This dataset documents rates and trends in heart disease and stroke mortality. Specifically, this report presents county (or county equivalent) estimates of heart disease and stroke death rates in 2000-2019 and trends during two intervals (2000-2010, 2010-2019) by age group (ages 35–64 years, ages 65 years and older), race/ethnicity (non-Hispanic American Indian/Alaska Native, non-Hispanic Asian/Pacific Islander, non-Hispanic Black, Hispanic, non-Hispanic White), and sex (women, men). The rates and trends were estimated using a Bayesian spatiotemporal model and a smoothed over space, time, and demographic group. Rates are age-standardized in 10-year age groups using the 2010 US population. Data source: National Vital Statistics System.

Financial overview and grant giving statistics of American Heart Association

This dataset documents rates and trends in local coronary heart disease (CHD) and stroke death rates. Specifically, this report presents county (or county equivalent) estimates of stroke and CHD death rates in 1999-2018 and trends during three intervals (1999-2005, 2005-2011, 2011-2018) by age group (ages 35–64 and 65 and older). The rates and trends were estimated using a Bayesian spatiotempotal model and a smoothed over space, time, and age group. Rates are age-standardized. Data source: National Vital Statistics System.

2014 to 2016, 3-year average. Rates are age-standardized. County rates are spatially smoothed. The data can be viewed by gender and race/ethnicity. Data source: National Vital Statistics System. Additional data, maps, and methodology can be viewed on the Interactive Atlas of Heart Disease and Stroke http://www.cdc.gov/dhdsp/maps/atlas

The classification into well-documented and modifiable risk factors versus less well-documented or potentially modifiable risk factors is adopted from the guidelines.

Model 1 was a single-factor analysis model; model 2 was adjusted for age, gender, alcohol consumption, income, education and history of cardiovascular disease on the basis of model 1; model 3 was further adjusted for heart rate, uric acid, and high-sensitivity CRP on the basis of model 2.CVH score, Cardiovascular Health Score; HR, hazard ratio; CI, confidence interval.Hazard Ratios (95% CI) of Incidence of Total CVD Events, Myocardial Infarction, and Stroke among Different Groups According to the CVH Score at Baseline.

AHA  =  American Heart Association, ACC  =  American College of Cardiology EF  =  ejection fraction, LV  =  left ventricle, LVESV  =  left ventricular end systolic volume, LVEDV  =  left ventricular end diastolic volume, SV  =  stroke volume.Statistical comparison of parameters from the patient data for each American Heart Association/American College of Cardiology heart failure stage, using 2-tailed Student's T-Test.

2015 to 2017, 3-year average. Rates are age-standardized. County rates are spatially smoothed. The data can be viewed by gender and race/ethnicity. Data source: National Vital Statistics System. Additional data, maps, and methodology can be viewed on the Interactive Atlas of Heart Disease and Stroke http://www.cdc.gov/dhdsp/maps/atlas

Background: Postmenopausal hormone therapy (HT) increases the risk of stroke. Here we evaluate whether leisure time physical activity (LTPA) can change stroke risk in women using HT, leveraging data from the California Teachers Study. Methods: Female California educators without a prior history of stroke (n = 118,294) were followed from 1995 through 2015 for stroke end points. Based on statewide hospitalization data, 4,437 women had ischemic (n = 3,162; International Classification of Diseases [ICD]-9 433, 434, 436) or hemorrhagic (n = 1,275; ICD-9 430–432, excluding 432.1) stroke. LTPA and HT use were evaluated at 2 time points (baseline [1995–1996] and 10-year follow-up [2005–2006]). LTPA was assessed using American Heart Association (AHA) recommendations (>150 min/week moderate or >75 min/week strenuous physical activity). Using multivariable Cox proportional hazards models, we estimated the hazard ratios (HRs) and 95% CIs for the associations between HT use and concurrent LTPA with incident stroke. Results: Compared to women who never used HT, stroke risk was highest among women who were current HT users and did not meet AHA recommendations for LTPA at the time of their HT use: HRbaseline 1.28 (95% CI 1.13–1.44); HR10-year follow-up 1.17 (95% CI 0.91–1.50). Based on the baseline questionnaire, current HT users who met AHA recommendations for LTPA in 1995–1996 still had elevated stroke risk in the 20-year follow-up (HR 1.22, 95% CI 1.08–1.37). However, among current HT users who met AHA recommendations for LTPA at the 2005–2006 follow-up questionnaire, stroke risk was not elevated (HR 1.01, 95% CI 0.80–1.29). Evaluation of the 2 time points in concert further demonstrated that meeting AHA recommendations for LTPA at the most recent follow-up time point was required to reduce HT-related stroke risk. Conclusion: Concurrent physical activity may attenuate the short-term increase in risk of stroke risk associated with HT use.

2016 to 2018, 3-year average. Rates are age-standardized. County rates are spatially smoothed. The data can be viewed by gender and race/ethnicity. Data source: National Vital Statistics System. Additional data, maps, and methodology can be viewed on the Interactive Atlas of Heart Disease and Stroke http://www.cdc.gov/dhdsp/maps/atlas

The American Heart Association/American College of Cardiology Heart Failure classification From Jessup et al. (2009) [4].

2013 to 2015, 3-year average. Rates are age-standardized. County rates are spatially smoothed. The data can be viewed by gender and race/ethnicity. Data source: National Vital Statistics System. Additional data, maps, and methodology can be viewed on the Interactive Atlas of Heart Disease and Stroke http://www.cdc.gov/dhdsp/maps/atlas

BackgroundLimited data exist regarding cardiac manifestations of Chagas disease in migrants living in non-endemic regions.MethodsA retrospective cohort analysis of 109 patients with Chagas disease seen at Boston Medical Center (BMC) between January 2016 and January 2023 was performed. Patients were identified by screening and testing migrants from endemic regions at a community health center and BMC. Demographic, laboratory, and cardiac evaluation data were collected.ResultsMean age of the 109 patients was 43 years (range 19–76); 61% were female. 79% (86/109) were diagnosed with Chagas disease via screening and 21% (23/109) were tested given symptoms or electrocardiogram abnormalities. Common symptoms included palpitations (25%, 27/109) and chest pain (17%, 18/109); 52% (57/109) were asymptomatic. Right bundle branch block (19%, 19/102), T-wave changes (18%, 18/102), and left anterior fascicular block (11%, 11/102) were the most common electrocardiogram abnormalities; 51% (52/102) had normal electrocardiograms. Cardiomyopathy stage was ascertained in 94 of 109 patients: 51% (48/94) were indeterminate stage A and 49% (46/94) had cardiac structural disease (stages B1-D). Clinical findings that required clinical intervention or change in management were found in 23% (25/109), and included cardiomyopathy, apical hypokinesis/aneurysm, stroke, atrial or ventricular arrhythmias, and apical thrombus.ConclusionsThese data show high rates of cardiac complications in a cohort of migrants living with Chagas disease in a non-endemic setting. We demonstrate that Chagas disease diagnosis prompts cardiac evaluation which often identifies actionable cardiac disease and provides opportunities for prevention and treatment.

CRDC = Chart Review, Diagnostic Criteria–the charts of potential cases were reviewed, and a formal set of diagnostic criteria were applied when evaluating cases; CRMD = Chart Review, Medical Doctor–the charts of potential cases were reviewed by a physician, who evaluated cases using their clinical judgment or an otherwise unspecified set of criteria; AHA = American Heart Association; ASA = American Stroke Association; CABG = coronary artery bypass graft; EMRALD = Electronic Medical Record Administrative Data Linked Database; ICD = International Classification of Diseases; MONICA = MONItoring Trends and Determinants in CArdiovascular Disease; NSAID = non-steroid anti-inflammatory drug; PCI = percutaneous coronary intervention; TOAST = Trial of ORG 10172 in Acute Stroke Treatment; TIA = transient ischaemic attack; WHO = World Health OrganizationCharacteristics of Included Studies.

Background: The recent American College of Cardiology/American Heart Association (ACC/AHA) guidelines redefined blood pressure levels 130-139/80-89 mmHg as stage 1 hypertension. However, the association of stage 1 hypertension with cardiovascular disease (CVD) and its age-specific differences among the rural women in Liaoning province remains unclear. It needs to be quantified in considering guideline adoption in China.Methods: In total, 19,374 women aged ≥35 years with complete data and no cardiovascular disease at baseline were followed in a rural community-based prospective cohort study of Liaoning province, China. Follow-up for the new cases of CVD was conducted from the end of the baseline survey to the end of the third follow-up survey (January 1, 2008–December 31, 2017). Adjusted Cox proportional hazards models were applied to estimate the Hazard Ratios (HR) and 95% Confidence Intervals (CI) with the normal blood pressure as a reference.Results: During the median follow-up period of 12.5 years, 1,419 subjects suffered all-cause death, 748 developed CVD, 1,224 participants suffered stroke and 241 had Myocardial Infarction (MI). Compared with normal BP, Stage 1 hypertension had a HR (95% CI) of 1.694 (1.202–2.387) in CVD mortality, 1.575 (1.244–1.994) in the incidence of stroke. The results obtained that the risk of CVD mortality and incidence of stroke was significantly associated with stage 1 hypertension in rural women aged ≥45 years after adjusting for other potential factors. However, in participants aged 35–44 years, stage 1 hypertension was not associated with an increased risk of cardiovascular disease.Conclusions: The newly defined stage 1 hypertension is associated with an increased risk of CVD mortality and also incidence of stroke in the rural women aged ≥45 years population of Liaoning province. This study can be a good reference for health policy makers and clinicians workers to make evidence-based decisions toward lowering burden of cardiovascular disease more efficient, timely measures on prevention and control of stage 1 hypertension in China.

Physical Activity - This indicator shows the number of persons who reported at least 150 minutes of moderate physical activity or at least 75 minutes of vigorous physical activity per week. Physical activity is important to prevent heart disease and stroke, two of the important causes of death in United States. In order to improve overall cardiovascular health, The American Heart Association suggests at least 150 minutes per week of moderate exercise or 75 minutes per week of vigorous exercise. Link to Data Details

ObjectiveTo quantify the association between ideal cardiovascular health (CVH) metrics and incident cardiovascular disease (CVD) including different subtypes [coronary heart disease (CHD), stroke, and sudden death], and all-cause mortality in an Iranian population.MethodsThe study population included 6,388 participants (2,726 men) aged 48.0 ± 12.4 years free of CVD at baseline. We utilized the American Heart Association’s 2020 impact target criteria of ideal, intermediate, and poor CVH. The multivariate Cox proportional Hazard model, adjusted for age, sex, educational level, marital status, and family history of CVD, was applied to estimate the hazard ratio (HR) of outcomes per one additional metric of ideal CVH metrics. Furthermore, the risk was also calculated for ideal and intermediate categories considering poor category as a reference.ResultsDuring the median follow-up of 11.26 years, 692 CVD, 589 CHD, 130 stroke, 111 sudden death, and 519 all-cause mortality events were reported. All of the individual ideal CVH metrics were independent predictors except intermediate physical activity level for CVD, BMI < 25 kg/m2, and intermediate physical activity for all-cause mortality. Each additional metrics of ideal CVH decreased the risk by 31 (0.69, 0.65–0.73) for CVD, 32 (0.68, 0.64–0.73) for CHD, 31 (0.69, 0.60–0.80) for stroke, 25 (0.75, 0.64–0.88) for sudden death, and 13% (0.87, 0.81–0.93) for all-cause mortality events. Moreover, intermediate and ideal categories of CVH metrics were associated with lower risk for different CVD outcomes, i.e., 44 (0.56, 0.48–0.65) and 76% (0.24, 0.17–0.35) for CVD; 43 (0.57, 0.47–0.67) and 75% (0.25, 0.16–0.37) for CHD, 58 (0.42, 0.29–0.61) and 86% (0.14, 0.04–0.44) for stroke; 56 (0.44, 0.29–0.66) and 55% (0.45, 0.21–0.99) for sudden death; and 25 (0.75, 0.62–0.90) and 46% (0.54, 0.37–0.80) for all-cause mortality events, respectively. We also assessed the impact of changes in ideal CVH status from phase III to phase IV (2008–2011) on CVD events among 5,666 participants. Accordingly, compared to those remaining in the poor category, all of the changes in ideal CVH categories showed a lower risk for CVD events.ConclusionAmong the Iranian population, meeting higher ideal CVH metrics is associated with a lower risk of different CVD events and mortality outcomes.

Age-adjusted mortality rates for the contiguous United States in 2000–2005 were obtained from the Wide-ranging Online Data for Epidemiologic Research system of the U.S. Centers for Disease Control and Prevention (CDC) (2015). Age-adjusted mortality rates were weighted averages of the age-specific death rates, and they were used to account for different age structures among populations (Curtin and Klein 1995). The mortality rates for counties with < 10 deaths were suppressed by the CDC to protect privacy and to ensure data reliability; only counties with ≥ 10 deaths were included in the analyses. The underlying cause of mortality was specified using the World Health Organization’s International Statistical Classification of Diseases and Related Health Problems (10th revision; ICD-10). In this study, we focused on the all-cause mortality rate (A00-R99) and on mortality rates from the three leading causes: heart disease (I00-I09, I11, I13, and I20-I51), cancer (C00-C97), and stroke (I60- I69) (Heron 2013). We excluded mortality due to external causes for all-cause mortality, as has been done in many previous studies (e.g., Pearce et al. 2010, 2011; Zanobetti and Schwartz 2009), because external causes of mortality are less likely to be related to environmental quality. We also focused on the contiguous United States because the numbers of counties with available cause-specific mortality rates were small in Hawaii and Alaska. County-level rates were available for 3,101 of the 3,109 counties in the contiguous United States (99.7%) for all-cause mortality; for 3,067 (98.6%) counties for heart disease mortality; for 3,057 (98.3%) counties for cancer mortality; and for 2,847 (91.6%) counties for stroke mortality. The EQI includes variables representing five environmental domains: air, water, land, built, and sociodemographic (2). The domain-specific indices include both beneficial and detrimental environmental factors. The air domain includes 87 variables representing criteria and hazardous air pollutants. The water domain includes 80 variables representing overall water quality, general water contamination, recreational water quality, drinking water quality, atmospheric deposition, drought, and chemical contamination. The land domain includes 26 variables representing agriculture, pesticides, contaminants, facilities, and radon. The built domain includes 14 variables representing roads, highway/road safety, public transit behavior, business environment, and subsidized housing environment. The sociodemographic environment includes 12 variables representing socioeconomics and crime. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files. This dataset is associated with the following publication: Jian, Y., L. Messer, J. Jagai, K. Rappazzo, C. Gray, S. Grabich, and D. Lobdell. Associations between environmental quality and mortality in the contiguous United States 2000-2005. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 125(3): 355-362, (2017).

Abstract Background The association between ideal cardiovascular health (ICVH) status and atrial fibrillation or flutter (AFF) diagnosis has been less studied compared to other cardiovascular diseases. Objective To analyze the association between AFF diagnosis and ICVH metrics and scores in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Methods This study analyzed data from 13,141 participants with complete data. Electrocardiographic tracings were coded according to the Minnesota Coding System, in a centralized reading center. ICVH metrics (diet, physical activity, body mass index, smoking, blood pressure, fasting plasma glucose, and total cholesterol) and scores were calculated as proposed by the American Heart Association. Crude and adjusted binary logistic regression models were built to analyze the association of ICVH metrics and scores with AFF diagnosis. Significance level was set at 0.05. Results The sample had a median age of 55 years and 54.4% were women. In adjusted models, ICVH scores were not significantly associated with prevalent AFF diagnosis (odds ratio [OR]:0.96; 95% confidence interval [95% CI]:0.80-1.16; p=0.70). Ideal blood pressure (OR:0.33; 95% CI:0.15–0.74; p=0.007) and total cholesterol (OR:1.88; 95% CI:1.19–2.98; p=0.007) profiles were significantly associated with AFF diagnosis. Conclusions No significant associations were identified between global ICVH scores and AFF diagnosis after multivariable adjustment in our analyses, at least partially due to the antagonistic associations of AFF with blood pressure and total cholesterol ICVH metrics. Our results suggest that estimating the prevention of AFF burden using global ICVH scores may not be adequate, and ICVH metrics should be considered in separate.