Coronary Heart Attack Research Articles

Association of body roundness index with cardiovascular disease in patients with cardiometabolic syndrome: a cross-sectional study based on NHANES 2009-2018

BackgroundCardiometabolic syndrome (CMS), marked by abdominal obesity and metabolic dysregulation, is associated with a heightened risk of cardiovascular disease (CVD). Compared to the traditional anthropometric predictors represented by body mass index (BMI) and waist circumference (WC), body roundness index (BRI) appears to provide a more accurate reflection of the abdominal fat distribution associated with metabolic diseases. Therefore, this study intends to investigate the association of BRI with the risk of CVD and its components including congestive heart failure (CHF), coronary heart disease (CHD), angina, heart attack, and stroke in patients with CMS. At the same time, we hypothesized that BRI would identify CVD better than BMI or WC.MethodsData from the 2009-2018 National Health and Nutrition Examination Survey (NHANES). Logistic regression models were mainly utilized to evaluate the relationship between BRI and CVD in patients with CMS, including smooth curve analysis, threshold effects analysis, subgroup analysis and multiple imputation. In addition, receiver operating characteristic (ROC) curves were used to assess the ability of BRI to predict CVD.ResultsThe logistic regression model showed a positive association between the BRI and CVD. The highest quartile of BRI (Q4) showing the strongest association with CVD. The smoothed curve revealed a linear relationship between BRI and CVD, but a U-shaped association between the BRI and CHF. For CVD, stratified analyses did not show significant difference between strata. For CHF, BMI interacted with the association, with BRI being associated with decreased risk of CHF in a subgroup of normal weight subjects and increased risk of CHF in a subgroup of obese subjects. The multiple imputation further confirmed the robustness of these results. Additionally, the ROC curve indicated that BRI, BMI and WC had predictive power for CVD and CHF (AUC > 0.05). BRI has similar predictive power to WC but better than BMI.ConclusionsAn elevated BRI is associated with a heightened risk of CVD in patients with CMS. BRI has similar ability to predict CVD and CHF as WC, but superior to BMI.

Sex-specific associations of cigarettes and e-cigarettes use with self-reported premature atherosclerotic cardiovascular disease among adults aged 18–54 in the United States

Premature atherosclerotic cardiovascular disease (ASCVD) is increasing in young adults (<55years old). While research suggests females who smoke cigarettes have a higher risk of ASCVD than males, studies on the impact of exclusive e-cigarette and dual use on premature ASCVD are limited. This study investigated the association between tobacco use and self-reported premature ASCVD and explored potential sex differences. Using pooled data from 480,317 adults (ages 18-54; ∼50% female) from the 2020-2022 Behavioral Risk Factor Surveillance System from the United States, logistic regression models assessed associations between cigarette and e-cigarette use patterns and self-reported premature ASCVD. Tobacco use categories were defined as: non-use, former use (cigarettes, e-cigarettes), and current use (cigarettes, e-cigarettes) and dual use. Self-reported premature ASCVD was defined as self-reported angina or coronary heart disease, heart attack, or stroke. Weighted analyses were conducted for the overall sample and stratified by sex. After controlling for potential confounders, former exclusive cigarette (adjusted OR: 1.47 [95% CI 1.29, 1.67]), current exclusive cigarette (1.68 [1.47-1.94]) and current dual (2.03 [1.69-2.44]) use were associated with higher odds of self-reported premature ASCVD. There was no significant association for e-cigarette use. Sex-specific analyses revealed similar patterns but the magnitude of these associations varied between males and females. Both sexes showed higher odds of self-reported premature ASCVD for dual and exclusive cigarette use. Although the cross-sectional design precludes causal inferences, the findings suggest comprehensive tobacco cessation programs tailored to diverse use patterns are needed to reduce the burden of premature ASCVD.

Abstract 4125581: Association Between Life’s Essential 8 and Premature Atherosclerotic Cardiovascular Disease: A Cross-sectional Study Among Young Adults in the United States

Background: Among patients presenting with atherosclerotic cardiovascular disease (ASCVD), the proportion of young individuals has increased in recent years. Life’s Essential 8 (LE8), containing two domains of health behaviors and health factors, is an updated monitoring measurement of cardiovascular health by assessing 8 modifiable risk factors. Objective: The objective of this study is to investigate the potential relationship between the LE8 score and a history of premature ASCVD among young adults residing in the United States. Methods: This population-based cross-sectional study utilized data from the National Health and Nutrition Examination Survey spanning 2005 to 2018, focusing specifically on adults aged 20 to 45. LE8 score was measured and categorized into low (0-49), moderate (50-79), and high (80-100) levels (Figure 1). Premature ASCVD status was determined by interviews conducted at enrollment, encompassing a self-reported composite disease history of coronary heart disease, angina pectoris, heart attack, and stroke. Following descriptive statistics, weighted multivariable logistic regression and restricted cubic spline models were employed to evaluate the associations between the LE8 score and premature ASCVD. Additionally, subscale and subgroup analysis were developed. Results: Among 17,499 participants, 9846 were eligible for analysis (weighted mean age, 32.7 years; male, 50.3%), and 167 had premature ASCVD history (weighted percentage, 1.46%). The weighted mean LE8 score of the study population was 71.99 (0.3). Following the adjustment for potential confounders, individuals with higher LE8 scores exhibited a reduced risk of developing premature ASCVD (Table 1). A nonlinear relationship was observed and similar patterns were also identified in the association of health behaviors and health factors scores with premature ASCVD (Figure 2). This inverse association was consistently observed across various subgroups, including sex, age strata, ethnicity, education, and income levels, with no significant interactions identified. Conclusions: The LE8 score and its subscale scores exhibited a negative, nonlinear association with premature ASCVD. Maintaining a healthy lifestyle and controlling modifiable risk factors are crucial in preventing premature ASCVD in the younger demographic. Further studies, encompassing prospective cohorts, are needed to confirm this finding.

Development of an efficient novel method for coronary artery disease prediction using machine learning and deep learning techniques.

Heart disease is a severe health issue that results in high fatality rates worldwide. Identifying cardiovascular diseases such as coronary artery disease (CAD) and heart attacks through repetitive clinical data analysis is a significant task. Detecting heart disease in its early stages can save lives. The most lethal cardiovascular condition is CAD, which develops over time due to plaque buildup in coronary arteries, causing incomplete blood flow obstruction. Machine Learning (ML) is progressively used in the medical sector to detect CAD disease. The primary aim of this work is to deliver a state-of-the-art approach to enhancing CAD prediction accuracy by using a DL algorithm in a classification context. A unique ML technique is proposed in this study to predict CAD disease accurately using a deep learning algorithm in a classification context. An ensemble voting classifier classification model is developed based on various methods such as Naïve Bayes (NB), Logistic Regression (LR), Decision Tree (DT), XGBoost, Random Forest (RF), Convolutional Neural Network (CNN), Support Vector Machine (SVM), K Nearest Neighbor (KNN), Bidirectional LSTM and Long Short-Term Memory (LSTM). The performance of the ensemble models and a novel model are compared in this study. The Alizadeh Sani dataset, which consists of a random sample of 216 cases with CAD, is used in this study. Synthetic Minority Over Sampling Technique (SMOTE) is used to address the issue of imbalanced datasets, and the Chi-square test is used for feature selection optimization. Performance is assessed using various assessment methodologies, such as confusion matrix, accuracy, recall, precision, f1-score, and auc-roc. When a novel algorithm achieves the highest accuracy relative to other algorithms, it demonstrates its effectiveness in several ways, including superior performance, robustness, generalization capability, efficiency, innovative approaches, and benchmarking against baselines. These characteristics collectively contribute to establishing the novel algorithm as a promising solution for addressing the target problem in machine learning and related fields. Implementing the novel model in this study significantly improved performance, achieving a prediction accuracy rate of 92% in the detection of CAD. These findings are competitive and on par with the top outcomes among other methods.

Association between platelet to high-density lipoprotein cholesterol ratio (PHR) and hypertension: evidence from NHANES 2005–2018

BackgroundThe Platelet to High-Density Lipoprotein cholesterol Ratio (PHR) is a novel indicator of inflammatory response and metabolic disorders, linked to various chronic diseases. This study aims to investigate the relationship between PHR and hypertension.MethodsData from the National Health and Nutrition Examination Survey (NHANES), collected across seven consecutive cycles from 2005 to 2018, were analyzed. The dataset included participants’ hypertension status as reported by a doctor, their use of antihypertensive medications, and the average of three blood pressure measurements to identify hypertensive adults, along with complete information for PHR calculation. PHR was calculated based on Platelet (PLT) count and High-Density Lipoprotein cholesterol (HDL-C) using the following formula: PHR = [PLT (1000 cells/µL) / HDL-C (mmol/L)]. A multivariable logistic regression model was employed to assess the association between PHR and hypertension, and subgroup analyses were conducted to explore potential influencing factors. Additionally, Restricted Cubic Spline (RCS) curves were applied for threshold effect analysis to describe nonlinear relationships.ResultsHigher PHR was associated with an increased prevalence of hypertension. After adjusting for various covariates, including race, education level, Family Poverty Income Ratio (PIR), smoking, alcohol consumption, sleep disturbances, waist circumference, diabetes, coronary heart disease, angina, heart attack, and stroke, the results remained significant (OR = 1.36; 95% CI, 1.32, 1.41, P < 0.001). Participants with the highest PHR levels had a 104% higher risk of hypertension compared to those with the lowest PHR levels (OR = 2.04; 95% CI, 1.89, 2.21, P < 0.001).ConclusionElevated PHR levels are strongly associated with an increased risk of hypertension. Specifically, when PHR is below 280, the risk of hypertension increases in proportion to PHR. This suggests that regular monitoring of PHR may help identify patients at risk of hypertension early, allowing for timely interventions to slow disease progression. Larger cohort studies are necessary to confirm these findings.

The correlation between Life’s essential 8 and cardiovascular disease and mortality in individuals with nonalcoholic fatty liver disease: a cross-sectional study

It is currently unclear whether there is a connection between Life’s Essential 8 (LE8) and cardiovascular disease (CVD), as well as mortality in people with nonalcoholic fatty liver disease (NAFLD). Our goal was to explore these relationships by examining data collected in the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018. We identified eligible participants with NAFLD based on NHANES 2005–2018 data. CVD status was acquired through self-reported information, and using the National Death Index, mortality data were prospectively matched. The diagnosis of NAFLD relied on noninvasive biomarkers. The research involved 9094 individuals who were identified as having NAFLD, with a mean age of 52.05 years. Each incremental LE8 score exhibited a significant association, leading to a 3%, 3%, 4%, 3%, 3%, 4%, and 4% reduction in the odds of experiencing CVD, ischemic heart disease, congestive heart failure, coronary heart disease, heart attack, angina, and stroke in individuals with NAFLD. A strong correlation was found between maintaining a superior level of Cardiovascular Health (CVH), as shown by a LE8 score ranging from 80 to 100, and a reduced occurrence of CVD and its various forms in NAFLD (all p for trend < 0.0001). Likewise, LE8 demonstrated protective benefits on mortality in NAFLD, showing that following a high CVH (in contrast to low CVH) was linked to reductions of 64%, 71%, and 74% in all-cause, CVD, and cancer mortality, respectively. Restricted cubic spline analyses suggested noteworthy dose-response relationships between LE8 and CVD, specifically its types in NAFLD, and a nonlinear correlation with CVD mortality. Interaction analyses highlighted age and race as significant effect modifiers. CVH, as evaluated by LE8, demonstrated an independent association with decreased odds of CVD and mortality risk in individuals with NAFLD. Our findings substantiate that adhering to LE8 may alleviate the excessive burden of CVD and mortality in the context of NAFLD.

Reduced Income and Its Associations with Physical Inactivity, Unhealthy Habits, and Cardiac Complications in the Hypertensive Population.

(1) Background: A low socioeconomic status significantly increases the risk of hypertension and its associated cardiovascular diseases due to limited access to healthcare and may be even more accentuated by the presence of unhealthy lifestyle habits. The aim of the present research was to study if associations exist between having a family income under the poverty threshold and having an unhealthy diet, being physically inactive, being an alcohol drinker, perceiving one's own health as bad, and suffering from congestive heart failure, coronary heart disease, angina pectoris, heart attack, or stroke. Additionally, the odds ratios of having these unhealthy habits and of suffering from the abovementioned cardiac complications of participants under the poverty threshold were calculated. (2) Methods: This cross-sectional study was based on the National Health and Nutrition Examination Survey (NHANES) 2011-2020. The sample comprised 6120 adults with hypertension (3188 males and 2932 females). A descriptive analysis and non-parametric chi-squared tests were used to study the associations. A binary logistic regression model and backward LR method were used to calculate the odds ratios, normalized by age and sex. (3) Results: The chi-squared test showed associations between having a family income under the poverty threshold and being physically inactive (p < 0.001), having an unhealthy diet (p < 0.001), being an alcohol drinker (p < 0.001), perceiving one's own health as bad (p < 0.001), and suffering from congestive heart failure (p = 0.002), heart attack (p = 0.001), or stroke (p = 0.02). A significantly increased odds ratio for these unhealthy habits and cardiac complications, and also for having coronary heart disease and angina pectoris, were found for hypertension sufferers under the poverty threshold. (4) Conclusions: It was confirmed that having a family income under the poverty threshold is associated with perceiving one's own health as bad, having a series of negative habits in terms of physical activity, diet, and alcohol consumption, and with suffering from congestive heart failure, heart attack, or stroke. Increased odds ratios for these unhealthy habits and these conditions, plus coronary heart disease and angina pectoris, were found for hypertension sufferers under the poverty threshold.

Cardiovascular Disease Patterns, Mortality, and Hospitalization Trends in Adults Over 18: Insights From the Behavioral Risk Factor Surveillance System Database.

Background Cardiovascular diseases (CVDs), including coronary artery disease, heart attacks, strokes, and hypertension, are the leading cause of global morbidity and mortality. Despite advancements in diagnostic techniques, treatment protocols, and public health initiatives, the prevalence of CVD continues to rise. Hence, understanding trends of predisposing factors for CVD and current treatment modalities such as medication use and frequency of hospitalization is essential for developing effective interventions and improving public health strategies. This study leverages Behavioral Risk Factor Surveillance System (BRFSS) data to analyze these trends among adults older than 18 years. Methods Data were sourced from the BRFSSdatabase, analyzing CVD patterns from 2019 to 2021. The study included adults with high cholesterol or blood pressure, coronary heart disease, stroke, and heart failure. Data analysis utilized age-adjusted prevalence, mortality, and hospitalization rates. Results The analysis of the BRFSS data revealed several key trends in CVD patterns from 2019 to 2021. There was a statistically significant increase (p<0.05) in the age-adjusted prevalence of adults taking medication for high cholesterol, rising from 28.9% to 31%, and for controlling high blood pressure, increasing from 57.7% to 60.4%. From 2019 to 2021, coronary heart disease mortality increased from 360,900 to 382,820, while stroke deaths rose from 150,005 to 162,890. Trends show rising mortality for both conditions despite missing data for some years. Mortality rates for coronary heart disease and stroke also rose and were statistically significant (p<0.05), with coronary heart disease mortality increasing from 88 to 92.8 cases per 100,000, and stroke mortality from 37 to 41.1 cases per 100,000.Hospitalization rates for heart failure among Medicare beneficiaries aged 65 and older initially decreased in 2020, likely due to the COVID-19 pandemic impacting hospital admissions, but rose again in 2021 as healthcare-seeking behaviors normalized.Significant gender and racial disparities were observed, with higher mortality rates among males (127.4 per 100,000) and Black, non-Hispanic individuals (110.5 per 100,000). Conclusions This study highlights the increasing medication use for cholesterol and blood pressure among adults older than 18 years, yet mortality rates for coronary heart disease and stroke persist. Significant gender and racial disparities in medication use and mortality rates were observed. These findings underscore the need for targeted public health intervention towards improving medication adherence and addressing social determinants of health, to reduce CVD burden and enhance health equity across diverse populations.

Association of Depression and Cognitive Performance in US Older Adults: A Secondary Analysis of Cross-Sectional Data Using NHANES 2013–2014

Introduction: Depression has been associated with cognitive performance, but whether sociodemographic and clinical characteristics might influence this association is not well elaborated. This study aimed to further explore this relationship in older adults. Methods: This cross-sectional study is based on data from the National Health and Nutrition Examination Survey (NHANES) 2013–2014. A total of 1,433 individuals with complete information on depressive symptoms and cognitive function variables were included in this study. Patient Health Questionnaire 9 (PHQ-9) score ≥10 as the cutoff to identify cases of depression in our study. We defined poor cognitive performance as a composite cognitive score <47. Logistic regression models were used to examine the association of depression with cognitive performance (model 1). We progressively adjusted the covariates as confounders (model 2: model 1 + age, and gender; model 3: model 2 + race, education level, family income, drinking, and smoking; model 4: model 3 + overweight, arthritis, hyperlipidemia, diabetes, hypertension, heart failure, coronary heart disease, heart attack, stroke, and cancer). We then conducted subgroup, interaction, and restricted cubic spline (RCS) analyses to examine this association. Results: The prevalence of poor cognitive performance was 36.6% (53/145) in the depression group and 14.1% (182/1,288) in the non-depression group. In the fully adjusted model, depression was significantly associated with poor cognitive performance (adjusted odds ratio: 2.25; 95% confidence interval: 1.31–3.81). The results were robust to sensitivity analyses. Gender and education level may modify the association between depression and poor cognitive performance. RCS analysis revealed that the PHQ-9 score was related to poor cognitive performance in a nonlinear manner (p for nonlinearity <0.001), and exhibited a J-shaped curve. Conclusion: Depression is associated with poor cognitive performance in US older adults. Early recognition and treatment of depression may be potential intervention strategies to protect cognitive health.

Nonlinear associations between dietary zinc intake and cardiovascular disease risk, a National cross-sectional study based on the NHANES 2005–2018

To explore the associations between dietary zinc intake and cardiovascular diseases (CVDs), including congestive heart failure (CHF), coronary heart disease (CHD), angina, heart attack, and cerebrovascular accident (CVA), this study was performed. Data from the National Health and Nutrition Examination Survey (2005-2018) were used in this study. Dietary zinc intake was stratified into quartiles. Restricted cubic splines were constructed to assess nonlinear associations and identify cut-off values based on the type of nonlinearity. Binary logistic regressions were performed using the cut-offs. Positive associations were detected between the second, third, and fourth quantiles of dietary zinc intake and decreased risks of overall CVDs (Q2: OR=0.83, 95% CI=0.72-0.96; Q3: OR=0.83, 95% CI=0.71-0.96; Q4: OR=0.79, 95% CI=0.67-0.93). The second, third, and fourth quantiles were significantly associated with decreased risks of various CVDs (all P<0.05), except for CHD and angina (all P>0.05). Restricted cubic spline regression revealed significant nonlinear trends for associations of dietary zinc intake with the risk of developing CVDs and CHF (both P for nonlinear <0.05), whereas those for heart attack and CVA were marginally significant (P for nonlinear=0.072, and 0.075, respectively). This study revealed that high dietary zinc intake is associated with reduced risks of developing CVDs, CHF, heart attack, and CVA, but not CHD or angina.

The State of Lipid Metabolism in Old Rats in High Altitude Conditions Against the Background of the Use of Coenzyme Q10

The problem of population aging is relevant both in Kyrgyzstan and in the global space. At the same time, the preservation of the functional capabilities of the body of elderly people living in adverse climatic conditions is of particular importance. 20-30% of the inhabitants live in the mountainous area of Kyrgyzstan at an altitude of 2000-4000 meters above sea level. It is known that in high-altitude conditions, the body is influenced by extreme factors of the highlands, which accelerate the aging process and reduce life expectancy. This article presents data from experimental studies of energy metabolism disorders in old rats and its correction of coenzyme Q10 at an altitude of 3200 m above sea level. It was found that in old rats, under conditions of short-term adaptation in the mountains, an increase in the level of total cholesterol, triglycerides and low-density lipoproteins was shown, and the level of high-density lipoproteins decreased, indicating a violation of lipid metabolism. Also, due to oxidative stress in high-altitude conditions, the level of malondialdehyde, superoxide dismutase and catalase in the blood of animals was increased. Oral administration of coenzyme Q10 at a dose of 30 mg/kg of body weight 1 time per day for 30 days to old rats led to a decrease in total cholesterol, low-density lipoproteins, triglycerides and an increase in high-density lipoproteins, due to the fact that coenzyme Q10 protects the plasma membrane of the cell from lipid peroxidation, preventing oxidative modifications lipids, which leads to a reduced risk of coronary heart disease, heart attack and stroke.

Obstructive Sleep Apnea and Its Cardiac Implications in the United States: An Age-Stratified Analysis Between Young andOlder Adults.

Obstructive sleep apnea (OSA) is a common sleep disorder associated with cardiovascular risks. This study aimed to assess the prevalence of probable OSA and its relationship with cardiovascular risks and diseases focusing on age-stratified young adults (20-40 years) and older (>40 years). The study used a cross-sectional design, analyzing data from the National Health and Nutrition Examination Survey conducted between 2013 and 2018, comprising 9887 community-dwelling adults aged ≥20 years. Probable OSA was determined on the basis of self-report of OSA-related symptoms (eg, snoring, gasping/breath cessation while sleeping). Cardiovascular risk factors, including hypertension, diabetes, hyperlipidemia, and metabolic syndrome, were evaluated according to established guidelines. Cardiovascular diseases (CVDs) included self-reported heart conditions, including congestive heart failure, coronary heart disease, angina, heart attacks, and strokes. Individuals with probable OSA showed a significantly higher prevalence of health conditions, including hypertension (adjusted prevalence ratio [aPR], 1.19; P<0.001), diabetes (aPR, 1.17; P: 0.01), metabolic syndrome (aPR, 1.14; P<0.001), heart attack (aPR, 1.63; P<0.01), stroke (aPR, 1.41; P: 0.03), and any CVD event (aPR, 1.36; P: 0.01) after adjusting for relevant factors. Young adults with probable OSA showed higher prevalence rates of any CVD events (aPR, 3.44; P<0.001), hypertension (aPR, 1.45; P<0.001), metabolic syndrome (aPR, 1.25; P<0.001), and angina (aPR, 10.39; P<0.001). The study suggests early identification and management of OSA in individuals at risk for CVD. While cross-sectional, it emphasizes that health care providers should recognize OSA as significantly associated with CVDs and its precursor risks in young adults, stressing proactive care and screening to reduce CVD risk in this population.

Sex Differences in the Association of Depression Symptoms and Cardiovascular Disease in Adults in the United States.

This study explores the relationship between depression and cardiovascular disease (CVD) in the US adult population, focusing on sex differences. Cross-sectional study. National Health and Nutrition Examination Survey data (2013-2018). A total of 14699 community-dwelling adults (≥20years). The Patient Health Questionnaire (PHQ-9) depression screening tool assessed depressive symptoms. CVD events included heart failure, coronary heart disease, angina, heart attack, or stroke. Adjusted prevalence ratios were estimated using a Poisson regression model. The study finds a positive association between CVD incidents and both mild to moderate depressive symptoms (aPR:1.42, P = .002) and moderately severe to severe depression (aPR:1.72, P = .024). Overall, females exhibit a 47% lower likelihood of CVD incidents compared to males. However, in a subgroup analysis, increased depressive symptoms correlate with higher CVD incidents in females (aPRs range: 2.09 to 3.43, P < .001) compared to males (aPRs range: 1.45 to 1.77, P < .001). Depression is associated with increased cardiovascular disease (CVD) risk. Females generally have a lower CVD risk than males, but more severe depressive symptoms elevate CVD risk in females. These findings emphasize the significance of considering sex differences. Further research is needed to understand the underlying mechanisms.

Irregular Cycles, Ovulatory Disorders, and Cardiometabolic Conditions in a US-Based Digital Cohort

Polycystic ovary syndrome (PCOS), characterized by irregular menstrual cycles and hyperandrogenism, is a common ovulatory disorder. Having an irregular cycle is a potential marker for cardiometabolic conditions, but data are limited on whether the associations differ by PCOS status or potential interventions. To evaluate the association of PCOS, time to regularity since menarche (adolescence), and irregular cycles (adulthood) with cardiometabolic conditions. This cross-sectional study used a large, US-based digital cohort of users of the Apple Research application on their iPhone. Eligibility criteria were having ever menstruated, living in the US, being at age of consent of at least 18 years (or 19 years in Alabama and Nebraska or 21 years in Puerto Rico), and being able to communicate in English. Participants were enrolled between November 14, 2019, and December 13, 2022, and completed relevant surveys. Self-reported PCOS diagnosis, prolonged time to regularity (not spontaneously establishing regularity within 5 years of menarche), and irregular cycles. The primary outcome was self-reported cardiometabolic conditions, including obesity, prediabetes, type 1 and 2 diabetes, high cholesterol, hypertension, metabolic syndrome, arrhythmia, congestive heart failure, coronary artery disease, heart attack, heart valve disease, stroke, transient ischemic attack (TIA), deep vein thrombosis, and pulmonary embolism measured using descriptive statistics and logistic regression to estimate prevalence odds ratios (PORs) and 95% CIs. Effect modification by lifestyle factors was also estimated. The study sample (N = 60 789) had a mean (SD) age of 34.5 (11.1) years, with 12.3% having PCOS and 26.3% having prolonged time to regularity. Among a subset of 25 399 participants who completed the hormonal symptoms survey, 25.6% reported irregular cycles. In covariate-adjusted logistic regression models, PCOS was associated with a higher prevalence of all metabolic and several cardiovascular conditions, eg, arrhythmia (POR, 1.37; 95% CI, 1.20-1.55), coronary artery disease (POR, 2.92; 95% CI, 1.95-4.29), heart attack (POR, 1.79; 95% CI, 1.23-2.54), and stroke (POR, 1.66; 95% CI, 1.21-2.24). Among participants without PCOS, prolonged time to regularity was associated with type 2 diabetes (POR, 1.24; 95% CI, 1.05-1.46), hypertension (POR, 1.09; 95% CI, 1.01-1.19), arrhythmia (POR, 1.20; 95% CI, 1.06-1.35), and TIA (POR, 1.33; 95% CI, 1.01-1.73), and having irregular cycles was associated with type 2 diabetes (POR, 1.36; 95% CI, 1.08-1.69), high cholesterol (POR, 1.17; 95% CI, 1.05-1.30), arrhythmia (POR, 1.21; 95% CI, 1.02-1.43), and TIA (POR, 1.56; 95% CI, 1.06-2.26). Some of these associations were modified by high vs low body mass index or low vs high physical activity. These findings suggest that PCOS and irregular cycles may be independent markers for cardiometabolic conditions. Early screening and intervention among individuals with irregular menstrual cycles may be beneficial.

Awareness of Atherosclerosis and Cardiovascular Events Among Undergraduate Healthcare Professionals

The word atherosclerosis consists of two parts: atherosis (accumulation of fats accompanied by several macrophages) and sclerosis (fibrosis layer comprising smooth muscle cells. The presence of hyperlipaemia is the major risk issue factor for coronary artery disease. In 2016 advances in atherosclerosis research were focused on the discovery and validation of newly targeted genetics and mechanistic connection to atherothrombotic heart diseases. The Survey on awareness about the risk factors and complications of liver cirrhosis among college students was conducted using a Google form link. We have distributed our survey among 100 college students. Pie charts and Bar diagrams were used to represent output variables. Results showed that the knowledge of cardiovascular 54.00 % said No and 46.00 % said yes. Stroke caused due to lack of blood supply to 44.00 % said heart, 50.00 % said brain, and 6.00 % said I don’t know. These findings conclude that the majority of the population is unaware of the risk factors such as obesity, LDL, and family history, which lead to the development of atherosclerosis, but only a few populations are aware of stress, smoking, coronary heart attack, cholesterol, sleep apnea, HDL, work pressure, physical activity, heart disease, and coronary disease that leads to atherosclerosis.

Abstract P381: Geographic Variation in Financial Strain and Food Insecurity After the COVID-19 Pandemic: Implications for Cardiovascular Health Equity

Reduced food security is associated with higher healthcare expenditures and increased risk of coronary heart disease, angina, heart attacks, and hypertension. State-level responses to the COVID-19 pandemic and support policies may contribute to regional differences in financial strain and food insecurity, which could have implications for cardiovascular outcomes. Hypothesis: We assessed the hypothesis that there is geographic variation in financial strain and food insecurity in the United States three years after the start of the pandemic. Methods: This study utilizes weighted data from the U. S. Census Bureau’s Household Pulse Survey Phase 3.10 conducted from August 23 - September 4, 2023. We organized data responses according to the Department of Health and Human Services regions - Boston, New York, Philadelphia, Atlanta, Chicago, Dallas, Kansas City, Denver, San Francisco, and Seattle. Food insecurity was measured using a single survey item about having sufficient food to eat in the last 7 days. Financial strain was defined as difficulty paying expenses in the last seven days. Results: There were 254,966,752 adults in the total sample population, (59%) reported difficulty with expenses due to the COVID-19 pandemic. The Atlanta region reported the most financial strain (13%), while the Denver region reported the least (2%), p-value=0.000. The rate of food insecurity was highest in the Atlanta region at 8% compared with 5% or less in other regions, p-value=0.000. Among the 8 states in the Atlanta region, Black individuals were disproportionately more likely to be food insecure, with the greatest difference for Kentucky, Florida, Tennessee, and South Carolina. All states in the Atlanta region had similar odds of food insecurity, but Mississippi residents were nearly twice as likely to experience food insecurity than residents of other states (OR 1.87, p =0.016). Conclusions: The Atlanta region (i.e., the “Deep South”) consists of the most populous states for non-Hispanic Black people and is experiencing the worst food insecurity and financial strain post-pandemic. The economic toll of the pandemic and post-pandemic inflation may contribute to worsening food insecurity and cardiovascular outcomes in a region that is already burdened by poor cardiovascular health. Multilevel intervention is needed to support full pandemic recovery and avoid exacerbating inequities in cardiovascular disease.

Cardiovascular Health, Lifestyle Factors, and Social Determinants in Asian Subpopulations in the United States

Asian Americans are often aggregated in national public health surveillance efforts, which may conceal important differences in the health status of subgroups that are included in this highly diverse population. Little is known about how cardiovascular health varies across Asian subpopulations and the extent to which lifestyle and social risk factors contribute to any observed differences. This national study used data from the National Health Interview Survey to evaluate the burden of cardiovascular risk factors (hypertension, hyperlipidemia, diabetes mellitus) and cardiovascular diseases (heart attack, coronary heart disease, angina, stroke) across Asian groups (Chinese, Asian Indian, Filipino, Other Asian), and determine whether differences are related to lifestyle factors and/or social determinants of health. The weighted study population included 13,592,178 Asian adults. Filipino adults were more likely to have hypertension than Chinese adults (29.4% vs 15.4%; adjusted odds ratio [OR] 2.40, 95% confidence interval [1.91 to 3.02]), as were Asian Indians (15.7%; OR 1.59 [1.25 to 2.02]). These patterns were similar for hyperlipidemia and diabetes mellitus. For cardiovascular diseases, Filipino adults were significantly more likely to have coronary heart disease (4.2% vs 1.9%; OR 2.19 [1.32 to 3.56]), heart attack (2.6% vs 0.9%; OR 2.79 [1.44 to 5.41]), angina (1.8% vs 0.9%; OR 2.15 [1.06 to 4.32]), and stroke (2.1% vs 0.8%; OR 2.54 [1.42 to 4.55]) compared with Chinese adults, whereas there were no differences compared with Asian Indian adults. Adjustments for lifestyle factors and social determinants completely attenuated differences in coronary heart disease, heart attack, and angina among subpopulations. In conclusion, these findings demonstrate that cardiovascular risk factors and diseases vary significantly across Asian subpopulations, with Filipino adults experiencing the highest burden and Chinese adults the lowest, and that differences in cardiovascular disease are largely attenuated after adjustment for lifestyle and social determinants.

Vitamin D levels and five cardiovascular diseases: A Mendelian randomization study

Cardiovascular disease is the leading cause of death worldwide, whilst vitamin D levels have been found to be associated with cardiovascular disease. To investigate the causal relationship between vitamin D levels and five cardiovascular diseases, a genome-wide association study (GWAS) was carried out using data on vitamin D levels (sample size=79366), angina pectoris (18168 cases and 187840 controls), coronary heart disease (21012 cases and 197780 controls), lacunar stroke (6030 cases and 248929 controls), heart attack (10693 cases and 451187 controls), and hypertension (55917 cases and 162837 controls), with a Mendelian randomization (MR) analysis being subsequently performed. Six single nucleotide polymorphisms were used as instrumental variables (IVs). In addition, sensitivity analysis was performed to verify the reliability of the MR results here. The results showed a causal relationship between vitamin D levels and angina pectoris (OR=0.51, 95% CI: 0.28-0.93, P=0.03), coronary heart disease (OR=0.53, 95% CI: 0.34-0.81, P=0.004), and lacunar stroke (OR=0.41, 95% CI: 0.20-0.86, P=0.02), but no causal relationship with heart attacks (OR=1.00, 95% CI: 0.99-1.01, P=0.76) or hypertension (OR=0.99, 95% CI: 0.73-1.34, P=0.94). Additionally, our IVs data showed no heterogeneity or pleiotropy, whilst the results of the MR analysis were reliable. This study contributes to the prevention and treatment of these five cardiovascular diseases.

Congestive Coronary Heart Failure

Congestive heart failure (CHF) is a continual condition characterized by the heart's inability to pump blood efficiently, which is essential for the buildup of fluid within the lungs and distinctive components of the body. It is a critical and regular health problem globally, affecting hundreds of thousands of people, primarily the elderly. CHF can cease owing to several underlying reasons, including coronary artery sickness, excessive blood strain, heart valve troubles, and cardiomyopathy. This summary aims to define CHF together with its pathophysiology, threat elements, clinical manifestations, analysis, and control. The pathophysiology of CHF includes weakening of the coronary heart muscle, which can also occur because of harm from preceding coronary heart attacks, extended high blood pressure, or special elements affecting coronary heart features. Because the pumping ability of the heart diminishes, blood glide in critical organs becomes inadequate, leading to symptoms, shortness of breath, fatigue, and fluid retention. Numerous risk factors contribute to the development of CHF, including age, coronary heart sickness, obesity, diabetes, smoking, and a sedentary lifestyle. Early diagnosis of CHF is critical for saving the patient from improving and decorating consequences. Diagnostic methods may additionally include medical records, physical examinations, imaging checks such as echocardiography, and blood tests to evaluate coronary heart characteristics and discover the underlying functionality. CHF control aims to alleviate signs and symptoms, sluggish sickness development, and enhance the pleasantness of life. Treatment strategies usually involve lifestyle changes such as adopting a coronary heart-wholesome diet, engaging in regular exercise, and quitting smoking. Medicinal pills such as diuretics, ACE inhibitors, beta-blockers, and angiotensin receptor blockers are prescribed to enhance coronary heart characteristics and decrease signs and signs. In severe cases, surgical interventions, such as coronary artery pass grafting or coronary heart transplantation, can be considered. As CHF is a continual condition, affected individual education and regular compliance with healthcare carriers are vital to display the ailment's improvement and regulate remedies. With improvements in scientific treatment plans and early detection, CHF analysis has advanced over the years. However, it remains a vast public health challenge, necessitating continuous research and cognizance efforts to beautify affected person consequences and decrease the load of this situation on affected human beings and healthcare systems.

Predictive Power of XGBoost_BiLSTM Model: A Machine-Learning Approach for Accurate Sleep Apnea Detection Using Electronic Health Data

Sleep apnea is a common disorder that can cause pauses in breathing and can last from a few seconds to several minutes, as well as shallow breathing or complete cessation of breathing. Obstructive sleep apnea is strongly associated with the risk of developing several heart diseases, including coronary heart disease, heart attack, heart failure, and stroke. In addition, obstructive sleep apnea increases the risk of developing irregular heartbeats (arrhythmias), which can lead to low blood pressure. To prevent these conditions, this study presents a novel machine-learning (ML) model for predicting sleep apnea based on electronic health data that provides accurate predictions and helps in identifying the risk factors that contribute to the development of sleep apnea. The dataset used in the study includes 75 features and 10,765 samples from the Swedish National Study on Aging and Care (SNAC). The proposed model is based on two modules: the XGBoost module assesses the most important features from feature space, while the Bidirectional Long Short-Term Memory Networks (BiLSTM) module classifies the probability of sleep apnea. Using a cross-validation scheme, the proposed XGBoost_BiLSTM algorithm achieves an accuracy of 97% while using only the six most significant features from the dataset. The model’s performance is also compared with conventional long-short-term memory networks (LSTM) and other state-of-the-art ML models. The results of the study suggest that the proposed model improved the diagnosis and treatment of sleep apnea by identifying the risk factors.