Population assessment of future trajectories in coronary heart disease mortality.

Background: Coronary heart disease (CHD) mortality rates have been decreasing in Iceland since the 1980s, largely reflecting improvements in cardiovascular risk factors. The purpose of this study was to predict future CHD mortality in Iceland based on potential risk factor trends. Methods and findings: The previously validated IMPACT model was used to predict changes in CHD mortality between 2010 and 2040 among the projected population of Iceland aged 25–74. Calculations were based on combining: i) data on population numbers and projections (Statistics Iceland), ii) population risk factor levels and projections (Refine Reykjavik study), and iii) effectiveness of specific risk factor reductions (published meta-analyses). Projections for three contrasting scenarios were compared: 1) If the historical risk factor trends of past 30 years were to continue, the declining death rates of past decades would level off, reflecting population ageing. 2) If recent trends in risk factors (past 5 years) continue, this would result in a death rate increasing from 49 to 70 per 100,000. This would reflect a recent plateau in previously falling cholesterol levels and recent rapid increases in obesity and diabetes prevalence. 3) Assuming that in 2040 the entire population enjoys optimal risk factor levels observed in low risk cohorts, this would prevent almost all premature CHD deaths before 2040. Conclusions: The potential increase in CHD deaths with recent trends in risk factor levels is alarming both for Iceland and probably for comparable Western populations. However, our results show considerable room for reducing CHD mortality. Achieving the best case scenario could eradicate premature CHD deaths by 2040. Public health policy interventions based on these predictions may provide a cost effective means of reducing CHD mortality in the future

Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase

Identification of Digital Health Priorities for Palliative Care Research: Modified Delphi Study.

Background: Developments in digital health have the potential to transform the delivery of health and social care to help citizens manage their health. Currently, there is a lack of consensus about digital health research priorities in palliative care and a lack of theories about how these technologies might improve care outcomes. Therefore, it is important for health care leaders to identify innovations to ensure that an increasingly frail population has appropriate access to palliative care services. Consequently, it is important to articulate research priorities as the first step in determining how finite resources should be allocated to a field saturated with rapidly developing innovation. Objective: The aim of this study is to identify research priority areas for digital health in palliative care. Methods: We selected digital health trends, most relevant to palliative care, from a list of emerging trends reported by a leading institute of quantitative futurists. We conducted 2 rounds of the Delphi questionnaire, followed by a consensus meeting and public engagement workshop to establish a final consensus on research priorities for digital technology in palliative care. We used the views of public representatives to gain their perspectives on the agreed priorities. Results: A total of 103 experts (representing 11 countries) participated in the first Delphi round. Of the 103 experts, 55 (53.3%) participated in the second round. The final consensus meetings were attended by 10.7% (11/103) of the experts. We identified 16 priority areas, which involved many applications of technologies, including care for patients and caregivers, self-management and reporting of diseases, education and training, communication, care coordination, and research methodology. We summarized the priority areas into eight topics: big data, mobile devices, telehealth and telemedicine, virtual reality, artificial intelligence, smart home, biotechnology, and digital legacy. Conclusions:The priorities identified in this study represent a wide range of important emerging areas in the fields of digital health, personalized medicine, and data science. Human-centered design and robust governance systems should be considered in future research. It is important that the risks of using these technologies in palliative care are properly addressed to ensure that these tools are used meaningfully, wisely, and safely and do not cause unintentional harm

Obesity and treatment meanings in bariatric surgery candidates: a qualitative study

Background This study used a qualitative approach to comprehend how the morbid obese conceptualize and deal with obesity and obesity treatment, with the particular aim of exploring the expectations and beliefs about the exigencies and the impact of bariatric surgery. Methods The study population included 30 morbid obese patients (20 women and 10 men) with a mean age of 39.17 years (SD = 8.81) and a mean body mass index of 47.5 (SD = 8.2) interviewed individually before surgery using open-ended questions. The interviews were audiotaped, transcribed, and then coded according to grounded analysis methodology. Results Three main thematic areas emerged from the data: obesity, eating behavior, and treatment. Obesity is described as a stable and hereditary trait. Although participants recognize that personal eating behavior exacerbates this condition, patients see their eating behavior as difficult to change and control. Food seems to be an ever-present dimension and a coping strategy, and to follow an adequate diet plan is described as a huge sacrifice. Bariatric surgery emerges as the only treatment for obesity, and participants highlight this moment as the beginning of a new life where health professionals have the main role. Bariatric surgery candidates see their eating behavior as out of their control, and to commit to its demands is seen as a big sacrifice. For these patients, surgery is understood as a miracle moment that will change their lives without requiring an active role or their participation. Conclusion According to these results, it is necessary to validate them with qualitative and quantitative studies; it is necessary to promote a new awareness of the weight loss process and to empower patients before and after bariatric surgery.Bolsa de doutoramento SFRH/BD/37069/2007 da Fundação para a Ciência e a Tecnologia (FCT

Impact of FTO genotypes on BMI and weight in polycystic ovary syndrome : a systematic review and meta-analysis

Aims/hypothesis FTO gene single nucleotide polymorphisms (SNPs) have been shown to be associated with obesity-related traits and type 2 diabetes. Several small studies have suggested a greater than expected effect of the FTO rs9939609 SNP on weight in polycystic ovary syndrome (PCOS). We therefore aimed to examine the impact of FTO genotype on BMI and weight in PCOS. Methods A systematic search of medical databases (PubMed, EMBASE and Cochrane CENTRAL) was conducted up to the end of April 2011. Seven studies describing eight distinct PCOS cohorts were retrieved; seven were genotyped for SNP rs9939609 and one for SNP rs1421085. The per allele effect on BMI and body weight increase was calculated and subjected to meta-analysis. Results A total of 2,548 women with PCOS were included in the study; 762 were TT homozygotes, 1,253 had an AT/CT genotype, and 533 were AA/CC homozygotes. Each additional copy of the effect allele (A/C) increased the BMI by a mean of 0.19 z score units (95% CI 0.13, 0.24; p = 2.26 × 10−11) and body weight by a mean of 0.20 z score units (95% CI 0.14, 0.26; p = 1.02 × 10−10). This translated into an approximately 3.3 kg/m2 increase in BMI and an approximately 9.6 kg gain in body weight between TT and AA/CC homozygotes. The association between FTO genotypes and BMI was stronger in the cohorts with PCOS than in the general female populations from large genome-wide association studies. Deviation from an additive genetic model was observed in heavier populations. Conclusions/interpretation The effect of FTO SNPs on obesity-related traits in PCOS seems to be more than two times greater than the effect found in large population-based studies. This suggests an interaction between FTO and the metabolic context or polygenic background of PCOS

Adiposity has differing associations with incident coronary heart disease and mortality in the Scottish population: cross-sectional surveys with follow-up

Objective: Investigation of the association of excess adiposity with three different outcomes: all-cause mortality, coronary heart disease (CHD) mortality and incident CHD. Design: Cross-sectional surveys linked to hospital admissions and death records. Subjects: 19 329 adults (aged 18–86 years) from a representative sample of the Scottish population. Measurements: Gender-stratified Cox proportional hazards models were used to estimate hazard ratios (HRs) for all-cause mortality, CHD mortality and incident CHD. Separate models incorporating the anthropometric measurements body mass index (BMI), waist circumference (WC) or waist–hip ratio (WHR) were created adjusted for age, year of survey, smoking status and alcohol consumption. Results: For both genders, BMI-defined obesity (greater than or equal to30 kg m−2) was not associated with either an increased risk of all-cause mortality or CHD mortality. However, there was an increased risk of incident CHD among the obese men (hazard ratio (HR)=1.78; 95% confidence interval=1.37–2.31) and obese women (HR=1.93; 95% confidence interval=1.44–2.59). There was a similar pattern for WC with regard to the three outcomes; for incident CHD, the HR=1.70 (1.35–2.14) for men and 1.71 (1.28–2.29) for women in the highest WC category (men greater than or equal to102 cm, women greater than or equal to88 cm), synonymous with abdominal obesity. For men, the highest category of WHR (greater than or equal to1.0) was associated with an increased risk of all-cause mortality (1.29; 1.04–1.60) and incident CHD (1.55; 1.19–2.01). Among women with a high WHR (greater than or equal to0.85) there was an increased risk of all outcomes: all-cause mortality (1.56; 1.26–1.94), CHD mortality (2.49; 1.36–4.56) and incident CHD (1.76; 1.31–2.38). Conclusions: In this study excess adiposity was associated with an increased risk of incident CHD but not necessarily death. One possibility is that modern medical intervention has contributed to improved survival of first CHD events. The future health burden of increased obesity levels may manifest as an increase in the prevalence of individuals living with CHD and its consequences

Integrating lived experiences of out-of-hours health services for people with palliative and end-of-life care needs with national datasets for people dying in Scotland in 2016:A mixed methods, multi-stage design

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Marie Curie and Chief Scientist Office Scotland, combined grant MCRGS-07-16-37.Peer reviewedPublisher PD