Abstract only Introduction: Less than 10% of U.S. adults meet the guidelines for whole grains, fruits, and vegetables each day. The Healthy for Life community-based program aims to change confidence ...and health behaviors, by equipping individuals with new skills for healthy living. As a result of the COVID-19 pandemic in 2020 and 2021, the program pivoted from in-person to a virtual implementation model. This required more advanced planning due to additional logistics to ensure a skills-based learning environment. Objectives: To examine the effectiveness of the Healthy for Life program over time, specifically: o Changes in participant confidence in the preparation of healthy foods at home o Changes in participant consumption of fruits, vegetables, and whole grains o Changes in participant frequency of healthy shopping habits Methods: A community engagement program was implemented and evaluated in 17 community centers in 2020-2021 to measure changes in participant confidence to prepare healthy meals at home, consumption of fruits, vegetables and whole grains, and frequency of healthy shopping habits. Community center facilitators administered the same pre/post survey to participants at the first educational experience, and then again at the final experience. Facilitators entered the participant data into an online survey portal. Analysis was conducted with 235 participants who completed both pre and post surveys. Two-way repeated ordinal regression was used to assess changes in key metrics over time. Results: Participants were predominately female (90.6%), about two-thirds (65.2%) were between 25-55 years old, and most identified as non-Hispanic White/Caucasian (42.6%) or Black/African American (35.7%). Close to half (45.9%) of participants had a college degree or higher, over a quarter (28.1%) received benefits from SNAP and/or WIC, and more than two-thirds (63.8%) indicated they are the only person in their household preparing meals. Almost half (49.3%) of respondents attended the suggested minimum of 4 educational experiences. On average, respondents statistically significantly increased their daily fruit & vegetable consumption by 1.21 serving(s). In addition, over one-third (34%) of respondents increased their level of confidence to prepare healthy meals at home and (37%) respondents increased their level of confidence to substitute healthier cooking and food preparation methods. Close to half (47.2%) respondents reported increased frequency of reading food labels and checking the nutritional values when purchasing food. Conclusions: Despite the shift to virtual implementation, the Healthy for Life community education program, was still effective in improving participant confidence and dietary behaviors over time. However, additional research studies are required to further assess whether virtual implementation of this type of intervention will continue to be effective.
The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk ...factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).
The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.
Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.
The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk ...factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).
The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.
Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.
The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
Abstract only Introduction: Support of patients with cardiovascular (CV) disease and stroke is often associated with improved health-related quality of life (HRQOL). Hypothesis: We assessed the ...hypothesis that change in patient HRQOL, perception of emotional and informational support, and satisfaction with the American Heart Association/American Stroke Association’s (AHA/ASA) online Support Network (SN) would be observed from before joining the SN to two months after joining the SN. Methods: Using a pre/post-test design, between April 2018 and March 2020, 2,542 adult patients completed a baseline online survey, of whom 412 completed a survey two months later (response rate=16%). Self-report instruments included: Patient Reported Outcomes Measurement Information System (PROMIS) Global Health Questionnaire, Emotional Support (ES), Informational Support (IS), and an AHA/ASA-developed measure of satisfaction with the SN. After converting raw scores into T-scores, linear mixed effects models were used to compare pre and post T-scores. Results: Patients were on average 56± 12.8 years of age, female (63.3%), non-Hispanic White (76.5%), married (58.3%), employed (49.8%), and >high school education (85.0%). 83.5% reported having a CV condition, most commonly hypertension (38.8%), myocardial infarction (31.3%), high cholesterol (31.1%), atrial fibrillation (25.2%); 58.0% reported ≤ 4 co-morbidities. T-scores (mean±SD) did not differ significantly from before to two months after joining the SN: physical health domain (pre=39.2±3.6, post=39.3±3.4) and mental health domain (pre=43.3±9.6, post=44.5±9.7); ES (pre=49.5±9.8, post=49.3±9.8), and IS (pre=49.8±10.3, post=50.5±10.5). At two months, satisfied, neutral, and dissatisfied with SN were 46.3%,44.2%, and 5.1% respectively. 61.5% were likely to recommend the SN to others. Conclusions: In conclusion, HRQOL measures remained stable. Before and after SN participation, physical and mental domain global health scores were lower than the U.S. general population mean of 50, while ES and IS scores approximated the U.S. general population mean. Satisfaction with the SN was moderate with the majority of respondents likely to recommend to others. Future research might explore extending the timeframe to observe change in global health scores.
Abstract only Introduction: Poor diet is the leading risk factor for death globally. Community-based programs can have a positive impact on promoting healthy dietary attitudes and behaviors. The ...American Heart Association and Aramark’s initiative, Healthy for Life 20 by 20 aims to change food and health confidence and behaviors, equipping individuals with new skills for healthy living. The program includes healthy cooking demonstrations, hands-on skills practice and nutrition and heart health workshops. Objectives: To examine the effectiveness of the Healthy for Life program over time, specifically: -Changes in participant confidence in the preparation of healthy foods at home -Changes in participant consumption of fruits, vegetables, and whole grains -Changes in participant frequency of healthy shopping habits Methods: A community engagement program was implemented and evaluated in 22 community centers. Sessions were focused on enhancement of confidence and behaviors around healthy shopping, cooking and consumption. Two delivery methods were offered: 10 classes over 24 weeks or 4 classes over 8-12 weeks. Community center facilitators administered the same paper survey to participants at the first educational experience, and then again at the final experience or every 3 months following the first educational experience. Results: Analysis was conducted with 418 participants to measure change in healthy behaviors and confidence over time. Participants were predominately female (83%), 55 or older (55.9%), African American (68.4%) and non-Hispanic (81.6%). About half (44.7%) had a college degree or higher, nearly a fifth (17.9%) received benefits from SNAP and almost half (48.3%) indicated they are the only person in their household preparing meals. Almost half (42%) of respondents attended 4 or more educational experiences. On average, respondents statistically significantly increased their daily fruit & vegetable consumption by .43 serving(s). After taking classes, 119 of 394 (30.2%) respondents increased their level of confidence to prepare healthy meals at home and 128 of 379 (33.8%) respondents increased their level of confidence to substitute healthier cooking and food preparation methods. Similarly, 120 of 385 (31.2%) respondents reported increased frequency of reading food labels and checking the nutritional values when purchasing food. Conclusions: The Healthy for Life community program involving a skills-based format can be an effective health promotion model in improving confidence and dietary behaviors over time. However, additional research studies are required to further assess the long-term health impacts of this type of intervention.
Abstract only Background: Growing evidence exists indicate that subjective perceptions of well-being (i.e. life satisfaction) are favorably associated with overall health status. Few reports are ...available that explore this association in nationally representative samples of US adults. Methods: Data from were collected from 115,929 US adults (18+ y) from all 50 states via dual mail and web-based sampling through the 2018 Gallup National Health and Well-Being Survey. Well-being was assessed by asking individuals to place themselves on a 10-step ladder with ‘worst possible life’ representing the lowest rung and ‘best possible life’ the top rung; ratings were collected for both their current life and their life in 5 years. Based on both current and future life ratings, individuals were categorized as thriving, struggling, or suffering. General health status was assessed based 5 options (excellent to poor). Results: Significant positive trends were observed between current and future levels of life satisfaction with ratings of general health status after accounting for age, sex, education, an income (p<0.001 and p<0.001, respectively) (Figure 1). Similarly, the proportion of adults categorized as “Thriving” was higher across more favorable levels of general health status. Conclusions: Level of well-being assessed by subjective rating of life satisfaction is strongly, positively, and independently associated with perception of general health status in a large sample of US adults. These results may demonstrate the strong influence of well-being on the preservation of health, however, further prospective examination of these associations are warranted.
Abstract only
Introduction:
The American Heart Association Get With the Guidelines - Coronary Artery Disease (GWTG-CAD) Registry is a quality improvement program with over 2600 participating U.S. ...hospitals. Among the collected data elements is the yes-no variable “Heart failure documented on First Medical Contact” (HF-FMC), an important clinical predictor of in-hospital mortality. Before 2018, the missing rate of HF-FMC exceeded 60% in some years, significantly limiting its utility as a predictor of in-hospitality mortality. We compared machine learning (ML)-based with traditional statistical methods to accurately impute missing HF-FMC values.
Methods:
We utilized admission records from the GWTG CAD Registry data from 2018 to 2021, including both STEMI and NSTEMI patients. We removed missing HF-FMC, using complete data as ground truth. The data was split into training and test datasets in a 3:1 ratio. Imputation was framed as a prediction task. For evaluation, we masked HF-FMC in the test set and compared the imputed values against the ground truth. For traditional methods, mode imputation, K-nearest neighbor imputer (KNN), and Multiple Imputation by Chained Equations (MICE) were applied. For ML models, we applied logistic regression, random forest and XGBoost. Shapley Additive exPlanations (SHAP) values were utilized to identify key features contributing to the ML models.
Results:
The study included 223,074 individuals (12.2% HF-FMC = “yes”), with mean (SD) age 64.9 (13.4) years (33.8% Female; and 77.3% White and 13.8% Black). Machine Learning models achieved higher AUROC scores compared to traditional models in imputing HF-FMC (Table 1). Top features for predicting HF-FMC are shown (Figure 1).
Conclusions:
Machine learning models outperformed traditional methods in imputing missing HF-FMC, a critical predictor of in-hospital mortality. SHAP values can identify key features in imputing clinically important variables with high degree of missingness.
Abstract only Nicotine, present in combustible cigarettes, is a strong sympathomimetic drug, and many of the cardiovascular and metabolic effects of smoking have been linked to increases in ...catecholamine production. However, it is not known whether vaping also leads to an increased catecholamine formation. Therefore, we measured the urinary catecholamines and their metabolites associated with vaping and smoking, or no tobacco use. Healthy adults 18-45 yoa who use tobacco products were asked to vape for every 30sec for 10min, smoke 1 cigarette, or inhale through a straw (sham) prior to providing urine samples three times: before tobacco use (T0), one hour (T1), and two hours (T2) after tobacco exposure. Catecholamines and their metabolites were measured in urine samples containing internal standards analyzed on a LC/MS/MS. Participants were categorized by the product used at the study visit: combustible cigarettes (n=70), e-cigarette (n=171), or sham use of a straw (n=82). Log transformed catecholamines and metabolites, normalized to urinary creatinine, were compared among each tobacco use group. Generalized linear models were used to estimate the associations between the outcomes and tobacco product use at each time point, adjusting for age, race and sex seen in table 1. At T0, smoking was associated with lower metanephrine, 5-hydroxindole-3-acetic acid, and vanillymandelic acid. At T1, after vaping normetanephrine and 3-methoxytyramine, epinephrine and homovanillic acid were higher. After smoking, norepinephrine, dopamine, normetnephrine, epinephrine and homovanillic acid were higher at T1. Whereas at T2 there was lower 5-hydroxindole-3-acetic acid in e-cigarette users. Our findings that both vaping and smoking are associated with increased urinary catecholamines or their metabolites, suggesting that the use of either product could elevate CVD risk due to repeated sympathetic stimulation. Catecholamines could be useful as a biomarker of harm for tobacco use.
Abstract only Background: Data visualization (DV) is a creative method to depict data and convey the underlying meaning of analytical results. Effective and interactive DV includes integrating, ...unifying, and standardizing data from different sources, allowing users to directly modify the style and outcome of the results to create visual access of big data in simple ingestible pieces. Such freedom to users brings substantial enhancements in productivity and practicality of complex surveillance data. Well-designed interactive DV also increases value gained from data and analytics. The American Heart Association’s (AHA) Center for Heath Metrics and Evaluation (CHME) has developed resources and tools for DV of surveillance data. The purpose of this study is to illustrate the processes of data analyses and visualizations of national surveillance data. Methods: This study introduces the different surveillance data, describes the concept, analytic approaches, and demonstrates the visualization platforms. The National Health and Nutrition Examination Survey (NHANES) data from 1999 - 2016 and Compressed Mortality data from the CDC (Centers for Disease Control and Prevention) WONDER, which included mortality by 15 underlying causes of cardiovascular diseases using ICD-10 from 1999 to 2017, were used to apply DV methods and tools for programming and creating interactive dashboards depicting trends in key cardiovascular health indices. Data were extracted, cleaned, and merged using SAS 9.4. Final estimates were calculated using SUDAAN 11 for weighting, imputing, and analyzing. Tableau 18.2 was used to share an interactive visualization of the analyzed data. Results: The CHME DV resources offer a variety of options to help parse and understand the significance of key health indicator data by placing it in a visual context. Using the NHANES and CDC Wonder datasets we developed interactive dashboards and a visualization platform depicting trends over time in cardiovascular metrics such as AHA’s Life’s Simple 7 indices of Blood Pressure, Blood Sugar, Cholesterol, Physical Activity, Diet, Body Weight, and Smoking. Trends in cardiovascular disease mortality in the United States were also developed. A visualization platform has been imbedded into the AHA CHME website for a wide variety of stakeholders, such as consumers and researchers, to view dashboards and customize products based on their specific needs. Conclusion: Patterns, trends, and associations that may otherwise go undetected or overlooked can be clearly exposed and communicated with an effective DV approach. DV tools comprise an array of resources from simple infographics to interactive dashboards. More interactive visualizations using other data sources, innovative methodologies and tools are needed and being developed by the CHME to present data more interactively enabling users to further understand and leverage data and trends.
Abstract only Background: Cardiovascular diseases (CVD) are ranked as the top health problem in the US. Approximately 1 of 3 deaths results from CVD, which is more than cancer, chronic lower ...respiratory diseases, and accidents combined. Stroke, an important CVD itself, is a foremost cause of serious and long-term disability accounting for more than 50% percent of hospitalized patients for neurological diseases. Access to an efficient healthcare facility can contribute positively to overall population health by effective prognosis and timely care of CVD. This study aimed to evaluate the patterns of healthcare utilization by adults with non-fatal CVD in the United States of America. Method: Cross-sectional survey data from the National Health and Nutrition Examination Surveys (NHANES) 2015-2016 were used for this study. Using highly stratified, multistage probability designs, participants aged 20 years and more within the NHANES 2015-2016 cycle were included in this study. Pregnant women and participants who did not answer questions regarding CVD status were excluded. Participants diagnosed with congestive heart failure or coronary heart disease or angina/angina pectoris, or heart attack, or stroke were defined as having non-fatal CVD. Adults participants utilizing healthcare were those who visited the clinic, doctor’s office, or hospital outpatient department for treatment. Using SAS 9.4 and SUDAAN 11, appropriate age-standardization and tests were performed to assess the difference among races and other demographic variables in relation to healthcare utilization. Results: Of 5621 adults (representing 230.8 million (M) adults), 634 adults representing 18.5 million had self-reported CVD. Age adjusted prevalence of CVD by race/ethnicity was significantly different (p<0.05). African American adults had the highest prevalence of 2.8 M of 26.2 M (10.7%) followed by White adults at 10.8 M of 147.8 M (7.3%), Hispanic adults with 2.6 M of 35.1 M (7.4%). Asian adults had the least prevalence at 0.6 M of 13.4 M (4.5%). Among adults who had non-fatal CVD, healthcare utilization was also found to be significantly different (p<0.05). White adults were on the top of healthcare utilization at 9.7 M of 10.8 M (89.8%) followed by Asian adults at 0.5 M of 0.6 M (83.3%). African American adults ranked third at 2.1 M of 2.8 M (75.0%) and Hispanic adults were on the bottom the list at 1.1 M of 2.6 M (42.3%). Healthcare utilization amongst females was 6.5 M of 7.7 M (84.4%), compared to males at 6.5 M of 10.8 M (61.90%). Prevalence and utilization along education and income poverty ratio (IPR) were also examined. Conclusion: There are high discrepancies in CVD prevalence and healthcare utilization by race/ethnicity and other demographic variables. Further studies are required to assess the underlying causes of such discrepancies.
PDF
