Development and validation of a lifetime prediction model for incident type 2 diabetes in patients with established cardiovascular disease: the CVD2DM model.

AIMS: Identifying patients with established cardiovascular disease (CVD) who are at high risk of type 2 diabetes (T2D) may allow for early interventions, reducing the development of T2D and associated morbidity. The aim of this study was to develop and externally validate the CVD2DM model to estimate the 10-year and lifetime risks of T2D in patients with established CVD. METHODS AND RESULTS: Sex-specific, competing risk-adjusted Cox proportional hazard models were derived in 19 281 participants with established CVD and without diabetes at baseline from the UK Biobank. The core model's pre-specified predictors were age, current smoking, family history of diabetes mellitus, body mass index, systolic blood pressure, fasting plasma glucose, and HDL cholesterol. The extended model also included HbA1c. The model was externally validated in 3481 patients from the UCC-SMART study. During a median follow-up of 12.2 years (interquartile interval 11.3-13.1), 1628 participants with established CVD were diagnosed with T2D in the UK Biobank. External validation c-statistics were 0.79 [95% confidence interval (CI) 0.76-0.82] for the core model and 0.81 (95% CI 0.78-0.84) for the extended model. Calibration plots showed agreement between predicted and observed 10-year risk of T2D. CONCLUSION: The 10-year and lifetime risks of T2D can be estimated with the CVD2DM model in patients with established CVD, using readily available clinical predictors. The model would benefit from further validation across diverse ethnic groups to enhance its applicability. Informing patients about their T2D risk could motivate them further to adhere to a healthy lifestyle.

In this study, we developed and externally validated the CVD2DM model, which predicts the 10-year and lifetime risk of type 2 diabetes (T2D) in individuals who already have cardiovascular disease (CVD). The key findings are as follows: The CVD2DM model is the first model to estimate the risk of developing T2D applicable in all patients with atherosclerotic CVD. The model is based on several factors available in clinical practice, such as age, fasting plasma glucose, family history of diabetes, and body mass index. It was developed in 19 281 patients from the UK Biobank. The model performed well in 3481 patients from the UCC-SMART study.Informing patients about their T2D risk could motivate them further to adhere to a healthy lifestyle.

Improving 10-year cardiovascular risk prediction in apparently healthy people: flexible addition of risk modifiers on top of SCORE2.

AIMS: In clinical practice, factors associated with cardiovascular disease (CVD) like albuminuria, education level, or coronary artery calcium (CAC) are often known, but not incorporated in cardiovascular risk prediction models. The aims of the current study were to evaluate a methodology for the flexible addition of risk modifying characteristics on top of SCORE2 and to quantify the added value of several clinically relevant risk modifying characteristics. METHODS AND RESULTS: Individuals without previous CVD or DM were included from the UK Biobank; Atherosclerosis Risk in Communities (ARIC); Multi-Ethnic Study of Atherosclerosis (MESA); European Prospective Investigation into Cancer, The Netherlands (EPIC-NL); and Heinz Nixdorf Recall (HNR) studies (n = 409 757) in whom 16 166 CVD events and 19 149 non-cardiovascular deaths were observed over exactly 10.0 years of follow-up. The effect of each possible risk modifying characteristic was derived using competing risk-adjusted Fine and Gray models. The risk modifying characteristics were applied to individual predictions with a flexible method using the population prevalence and the subdistribution hazard ratio (SHR) of the relevant predictor. Risk modifying characteristics that increased discrimination most were CAC percentile with 0.0198 [95% confidence interval (CI) 0.0115; 0.0281] and hs-Troponin-T with 0.0100 (95% CI 0.0063; 0.0137). External validation was performed in the Clinical Practice Research Datalink (CPRD) cohort (UK, n = 518 015, 12 675 CVD events). Adjustment of SCORE2-predicted risks with both single and multiple risk modifiers did not negatively affect calibration and led to a modest increase in discrimination [0.740 (95% CI 0.736-0.745) vs. unimproved SCORE2 risk C-index 0.737 (95% CI 0.732-0.741)]. CONCLUSION: The current paper presents a method on how to integrate possible risk modifying characteristics that are not included in existing CVD risk models for the prediction of CVD event risk in apparently healthy people. This flexible methodology improves the accuracy of predicted risks and increases applicability of prediction models for individuals with additional risk known modifiers.

Heart disease is a major health concern worldwide, and predicting an individual's risk for developing heart disease is an important tool for prevention. Current risk prediction models often use factors such as age, gender, smoking, and blood pressure, but other factors like education level, albuminuria (protein in the urine), and coronary artery calcium (CAC) may also affect an individual's risk. The aim of this study was to develop a new method for using these additional risk factors for predicting risk even more accurately. The researchers used data from several large studies that included over 400 000 apparently healthy individuals who were followed for 10 years. They examined the effect of various risk factors on cardiovascular disease (CVD) risk using a statistical model. They found that adding coronary scan ('CAC score'); NT-proBNP, a biomarker of heart strain; and hs-Troponin-T, a marker of heart damage, to the existing risk prediction model (SCORE2) improved the accuracy of predicted CVD risk. The key findings are: The methods presented in the current study can help to add additional risk factors to predictions of existing models, such as SCORE2. This flexible method may help identify individuals who are at higher risk for CVD and guide prevention strategies.

Evaluation of Epigenetic Age Acceleration Scores and Their Associations with CVD-Related Phenotypes in a Population Cohort.

We evaluated associations between nine epigenetic age acceleration (EAA) scores and 18 cardiometabolic phenotypes using an Eastern European ageing population cohort richly annotated for a diverse set of phenotypes (subsample, n = 306; aged 45-69 years). This was implemented by splitting the data into groups with positive and negative EAAs. We observed strong association between all EAA scores and sex, suggesting that any analysis of EAAs should be adjusted by sex. We found that some sex-adjusted EAA scores were significantly associated with several phenotypes such as blood levels of gamma-glutamyl transferase and low-density lipoprotein, smoking status, annual alcohol consumption, multiple carotid plaques, and incident coronary heart disease status (not necessarily the same phenotypes for different EAAs). We demonstrated that even after adjusting EAAs for sex, EAA-phenotype associations remain sex-specific, which should be taken into account in any downstream analysis involving EAAs. The obtained results suggest that in some EAA-phenotype associations, negative EAA scores (i.e., epigenetic age below chronological age) indicated more harmful phenotype values, which is counterintuitive. Among all considered epigenetic clocks, GrimAge was significantly associated with more phenotypes than any other EA scores in this Russian sample.

Going upstream - an umbrella review of the macroeconomic determinants of health and health inequalities.

BACKGROUND: The social determinants of health have been widely recognised yet there remains a lack of clarity regarding what constitute the macro-economic determinants of health and what can be done to address them. An umbrella review of systematic reviews was conducted to identify the evidence for the health and health inequalities impact of population level macroeconomic factors, strategies, policies and interventions. METHODS: Nine databases were searched for systematic reviews meeting the Database of Abstracts of Reviews of Effects (DARE) criteria using a novel conceptual framework. Studies were assessed for quality using a standardised instrument and a narrative overview of the findings is presented. RESULTS: The review found a large (n = 62) but low quality systematic review-level evidence base. The results indicated that action to promote employment and improve working conditions can help improve health and reduce gender-based health inequalities. Evidence suggests that market regulation of tobacco, alcohol and food is likely to be effective at improving health and reducing inequalities in health including strong taxation, or restriction of advertising and availability. Privatisation of utilities and alcohol sectors, income inequality, and economic crises are likely to increase health inequalities. Left of centre governments and welfare state generosity may have a positive health impact, but evidence on specific welfare interventions is mixed. Trade and trade policies were found to have a mixed effect. There were no systematic reviews of the health impact of monetary policy or of large economic institutions such as central banks and regulatory organisations. CONCLUSIONS: The results of this study provide a simple yet comprehensive framework to support policy-makers and practitioners in addressing the macroeconomic determinants of health. Further research is needed in low and middle income countries and further reviews are needed to summarise evidence in key gaps identified by this review. TRIAL REGISTRATION: Protocol for umbrella review prospectively registered with PROSPERO CRD42017068357.

Understanding the consequences of education inequality on cardiovascular disease: mendelian randomisation study.

OBJECTIVES: To investigate the role of body mass index (BMI), systolic blood pressure, and smoking behaviour in explaining the effect of education on the risk of cardiovascular disease outcomes. DESIGN: Mendelian randomisation study. SETTING: UK Biobank and international genome-wide association study data. PARTICIPANTS: Predominantly participants of European ancestry. EXPOSURE: Educational attainment, BMI, systolic blood pressure, and smoking behaviour in observational analysis, and randomly allocated genetic variants to instrument these traits in mendelian randomisation. MAIN OUTCOMES MEASURE: The risk of coronary heart disease, stroke, myocardial infarction, and cardiovascular disease (all subtypes; all measured in odds ratio), and the degree to which this is mediated through BMI, systolic blood pressure, and smoking behaviour respectively. RESULTS: Each additional standard deviation of education (3.6 years) was associated with a 13% lower risk of coronary heart disease (odds ratio 0.86, 95% confidence interval 0.84 to 0.89) in observational analysis and a 37% lower risk (0.63, 0.60 to 0.67) in mendelian randomisation analysis. As a proportion of the total risk reduction, BMI was estimated to mediate 15% (95% confidence interval 13% to 17%) and 18% (14% to 23%) in the observational and mendelian randomisation estimates, respectively. Corresponding estimates were 11% (9% to 13%) and 21% (15% to 27%) for systolic blood pressure and 19% (15% to 22%) and 34% (17% to 50%) for smoking behaviour. All three risk factors combined were estimated to mediate 42% (36% to 48%) and 36% (5% to 68%) of the effect of education on coronary heart disease in observational and mendelian randomisation analyses, respectively. Similar results were obtained when investigating the risk of stroke, myocardial infarction, and cardiovascular disease. CONCLUSIONS: BMI, systolic blood pressure, and smoking behaviour mediate a substantial proportion of the protective effect of education on the risk of cardiovascular outcomes and intervening on these would lead to reductions in cases of cardiovascular disease attributable to lower levels of education. However, more than half of the protective effect of education remains unexplained and requires further investigation.

Education and coronary heart disease: mendelian randomisation study.

Objective To determine whether educational attainment is a causal risk factor in the development of coronary heart disease.Design Mendelian randomisation study, using genetic data as proxies for education to minimise confounding.Setting The main analysis used genetic data from two large consortia (CARDIoGRAMplusC4D and SSGAC), comprising 112 studies from predominantly high income countries. Findings from mendelian randomisation analyses were then compared against results from traditional observational studies (164 170 participants). Finally, genetic data from six additional consortia were analysed to investigate whether longer education can causally alter the common cardiovascular risk factors.Participants The main analysis was of 543 733 men and women (from CARDIoGRAMplusC4D and SSGAC), predominantly of European origin.Exposure A one standard deviation increase in the genetic predisposition towards higher education (3.6 years of additional schooling), measured by 162 genetic variants that have been previously associated with education.Main outcome measure Combined fatal and non-fatal coronary heart disease (63 746 events in CARDIoGRAMplusC4D).Results Genetic predisposition towards 3.6 years of additional education was associated with a one third lower risk of coronary heart disease (odds ratio 0.67, 95% confidence interval 0.59 to 0.77; P=3×10-8). This was comparable to findings from traditional observational studies (prevalence odds ratio 0.73, 0.68 to 0.78; incidence odds ratio 0.80, 0.76 to 0.83). Sensitivity analyses were consistent with a causal interpretation in which major bias from genetic pleiotropy was unlikely, although this remains an untestable possibility. Genetic predisposition towards longer education was additionally associated with less smoking, lower body mass index, and a favourable blood lipid profile.Conclusions This mendelian randomisation study found support for the hypothesis that low education is a causal risk factor in the development of coronary heart disease. Potential mechanisms could include smoking, body mass index, and blood lipids. In conjunction with the results from studies with other designs, these findings suggest that increasing education may result in substantial health benefits.

Framing the tax and health nexus: a neglected aspect of public health concern.

Previous studies have described various associations between tax policy and health. Here we propose a unifying conceptual framework of 'Five R's' to stimulate awareness about the importance of tax to health improvement. First, tax can improve representation and democratic accountability, and help make governments more responsive to the needs of its citizens. Second, tax can create a revenue stream for a universal pool of public finance for health care and other public services. Third, progressive taxation when combined with appropriate public spending can help redistribute wealth and income and mitigate social and health inequalities. Fourth, the re-pricing of harmful products (e.g. tobacco, alcohol and unhealthy food) can help reduce their consumption. Fifth, taxation provides a route by which certain harmful industries can be regulated. The paper also discusses the barriers that hinder the full potential for taxation to be used to improve health, including: weak tax administrations, large 'shadow economies', international trade liberalisation, tax avoidance, transfer pricing by transnational corporations and banking secrecy. We suggest that a greater awareness of the manifold associations between tax and health will encourage health practitioners to actively promote fairer and better taxation, thereby helping to improve health and reduce health inequalities.

Knowledge gaps and acceptability of abbreviated alcohol screening in general practice: a cross-sectional survey of hazardous and non-hazardous drinkers.

BACKGROUND: General practice provides a unique setting where hazardous alcohol consumption can be screened for and behavioural interventions can be implemented in a continuous care model. Our aim was to assess in a general practice population, the prevalence of hazardous drinking, the knowledge and attitudes surrounding alcohol, and the acceptability of brief interventions in alcohol. METHODS: A cross-sectional survey in a practice in South London, performed as part of a wider service evaluation. Questionnaires were offered to adult patients awaiting their appointments. Responses were stratified according to hazardous drinking, as per the abbreviated 'Alcohol Use Disorders Identification Test' (AUDIT-C). RESULTS: Of 179 respondents (30 % male), 34 % yielded an AUDIT-C ≥5 and 18 % reported that they never drink alcohol. Male and Caucasian patients were more likely to self-report hazardous drinking, who in turn were more likely to believe in the health benefits of moderate consumption. Little over half of patents thought that alcohol is a risk factor for cancer and were misinformed of its calorific content, suggesting two targets for future improvement. Patients' knowledge about what is a single 'unit' of alcohol was below that expected by random chance 66 % agreed that alcohol screening should feature in all GP consultations. CONCLUSIONS: While awareness of alcohol related health risks is generally good, future efforts may benefit from focusing on the association with cancer and calories. Our findings question the utility of the 'unit' system, as well as dissemination of suggested 'health benefits' of moderate consumption. General practice initiatives in screening and brief advice for alcohol deserve further study.