Metabolomic profiling identifies novel metabolites associated with cardiac dysfunction.

Metabolic comorbidities, such as obesity and diabetes, are associated with subclinical alterations in both cardiac structure/function and natriuretic peptides prior to the onset of heart failure (HF). Despite this, the exact metabolic pathways of cardiac dysfunction which precede HF are not well-defined. Among older individuals without HF in the Multi-Ethnic Study of Atherosclerosis (MESA), we evaluated the associations of 47 circulating metabolites measured by 1H-NMR with echocardiographic measures of cardiac structure and function. We then evaluated associations of significant metabolites with circulating N-terminal pro-B-type natriuretic peptide (NT-proBNP). In a separate cohort, we evaluated differences between top metabolites in patients with HF with preserved ejection fraction (HFpEF) and comorbidity-matched controls. Genetic variants associated with top metabolites (mQTLs) were then related to echocardiographic measures and NT-proBNP. Among 3440 individuals with metabolic and echocardiographic data in MESA (62 ± 10 years, 52% female, 38% White), 10 metabolites broadly reflective of glucose and amino acid metabolism were associated with at least 1 measure of cardiac structure or function. Of these 10 metabolites, 4 (myo-inositol, glucose, dimethylsulfone, carnitine) were associated with higher NT-proBNP and 2 (d-mannose, acetone) were associated with lower NT-proBNP. In a separate cohort, patients with HFpEF had higher circulating myo-inositol levels compared with comorbidity-matched controls. Genetic analyses revealed that 1 of 6 known myo-inositol mQTLs conferred risk of higher NT-proBNP. In conclusion, metabolomic profiling identifies several novel metabolites associated with cardiac dysfunction in a cohort at high risk for HF, revealing pathways potentially relevant to future HF risk.

Improving Cardiovascular Disease Primary Prevention Treatment Thresholds in a New England Health Care System.

Background: Atherosclerotic cardiovascular disease (ASCVD) risk estimation based on the pooled cohort equation (PCE) overestimates in population-based cohorts. Whether it performs equally across disaggregated demographics in health care populations is less known. Objectives: The purpose of the study was to recalibrate PCE and rederive prevention thresholds in a contemporary health care system and evaluate its performance across sociodemographics. Methods: We retrospectively inspected electronic health records between 2010 to 2012 and 2020 to 2022 within Mass General Brigham health care in New England region. We compared performance of the original vs recalibrated PCE measured by calibration, discrimination, reclassification rate, and net benefit among 160,926 patients aged 40 to 79 years and without prior ASCVD or lipid-lowering medication. Results: Of the 160,926 patients (mean age: 54.6 ± 8.6 years; 61.4% female), 20,373 (12.7%) developed ASCVD over 10 years. The original PCE globally underestimated ASCVD risk (observed vs predicted incidence rate: 0.13 vs 0.05). Recalibration upclassified risk primarily among individuals with low-to-borderline risk by the original PCE and additionally identified 40% of patients who had undergone ASCVD events yet deemed statin-ineligible based on the original PCE. Treatment thresholds yielding the greatest net benefit were ≥24.0% for women (+23.3%) vs ≥26.0% for men (+18.7%), whereas ≥26.0% for White or other race (+24.7%) vs ≥14.0% Black or African American (+12.5%), respectively. Specifically, Hispanic or Latino and non-Hispanic Black patients conferred the greatest sensitivity improvement at ≥12.3% threshold compared to higher ≥23.6% among non-Hispanic Asian or Pacific Islanders. Generally, lower thresholds earlier in life were optimal. Conclusions: Recalibration and personalized treatment thresholds derived within a health system may improve prevention treatment allocation efficiency.

Blood Pressure Trajectories During Young Adulthood and Cardiovascular Events in Later Life.

BACKGROUND: Studying the association between blood pressure (BP) trajectories during young adulthood and subsequent cardiovascular disease (CVD) risk can provide insights into how long-term BP patterns in early life influence the development of CVD later in life. METHODS: We pooled data from two US cohorts (CARDIA, FHS). We used latent growth curve models to identify distinct BP trajectory groups during ages 18-39 years. We then used Cox proportional hazards models to assess the associations between BP trajectories and CVD events (composite of coronary heart disease [CHD], stroke, and heart failure [HF]) after age 40 years. RESULTS: We included 6,579 participants and identified four distinct systolic BP trajectory groups during young adulthood. During a median follow-up of 18.2 years after age 40 years, 213 CHD, 139 stroke, 120 HF, and 400 composite CVD events occurred. Individuals in an elevated-increasing vs. low-stable systolic BP trajectory during young adulthood was associated with a higher risk of CVD after adjusting for traditional CVD risk factors, with hazard ratios (95% CI) of 3.25 (1.63, 6.46) for CHD, 3.92 (1.63, 9.43) for stroke, 8.30 (2.97, 23.17) for HF, and 3.91 (2.38, 6.41) for composite CVD outcomes. Adding BP trajectory to BP at baseline improved model discrimination for all outcomes (changes in Harrell's C-index 0.0084 to 0.0192). CONCLUSIONS: An elevated-increasing BP trajectory during young adulthood is associated with a higher risk of CVD later in life, highlighting the importance of maintaining a low-stable BP trajectory throughout the young adulthood period for prevention of CVD in later life.

psHarmonize: Facilitating reproducible large-scale pre-statistical data harmonization and documentation in R.

Combining pertinent data from multiple studies can increase the robustness of epidemiological investigations. Effective "pre-statistical" data harmonization is paramount to the streamlined conduct of collective, multi-study analysis. Harmonizing data and documenting decisions about the transformations of variables to a common set of categorical values and measurement scales are time consuming and can be error prone, particularly for numerous studies with large quantities of variables. The psHarmonize R package facilitates harmonization by combining multiple datasets, applying data transformation functions, and creating long and wide harmonized datasets. The user provides transformation instructions in a "harmonization sheet" that includes dataset names, variable names, and coding instructions and centrally tracks all decisions. The package performs harmonization, generates error logs as necessary, and creates summary reports of harmonized data. psHarmonize is poised to serve as a central feature of data preparation for the joint analysis of multiple studies.

Prediction of Cumulative Exposure to Atherogenic Lipids During Early Adulthood.

BACKGROUND: The ability of a 1-time measurement of non-high-density lipoprotein cholesterol (non-HDL-C) or low-density lipoprotein cholesterol (LDL-C) to predict the cumulative exposure to these lipids during early adulthood (age 18-40 years) and the associated atherosclerotic cardiovascular disease (ASCVD) risk after age 40 years is not clear. OBJECTIVES: The objectives of this study were to evaluate whether a 1-time measurement of non-HDL-C or LDL-C in a young adult can predict cumulative exposure to these lipids during early adulthood, and to quantify the association between cumulative exposure to non-HDL-C or LDL-C during early adulthood and the risk of ASCVD after age 40 years. METHODS: We included CARDIA (Coronary Artery Risk Development in Young Adults Study) participants who were free of cardiovascular disease before age 40 years, were not taking lipid-lowering medications, and had ≥3 measurements of LDL-C and non-HDL-C before age 40 years. First, we assessed the ability of a 1-time measurement of LDL-C or non-HDL-C obtained between age 18 and 30 years to predict the quartile of cumulative lipid exposure from ages 18 to 40 years. Second, we assessed the associations between quartiles of cumulative lipid exposure from ages 18 to 40 years with ASCVD events (fatal and nonfatal myocardial infarction and stroke) after age 40 years. RESULTS: Of 4,104 CARDIA participants who had multiple lipid measurements before and after age 30 years, 3,995 participants met our inclusion criteria and were in the final analysis set. A 1-time measure of non-HDL-C and LDL-C had excellent discrimination for predicting membership in the top or bottom quartiles of cumulative exposure (AUC: 0.93 for the 4 models). The absolute values of non-HDL-C and LDL-C that predicted membership in the top quartiles with the highest simultaneous sensitivity and specificity (highest Youden's Index) were >135 mg/dL for non-HDL-C and >118 mg/dL for LDL-C; the values that predicted membership in the bottom quartiles were <107 mg/dL for non-HDL-C and <96 mg/dL for LDL-C. Individuals in the top quartile of non-HDL-C and LDL-C exposure had demographic-adjusted HRs of 4.6 (95% CI: 2.84-7.29) and 4.0 (95% CI: 2.50-6.33) for ASCVD events after age 40 years, respectively, when compared with each bottom quartile. CONCLUSIONS: Single measures of non-HDL-C and LDL-C obtained between ages 18 and 30 years are highly predictive of cumulative exposure before age 40 years, which in turn strongly predicts later-life ASCVD events.

Nontraditional Risk Markers for Incident Coronary Artery Calcium Among Persons ≥65 Years of Age.

Background: The initiation of coronary artery calcium (CAC) is an important physiologic milestone associated with increased cardiovascular disease risk. However, traditional risk factors (RF) do not perform well for predicting incident CAC among the 54 million older U.S. adults. Objectives: The authors sought to assess the association between nontraditional cardiovascular disease RF and incident CAC in older persons. Methods: There were 815 MESA (Multi-Ethnic Study of Atherosclerosis) participants ≥65 years of age who had CAC = 0 at Visit 1 and a follow-up CAC scan. Multivariable adjusted Cox hazards ratios (aHR) and C-statistics were calculated to examine the association of nontraditional RF with incident CAC. Results: The mean age was 70.2 years and 67% were women. The median follow-up time to repeat CAC scan was 3.6 years (IQR: 2.6-9.2 years) and 45% of participants developed incident CAC. Albuminuria (aHR: 1.50, 95% CI: 1.07-2.09), carotid plaque (aHR: 1.32, 95% CI: 1.04-1.66), and thoracic aortic calcification (TAC) (aHR: 1.38, 95% CI: 1.10-1.75) were significantly associated with incident CAC, while higher levels of nontraditional RF including apolipoprotein-B, lipoprotein(a), high-sensitivity troponin T, and N-terminal pro-brain natriuretic peptide were not. When added to demographics, albuminuria, carotid plaque, and TAC provided a greater C-statistic improvement (+0.047, P = 0.004) vs all traditional RF combined (+0.033, P = 0.05). Conclusions: Among nontraditional RF and measures of subclinical atherosclerosis, only albuminuria, carotid plaque, and TAC were significantly associated with incident CAC in persons ≥65 years of age. Identification of albuminuria or extracoronary atherosclerosis may help guide the timing of repeat CAC scoring in older persons with baseline CAC = 0.

Epidemiologic Features of Recovery From SARS-CoV-2 Infection.

Importance: Persistent symptoms and disability following SARS-CoV-2 infection, known as post-COVID-19 condition or "long COVID," are frequently reported and pose a substantial personal and societal burden. Objective: To determine time to recovery following SARS-CoV-2 infection and identify factors associated with recovery by 90 days. Design, Setting, and Participants: For this prospective cohort study, standardized ascertainment of SARS-CoV-2 infection was conducted starting in April 1, 2020, across 14 ongoing National Institutes of Health-funded cohorts that have enrolled and followed participants since 1971. This report includes data collected through February 28, 2023, on adults aged 18 years or older with self-reported SARS-CoV-2 infection. Exposure: Preinfection health conditions and lifestyle factors assessed before and during the pandemic via prepandemic examinations and pandemic-era questionnaires. Main Outcomes and Measures: Probability of nonrecovery by 90 days and restricted mean recovery times were estimated using Kaplan-Meier curves, and Cox proportional hazards regression was performed to assess multivariable-adjusted associations with recovery by 90 days. Results: Of 4708 participants with self-reported SARS-CoV-2 infection (mean [SD] age, 61.3 [13.8] years; 2952 women [62.7%]), an estimated 22.5% (95% CI, 21.2%-23.7%) did not recover by 90 days post infection. Median (IQR) time to recovery was 20 (8-75) days. By 90 days post infection, there were significant differences in restricted mean recovery time according to sociodemographic, clinical, and lifestyle characteristics, particularly by acute infection severity (outpatient vs critical hospitalization, 32.9 days [95% CI, 31.9-33.9 days] vs 57.6 days [95% CI, 51.9-63.3 days]; log-rank P < .001). Recovery by 90 days post infection was associated with vaccination prior to infection (hazard ratio [HR], 1.30; 95% CI, 1.11-1.51) and infection during the sixth (Omicron variant) vs first wave (HR, 1.25; 95% CI, 1.06-1.49). These associations were mediated by reduced severity of acute infection (33.4% and 17.6%, respectively). Recovery was unfavorably associated with female sex (HR, 0.85; 95% CI, 0.79-0.92) and prepandemic clinical cardiovascular disease (HR, 0.84; 95% CI, 0.71-0.99). No significant multivariable-adjusted associations were observed for age, educational attainment, smoking history, obesity, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, or elevated depressive symptoms. Results were similar for reinfections. Conclusions and Relevance: In this cohort study, more than 1 in 5 adults did not recover within 3 months of SARS-CoV-2 infection. Recovery within 3 months was less likely in women and those with preexisting cardiovascular disease and more likely in those with COVID-19 vaccination or infection during the Omicron variant wave.

Fatherhood and Cardiovascular Health, Disease, and Mortality: Associations From the Multi-Ethnic Study of Atherosclerosis.

Introduction: Emerging literature links fatherhood to men's health but lacks comprehensive assessment of health outcomes, especially among multiethnic populations. This study's objective was to evaluate the associations of fatherhood (age at onset and status) with cardiovascular health scores, incident cardiovascular disease, cardiovascular disease death, and all-cause mortality, examining differences by race/ethnicity. Methods: The study sample included men from Multi-Ethnic Study of Atherosclerosis, prospective cohort study that enrolled adults aged 45-84 years without known cardiovascular disease at baseline. Cardiovascular health was defined using the American Heart Association's Life's Essential 8 scores (0-100), excluding sleep (cardiovascular health score). Results: In this sample of 2,814 men, mean age at cardiovascular health assessment was 62.2 years, 82% were fathers, 24% self-identified as Black, 13% self-identified Chinese, 22% self-identified Hispanic, and 41% self-identified White. Fathers who were aged <20 years and 20-24 years at their oldest child's birth had worse overall cardiovascular health than fathers who were aged >35 years (adjusted mean score of 61.1 vs 64.7 [p=0.01] and 61.0 vs 64.7 [p<0.001], respectively). Fathers had worse overall cardiovascular health (adjusted mean score of 63.2 vs 64.7, p=0.03) and more nicotine exposure (63.1 vs 66.6, p=0.04) than nonfathers. In age-adjusted models, fathers overall (hazard ratio=0.82; 95% CI=0.69, 0.98) and Black fathers (hazard ratio=0.73; 95% CI=0.53, 0.999) had a lower rate of all-cause mortality rate than nonfathers, but these associations were no longer significant in fully adjusted models. Conclusions: Fatherhood is a social determinant of health, and understanding its influence may provide opportunities to improve men's health, particularly among men of color.

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 blood pressure (BP) trajectories. METHODS: Baseline CVH (defined by 7 of the American Heart Association's [AHA] 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 systolic blood pressure [SBP] and diastolic blood pressure [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 the primordial prevention of hypertension.

Longitudinal associations of screen time, physical activity, and sleep duration with body mass index in U.S. youth.

BACKGROUND: Youth use different forms of screen time (e.g., streaming, gaming) that may be related to body mass index (BMI). Screen time is non-independent from other behaviors, including physical activity and sleep duration. Statistical approaches such as isotemporal substitution or compositional data analysis (CoDA) can model associations between these non-independent behaviors and health outcomes. Few studies have examined different types of screen time, physical activity, and sleep duration simultaneously in relation to BMI. METHODS: Data were baseline (2017-2018) and one-year follow-up (2018-2019) from the Adolescent Brain Cognitive Development Study, a multi-site study of a nationally representative sample of U.S. youth (N = 10,544, mean [SE] baseline age = 9.9 [0.03] years, 48.9% female, 45.4% non-White). Participants reported daily minutes of screen time (streaming, gaming, socializing), physical activity, and sleep. Sex-stratified models estimated the association between baseline behaviors and follow-up BMI z-score, controlling for demographic characteristics, internalizing symptoms, and BMI z-score at baseline. RESULTS: In females, isotemporal substitution models estimated that replacing 30 min of socializing (ß [95% CI] = -0.03 [-0.05, -0.002]), streaming (-0.03 [-0.05, -0.01]), or gaming (-0.03 [-0.06, -0.01]) with 30 min of physical activity was associated with a lower follow-up BMI z-score. In males, replacing 30 min of socializing (-0.03 [-0.05, -0.01]), streaming (-0.02 [-0.03, -0.01]), or gaming (-0.02 [-0.03, -0.01]) with 30 min of sleep was associated with a lower follow-up BMI z-score. In males, replacing 30 min of socializing with 30 min of gaming was associated with a lower follow-up BMI z-score (-0.01 [-0.03, -0.0001]). CoDA estimated that in males, a greater proportion of time spent in baseline socializing, relative to the remaining behaviors, was associated with a higher follow-up BMI z-score (0.05 [0.02, 0.08]). In females, no associations between screen time and BMI were observed using CoDA. CONCLUSIONS: One-year longitudinal associations between screen time and BMI may depend on form of screen time, what behavior it replaces (physical activity or sleep), and participant sex. The alternative statistical approaches yielded somewhat different results. Experimental manipulation of screen time and investigation of biopsychosocial mechanisms underlying the observed sex differences will allow for causal inference and can inform interventions.

Multimorbidity trajectories in early adulthood and middle age: Findings from the CARDIA prospective cohort study.

Background: Multimorbidity research has focused on the prevalence and consequences of multimorbidity in older populations. Less is known about the accumulation of chronic conditions earlier in the life course. Methods: We identified patterns of longitudinal multimorbidity accumulation using 30 years of data from in-person exams, annual follow-ups, and adjudicated end-points among 4,945 participants of the Coronary Artery Risk Development in Young Adults (CARDIA) study. Chronic conditions included arthritis, asthma, atrial fibrillation, cancer, end stage renal disease, chronic obstructive pulmonary disease, coronary heart disease, diabetes, heart failure, hyperlipidemia, hypertension, and stroke. Trajectory patterns were identified using latent class growth curve models. Results: Mean age (SD) at baseline (1985-6) was 24.9 (3.6), 55% were female, and 51% were Black. The median follow-up was 30 years (interquartile range 25-30). We identified six trajectory classes characterized by when conditions began to accumulate and the rapidity of accumulation: (1) early-fifties, slow, (2) mid-forties, fast, (3) mid-thirties, fast, (4) late-twenties, slow, (5) mid-twenties, slow, and (6) mid-twenties, fast. Compared with participants in the early-fifties, slow trajectory class, participants in mid-twenties, fast were more likely to be female, Black, and currently smoking and had a higher baseline mean waist circumference (83.6 vs. 75.6 cm) and BMI (27.0 vs. 23.4 kg/m2) and lower baseline physical activity (414.1 vs. 442.4 exercise units). Conclusions: A life course approach that recognizes the heterogeneity in patterns of accumulation of chronic conditions from early adulthood into middle age could be helpful for identifying high risk subgroups and developing approaches to delay multimorbidity progression.

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.

Association Between Young Adult Characteristics and Blood Pressure Trajectories.

BACKGROUND: Blood pressure (BP) trajectories from young adulthood through middle age are associated with cardiovascular risk. We examined the associations of hypertension risk factors with BP trajectories among a large diverse sample. METHODS AND RESULTS: We analyzed data from young adults, aged 18 to 39 years, with untreated BP <140/90 mm Hg at baseline from Kaiser Permanente Southern California (N=355 324). We used latent growth curve models to identify 10-year BP trajectories and to assess the associations between characteristics in young adulthood and BP trajectories. We identified the following 5 distinct systolic BP trajectories, which appeared to be determined mainly by the baseline BP with progressively higher BP at each year: group 1 (lowest BP trajectory, 7.9%), group 2 (26.5%), group 3 (33.0%), group 4 (25.4%), and group 5 (highest BP trajectory, 7.3%). Older age (adjusted odds ratio for 30-39 versus 18-29 years, 1.23 [95% CI, 1.18-1.28]), male sex (13.38 [95% CI, 12.80-13.99]), obesity (body mass index ≥30 versus 18.5-24.9 kg/m2, 14.81 [95% CI, 14.03-15.64]), overweight (body mass index 25-29.9 versus 18.5-24.9 kg/m2, 3.16 [95% CI, 3.00-3.33]), current smoking (1.58 [95% CI, 1.48-1.67]), prediabetes (1.21 [95% CI, 1.13-1.29]), diabetes (1.60 [95% CI, 1.41-1.81]) and high low-density lipoprotein cholesterol (≥160 versus <100 mg/dL, 1.52 [95% CI, 1.37-1.68]) were associated with the highest BP trajectory (group 5) compared with the reference group (group 2). CONCLUSIONS: Traditional hypertension risk factors including smoking, diabetes, and elevated lipids were associated with BP trajectories in young adults, with obesity having the strongest association with the highest BP trajectory group.

Comparison of Cardiovascular Health Profiles Across Population Surveys From 5 High- to Low-Income Countries.

Background: To facilitate the shift from risk-factor management to primordial prevention of cardiovascular disease, the American Heart Association developed guidelines to score and track cardiovascular health (CVH). How the prevalence and trajectories of a high level of CVH across the life course compare among high- and lower-income countries is unknown. Methods: Nationally representative survey data with CVH variables (physical activity, cigarette smoking, body mass index, blood pressure, blood glucose, and total cholesterol levels) were identified in Ethiopia, Bangladesh, Brazil, England, and the US for adults (aged 18-69 years and not pregnant). Data were harmonized, and CVH metrics were scored using the American Heart Association guidelines, as high (2), moderate (1), or low (0), with the prevalence of high scores (better CVH) across the life course compared across countries. Results: Among 28,092 adults (Ethiopia n = 7686, 55.2% male; Bangladesh n = 6731, 48.4% male; Brazil n = 7241, 47.9% male; England n = 2691, 49.5% male, and the US n = 3743, 50.3% male), the prevalence of high CVH scores decreased as country income level increased. Declining CVH with age was universal across countries, but differences were already observable in those aged 18 years. Excess body weight appeared to be the main driver of poor CVH in higher-income countries, and the prevalence of current smoking was highest in Bangladesh. Conclusions: Our findings suggest that CVH decline with age may be universal. Interventions to promote and preserve CVH throughout the life course are needed in all populations, tailored to country-specific time courses of the decline. In countries where the level of CVH remains relatively high, protection of whole societies from risk-factor epidemics may still be feasible.

Contexte: Afin de faciliter la transition de la prise en charge des facteurs de risque vers la prévention primordiale des maladies cardiovasculaires, l'American Heart Association a élaboré des lignes directrices en vue de mesurer la santé cardiovasculaire (SCV) et d'en faire le suivi. On ignore dans quelle mesure la prévalence et la trajectoire d'un niveau élevé de SCV au cours d'une vie se comparent entre les pays à revenu élevé et les pays à plus faible revenu. Méthodologie: Des résultats de sondages représentatifs des pays concernant les variables de la SCV (activité physique, tabagisme, indice de masse corporelle, pression artérielle, glycémie et taux de cholestérol total) ont été obtenus de l'Éthiopie, du Bangladesh, du Brésil, de l'Angleterre et des États-Unis, pour des adultes âgés de 18 à 69 ans, excluant les femmes enceintes. Les données ont été harmonisées, et la SCV a été mesurée conformément aux lignes directrices de l'American Heart Association, et notée en fonction des scores suivants : élevée (2), modérée (1) ou faible (0). La prévalence de scores élevés, soit une meilleure SCV tout au long de la vie, a été comparée entre les pays. Résultats: Parmi 28 092 adultes (Éthiopie, n = 7 686, 55,2 % de sexe masculin; Bangladesh, n = 6 731, 48,4 % de sexe masculin; Brésil, n = 7 241, 47,9 % de sexe masculin; Angleterre, n = 2 691, 49,5 % de sexe masculin, et États-Unis, n = 3 743, 50,3 % de sexe masculin), la prévalence de scores correspondant à une SCV élevée diminuait à mesure que le niveau de revenu du pays augmentait. La diminution de la SCV avec l'âge était universelle dans tous les pays, mais des différences étaient déjà observables chez les personnes âgées de 18 ans. Un surplus de poids corporel semblait être le principal facteur d'une faible SCV dans les pays à revenu plus élevé; la prévalence d'un tabagisme actuel était la plus élevée au Bangladesh. Conclusions: Nos observations laissent croire que le déclin de la SCV avec l'âge pourrait être universel. Il est nécessaire de mener des interventions adaptées à la progression du déclin dans chacun des pays en vue de favoriser et de préserver la SCV tout au long de la vie, et ce, dans toutes les populations. Dans les pays où le niveau de SCV demeure relativement élevé, il pourrait être encore possible de protéger des sociétés entières contre des épidémies liées aux facteurs de risque.

Social and psychosocial determinants of racial and ethnic differences in cardiovascular health: The MASALA and MESA studies.

Background: Social and psychosocial determinants are associated with cardiovascular health (CVH). Objectives: To quantify the contributions of social and psychosocial factors to racial/ethnic differences in CVH. Methods: In the Multi-Ethnic Study of Atherosclerosis and Mediators of Atherosclerosis in South Asians Living in America cohorts, Kitagawa-Blinder-Oaxaca decomposition quantified the contributions of social and psychosocial factors to differences in mean CVH score (range 0-14) in Black, Chinese, Hispanic, or South Asian compared with White participants. Results: Among 7,978 adults (mean age 61 [SD 10] years, 52 % female), there were 1,892 Black (mean CVH score for decomposition analysis 7.96 [SD 2.1]), 804 Chinese (CVH 9.69 [1.8]), 1,496 Hispanic (CVH 8.00 [2.1]), 1,164 South Asian (CVH 9.16 [2.0]), and 2,622 White (CVH 8.91 [2.1]) participants. The factors that were associated with the largest magnitude of explained differences in mean CVH score were income for Black participants (if mean income in Black participants were equal to White participants, Black participants' mean CVH score would be 0.14 [SE 0.05] points higher); place of birth for Chinese participants (if proportion of US-born and foreign-born individuals among Chinese adults were equivalent to White participants, Chinese participants' mean CVH score would be 0.22 [0.10] points lower); and education for Hispanic and South Asian participants (if educational attainment were equivalent to White participants, Hispanic and South Asian participants' mean CVH score would be 0.55 [0.11] points higher and 0.37 [0.11] points lower, respectively). Conclusions: In these multiethnic US cohorts, social and psychosocial factors were associated with racial/ethnic differences in CVH.