Risk Factors For Heart Disease Research Articles

Heart Disease Prediction using Machine Learning

Abstract: Heart disease remains a leading cause of morbidity and mortality worldwide. Early detection and accurate prediction of heart disease risk factors are crucial for effective prevention and timely intervention. In recent years, machine learning techniques have emerged as powerful tools for predictive analytics in healthcare. This paper presents a comprehensive review of recent advances in the application of machine learning algorithms for heart disease prediction. The review begins by discussing the significance of heart disease prediction and the limitations of traditional risk assessment methods.

Association between infertility and risk of cardiovascular diseases in young women

Scientists and medical experts are beginning to understand the significant role that a woman’s past reproductive experiences play in her potential risk of developing heart disease. Reproductive history is seldom considered when assessing the cardiovascular risk. Infertility, high blood pressure, and hypertension are risk factors for heart disease. Additional analyses were conducted to determine whether the apparent increase in risk could be influenced by other risk factors associated with infertility such as irregular menstruation, thyroid conditions, and waist circumference. This study aimed to investigate the association between cardiovascular risk and infertility in women and those who are fertile. The objectives of this study were to estimate the levels of serum creatinine kinase (MB) in both infertile and fertile control groups, as well as to estimate the LDL and HDL levels in the same groups. The study group comprised 78 participants, of which 39 were fertile and 39 were infertile. CK (MB), HDL, LDL, Uric acid, and high sensitivity C reactive Protein (hs-CRP) levels were analyzed. In this study, we discuss how infertility may share common pathways with cardiovascular diseases. Numerous mechanisms may be involved in mediating infertility, including ovulatory abnormalities, endometriosis, and uterine fibroids. For example, in addition to having lower HDL levels, women with polycystic ovary syndrome (PCOS) are more likely to have higher levels of total cholesterol, triglycerides, and LDL. PCOS patients typically exhibit elevated UA levels and hyperuricemia, which are commonly associated with increased androgen levels.

Dietary patterns and metabolic syndrome in patients with premature heart disease: a cross-sectional study

Purpose Due to the increase in the prevalence of other risk factors of heart diseases, the age of heart disease has decreased and it has led to premature heart disease. One of the main risk factors of this disease is metabolic syndrome (MetS). One of the key ways to control MetS is dietary modification. The purpose of this study is to investigate the relationship between dietary patterns and MetS in patients with premature heart disease. Design/methodology/approach This study was conducted on 409 people with premature heart disease. The diagnosis of MetS was made based on the ATP III criteria. Dietary intake for the past year was collected using the validated semi-quantitative food frequency questionnaire. Dietary patterns were determined by factor analysis with principal components approach. Findings Three dietary patterns were identified, including the healthy, western and traditional patterns. The findings showed that people who followed the traditional pattern more than those who followed less had a lower risk of MetS. (OR:0.23; 95% CI: 0.11–0.52). But, no relation was observed between healthy (OR:1.45; 95% CI:0.64–3.25) and western (OR:1.04; 95% CI:0.51–2.13) patterns with MetS. Originality/value The findings of this study showed that following a traditional dietary pattern based on high consumption of whole grains, red meat, viscera, fish, eggs, high-fat dairy products, soft drinks, mayonnaise and solid oil was associated with a lower risk of MetS.

Food contamination and cardiovascular disease: a narrative review.

Cardiovascular disease is a significant cause of morbidity and mortality among non-communicable diseases worldwide. Evidence shows that a healthy dietary pattern positively influences many risk factors of cardiometabolic health, stroke, and heart disease, supported by the effectiveness of healthy diet and lifestyles for the prevention of CVD. High quality and safety of foods are prerequisites to ensuring food security and beneficial effects. Contaminants can be present in foods mainly because of contamination from environmental sources (water, air, or soil pollution), or artificially introduced by the human. Moreover, the cross-contamination or formation during food processing, food packaging, presence or contamination by natural toxins, or use of unapproved food additives and adulterants. Numerous studies reported the association between food contaminants and cardiovascular risk by demonstrating that (1) the cross-contamination or artificial sweeteners, additives, and adulterants in food processing can be the cause of the risk for major adverse cardiovascular events and (2) environmental factors, such as heavy metals and chemical products can be also significant contributors to food contamination with a negative impact on cardiovascular systems. Furthermore, oxidative stress can be a common mechanism that mediates food contamination-associated CVDs as substantiated by studies showing impaired oxidative stress biomarkers after exposure to food contaminants.This narrative review summarizes the data suggesting how food contaminants may elicit artery injury and proposing oxidative stress as a mediator of cardiovascular damage.

Assessment of Knowledge, Attitudes, and Practices Regarding Non-Inherited Risk Factors for Congenital Heart Disease Among Mothers in Al-Baha City, Saudi Arabia: A Cross-Sectional Study

Assessment of Knowledge, Attitudes, and Practices Regarding Non-Inherited Risk Factors for Congenital Heart Disease Among Mothers in Al-Baha City, Saudi Arabia: A Cross-Sectional Study

A retrospective study of congenital anomalies and associated risk factors among children admitted at a tertiary hospital in northwestern Tanzania.

Congenital anomalies in Sub-Sahara Africa (SSA) are understudied despite the significant pediatric health burden. This retrospective longitudinal hospital-based study evaluated the records of 326 inpatient children under the age of two years with congenital anomalies at Bugando Medical Centre, a tertiary referral hospital in northwestern Tanzania. Classical logistic regression was used in the analysis of congenital malformation of muscles, gastrointestinal malformation, oral facial clefts, neural tube defects, and skeletal malformations. A modified poisson regression was used to model risk factors for Central Nervous System (CNS) hydrocephalus and congenital heart disease (CHD). A majority (78.8%) of children included in the study were less than six months of age. Nearly half (48.8%) were diagnosed with CHD followed by CNS hydrocephalus (10.4%) and congenital malformation of muscles (8.9%). Babies whose mothers missed periconceptual folic acid supplementation had 83% higher risk of hydrocephalus (aPR = 1.83, 95% CI = 1.11-1.96) and 78% higher for CHD (aPR = 1.78, 95% CI = 1.31-1.94). Male children had 1.67 higher odds of muscular congenital malformations (aOR = 1.67, 95% CI = 1.23-1.89). Less than 37 gestational age had a 1.86 higher odds of muscular congenital malformations (aOR = 1.86, 95% CI = 1.53-3.66). Our study highlights the critical need for folic acid supplementation and establishes a need for a registry and the potential for mapping.

Lp(a) Levels in Relatives of Patients with Acute Coronary Syndrome and Elevated Lp(a): HER(a) Study.

Background: Lipoprotein(a) [Lp(a)] is a proatherogenic particle associated with increased cardiovascular risk. It is mainly genetically determined; so, the aim of our study is to evaluate the levels of Lp(a) in the relatives of a prospective cohort of patients who have suffered from an acute coronary syndrome (ACS) with Lp(a) ≥ 50 mg/dL. Methods: We conducted a multicenter prospective study, in which consecutive patients who had suffered from an ACS and presented Lp(a) ≥ 50 mg/dL and their first-degree relatives were included. Results: We included 413 subjects, of which 56.4% were relatives of the patients. Family history of early ischemic heart disease was present in 57.5%, and only 20.6% were receiving statin treatment. The family cohort was younger (37.5 vs. 59.1 years; p < 0.001), and 4% had ischemic heart disease and fewer cardiovascular risk factors. Mean Lp(a) levels were 64.9 mg/dL, 59.4% had levels ≥ 50 mg/dL, and 16.1% had levels ≥ 100 mg/dL. When comparing the patients with respect to their relatives, the mean level of Lp(a) was lower but without significant differences regarding the levels of LDLc, ApoB, and non-HDL. However, relatives with Lp(a) ≥ 50 mg/dL, had values similar to the group of patients with ACS (96.8 vs. 103.8 mg/dL; p = 0.18). No differences were found in Lp(a) levels in relatives based on the other lipid parameters. Conclusions: Overall, 59.4% of the first-degree relatives of patients who suffered from an ACS with Lp(a) ≥ 50 mg/dL also had elevated levels. Relatives with elevated Lp(a) had similar levels as patients.

The Impact of Periodontal Inflammation on the Severity of Coronary Atherosclerosis.

Introduction Through plausible biological mechanisms, periodontitis causes systemic inflammatory burden and response, thus resulting in damage far beyond the oral cavity. Studies have demonstrated periodontitis to be a significant risk factor for coronary heart disease (CHD) and stroke. The larger the quantum of periodontal inflamed tissue, the greater the chances of periodontitis eliciting bacteremiaand systemic inflammatory responses. Studies have reported that periodontitis and other common oral infections play an important role in the development of atherosclerosis. Therefore, the quantity of inflamed periodontal tissue assumes significance in determining the severity of atherosclerosis. Hence, this study investigates the impact of periodontal inflamed surface area (PISA) on the severity of coronary atherosclerosis. Materials and methods In this cross-sectional study, a total of 160 patients who presented at the department of periodontics of The British University in Egypt (BUE) from 1 January 2023 to 30 September 2023 were enrolled. Patients were only enrolled if they had undergone coronary angiography within the last six months, were less than 60 years of age, shared their previous medical history and coronary angiographic report, and gave informed written consent. Data on classic coronary risk factors and periodontal inflammatory status and angiographic findings were recorded and subjected to appropriate statistical analysis. Results The results revealed that the periodontal inflamed surface area (p = 0.002) apart from age (p < 0.047) and low-density lipoprotein cholesterol(LDL-C) (p < 0.001) is a significant independent predictor of the severity of coronary atherosclerosis. Conclusions The periodontal inflamed surface area is an independent predictor of the severity of coronary atherosclerosis.

Adapting transformer-based language models for heart disease detection and risk factors extraction

Efficiently treating cardiac patients before the onset of a heart attack relies on the precise prediction of heart disease. Identifying and detecting the risk factors for heart disease such as diabetes mellitus, Coronary Artery Disease (CAD), hyperlipidemia, hypertension, smoking, familial CAD history, obesity, and medications is critical for developing effective preventative and management measures. Although Electronic Health Records (EHRs) have emerged as valuable resources for identifying these risk factors, their unstructured format poses challenges for cardiologists in retrieving relevant information. This research proposed employing transfer learning techniques to automatically extract heart disease risk factors from EHRs. Leveraging transfer learning, a deep learning technique has demonstrated a significant performance in various clinical natural language processing (NLP) applications, particularly in heart disease risk prediction. This study explored the application of transformer-based language models, specifically utilizing pre-trained architectures like BERT (Bidirectional Encoder Representations from Transformers), RoBERTa, BioClinicalBERT, XLNet, and BioBERT for heart disease detection and extraction of related risk factors from clinical notes, using the i2b2 dataset. These transformer models are pre-trained on an extensive corpus of medical literature and clinical records to gain a deep understanding of contextualized language representations. Adapted models are then fine-tuned using annotated datasets specific to heart disease, such as the i2b2 dataset, enabling them to learn patterns and relationships within the domain. These models have demonstrated superior performance in extracting semantic information from EHRs, automating high-performance heart disease risk factor identification, and performing downstream NLP tasks within the clinical domain. This study proposed fine-tuned five widely used transformer-based models, namely BERT, RoBERTa, BioClinicalBERT, XLNet, and BioBERT, using the 2014 i2b2 clinical NLP challenge dataset. The fine-tuned models surpass conventional approaches in predicting the presence of heart disease risk factors with impressive accuracy. The RoBERTa model has achieved the highest performance, with micro F1-scores of 94.27%, while the BERT, BioClinicalBERT, XLNet, and BioBERT models have provided competitive performances with micro F1-scores of 93.73%, 94.03%, 93.97%, and 93.99%, respectively. Finally, a simple ensemble of the five transformer-based models has been proposed, which outperformed the most existing methods in heart disease risk fan, achieving a micro F1-Score of 94.26%. This study demonstrated the efficacy of transfer learning using transformer-based models in enhancing risk prediction and facilitating early intervention for heart disease prevention.

Clopidogrel induced reduction in neutrophil count: An overlooked beneficial effect?

Complement-stimulated neutrophils are able to adhere to the endothelium and damage endothelial cells both in vitro and in vivo. These blood cells participate in the early stages, growth and complications of atherosclerotic plaques. Recent findings, based on mendelian randomization analysis, support the concept that high neutrophil counts are a causal risk factor for ischemic heart disease and myocardial infarction . Clopidogrel decreases leukocyte count and inflammatory markers in patients with acute coronary syndromes; this off-target effect, which is independent of the antiplatelet action, may help explaining secondary prevention data showing a superiority of clopidogrel over aspirin in reducing new cardiovascular events.

Dietary fat consumption frequency and body mass index of middle-age adults in Mumbai city, India during COVID-19 pandemic

Obesity and COVID-19 are global pandemics listed by World Health Organization, which need urgent attention. Obesity involves low grade chronic inflammation, which is characterised by sustained pro-inflammatory innate immune responses mediated through activation of the NLR family pyrin domain-containing 3 (NLRP3) inflammasome/IL-1 axis, and is a strong risk factor for Diabetes and Heart diseases(1). Dietary fats provide energy, satiety, source of fat-soluble vitamins and essential fatty acids – Omega 3 (n-3) and Omega 6 (n-6) fatty acids, but must be consumed in right amounts and ratios. Essential fatty acids (EFA) deficiency and n-6/n-3 imbalance is linked with chronic illnesses such as, heart attacks, cancer, insulin resistance, stroke, obesity, and diabetes(2). Excess dietary fat intake and imbalance of fatty acids, contribute to obesity, inflammation, comorbidities and faster disease progression. A cross-sectional survey aimed to understand the fatty food frequency of overweight and obese middle age adults from Mumbai, India during the COVID-19 outbreak. Using purposive sampling, 100 adults (30-60 years), a questionnaire (demographics, anthropometrics and fat food frequency questionnaire) was administered. Data was analysed using SPSS 26.0. As per BMI standards, 60.2% participants were overweight, 12.6% were obese and 27.1% had normal BMI. For visible fat consumption, sunflower oil (47.6%), ghee (38.8%), rice bran oil (34%) groundnut oil (11.7%) and invisible fats – milk (100%). Other dairy products, nuts and oilseeds were consumed weekly. twice a week, majority (92.3%) consumed packaged high fat foods as compared to eating deep-fried items (58.9%). We concluded that excess dietary fat intake is high risk factor for obesity and related comorbidities diabetes, and hypertension. High BMI increases the risk for non-communicable diseases (NCDs) such as obesity, cardiovascular disease (CVD), insulin resistance and type 2 diabetes. People with co-morbidities are high risk groups for COVID-19 infection susceptibility. Hence, managing weight could be a cost-effective preventive strategy to help in delaying the onset and progression of NCDs, thereby lowering the susceptibility to COVID-19. Our findings have important implications in working towards adopting healthy fats and reducing mortality and reducing the global burden of pandemic. High dietary fat intake is a modifiable risk factor for overweight and obesity. Comorbidities increased risk for COVID-19 infection, disease severity and mortality. Hence, there is a need to understand the dietary fat consumption patterns in obesity and COVID-19. Dietary carbohydrate, sugar and fat quality in relation to obesity and pandemic such as, COVID-19 could be explored in future studies.

PERCEIVED EFFECT OF PHYSICAL EXERCISE ON SMOKING STATUS AMONG SAUDI POPULATION IN THE EASTERN PROVINCE OF KSA: A CROSS-SECTIONAL STUDY

Background: Smoking is a well-known risk factor for heart and lung disease and one of the most common causes of lung cancer. Recently, more attention has been focused on interventions that can be utilized in smoking cessation programs including regular exercise. However, there is contradicting evidence regarding the effect of regular exercise on smoking habits and smoking cessation exist in the literature. Aim: The study aims to evaluate the populations perception of the effect of regular exercise on smoking habits and its aid in smoking cessation in the Eastern Province. Materials and Methods: This study was a quantitative cross-sectional analytical study for the Saudi population of the Eastern Province, KSA. Results: The total number of respondents participating in this study was 235. The majority of them were male, had regular physical exercise, with a Bachelors or Diploma educational level and aged 40 years or above. More than half of the participants were smokers and married.More than half of the sample reported that exercise decreases or strongly decreases smoking times and decreases or strongly decreases the desire to quit. Less than half of the participants perceived that exercise decreases the desire, enjoyment and symptoms. A statistically significant difference between educational level, smoking status and physical exercise of respondents and their perceived effect of physical exercise on smoking status was found. Also, there was a statistically significant difference between exercise duration, frequency per week and the perceived effect of physical exercise on smoking status.

Work stress and changes in heart rate variability among employees after first acute coronary syndrome: a hospital-based longitudinal cohort study.

Work stress is considered as a risk factor for coronary heart disease, but its link with heart rate variability (HRV) among heart attack survivors is unknown yet. The aim of this study was to investigate associations between baseline work stress and the changes of HRV over one-year after onset of acute coronary syndrome (ACS). Hundred and twenty-two patients with regular paid work before their first ACS episode were recruited into this hospital-based longitudinal cohort study. During hospitalization (baseline), all patients underwent assessments of work stress by job strain (JS) and effort-reward imbalance (ERI) models, and were assigned into low or high groups; simultaneously, sociodemographic and clinical data, as well depression, anxiety, and job burnout, were collected. Patients were followed up 1, 6, and 12 months after discharge, with HRV measurements at baseline and each follow-up point. Generalized estimating equations were used to analyze the effects of baseline work stress on HRV over the following 1 year. After adjusting for baseline characteristics and clinical data, anxiety, depression, and burnout scores, high JS was not associated with any HRV measures during follow-up (all p > 0.10), whereas high ERI was significantly related to slower recovery of 5 frequency domain HRV measures (TP, HF, LF, VLF, and ULF) (all p < 0.001), and marginally associated with one time domain measure (SDNN) (p = 0.069). When mutually adjusting for both work stress models, results of ERI remained nearly unchanged. Work stress in terms of ERI predicted lower HRV during the one-year period after ACS, especially frequency domain measures.

The secondary prevention of coronary heart disease in US adults 75 Years and older in daily practice: Results from the National Health and Nutrition Examination Survey 1999–2018 survey

BackgroundPharmacologic therapies, risk factor control, and lifestyle alterations were independently proven to reduce long-term cardiovascular events. However, comprehensive research examining the extent to which individuals aged 75 and above in the United States adhere to national guidelines for the secondary prevention of coronary heart disease is limited. Therefore, the primary objective of this study was to examine the current state of secondary prevention of coronary heart disease in persons 75 years of age and older in the United States and to examine the factors that contribute to inadequate drug utilization and poor control of numerous risk factors. MethodsWe identified patients over 75 years of age with coronary heart disease based on the National Health and Nutrition Examination Survey from 1999 to 2018 and analyzed the adequacy of risk factor control and adherence to lifestyle and medication recommendations to assess the effectiveness of coronary heart disease management. Logistic regression analysis was used to identify factors associated with uncontrolled risk factors or noncompliance with recommended medications. ResultsWe collected information from 1566 known coronary heart disease patients aged ≥75 years of age. The majority were at target goals for blood pressure (58.88%), low-density lipoprotein cholesterol (66.85%), and glycated hemoglobin (76.12%). Only 27.8% and 36.06% were at targets for body mass index and waist circumference, respectively. 91.95% reported smoking cessation, 85.98% followed recommended alcohol consumption, whereas only 10.34% reported sufficient physical activity. For β blockers, angiotensin -converting enzyme inhibitors/angiotensin receptor blockers, statins, and antiplatelet drugs, the utilization of indicated therapy was 54.41%, 49.36%, 54.79%, and 19.03%, respectively (6.26% for all 4 medications). The results of the logistic regression analysis demonstrated that diabetes mellitus and metabolic syndrome were critical markers of numerous uncontrolled risk variables as well as noncompliance with medication regimens. ConclusionsA vast majority of coronary heart disease patients ≥75 years in the USA exhibited suboptimal overall control of critical coronary heart disease risk factors. For this patient population, more knowledge is necessary to enable patients to receive continuous support, guidance, and counseling.

Abstract P277: Adherence to Time-Restricted Eating, Plasma Metabolomic Signatures, and Risk of Coronary Heart Disease

Introduction: Early time-restricted eating (TRE) has been recently suggested as an effective dietary intervention strategy to improve risk factors of coronary heart disease (CHD), whereas late TRE may be related to poor cardiometabolic health. Metabolomic pathways linking the adherence to habitual TREs depending on the time of the day and CHD risk are unknown. Hypothesis: We tested whether adherence to early or late TRE was related to distinct metabolomic signatures (including those in pathways of energy/purine pyrimidine metabolism, lipids, carbohydrates, and acylcarnitines). We then tested whether TRE-related plasma metabolites were associated with the risk of incident CHD among women without prior CHD. Methods: This study included 674 women without cardiovascular disease who completed 7-day food records and measurements of untargeted plasma metabolomics in a sub-study of the Nurses’ Health Studies (NHS/NHSII). TRE was indicated by 4-12 hours of daily eating window. The adherence to TRE was assessed by summing up the TRE days in a week (0-7 days). We analyzed two TRE habits: early TRE (starting before 9 a.m./ending no later than 9 p.m.) and late TRE (beginning after 9 a.m.). Separately, plasma metabolites were measured in a prospective nested case-control of 762 incident cases of CHD and 762 matched controls identified over 10-14 years of follow-up in the NHS. A metabolomic risk score for predicting adherence to late TRE (MRS-TRE late ) was created based on metabolites selected through the elastic net procedure with a 10-fold cross-validation. Results: Adherence to late TRE was positively associated with greater adiposity, insulin/proinsulin, uric acid, and medium-chain fatty acids/acylcarnitines; the late TRE habit was inversely related to metabolites in the TCA cycle/pyruvate metabolism and specific PC species ( P FDR &lt;0.05). On the other hand, metabolites in lipid pathways (including diglyceride DG 38:5) and glucose were inversely related to the adherence to early TRE. Individual levels of late-TRE-related metabolites in energy/phosphatidylcholine /acylcarnitine pathways were significantly associated with an increased risk of CHD. Every 1 SD increment of MRS-TRE late , based on 21 metabolites in various metabolic pathways, was associated with a relative risk (RR) of 1.24 (95% CI: 1.11, 1.38) for CHD in a model adjusted for matching factors, and a RR of 1.15 (1.02, 1.29) after adjusting for covariates, such as demographic factors, diet quality, alcohol, lifestyle factors, and BMI. Women in the top tertile of MRS-TRE late had a 1.44-fold (1.10, 1.89) increased risk of CHD as compared to those in the lowest tertile after adjusting for the covariates. Conclusions: TRE habit, depending on the timing, was related to distinct metabolomic pathways, and adherence to late TRE may be associated with metabolic reliance linked to the risk of incident CHD among women.

Abstract P105: Blood Lipids, Lipoproteins, and Apolipoproteins With Risk of Coronary Heart Disease: A Prospective Study Among Multi-Racial Populations

Background: Blood lipids, such as total cholesterol (TC), LDL-cholesterol (LDL-C), and triglycerides (TG), are well-known risk factors for coronary heart disease (CHD). However, studies that examined the associations of circulating lipids and apolipoproteins carried by different lipoproteins with incident CHD remain limited, particularly among racially diverse populations. Hypothesis: Potential novel lipoprotein biomarkers, other than TC, TG, LDL-C, and HDL-C, are associated with incident CHD in diverse populations. Methods: We conducted nested case-control studies of CHD among White Americans (542 pairs; n =1084), Black Americans (622 pairs; n =1244), and Chinese adults (557 pairs; n =1114) drawn from the Southern Community Cohort Study and Shanghai Women’s and Men’s Health Studies. We examined the associations of 36 plasma lipids, lipoproteins, and apolipoproteins (measured by Bruker IVDr NMR platform) with incident CHD using conditional logistic regression, adjusted for sociodemographics, lifestyle, family history of CHD, and menopausal status (women only). Race-specific odds ratios (ORs) were pooled using fixed-effect meta-analysis. Results: TC, TG, LDL-C, and HDL-C were associated with incident CHD, with pooled ORs being 1.35, 1.31, 1.26, and 0.79 per 1-SD increase. Sixteen lipoprotein biomarkers showed larger effect sizes than those conventional lipids, with pooled ORs per 1-SD ranged from 1.37 to 1.59 and a negative OR of 0.77 ( Figure 1 ); all associations were significant within each race. Significant associations were observed across subpopulations defined by sociodemographics, lifestyle, and status of obesity, diabetes, hypertension, and dyslipidemia, including among individuals with normal levels of TC, TG, LDL-C, and HDL-C. Conclusion: Our study identified several lipoprotein biomarkers (e.g., ApoB/ApoA1 ratio and LDL-TG) associated with incident CHD among multi-racial populations, suggesting potential clinical utility complementing the current lipid panel.

Abstract P363: The Influence of Social Support on Heart Disease Risk Factor Knowledge in Texas African American Women

Introduction: Heart disease disproportionately impacts African American (AA) women nationwide and in Texas. Heart disease disparities stem from risk factors related to limited heart disease risk factor knowledge and socioeconomic resources. Social support mitigates chronic disease risk, yet this is the first study to examine the relationship between perceived social support and heart disease risk within this population. The study aimed to (1) examine how perceived social support impacts heart disease risk factor knowledge among AA women and (2) examine whether demographic characteristics moderate a relationship between perceived social support and heart disease knowledge. Hypothesis: We hypothesize that social support moderates heart disease risk factor knowledge in AA women in Texas based on demographic variables. Methods: This was a quantitative study with purposeful, snowball sampling representative of AA women aged 30-55 in Texas (n = 121). The participants completed a survey comprised of demographic questions, the Heart Disease Knowledge Questionnaire, and the Multidimensional Scale for Perceived Social Support. Results: Approximately half the participants displayed heart disease knowledge deficiencies. Multiple regression analysis revealed that when demographic variables were controlled, age (standardized β= .28, p = .002) and income (standardized β= .19, p = .037) were the only predictor variables indicating that social support impacts heart disease knowledge, with nonsignificant differences in the regression model (standardized β = -.023, p = .80). Hierarchical multiple regression revealed that age (F change = 1.056, R square change = .008, and p = .306), education (F (3, 115) = .583, p = .627), family history (F (2, 116) = 1.51, p = .225), and income (F change = 1.006, R2 change = .008, and p = .318) as individual predictors yielded nonsignificant differences in the overall predictive model, indicating that demographic variables did not moderate a relationship between social support and heart disease knowledge. Conclusion: Overall, the study revealed a need to implement public health education programs to increase heart health knowledge through interventions that combine education and social support among AA women to influence health behavior change and reduce heart health disparities.

Effectiveness of Online Learning to Improve Knowledge About Metabolic Syndrome in Pregnancy

Background: Metabolic syndrome is a persistent global health problem and a risk factor for diabetes and heart disease. A metabolic syndrome that occurs during pregnancy will pose a threat to maternal and fetal health. The incidence of metabolic syndrome during pregnancy, especially in developing countries, will become a serious public health problem in the future. This study aims to assess the effectiveness of online learning in improving the knowledge of online learning participants on metabolic syndrome cases in pregnancy. Subjects and Method: This was a cross-sectional study conducted in July through Zoom online learning on Metabolic Syndrome in Pregnancy attended by 125 participants. The dependent variable was knowledge about metabolic syndrome in pregnancy. The independent variable was online learning. The data obtained from this study were in the form of pretest and post-test scores. The data were analyzed by t-test. Results: The mean score of knowledge about metabolic syndrome in pregnancy after online learning was higher (Mean= 90.8; SD= 14.05) than before (Mean= 60.08; SD= 6.94), and this was statistically significant (p= &lt;0.001). Conclusion: Online learning is effective to improve knowledge about metabolic syndrome in pregnancy among Indonesian Obstetrics and Gynecology Association (POGI) members and young POGI members. Keywords: metabolic syndrome, pregnancy, online learning. Correspondence: Nutria Widya Purna Anggraini. Department of Obstetrics and Gynecology, Faculty of Medicine, Universitas Sebelas Maret/Dr. Moewardi General Hospital, Surakarta, Central Java, Indonesia. Mobile: +62 812-2651-819. E-mail: nutria_dr@staff.uns.ac.id

Prevalence of Self-Reported Hypertension and Antihypertensive Medication Use Among Adults - United States, 2017-2021.

Hypertension, or high blood pressure, is a major risk factor for heart disease and stroke. It increases with age and is highest among non-Hispanic Black or African American persons, men, persons aged ≥65 years, those of lower socioeconomic status, and those who live in the southern United States. Hypertension affects approximately one half of U.S. adults, and approximately one quarter of those persons have their blood pressure under control. Reducing population-level hypertension prevalence and improving control is a national priority. In 2017, updated guidelines for high blood pressure in adults recommended lowering the blood pressure threshold for diagnosis of hypertension. Analysis of data from the Behavioral Risk Factor Surveillance System found that age-standardized, self-reported diagnosed hypertension was approximately 30% during 2017-2021, with persistent differences by age, sex, race and ethnicity, level of education, and state of residence. During this period, the age-standardized prevalence of antihypertensive medication use among persons with hypertension increased by 3.1 percentage points, from 59.8% to 62.9% (p<0.001). Increases in antihypertensive medication use were observed in most sociodemographic groups and in many states. Assessing current trends in hypertension diagnosis and treatment can help guide the development of policies and implementation of interventions to reduce this important risk factor for cardiovascular disease and can aid in addressing health disparities.

Description of Risk Factors for Coronary Heart Disease at the Family Medical Center Hospital Heart Clinic In 2021

Coronary heart disease (CHD) is a condition of reduced blood and oxygen supply to the heart muscle due to blockage by plaque in the blood vessels, called atherosclerosis. CHD is a health burden in the world because it contributes to high mortality rates, including in Indonesia according to Riskesdas 2018. This research aims to determine the description of risk factors for coronary heart disease at the Family Medical Center Hospital Heart Clinic in 2021. This research uses a descriptive survey method with a cross-sectional approach. The total population was 369 and the sample using the total sampling technique obtained 318 people who met the inclusion criteria. The research results showed that the largest age distribution was in the 60-69 year age range, as many as 111 people (34.9%), the largest gender was female, 165 people (51.9%), 15 people (4.7%) had a family history, hypertension 109 people (34.3%), diabetes mellitus 125 people (39.3%), dyslipidemia 201 people (70.4%), smoking 63 people (19.8%), overweight and obesity 224 people (70.3%). CHD patients at the Family Medical Center Hospital Heart Clinic are mostly aged 60-69 years, female, most have no family history, have dyslipidemia, have a BMI in the overweight and obese categories, most did not have a history of hypertension, did not have Diabetes Mellitus, and most did not smoke.