Cardiovascular diseases and malignant neoplasms — what do they have in common?

Atherosclerosis is an inflammatory disease and the major cause of cardiovascular disease (CVD) in general. Atherosclerotic plaques are characterized by the presence of activated immune competent cells, but antigens and underlying mechanisms causing this immune activation are not well defined. During recent years and with improved treatment of acute disease manifestations, it has become clear that the risk of CVD is very high in a prototypic autoimmune disease, systemic lupus erythematosus (SLE). SLE-related CVD and atherosclerosis are important clinical problems but may in addition also shed light on how immune reactions are related to premature atherosclerosis and atherothrombosis. A combination of traditional and nontraditional risk factors, including dyslipidaemia (and to a varying degree hypertension, diabetes and smoking), inflammation, antiphospholipid antibodies (aPL) and lipid oxidation are related to CVD in SLE. Premature atherosclerosis in some form leading to atherothrombosis is likely to be a major underlying mechanism, though distinctive features if any, of SLE-related atherosclerosis when compared with 'normal' atherosclerosis are not clear. One interesting possibility is that factors such as inflammation or aPL make atherosclerotic lesions in autoimmune disease more prone to rupture than in 'normal' atherosclerosis. Whether premature atherosclerosis is a general feature of SLE or only affects a subgroup of patients remains to be demonstrated. Treatment of SLE patients should also include a close monitoring of traditional risk factors for CVD. In addition, attention should also be paid to nontraditional risk factors such as inflammation and SLE-related factors such as aPL. Hopefully novel therapeutic principles will be developed that target the causes of the inflammation and immune reactions present in atherosclerotic lesions.

Growing evidence supports a strong and likely causal association between cardiovascular disease (CVD), and its risk factors, with incidence of cognitive decline and Alzheimer's disease. Individuals with subclinical CVD are at higher risk for dementia and Alzheimer's. Several cardiovascular risk factors are also risk factors for dementia, including hypertension, high LDL cholesterol, low HDL cholesterol and especially diabetes. Moderate alcohol appears to be protective for both CVD and dementia. In contrast, inflammatory markers predict cardiovascular risk, but not dementia, despite biological plausibility for such a link. The substantial overlap in risk factors points to new avenues for research and prevention.

Sleep-disordered breathing (SDB), which includes obstructive sleep apnea (OSA) as its most extreme variant, is characterized by intermittent episodes of partial or complete obstruction of the upper airway during sleep that disrupts normal ventilation and sleep architecture and is typically associated with snoring and daytime sleepiness. SDB is common, with an incidence in middle-aged men and women of 4% and 2%, respectively.1 Major risk factors for SDB include obesity, male gender, increasing age, and abnormalities of craniofacial morphology.2 There is an increasing perception that SDB/OSA via various mechanisms increases cardiovascular morbidity and mortality (Figure 1). However, many risk factors for SDB/OSA, such as obesity and male gender, are the same as for hypertension and cardiovascular disease.3 Thus, only recently has there been converging evidence that SDB is a risk factor for their development.4–6 Moreover, there is increasing information to indicate that SDB/OSA is linked to metabolic, vascular, hematologic, and genetic markers associated with increased cardiovascular disease risk. In addition, central sleep apnea (CSA), another form of SDB, appears to be an important factor that influences morbidity and mortality among those with heart failure (HF). Nevertheless, responsible mechanisms, the role of SDB as a risk factor “independent” of associated comorbidities, and whether treatment of SDB will mitigate this risk are unknown and remain to be determined. Figure 1. This illustrates the range of cardiovascular diseases and potential mechanisms that may be associated with sleep-disordered breathing. As illustrated in this figure, there is likely an interaction between multiple potential mechanisms, particularly in individuals who may have a genetic susceptibility for sleep-disordered breathing. This report summarizes the proceedings of a workshop sponsored by the National Center on Sleep Disorders Research and the National Heart, Lung, and Blood Institute on September 12 to 13, 2002, to assess a broad array …

ObjectiveTo estimate the incidence of major biological cardiovascular disease (CVD) risk factors in adults using non-exercise estimated cardiorespiratory fitness (eCRF).Methods200 039 healthy people (99 957 women), aged ≥18 years (38.5±12.1...

To the Editor: Recently, an update from the Framingham study could not find uric acid to be an independent risk factor for cardiovascular disease.1 While serum uric acid levels correlated significantly with the risk for cardiovascular events and mortality in women, this relationship became insignificant after factoring for 11 additional variables including hypertension, body mass index, and diuretic use.1 Both the authors1 and an accompanying editorial2 interpreted these findings as showing that uric acid is not a true risk factor for cardiovascular disease and that it should not be routinely measured to assess cardiovascular risk. The careful analysis of the Framingham study is to be commended, but one must be cautious in the interpretation of the findings. While some epidemiologic studies such as the current one have not been able to show uric acid to be an independent risk factor for cardiovascular disease, other studies using multivariate analyses3 4 5 6 came to an opposite conclusion. Another recently completed study, the Worksite,7 also found uric acid to be an independent risk factor for cardiovascular events and mortality, especially in women. One might look for subtle explanations to account for the differences in these various studies, as Culleton et al1 have attempted, but most of the studies examined the very same variables. A more central issue is whether one should interpret the finding that a risk factor is not statistically independent to mean that it should not be considered biologically important. We would argue that this is not true in several situations. First, if the risk factors are causally linked, then one may not be able to show that they are independent of each other. For example, although smoking is a risk factor for mortality, it might no longer be independent if it is …

In 2009, President Obama signed an Executive Order calling for strategies to improve the health of Asian Americans and to seek data on the health disparities in Asian American subgroups.1 Data on Asian American subgroups are scarce and many health disparities remain unknown. The purpose of this Advisory is to highlight the gaps in existing research on cardiovascular disease (CVD) among Asian Americans, and to serve as a call to action on behalf of the American Heart Association to address these areas of need. Asian Americans are the fastest growing racial/ethnic group in the United States, representing 25% of all foreign-born people in the United States.2 They are projected to reach nearly 34 million by 2050.3 Several major Federal surveys (eg, the American Community Survey, the National Health Interview Survey, and the Behavioral Risk Factor Surveillance Survey) only recently started to classify Asian Americans into 7 subgroups: Asian Indian, Chinese, Filipino, Korean, Japanese, Vietnamese, and Other Asian. The first six of these subgroups together constitute >90% of Asian Americans in the United States.4 Although some data are available on Asian subgroups from these major federal surveys, in general, these data are not available for public use because of the privacy concerns resulting from the small sample sizes within subgroups. This situation limits their utility for health-related research. Because health surveys and questionnaires almost universally combine persons of Asian ancestry into a single group, the heterogeneity within this classification is masked. Socioeconomic and cultural factors have been found to be associated with CVD and its risk factors, which is why it is important to understand these differences among Asian subgroups. The Table shows the number of persons in each group based on the most recent US Census data available (American Community Survey, 2008), with the recognition that …

Guest editorial: hypertension and kidney disease

BackgroundThe use of mobile health (mHealth) interventions, including smartphone apps, for the prevention of cardiovascular disease (CVD) has demonstrated mixed results for obesity, hypercholesterolemia, diabetes, and hypertension management. A major factor attributing to the variation in mHealth study results may be mHealth user engagement.ObjectiveThis systematic review aims to determine if user engagement with smartphone apps for the prevention and management of CVD is associated with improved CVD health behavior change and risk factor outcomes.MethodsWe conducted a comprehensive search of PubMed, CINAHL, and Embase databases from 2007 to 2020. Studies were eligible if they assessed whether user engagement with a smartphone app used by an individual to manage his or her CVD risk factors was associated with the CVD health behavior change or risk factor outcomes. For eligible studies, data were extracted on study and sample characteristics, intervention description, app user engagement measures, and the relationship between app user engagement and the CVD risk factor outcomes. App user engagement was operationalized as general usage (eg, number of log-ins or usage days per week) or self-monitoring within the app (eg, total number of entries made in the app). The quality of the studies was assessed.ResultsOf the 24 included studies, 17 used a randomized controlled trial design, 4 used a retrospective analysis, and 3 used a single-arm pre- and posttest design. Sample sizes ranged from 55 to 324,649 adults, with 19 studies recruiting participants from a community setting. Most of the studies assessed weight loss interventions, with 6 addressing additional CVD risk factors, including diabetes, sleep, stress, and alcohol consumption. Most of the studies that assessed the relationship between user engagement and reduction in weight (9/13, 69%), BMI (3/4, 75%), body fat percentage (1/2, 50%), waist circumference (2/3, 67%), and hemoglobin A1c (3/5, 60%) found statistically significant results, indicating that greater app user engagement was associated with better outcomes. Of 5 studies, 3 (60%) found a statistically significant relationship between higher user engagement and an increase in objectively measured physical activity. The studies assessing the relationship between user engagement and dietary and diabetes self-care behaviors, blood pressure, and lipid panel components did not find statistically significant results.ConclusionsIncreased app user engagement for prevention and management of CVD may be associated with improved weight and BMI; however, only a few studies assessed other outcomes, limiting the evidence beyond this. Additional studies are needed to assess user engagement with smartphone apps targeting other important CVD risk factors, including dietary behaviors, hypercholesterolemia, diabetes, and hypertension. Further research is needed to assess mHealth user engagement in both inpatient and outpatient settings to determine the effect of integrating mHealth interventions into the existing clinical workflow and on CVD outcomes.

Background: Cardiovascular disease (CVD) risk factors tend to cluster and progress from adolescence to young adulthood. Reliable and meaningful clustering of CVD risk factors is essential to circumvent loss of information. Tracking adverse and high-risk profiles of adolescents is hoped to curb CVD progression later in life. The study aims to investigate the clustering of biological CVD risk factor among adolescents in Malaysia and the transitions between clusters over time.Method: The Malaysian Health and Adolescents Longitudinal Research Team study (MyHeARTs) examined school students aged 13 in 2012 and re-examined them in 2014 and 2016. In a two-stage stratified cluster sampling, 1,361 students were recruited, of which, 1,320 had complete data. In the follow-up, there were 881 and 637 students in 2014 and in 2016, respectively. Pearson's correlation coefficients were used to identify and remove highly correlated CVD risk factors. All risk factors were standardized into z-scores. The hierarchical and non-hierarchical (k-means) cluster analyses were used to classify students into high, medium and low risk clusters in each screening year. The tracking and stability of cluster transitions through cross-classification were enumerated with Pearson's inter-age correlations and percentages.Results: Three significant clusters of high, medium and low risk groups were derived from the clustering of eight biological CVD risk factors. The transitions between risk clusters from one screening year to the other were categorized as either stagnant, improved or adverse. The number of students who had adverse transitions increased from 15.5% (13–15 year) to 19.5% (15–17 year), 13.8 to 18.2% among the girls and 19.9 to 22.8% among the boys. For girls, the number of them who remained at high risk over the two transition periods were about the same (13.6 vs. 13.8%) whereas for boys, the percentage reduced from 14.6 to 12.3%.Conclusion: Over time, more than 12% of adolescents remained in the high risk cluster. There were sizable adverse transitions over time as more adolescents appear to be shifting toward an increased risk of having CVD. Collaborative and constant measures should be taken by parents, school, health promotion boards and policy makers to curb the multiplicative effect of clustering CVD risk factors among adolescents.

Cognitive impairment in chronic kidney disease: keep vascular disease in mind

Novel data on the pathogenesis of atherosclerosis, treatment targets, and new therapeutic interventions in lipid-related cardiovascular risk factors.

BackgroundThere is limited evidence on whether having pre-existing cardiovascular disease (CVD) or risk factors for CVD such as diabetes, ensures greater knowledge of risk factors important for motivating preventative behaviours. Our objective was to compare knowledge among the Australian public participating in a health check program and their risk status.MethodsData from the Stroke Foundation ‘Know your numbers’ program were used. Staff in community pharmacies provided opportunistic health checks (measurement of blood pressure and diabetes risk assessment) among their customers. Participants were categorised: 1) CVD ± risk of CVD: history of stroke, heart disease or kidney disease, and may have risk factors; 2) risk of CVD only: reported having high blood pressure, high cholesterol, diabetes or atrial fibrillation; and 3) CVD risk free (no CVD or risk of CVD). Multivariable logistic regression analyses were performed including adjustment for age and sex.FindingsAmong 4,647 participants, 12% had CVD (55% male, 85% aged 55+ years), 47% were at risk of CVD (40% male, 72% 55+ years) and 41% were CVD risk free (33% male, 27% 55+ years). Participants with CVD (OR: 0.66; 95% CI: 0.55, 0.80) or risk factors for CVD (OR: 0.65; 95% CI: 0.57, 0.73) had poorer knowledge of the risk factors for diabetes/CVD compared to those who were CVD risk free. After adjustment, only participants with risk factors for CVD (OR: 0.80; 95% CI: 0.69, 0.93) had poorer knowledge. Older participants (55+ years) and men had poorer knowledge of diabetes/CVD risk factors and complications of diabetes.ConclusionsParticipants with poorer knowledge of risk factors were older, more often male or were at risk of developing CVD compared with those who were CVD risk free. Health education in these high risk groups should be a priority, as diabetes and CVD are increasing in prevalence throughout the world.

Ischemia-modified albumin and cardiovascular risk markers in polycystic ovary syndrome with or without insulin resistance

Cardiovascular Disease in Children with Chronic Kidney Disease

This statement examines the cardiovascular complications of diabetes mellitus and considers opportunities for their prevention. These complications include coronary heart disease (CHD), stroke, peripheral arterial disease, nephropathy, retinopathy, and possibly neuropathy and cardiomyopathy. Because of the aging of the population and an increasing prevalence of obesity and sedentary life habits in the United States, the prevalence of diabetes is increasing. Thus, diabetes must take its place alongside the other major risk factors as important causes of cardiovascular disease (CVD). In fact, from the point of view of cardiovascular medicine, it may be appropriate to say, “diabetes is a cardiovascular disease.” The most prevalent form of diabetes mellitus is type 2 diabetes. This disorder typically makes its appearance later in life. The underlying metabolic causes of type 2 diabetes are the combination of impairment in insulin-mediated glucose disposal (insulin resistance) and defective secretion of insulin by pancreatic β-cells. Insulin resistance develops from obesity and physical inactivity, acting on a substrate of genetic susceptibility.1 2 Insulin secretion declines with advancing age,3 4 and this decline may be accelerated by genetic factors.5 6 Insulin resistance typically precedes the onset of type 2 diabetes and is commonly accompanied by other cardiovascular risk factors: dyslipidemia, hypertension, and prothrombotic factors.7 8 The common clustering of these risk factors in a single individual has been called the metabolic syndrome. Many patients with the metabolic syndrome manifest impaired fasting glucose (IFG)9 even when they do not have overt diabetes mellitus.10 The metabolic syndrome commonly precedes the development of type 2 diabetes by many years11 ; of great importance, the risk factors that constitute this syndrome contribute independently to CVD risk. Recently, new criteria have been accepted for the diagnosis of diabetes.9 The upper threshold of fasting plasma glucose for the …