Early Prevention Of Cardiovascular Disease Research Articles

Depressive symptom clusters and biomarkers of monocyte activation, inflammation, and coagulation in people with HIV and depression.

We assess associations of somatic and cognitive/affective depressive symptom clusters with monocyte activation (soluble (s)CD14, sCD163), systemic inflammation (interleukin-6 (IL-6), high-sensitivity C-reactive protein (hsCRP)), and coagulation (D-dimer, fibrinogen) in people with HIV (PWH) on suppressive antiretroviral therapy with depression. Utilizing baseline data from a randomized controlled trial, we found no significant associations in linear regression models examining individual depressive symptom clusters; however, models examining both clusters simultaneously showed that the somatic cluster was positively associated with inflammation biomarkers, while the cognitive/affective cluster was negatively associated with inflammation and coagulation biomarkers (suggesting a cooperative suppression effect). Our findings indicate a differential association with depressive symptom clusters and biological mechanisms underlying cardiovascular disease (CVD) in HIV, which may be driven by unique components of each depressive symptom cluster. This line of research could identify subgroups of PWH with depression at elevated CVD risk needing early CVD prevention approaches. Supported by R01 HL126557.

Unsupervised identification of cardiometabolic profiles among adolescents: findings from the PARIS birth cohort study

Metabolic syndrome (MetS) is known as a risk factor in cardiometabolic morbidity but there is no consensus on its definition for teenagers. We aimed to identify cardiometabolic health profiles and which parameters best discriminate them. K-means partitioning identified cardiometabolic profiles by sex using data on health measurements of 530 adolescents from the PARIS birth cohort. A discriminant analysis was performed. Cardiometabolic risk score and handgrip strength were also measured. Depending on definitions, MetS prevalence ranged from 0.2% to 1.3%. Two profiles were identified for the entire group and by sex: “healthy” and “at cardiometabolic risk.” Weight and waist-to-height ratio or waist circumference explained more than 87% of the variance in the profile differentiation. The “at cardiometabolic risk” profiles included adolescents with overweight, a waist-to-height ratio over 0.5, and prehypertension. They had higher cardiometabolic risk scores and parents who were more likely to be overweight and have cardiometabolic diseases themselves. They also had higher birthweights, earlier adiposity-rebound and puberty ages, and lower relative handgrip strength. Conclusion: The two profiles identified, based on cardiometabolic health, were associated with early indicators and handgrip strength. Results suggest that the waist-to-height ratio is a useful clinical tool for screening individuals at cardiometabolic risk and who therefore require clinical follow-up.What is Known:• Although there is a need for tools to assess cardiometabolic health during adolescence, there is no consensus on the definition of metabolic syndrome for this age group.What is Knew:• The findings suggest that waist-to-height ratio can serve as a simple and valuable clinical tool for screening individuals at cardiometabolic risk who may require clinical monitoring for early prevention of cardiovascular diseases.

Unveiling the molecular Culprit of arterial stiffness in vitamin D deficiency and obesity: Potential for novel therapeutic targets

Cardiovascular diseases (CVDs) are highly associated with both vitamin D deficiency and obesity, two prevalent health conditions worldwide. Arterial stiffness, an independent predictor of CVDs, is particularly elevated in both conditions, yet the molecular mechanisms underlying this phenomenon remain elusive, hindering effective management of CVDs in this population. We recruited 20 middle-aged Emiratis, including 9 individuals with vitamin D deficiency (Vit D level ≤20 ng) and obesity (BMI ≥30) and 11 individuals as control with Vit D level >20 ng and BMI <30. We measured arterial stiffness using pulse wave velocity (PWV) and performed whole transcriptome sequencing to identify differentially expressed genes (DEGs) and enriched pathways. We validated these findings using qRT-PCR, Western blot, and multiplex analysis. PWV was significantly higher in the vitamin D deficient and obese group relative to controls (p ≤ 0.05). The DEG analysis revealed that pathways related to interleukin 1 (IL-1), nitrogen metabolism, HIF-1 signaling, and MAPK signaling were over-activated in the vitamin D deficient and obese group. We found that HIF-1alpha, NOX-I, NOX-II, IL-1b, IL-8, IL-10, and VEGF were significantly upregulated in the vitamin D deficient and obese group (p < 0.05). Our study provides new insights into the molecular mechanisms of arterial stiffness in vitamin D deficiency and obesity, demonstrating the role of oxidative stress and inflammation in this process. Our findings suggest that these biomarkers may serve as potential therapeutic targets for early prevention of CVDs. Further studies are needed to investigate these pathways and biomarkers with larger cohort.

Hypertensive pregnancy complications and maternal characteristics as predictors of cardiovascular health within ten years after delivery

ObjectiveTo identify the combination of maternal characteristics in women with hypertensive disorders of pregnancy (HDP) associated with hypertensive and other cardiovascular diseases (CVDs) within ten years following delivery. The aim is to understand who should receive the most intensive primary cardiovascular disease prevention. Study designA prospective cohort study. Main outcomeThe population was the FINNPEC cohort (2008–2011), including women with (n = 1837) and without (n = 847) HDP. The main exposures were maternal hypertensive pregnancy complications linked with maternal pregnancy data from hospital records. The outcomes were hypertensive diseases and other CVDs (International Classification of Diseases, Tenth Revision). ResultsWomen with de novo pre-eclampsia (PE) had an elevated risk for hypertensive diseases within ten years following delivery. The risk of CVD was increased in women with superimposed PE and chronic hypertension (CHT) only. Women with de novo PE and hypertensive diseases were more often primiparous (41.4% vs. 23.0%, p = 0.020), had gestational diabetes (GDM) (31.0% vs. 11.7%, p = 0.002), and higher pre-pregnancy body mass index (BMI) (28.7 ± 5.8 vs. 24.6 ± 4.8 kg/m2, p = 0.001), compared with women who remained normotensive. Women with superimposed PE with CVD had more likely early-onset PE, preterm delivery and were older than women without later CVD. ConclusionsHealthcare professionals should target early prevention of CVDs in women with chronic hypertension during pregnancy; of those who developed superimposed PE prior to 34th weeks of gestation and who delivered preterm. Women with de novo PE who are overweight/obese, primiparous, and with concurrent GDM need regular blood pressure monitoring.

Identifying Electrocardiogram Abnormalities Using a Handcrafted-Rule-Enhanced Neural Network.

A large number of people suffer from life-threatening cardiac abnormalities, and electrocardiogram (ECG) analysis is beneficial to determining whether an individual is at risk of such abnormalities. Automatic ECG classification methods, especially the deep learning based ones, have been proposed to detect cardiac abnormalities using ECG records, showing good potential to improve clinical diagnosis and help early prevention of cardiovascular diseases. However, the predictions of the known neural networks still do not satisfactorily meet the needs of clinicians, and this phenomenon suggests that some information used in clinical diagnosis may not be well captured and utilized by these methods. In this paper, we introduce some rules into convolutional neural networks, which help present clinical knowledge to deep learning based ECG analysis, in order to improve automated ECG diagnosis performance. Specifically, we propose a Handcrafted-Rule-enhanced Neural Network (called HRNN) for ECG classification with standard 12-lead ECG input, which consists of a rule inference module and a deep learning module. Experiments on two large-scale public ECG datasets show that our new approach considerably outperforms existing state-of-the-art methods. Further, our proposed approach not only can improve the diagnosis performance, but also can assist in detecting mislabelled ECG samples.

Wearable Continuous Blood Pressure Monitoring Devices Based on Pulse Wave Transit Time and Pulse Arrival Time: A Review.

Continuous blood pressure (BP) monitoring is of great significance for the real-time monitoring and early prevention of cardiovascular diseases. Recently, wearable BP monitoring devices have made great progress in the development of daily BP monitoring because they adapt to long-term and high-comfort wear requirements. However, the research and development of wearable continuous BP monitoring devices still face great challenges such as obvious motion noise and slow dynamic response speeds. The pulse wave transit time method which is combined with photoplethysmography (PPG) waves and electrocardiogram (ECG) waves for continuous BP monitoring has received wide attention due to its advantages in terms of excellent dynamic response characteristics and high accuracy. Here, we review the recent state-of-art wearable continuous BP monitoring devices and related technology based on the pulse wave transit time; their measuring principles, design methods, preparation processes, and properties are analyzed in detail. In addition, the potential development directions and challenges of wearable continuous BP monitoring devices based on the pulse wave transit time method are discussed.

Dysmetabolic Iron Overload Syndrome: Going beyond the Traditional Risk Factors Associated with Metabolic Syndrome

Dysmetabolic iron overload syndrome (DIOS) corresponds to the increase in iron stores associated with components of metabolic syndrome (MtS) and in the absence of an identifiable cause of iron excess. The objective of this work was to review the main aspects of DIOS. PUBMED and EMBASE were consulted, and PRISMA guidelines were followed. DIOS is usually asymptomatic and can be diagnosed by investigating MtS and steatosis. About 50% of the patients present altered hepatic biochemical tests (increased levels of γ-glutamyl transpeptidase itself or associated with increased levels of alanine aminotransferase). The liver may present parenchymal and mesenchymal iron overload, but the excess of iron is commonly mild. Steatosis or steatohepatitis is observed in half of the patients. Fibrosis is observed in about 15% of patients. Hyperferritinemia may damage the myocardium, liver, and several other tissues, increasing morbidity and mortality. Furthermore, DIOS is closely related to oxidative stress, which is closely associated with several pathological conditions such as inflammatory diseases, hypertension, diabetes, heart failure, and cancer. DIOS is becoming a relevant finding in the general population and can be associated with high morbidity/mortality. For these reasons, investigation of this condition could be an additional requirement for the early prevention of cardiovascular diseases.

Age-dependent prevalence of type 2 diabetes, cardiovascular risk profiles and use of diabetes drugs in Germany using health claims data.

This study evaluates type 2 diabetes mellitus (T2DM) prevalence in Germany, focusing on patients at risk for, or with already established, cardiovascular disease (CVD), as well as their antidiabetic and cardiovascular treatments. Using anonymized claims data from the WIG2 database, we calculated 2018 T2DM prevalence, extrapolating rates to the German statutory health insurance population. In the study period, 3 376 228 patients were eligible in the database. Forming antidiabetic medication groups, we evaluated treatment regimens of patients at risk for, or with already established CVD, based on the REWIND study criteria. We also evaluated their CVD medication prescriptions. Statutory health insurance extrapolated T2DM prevalence was estimated at 11.9%, with higher prevalence rates in older patients. When only patients with prescriptions of antidiabetic drugs were included, prevalence was 7.6%. At least 94% of patients with T2DM medication had at least one risk factor (without considering age) according to REWIND criteria, while 67%-80% had at least two risk factors depending on treatment received. Patients taking insulin combined with oral therapy comprised the largest proportion of patients with at least two REWIND risk factors. Approximately 85% of all patients with T2DM in the population were treated with antihypertensive medication. T2DM is widespread and affects older patients particularly. Most patients with T2DM had at least one CV risk factor, and about half already had established CVD. Early prevention of CVD, which disproportionately affects patients with T2DM, is necessary. Furthermore, the treatment of older patients with T2DM with insulin is still common and needs further evaluation.

Perceptions of an eHealth family-based cardiovascular disease risk reduction intervention: a mixed methods study

Abstract Funding Acknowledgements Type of funding sources: Other. Main funding source(s): Department for the Economy, Northern Ireland Introduction Controllable cardiovascular disease (CVD) risk factors are often initiated in the family home, yet risk reduction is seldom targeted toward families. Participatory design of eHealth interventions with end-users has potential to increase acceptability and adherence of such interventions. Despite their shared risk of developing CVD, few eHealth interventions target both parents and children at CVD risk. Therein lies an evidence gap; the need for coproduction of a family-based eHealth intervention aimed at early CVD prevention. Purpose The aim of this study was to identify the perceptions of families towards the design, functionality and acceptability of an eHealth, family-based, CVD prevention intervention. Methods Thee online focus groups comprising six families were conducted between April and May 2021. Families consisted of at least one parent who met CVD risk factor criteria, and at least one child aged five to 17 years. Content analysis and narrative synthesis were used to identify categories and subcategories regarding development of and engagement with the proposed intervention. Additionally, quantitative, and demographic measures were used to determine psychosocial and health profiles. Results Three categories were identified from the focus groups: 1) previous experiences of using health-related apps or devices 2) expectations of a newly developed eHealth family-based CVD prevention intervention 3) motivators for engagement with the intervention Goal setting, rewards, accountability, adaptability, recording achievements and competition were considered crucial motivators for engagement for both parents and children. Participants welcomed the intervention, and advised they would prefer a free, personalised, easy-to-use, non-time-consuming intervention, with multiple content formats, and additional information available should they seek to access it. Parents conveyed satisfactory general self-efficacy and quality of life, low anxiety and depression and high perceived social support. Conclusions Overall, families were constructive and forthcoming towards the idea of an eHealth, family-based CVD prevention intervention. These findings informed a prototype of a family-based eHealth intervention aimed at early CVD prevention. The prototype is currently being developed with plans for piloting via a randomised controlled trial in the home environment, by families as an early intervention for the prevention of CVD.

Hypertension in pregnancy as an early sex-specific risk factor for cardiovascular diseases: evidence and awareness.

Despite being a physiological condition, human pregnancy is known to cause numerous complications that can endanger the life of the mother and the fetus alike. While the majority of complications are mostly limited within the peripartum period, more and more information is available about persistently higher short- and long-term cardiovascular risk after a pregnancy complicated by a hypertensive disorder. There is evidence that women after gestational hypertension or preeclampsia are more likely to develop arterial hypertension, coronary atherosclerosis, myocardial infarction, stroke, peripheral artery disease, and even diabetes mellitus and venous thromboembolism years after the target pregnancy. This has urged some authors to view hypertensive disorders of pregnancy as a "stress test" for the maternal organism that unmasks latent endothelial dysfunction. An explanation is sought in the presence of common risk factors and underlying pathological pathways with cardiovascular diseases, although a certain etiological mechanism for the development of hypertensive disorders in pregnancy has not been established yet. More attention is needed towards the follow-up of women after a hypertensive pregnancy as it could be an opportunity for early prevention of cardiovascular diseases.

Early Change in Platelet Count and MPV Levels of Patients Who Received Hemodialysis for the First Time: Mogadishu Somalia Experience.

Introduction Mean platelet volume (MPV) is a marker used to assess the platelet' size and is also an indicator of platelet reactivity and prothrombotic status. Objective In this study, we aimed to determine the relationship between MPV and biochemical parameters in patients who had received hemodialysis (HD) for the first time and then in respect of those same patients after their fourth HD. Method 151 HD patients were enrolled in this study. Patients were eligible for inclusion if they had received their first HD session during this study protocol. Prehemodialysis blood samples were taken. Most laboratory values, including mean platelet volume (MPV) level and platelets (PLT) count, were measured before the first HD and after the fourth HD session for each patient. Results Among the patients in our study, the mean age profile of the male patients (n = 103; 68.2%) was found to be higher than that of the female patients (n = 48; 31.8%) (53.62 ± 18.19 vs. 46.17 ± 17.9 years) (p = 0.019).In the patients' laboratory results after the fourth HD session, MPV, MPV/Plt, and Na values had increased to those after the first HD session (p < 0.001). When age and gender status were taken into account, the level of weak positive correlation with white blood cell count (WBC), neutrophil, and red cell distribution width (RDW) was found, while the weak negative correlation with platelet to lymphocyte ratio (PLR) was found (p < 0.001). Conclusions In our study, we found that increase in MPV and MPV/PLT levels was significant in the fourth HD session of patients with CKD. It is also debatable that there are findings indicating an increase in platelet reactivity in the first weeks of the onset of HD. This could be an early indicator of the early prevention of cardiovascular diseases.

Multi-Distance Dispersion Entropy for ECG Signal Classification

Automatic detection of heartbeat is critical for early cardiovascular disease prevention and diagnosis. Traditional feature methodologies based on expert knowledge cannot abstract and represent multidimensional and multi-view information. Hence traditional research on heartbeat detection pattern recognition cannot produce adequate results. The proposed method in this research used Dispersion Entropy (DisEn) on Multidistance Signal Level Difference (MSLD) for feature extraction and Support Vector Machine (SVM) method for classifying the ECG signals. DisEn generates 20 DE values as feature vectors for each MSLD signal with a distance D of 1 to 20. The datasets used in this research were obtained from the MIT-BIH Arrhythmia database of ECG signals that consist of forty-five patients was captured using 200 [adu/mV] amplification and a sampling frequency of 360 Hz. The experiments result using 5-fold cross-validation revealed that at distance D= 1-15 had the highest accuracy of 91% to classify the ECG data into Normal Sinus Rhythm (NSR), Left Bundle Branch Block (LBBB), and Atrial Fibrillation (AFIB) from the MIT-BIH Arrhythmias database.&#x0D; &#x0D;

Psychosocial Well-Being and Progression of Coronary Artery Calcification in Midlife Women.

BackgroundPrevention of cardiovascular disease (CVD) is a public health priority. The combination of physical activity, a healthy diet, and abstaining from tobacco plays an important role in prevention whereas aspects of psychosocial well‐being have largely been examined separately with conflicting results. This study evaluated whether the combination of indices of psychosocial well‐being was associated with less progression of coronary artery calcium (CAC).Methods and ResultsParticipants were 312 women (mean age 50.8) from the SWAN (Study of Women’s Health Across the Nation) ancillary Heart Study, free of clinical CVD at baseline. A composite psychosocial well‐being score was created from 6 validated psychosocial questionnaires assessing optimism, vitality, life engagement, life satisfaction, rewarding multiple roles, and positive affect. Subclinical CAC progression was defined as an increase of ≥10 Agatston units over 2.3 years measured using electron beam tomography. Relative risk (RR) regression models examined the effect of well‐being on CAC progression, progressively adjusting for sociodemographic factors, depression, healthy lifestyle behaviors, and standard CVD risk factors. At baseline, 42.9% had a CAC score >0, and progression was observed in 17.6%. Well‐being was associated with less progression (RR, 0.909; 95% CI, 0.843−0.979; P=0.012), which remained significant with adjustment for potential confounders, depression, and health behaviors. Further adjustment for standard CVD risk factors weakened the association for the total sample (RR, 0.943; 95% CI, 0.871−1.020; P=0.142) but remained significant for the 134 women with baseline CAC>0 (RR, 0.921; 95% CI, 0.852−0.995; P=0.037).ConclusionsOptimum early prevention of CVD in women may result from including the mind side of the mind‐heart‐body continuum.

Prediabetes. A new paradigm for early prevention of cardiovascular disease

This literature review focuses on the association of prediabetes with cardiovascular disease (CVD). Recently, much attention has been paid to the study of prediabetes due to its extremely high prevalence and strong association with a high risk of developing serious complications that worsen the quality of kife of patients. Prediabetes is not only a metabolic condition with a high risk of developing type 2 diabetes mellitus (T2DM), but also CVD and death from all causes. This association is true for both patients who do not yet have CVD and those with a history of CVD. Also during the COVID-19 pandemic, attention is drawn to the fact that people with prediabetes have a higher risk of a severe course of infection, complications and a worse prognosis of the disease. This is associated with hyperglycemia, the presence of chronic systemic inflammation of a low degree of activity, impaired immune response mechanisms and a procoagulant state in patients with prediabetes, although these disorders are less developed than in patients with T2DM. Therefore, early screening of early disorders of normal metabolism. Since active early intervention at the stage of prediabetes helps to prevent the development of type 2 diabetes and CVD.

Imbalanced heartbeat classification using EasyEnsemble technique and global heartbeat information

Heartbeat classification, also known as arrhythmia detection, is essential for early prevention of cardiovascular diseases (CVD). However, in clinical, the physician checks the ECG signal beat-by-beat for diagnosis, which is time-consuming and laborious. Recently, some scholars have proposed computer-aided heartbeat classification methods, while these methods mainly focus on using the local information of heartbeat and ignore the role of the global information where the heartbeat is located. Meanwhile, the heartbeat is highly imbalanced, resulting in poor performance in the minority categories of existing methods. Based on these issues, in this study we propose a new method for classifying imbalanced heartbeat using EasyEnsemble technique with global heartbeat information. By testing on the MIT-BIH arrhythmia database using the inter-patient scheme, the experimental results show that the global heartbeat information is useful for heartbeat classification. Meanwhile, compared with the existing methods, our method can not only achieve the best overall performance, but also can significantly improve the performance of minority categories while maintaining the good performance of majority categories.

Short-term and Intermediate-term Fine Particulate Air Pollution are Synergistically Associated with Habitual Sleep Variability in Adolescents

BACKGROUND AND AIM: While both fine particulate (PM2.5) exposure and high sleep variability are potential risk factors for cardiovascular diseases (CVD), the association between PM2.5 and sleep variability remains unclear. Our study aimed at investigating the association between PM2.5 exposure and habitual sleep variability (HSV) in a population-based sample of U.S. adolescents. METHODS: Data obtained from 421 adolescents, who participated in the Penn State Child Cohort follow-up examination, were analyzed. For each participant, we collected 24-hour (i.e. short-term) individual-level PM2.5 exposure by using a personal nephelometer. We further estimated their residential-level PM2.5, during the 60-day period prior to the examination (i.e. intermediate-term), by utilizing a GIS-based kriging approach. Actigraphy was used to collect participants’ total sleep time (TST) for 7 consecutive nights. HSV was calculated as the standard deviation (SD) of the 7-night TST. Multivariable-adjusted linear regression was used to assess the association between PM2.5 exposures and HSV. An interaction between the short- and intermediate-term PM2.5 was created to test their potential synergistic impact on HSV. RESULTS:Both short-term and intermediate-term PM2.5 exposure were significantly (both p0.01) associated with HSV. There was a marginally significant (p=0.08) synergistic interaction between short-term and intermediate-term PM2.5. Specifically, the association between intermediate-term PM2.5 and HSV became stronger as short-term PM2.5 increased, and vice versa. For example, the regression coefficients (SE) between 1 SD (2.2 µg/m3) increase in intermediate-term PM2.5 and HSV were 3.5 (2.7, p=0.21), 5.1 (2.3, p=0.03), and 10.5 (3.4, p0.01) minutes, when short-term PM2.5 were at its 10th percentile (1.7 µg/m3), median (9.7 µg/m3), and 90th percentile (35.3 µg/m3), respectively. CONCLUSIONS:Both short-term and intermediate-term PM2.5 exposure were associated with higher sleep variability among adolescents. More importantly, short-term and intermediate-term PM2.5 exposure may impact sleep variability in a synergistic manner, which highlighted the importance of PM2.5 reduction in the early prevention of CVD. KEYWORDS: Particulate Matter, Sleep Variability, Adolescents

A Novel ECG Automatic Detection Using LongShort-Term Memory Network and Internet of Things Technology

The early detection of cardiovascular diseases based on electrocardiogram (ECG) is very important for the timely treatment of cardiovascular patients, which increases the survival rate of patients. ECG is a visual representation that describes changes in cardiac bioelectricity and is the basis for detecting heart health. With the rise of edge machine learning and Internet of Things (IoT) technologies, small machine learning models have received attention. This study proposes an ECG automatic classification method based on Internet of Things technology and LSTM network to achieve early monitoring and early prevention of cardiovascular diseases. Specifically, this paper first proposes a single-layer bidirectional LSTM network structure. Make full use of the timing-dependent features of the sampling points before and after to automatically extract features. The network structure is more lightweight and the calculation complexity is lower. In order to verify the effectiveness of the proposed classification model, the relevant comparison algorithm is used to verify on the MIT-BIH public data set. Secondly, the model is embedded in a wearable device to automatically classify the collected ECG. Finally, when an abnormality is detected, the user is alerted by an alarm. The experimental results show that the proposed model has a simple structure and a high classification and recognition rate, which can meet the needs of wearable devices for monitoring ECG of patients.

Shared genetic etiology and causality between body fat percentage and cardiovascular diseases: a large-scale genome-wide cross-trait analysis

BackgroundAccumulating evidences have suggested that high body fat percentage (BF%) often occurs in parallel with cardiovascular diseases (CVDs), implying a common etiology between them. However, the shared genetic etiology underlying BF% and CVDs remains unclear.MethodsUsing large-scale genome-wide association study (GWAS) data, we investigated shared genetics between BF% (N = 100,716) and 10 CVD-related traits (n = 6968-977,323) with linkage disequilibrium score regression, multi-trait analysis of GWAS, and transcriptome-wide association analysis, and evaluated causal associations using Mendelian randomization.ResultsWe found strong positive genetic correlations between BF% and heart failure (HF) (Rg = 0.47, P = 1.27 × 10− 22) and coronary artery disease (CAD) (Rg = 0.22, P = 3.26 × 10− 07). We identified 5 loci and 32 gene-tissue pairs shared between BF% and HF, as well as 16 loci and 28 gene-tissue pairs shared between BF% and CAD. The loci were enriched in blood vessels and brain tissues, while the gene-tissue pairs were enriched in the nervous, cardiovascular, and exo-/endocrine system. In addition, we observed that BF% was causally related with a higher risk of HF (odds ratio 1.63 per 1-SD increase in BF%, P = 4.16 × 10–04) using a MR approach.ConclusionsOur findings suggest that BF% and CVDs have shared genetic etiology and targeted reduction of BF% may improve cardiovascular outcomes. This work advances our understanding of the genetic basis underlying co-morbid obesity and CVDs and opens up a new way for early prevention of CVDs.

A prospective cohort study on the associations between vitamin D nutritional status and cardiometabolic abnormities in children

Objective: To investigate the relationships between vitamin D nutritional status and the risks of cardiometabolic abnormities in children. Methods: Data were obtained from the School-based Cardiovascular and Bone Health Promotion Program. In 2017, a total of 15 391 children aged 6-16 years in Beijing were selected by using a stratified cluster sampling method in the baseline survey. A Follow-up investigation was conducted in 2019. Log-binomial regression was used to analyze the relationships between baseline vitamin D nutritional status and the risks of cardiometabolic abnormities (obesity, hypertension, hyperglycemia, and dyslipidemia). Results: A total of 10 482 participants were involved in the study. The average vitamin D level was (35.6 ± 12.0) nmol/L, and the deficiency rate was 35.1%. The 2-year cumulative incidence rates of obesity, hypertension, hyperglycemia, high TC, high LDL-C, low HDL-C, high TG, and high non-HDL-C were 4.3%, 10.8%, 8.5%, 3.1%, 2.5%, 3.4%, 2.5%, and 3.9% respectively. After the adjustment of potential confounding factors, children with vitamin D inadequacy or deficiency had higher risks of high TC [RR (95%CI): inadequacy, 2.06 (1.19-3.58); deficiency, 2.80 (1.61-4.89)], high LDL-C [RR (95%CI): inadequacy, 1.67 (1.02-2.73); deficiency, 1.99 (1.19-3.33)], and high non-HDL-C [RR (95%CI): inadequacy, 2.00 (1.26-3.17); deficiency, 2.45 (1.53-3.92)] compared with children with adequate vitamin D, and the risks of them increased with the decrease of vitamin D level (trend P<0.05). The gender-stratified analysis showed that vitamin D deficiency was remained associated with high TC [RR (95%CI): boy, 2.64 (1.19-5.87); girl, 3.13 (1.43-6.83)] and high non-HDL-C [RR (95%CI): boy, 2.58(1.40-4.77); girl, 2.31 (1.10-4.84)]. Conclusions: The risks of abnormal TC, LDL-C, and non-HDL-C were inversely associated with vitamin D level. Maintenance of adequate vitamin D status in children may contribute to the early prevention of cardiovascular diseases.

The importance of cardiorespiratory fitness and sleep duration in early CVD prevention: BMI, resting heart rate and questions about sleep patterns are suggested in risk assessment of young adults, 18\u201325 years

BackgroundCardiorespiratory fitness (CRF) and sleep habits are lifestyle factors with potential to prevent cardiovascular disease (CVD). CVD is the leading cause of death worldwide. It is therefore important to establish a healthy lifestyle at a young age. In the Lifestyle, Biomarkers and Atherosclerosis (LBA) study we have examined 834 healthy non-smoking adults, aged 18–25 years. The general purpose of the LBA study was to study the effect of lifestyle on traditional biomarkers known to influence CVD risk. The aims of the present study were to evaluate sleep habits of young adult women and men participating in the LBA study, and to compare the importance of sleep and other lifestyle habits on clinically relevant biomarkers for CVD. An additional aim was to find easy and reliable non-invasive biomarkers to detect young adults with increased risk of developing CVD later in life.MethodsThe participants had previously been examined for lifestyle factors, biomarkers and CVD risk score. They filled in a validated computerized questionnaire about their general physical and mental health. The questionnaire included questions on sleep duration and experienced quality of sleep.ResultsIn total 27% of the young adult participants reported difficulties falling asleep or experienced troubled sleep with frequent awakenings per night. The experienced troubled sleep was not related to a higher CVD risk score, but sleep quality and duration were correlated. Shorter sleep duration was significantly associated to higher body mass index (BMI), body fat (%), homeostasis model assessment of insulin resistance (HOMA-IR) and CVD risk. The modifiable lifestyle factor with the highest odds ratio (OR) for CVD risk was CRF. Sleep duration was the second most influential lifestyle factor, more important than moderate- and vigorous physical activity (MVPA) and food habits. Correlations between CRF and heart rate (HR), (P < 0.01) and HOMA-IR and BMI (P < 0.01) were observed, indicating that BMI and resting HR in combination with questions about sleep patterns are easy and reliable non-invasive biomarkers to detect young adults who need counselling on a healthy lifestyle.ConclusionDecreased sleep duration in combination with decreased CRF, in young adults, is a serious health issue.