Association between clinically recorded alcohol consumption and initial presentation of 12 cardiovascular diseases: population based cohort study using linked health records

Alcohol consumption, cigarette smoking and incidence of aortic valve stenosis

BACKGROUND

Alcohol consumption and cigarette smoking are modifiable lifestyle factors with important impact on public health. It is unclear whether these factors influence the risk of aortic valve stenosis (AVS).

OBJECTIVE

To investigate the associations of alcohol consumption and smoking, including smoking intensity and time since cessation, with AVS incidence in two prospective cohorts.

METHODS

This analysis was based on data from the Swedish Mammography Cohort and the Cohort of Swedish Men, comprising 69 365 adults without cardiovascular disease at baseline. Participants were followed for AVS incidence and death by linkage to the Swedish National Patient and Causes of Death Registers. Hazard ratios (HR) with 95% confidence intervals (CI) were estimated by Cox proportional hazards regression.

RESULTS

Over a mean follow-up of 15.3 years, 1249 cases of AVS (494 in women and 755 in men) were recorded. Compared with never drinkers of alcohol (lifelong abstainers), the risk of AVS was significantly lower in current light drinkers (1-6 drinks per week [1 drink = 12 g alcohol]; multivariable HR 0.82; 95% CI: 0.68-0.99). The risk of AVS increased with increasing smoking intensity. Compared with never smokers, the HR was 1.46 (95% CI: 1.16-1.85) in current smokers of ≥30 pack-years. Former smokers who had quit smoking 10 or more years previously had similar risk for AVS as never smokers.

CONCLUSIONS

This study suggests that current light alcohol consumption is associated with a lower risk of AVS, and indicates that the association between smoking and AVS risk is reversible.

Challenges for learning health systems in the NHS. Case study: electronic health records in cardiology

Electronic health records (EHRs) are at the centre of advances in health informatics, but also many other innovations in healthcare. However, there are still obstacles to implementation and realisation of the full potential of EHRs as there are with learning health systems (LHS). Cardiovascular disease, in the UK and globally, carries greater morbidity and mortality than any other disease. Therefore, planning and delivery of health services represent major costs to individuals and populations. Both the scale of disease burden and the growing role of technology in cardiology practice make analysis of experiences with EHRs in cardiology a useful lens through which to view achievements and gaps to date. In this article regarding LHS, EHRs in cardiology are used as a case study of LHS in the NHS.

Gene-Dairy Food Interactions and Health Outcomes: A Review of Nutrigenetic Studies

Each person differs from the next by an average of over 3 million genetic variations in their DNA. This genetic diversity is responsible for many of the interindividual differences in food preferences, nutritional needs, and dietary responses between humans. The field of nutrigenetics aims to utilize this type of genetic information in order to personalize diets for optimal health. One of the most well-studied genetic variants affecting human dietary patterns and health is the lactase persistence mutation, which enables an individual to digest milk sugar into adulthood. Lactase persistence is one of the most influential Mendelian factors affecting human dietary patterns to occur since the beginning of the Neolithic Revolution. However, the lactase persistence mutation is only one of many mutations that can influence the relationship between dairy intake and disease risk. The purpose of this review is to summarize the available nutrigenetic literature investigating the relationships between genetics, dairy intake, and health outcomes. Nonetheless, the understanding of an individual’s nutrigenetic responses is just one component of personalized nutrition. In addition to nutrigenetic responses, future studies should also take into account nutrigenomic responses (epigenomic, transcriptomic, proteomic, metabolomic), and phenotypic/characteristic traits (age, gender, activity level, disease status, etc.), as these factors all interact with diet to influence health.

Ethnicity and the first diagnosis of a wide range of cardiovascular diseases: Associations in a linked electronic health record cohort of 1 million patients

BACKGROUND

While the association of ethnic group with individual cardiovascular diseases has been studied, little is known about ethnic differences in the initial lifetime presentation of clinical cardiovascular disease in contemporary populations.

METHODS AND RESULTS

We studied 1,068,318 people, aged ≥30 years and free from diagnosed CVD at baseline (90.9% White, 3.6% South Asian and 2.9% Black), using English linked electronic health records covering primary care, hospital admissions, acute coronary syndrome registry and mortality registry (CALIBER platform). During 5.7 years median follow-up between 1997-2010, 95,224 people experienced an incident cardiovascular diagnosis. 69.9% (67.2%-72.4%) of initial presentation in South Asian <60 yrs were coronary heart disease presentations compared to 47.8% (47.3%-48.3%) in White and 40.1% (36.3%-43.9%) in Black patients. Compared to White patients, Black patients had significantly lower age-sex adjusted hazard ratios (HRs) for initial lifetime presentation of all the coronary disease diagnoses (stable angina HR 0.80 (95% CI 0.68-0.93); unstable angina- 0.75 (0.59-0.97); myocardial infarction 0.49 (0.40-0.62)) while South Asian patients had significantly higher HRs (stable angina- 1.67 (1.52-1.84); unstable angina 1.82 (1.56-2.13); myocardial infarction- 1.67 (1.49-1.87). We found no ethnic differences in initial presentation with heart failure (Black 0.97 (0.79-1.20); S Asian 1.04(0.87-1.26)). Compared to White patients, Black patients were more likely to present with ischaemic stroke (1.24 (0.97-1.58)) and intracerebral haemorrhage (1.44 (0.97-2.12)). Presentation with peripheral arterial disease was less likely for Black (0.63 (0.50-0.80)) and South Asian patients (0.70 (0.57-0.86)) compared with White patients.

DISCUSSION

While we found the anticipated substantial predominance of coronary heart disease presentations in South Asian and predominance of stroke presentations in Black patients, we found no ethnic differences in presentation with heart failure. We consider the public health and research implications of our findings.

TRIAL REGISTRATION

NCT02176174, www.clinicaltrials.gov.

Alcohol and cardiovascular disease

Big data puts the link between moderate drinking and lower risk under the microscope

Methods for enhancing the reproducibility of biomedical research findings using electronic health records

BACKGROUND

The ability of external investigators to reproduce published scientific findings is critical for the evaluation and validation of biomedical research by the wider community. However, a substantial proportion of health research using electronic health records (EHR), data collected and generated during clinical care, is potentially not reproducible mainly due to the fact that the implementation details of most data preprocessing, cleaning, phenotyping and analysis approaches are not systematically made available or shared. With the complexity, volume and variety of electronic health record data sources made available for research steadily increasing, it is critical to ensure that scientific findings from EHR data are reproducible and replicable by researchers. Reporting guidelines, such as RECORD and STROBE, have set a solid foundation by recommending a series of items for researchers to include in their research outputs. Researchers however often lack the technical tools and methodological approaches to actuate such recommendations in an efficient and sustainable manner.

RESULTS

In this paper, we review and propose a series of methods and tools utilized in adjunct scientific disciplines that can be used to enhance the reproducibility of research using electronic health records and enable researchers to report analytical approaches in a transparent manner. Specifically, we discuss the adoption of scientific software engineering principles and best-practices such as test-driven development, source code revision control systems, literate programming and the standardization and re-use of common data management and analytical approaches.

CONCLUSION

The adoption of such approaches will enable scientists to systematically document and share EHR analytical workflows and increase the reproducibility of biomedical research using such complex data sources.