cohort Equations (PCEs) are race- and sex-specific Cox proportional hazards (PH)-based models used for 10-year atherosclerotic cardiovascular disease (ASCVD) risk prediction with acceptable discrimination. In recent years, neural network models have gained increasing popularity with their success in image recognition and text classification. Various survival neural network models have been proposed by combining survival analysis and neural network architecture to take advantage of the strengths from both. However, the performance of these survival neural network models compared to each other and to PCEs in ASCVD prediction is unknown. METHODS: In this study, we used 6 cohorts from the Lifetime Risk Pooling Project (with 5 cohorts as training/internal validation and one cohort as external validation) and compared the performance of the PCEs in 10-year ASCVD risk prediction with an all two-way interactions Cox PH model (Cox PH-TWI) and three state-of-the-art neural network survival models including Nnet-survival, Deepsurv, and Cox-nnet. For all the models, we used the same 7 covariates as used in the PCEs. We fitted each of the aforementioned models in white females, white males, black females, and black males, respectively. We evaluated models' internal and external discrimination power and calibration. RESULTS: The training/internal validation sample comprised 23216 individuals. The average age at baseline was 57.8 years old (SD = 9.6); 16% developed ASCVD during average follow-up of 10.50 (SD = 3.02) years. Based on 10 × 10 cross-validation, the method that had the highest C-statistics was Deepsurv (0.7371) for white males, Deepsurv and Cox PH-TWI (0.7972) for white females, PCE (0.6981) for black males, and Deepsurv (0.7886) for black females. In the external validation dataset, Deepsurv (0.7032), Cox-nnet (0.7282), PCE (0.6811), and Deepsurv (0.7316) had the highest C-statistics for white male, white female, black male, and black female population, respectively. Calibration plots showed that in 10 × 10 validation, all models had good calibration in all race and sex groups. In external validation, all models overestimated the risk for 10-year ASCVD. CONCLUSIONS: We demonstrated the use of the state-of-the-art neural network survival models in ASCVD risk prediction. Neural network survival models had similar if not superior discrimination and calibration compared to PCEs.

Atherosclerotic Cardiovascular Disease or Heart Failure: First Cardiovascular Event in Adults With Prediabetes and Diabetes.

BACKGROUND: Individuals with prediabetes and diabetes are at increased risk of atherosclerotic cardiovascular disease (ASCVD) and heart failure (HF). Whether ASCVD or HF is more likely to occur first in these populations within different race-sex groups is unknown. OBJECTIVE: To determine the competing risk for the first cardiovascular event by subtype in Black and white men and women with prediabetes and diabetes. METHODS: Individual-level data from adults without ASCVD or HF were pooled from 6 population-based cohorts. We estimated the competing cumulative incidences of ASCVD, HF and noncardiovascular death as the first event in middle-aged (40-59 years) and older (60-79 years) adults, stratified by race and sex, with normal fasting plasma glucose (FPG < 100 mg/dL), prediabetes (FPG 100-125 mg/dL) and diabetes (FPG ≥ 126 mg/dL or on antihyperglycemic agents) at baseline. Within each race-sex group, we estimated risk the adjusted hazard ratio of ASCVD, HF and noncardiovascular death in adults with prediabetes and diabetes relative to adults with normoglycemia after adjusting for cardiovascular risk factors. RESULTS: In 40,117 participants with 638,910 person-years of follow-up, 5781 cases of incident ASCVD and 3179 cases of incident HF occurred. In middle-aged adults with diabetes, competing cumulative incidence of ASCVD as a first event was higher than HF in white men (35.4% vs 11.6%), Black men (31.6% vs 15.1%) and white women (24.3% vs 17.2%) but not in Black women (26.4% vs 28.4%). Within each group, the adjusted hazard ratio of ASCVD and HF was significantly higher in adults with diabetes than in adults with normal FPG levels. Findings were largely similar in middle-aged adults with prediabetes and older adults with prediabetes or diabetes. CONCLUSIONS: Black women with diabetes are more likely to develop HF as their first CVD event, whereas individuals with diabetes from other race-sex groups are more likely to present first with ASCVD. These results can inform the tailoring of primary prevention therapies for either HF- or ASCVD-specific pathways based on individual-level risk.

Social and Psychosocial Determinants of Racial and Ethnic Differences in Cardiovascular Health in the United States Population.

BACKGROUND: Social and psychosocial factors are associated with cardiovascular health (CVH). Our objective was to examine the contributions of individual-level social and psychosocial factors to racial and ethnic differences in population CVH in the NHANES (National Health and Nutrition Examination Surveys) 2011 to 2018, to inform strategies to mitigate CVH inequities. METHODS: In NHANES participants ages ≥20 years, Kitagawa-Blinder-Oaxaca decomposition estimated the statistical contribution of individual-level factors (education, income, food security, marital status, health insurance, place of birth, depression) to racial and ethnic differences in population mean CVH score (range, 0-14, accounting for diet, smoking, physical activity, body mass index, blood pressure, cholesterol, blood glucose) among Hispanic, non-Hispanic Asian, or non-Hispanic Black adults compared with non-Hispanic White adults. RESULTS: Among 16 172 participants (representing 255 million US adults), 24% were Hispanic, 12% non-Hispanic Asian, 23% non-Hispanic Black, and 41% non-Hispanic White. Among men, mean (SE) CVH score was 7.45 (2.3) in Hispanic, 8.71 (2.2) in non-Hispanic Asian, 7.48 (2.4) in non-Hispanic Black, and 7.58 (2.3) in non-Hispanic White adults. In Kitagawa-Blinder-Oaxaca decomposition, education explained the largest component of CVH differences among men (if distribution of education were similar to non-Hispanic White participants, CVH score would be 0.36 [0.04] points higher in Hispanic, 0.24 [0.04] points lower in non-Hispanic Asian, and 0.23 [0.03] points higher in non-Hispanic Black participants; P<0.05). Among women, mean (SE) CVH score was 8.03 (2.4) in Hispanic, 9.34 (2.1) in non-Hispanic Asian, 7.43 (2.3) in non-Hispanic Black, and 8.00 (2.5) in non-Hispanic White adults. Education explained the largest component of CVH difference in non-Hispanic Black women (if distribution of education were similar to non-Hispanic White participants, CVH score would be 0.17 [0.03] points higher in non-Hispanic Black participants; P<0.05). Place of birth (born in the United States versus born outside the United States) explained the largest component of CVH difference in Hispanic and non-Hispanic Asian women (if distribution of place of birth were similar to non-Hispanic White participants, CVH score would be 0.36 [0.07] points lower and 0.49 [0.16] points lower, respectively; P<0.05). CONCLUSIONS: Education and place of birth confer the largest statistical contributions to the racial and ethnic differences in mean CVH score among US adults.

Cardiac Structure and Function Phenogroups and Risk of Incident Heart Failure (from the Multi-ethnic Study of Atherosclerosis).

Indices of cardiac structure and function, such as left ventricular (LV) mass and ejection fraction, have been associated with risk of incident heart failure (HF), but the clinical relevance of data-driven grouping of a comprehensive set of cardiac parameters is unclear. In Multi-Ethnic Study of Atherosclerosis participants, latent class analysis was applied in the sample stratified by gender to define phenogroups on the basis of cardiovascular magnetic resonance imaging parameters of right ventricular and LV structure and function at baseline. Cox proportional hazard models in gender-stratified analyses were used to assess the association between phenogroup membership and risk of HF subtypes adjusting for potential confounders. In the 4,204 participants (mean age 61 ± 10 years, 53% women), the mean follow-up time was 14 ± 4 years for men and 15 ± 4 years for women. For both genders, 4 distinct phenogroups were identified: (1) ideal cardiac mechanics; (2) higher output/hypertrophied LV; (3) impaired ejection fraction/dilated LV; and (4) higher output/hyperdynamic (LV). Men in phenogroups 4 (hazard ratio [HR] 2.91, 95% confidence interval [CI] 1.60 to 5.31, p = 0.0005), 3 (HR 3.52, 95% CI 1.90 to 6.53, p <0.0001), and 2 (HR 3.49, 95% CI 1.94 to 6.28, p <0.0001) had higher rates of incident HF than did men in phenogroup 1, in fully adjusted models. No significant associations were found between phenogroup membership and incident HF in women. In conclusion, phenogroup membership based on cardiac structure and function in men was significantly associated with incident HF. Integration of cardiac magnetic resonance imaging variables may help identify differential risk for HF in men.

Social Determinants of Cardiovascular Health in US Adolescents: National Health and Nutrition Examination Surveys 1999 to 2014.

Background Cardiovascular health (CVH) is suboptimal in US adolescents. Social determinants of health (SDOH) may affect CVH. We examined SDOH by race and ethnicity and assessed for associations between SDOH and CVH among US adolescents. Methods and Results We analyzed data from the National Health and Nutrition Examination Survey for 3590 participants aged 12 to 19 years from 1999 to 2014. SDOH variables were chosen and an SDOH score assigned (range, 0-7 points; higher=more favorable). CVH was classified according to American Heart Association criteria. We estimated population prevalence and used multivariable linear and polytomous logistic regression for associations between SDOH and CVH. SDOH varied by group, with the non-Hispanic White group (n=1155) having a higher/better mean SDOH score compared with non-Hispanic Black (n=1223) and Mexican American groups (n=1212). Associations between SDOH and CVH differed between racial and ethnic groups (interaction P<0.0001). For the non-Hispanic White group, each additional favorable SDOH variable was associated with a CVH score higher/better by 0.3 points (ß, 0.3, P<0.0001), 20% higher odds for moderate (versus low) CVH (odds ratio [OR], 1.2 [95% CI, 1.1-1.4]), and 80% higher odds for high/favorable (versus low) CVH (1.8 [1.5-2.1]). Associations between SDOH and CVH were more modest among the Mexican American group (ß, 0.12, P=0.001; OR 1.1 [1.0-1.2] for moderate CVH; OR, 1.3 [1.1-1.6] for high CVH) and were not significant among the non-Hispanic Black group (ß, 0.07; P=0.464). Conclusions SDOH and CVH were more favorable for non-Hispanic White adolescents compared with non-Hispanic Black and Mexican American adolescents. SDOH were strongly associated with CVH among the non-Hispanic White group. Racially and culturally sensitive public policy approaches may improve CVH in US adolescents.

Redefining Cardiovascular Health to Include Sleep: Prospective Associations With Cardiovascular Disease in the MESA Sleep Study.

Background Although sufficient and healthy sleep is inversely associated with cardiovascular disease (CVD) and its risk factors, the American Heart Association's Life's Simple 7 (LS7), as a measure of cardiovascular health (CVH), did not include sleep. We evaluated an expanded measure of CVH that includes sleep as an eighth metric in relation to CVD risk. Methods and Results The analytic sample consisted of MESA (Multi-Ethnic Study of Atherosclerosis) Sleep Study participants who had complete data on sleep characteristics from overnight polysomnography, 7-day wrist actigraphy, validated questionnaires, and the outcome. We computed the LS7 score and 4 iterations of a new CVH score: score 1 included sleep duration, score 2 included sleep characteristics linked to CVD in the literature (sleep duration, insomnia, daytime sleepiness, and obstructive sleep apnea), scores 3 and 4 included sleep characteristics associated with CVD in MESA (score 3: sleep duration and efficiency, daytime sleepiness, and obstructive sleep apnea; score 4: score 3+sleep regularity). Multivariable-adjusted logistic and Cox proportional hazards models evaluated associations of the LS7 and CVH scores 1 to 4 with CVD prevalence and incidence. Among 1920 participants (mean age: 69±9 years; 54% female), there were 95 prevalent CVD events and 93 incident cases (mean follow-up, 4.4 years). Those in the highest versus lowest tertile of the LS7 score and CVH scores 1 to 4 had up to 80% lower odds of prevalent CVD. The LS7 score was not significantly associated with CVD incidence (hazard ratio, 0.62 [95% CI, 0.37-1.04]). Those in the highest versus lowest tertile of CVH score 1, which included sleep duration, and CVH score 4, which included multidimensional sleep health, had 43% and 47% lower incident CVD risk (hazard ratio, 0.57 [95% CI, 0.33-0.97]; and hazard ratio, 0.53 [95% CI, 0.32-0.89]), respectively. Conclusions CVH scores that include sleep health predicted CVD risk in older US adults. The incorporation of sleep as a CVH metric, akin to other health behaviors, may enhance CVD primordial and primary prevention efforts. Findings warrant confirmation in larger cohorts over longer follow-up.

Analysis of apoB Concentrations Across Early Adulthood and Predictors for Rates of Change Using CARDIA Study Data.

The cumulative exposure to apolipoprotein B (apoB)-containing lipoproteins in the blood during early adult life is a central determinant of atherosclerotic cardiovascular disease risk. To date, the patterns and rates of change in apoB through early adult life have not been described. Here, we used NMR to measure apoB concentrations in up to 3055 Coronary Artery Risk Development in Young Adults (CARDIA) Study participants who attended the years 2 (Y2), 7 (Y7), 15 (Y15), 20 (Y20), and 30 (Y30) exams. We examined individual-level spaghetti plots of apoB change, and we calculated average annualized rate of apoB concentration change during follow-up. We used multivariable linear regression models to assess the associations between CARDIA participant characteristics and annualized rates of apoB change. Male sex, higher measures of adiposity, lower HDL-C, lower Healthy Eating Index, and higher blood pressures were observed more commonly in individuals with higher apoB level at Y2 and Y20. Inter- and intra-individual variation in apoB concentration over time was substantial-while the mean (SD) rate of change was 0.52 (1.0) mg/dl/year, the range of annualized rates of change was -6.26 to +9.21 mg/dl/year. At baseline, lower first apoB measurement, female sex, White race, lower BMI, and current tobacco use were associated with apoB increase. We conclude that the significant variance in apoB level over time and the modest association between baseline measures and rates of apoB change suggest that the ability to predict an individual's future apoB serum concentrations, and thus their cumulative apoB exposure, after a one-time assessment in young adulthood is low.

Status of Cardiovascular Health in US Adults and Children Using the American Heart Association's New "Life's Essential 8" Metrics: Prevalence Estimates From the National Health and Nutrition Examination Survey (NHANES), 2013 Through 2018.

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.

Associations of Clinical and Social Risk Factors With Racial Differences in Premature Cardiovascular Disease.

BACKGROUND: Racial differences in cardiovascular disease (CVD) are likely related to differences in clinical and social factors. The relative contributions of these factors to Black-White differences in premature CVD have not been investigated. METHODS: In Black and White adults aged 18 to 30 years at baseline in the CARDIA study (Coronary Artery Risk Development in Young Adults), the associations of clinical, lifestyle, depression, socioeconomic, and neighborhood factors across young adulthood with racial differences in incident premature CVD were evaluated in sex-stratified, multivariable-adjusted Cox proportional hazards models using multiply imputed data assuming missing at random. Percent reduction in the ß estimate (log-hazard ratio [HR]) for race quantified the contribution of each factor group to racial differences in incident CVD. RESULTS: Among 2785 Black and 2327 White participants followed for a median 33.9 years (25th-75th percentile, 33.7-34.0), Black (versus White) adults had a higher risk of incident premature CVD (Black women: HR, 2.44 [95% CI, 1.71-3.49], Black men: HR, 1.59 [1.20-2.10] adjusted for age and center). Racial differences were not statistically significant after full adjustment (Black women: HR, 0.91 [0.55-1.52], Black men: HR 1.02 [0.70-1.49]). In women, the largest magnitude percent reduction in the ß estimate for race occurred with adjustment for clinical (87%), neighborhood (32%), and socioeconomic (23%) factors. In men, the largest magnitude percent reduction in the ß estimate for race occurred with an adjustment for clinical (64%), socioeconomic (50%), and lifestyle (34%) factors. CONCLUSIONS: In CARDIA, the significantly higher risk for premature CVD in Black versus White adults was statistically explained by adjustment for antecedent multilevel factors. The largest contributions to racial differences were from clinical and neighborhood factors in women, and clinical and socioeconomic factors in men.

Lipoprotein Levels in Early Adulthood and NAFLD in Midlife: The Coronary Artery Risk Development in Young Adults (CARDIA) Study.

Objective: We evaluated the association of apolipoprotein B (apoB) with low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), and triglycerides (TG) in early adulthood with concordant/discordant associations and midlife NAFLD. Methods: Participants from the CARDIA study were included (n = 2,655; baseline mean age: 25.0, 59.1% female, and 48.6% black). NAFLD was defined as liver attenuation ≤40 Hounsfield units after excluding other causes of liver fat. Logistic regression models assessed the odds of Y25 NAFLD among tertiles of apoB, LDL-C, non-HDL-C, and TG and quartiles of the apoB/TG ratio. Discordance/concordance analyses examined the association of apoB with each lipid marker and Y25 NAFLD. Results: The Y25 NAFLD prevalence was 10%. The high-tertile TG group (OR 1.87, 95% CI, and 1.30-2.69) and the low- (OR 1.98, 95% CI, and 1.30-3.01) and middle-apoB/TG ratio groups (OR 1.78, 95% CI, and 1.17-2.72) had the greatest odds of midlife NAFLD. Using discordance/concordance analysis, the high-apoB/high-TG group had the highest odds of NAFLD (OR 1.69, 95% CI, and 1.09-2.61) followed by the low-apoB/high-TG group. The high apoB/low TG group had the lowest odds of NAFLD. Conclusions: Among the studied lipid markers in early adulthood, TG levels have the strongest and most consistent association with midlife NAFLD.

Corrigendum: Rationale and Design of a Pharmacist-led Intervention for the Risk-Based Prevention of Heart Failure: The FIT-HF Pilot Study.

[This corrects the article DOI: 10.3389/fcvm.2021.785109.].