Hypertension among adults in a deprived urban area of Peru – Undiagnosed and uncontrolled?

BACKGROUND: In Peru, cardiovascular disease was the second most common cause of death in those aged 65 years or more in 2000. Hypertension is a major modifiable risk factor for cardiovascular disease, and if treated can significantly reduce cardiovascular disease risk. The objectives of this study were to investigate the prevalence of hypertension and levels of awareness, treatment and control in a deprived urban area of Peru. METHODS: A cross-sectional study was completed. Blood pressure measurements were recorded in triplicate. Hypertension was defined as systolic blood pressure >/= 140 mmHg or diastolic blood pressure >/= 90 mmHg, or self report of receiving antihypertensive medication at the time of interview. RESULTS: The study sample was 584 adults (29.1% male, mean age 35.3 years). Age standardized prevalence of hypertension was 19.5% (95% CI 9.9%, 29.1%) in men, 11.4% (95% CI 3.7%, 19.1%) in women, and 13.2% (95% CI 5.0%, 21.5%) overall. Among those with hypertension 38.3% (95% CI 22.7%, 53.9%, n = 18/47) were aware of their condition with greater awareness among women than men. Of those aware, 61.1% (n = 11/18) were treated, equating to 23.4% (95% CI 10.1%, 36.7%, n = 11/47) of all adults with hypertension. Of those treated 63.6% (n = 7/11) had controlled hypertension, equating to 14.9% (95% CI 3.0%, 26.8%, n = 7/47) of all adults with hypertension. CONCLUSION: Levels of awareness and control in this population were low. Lack of control is likely to be due to both a failure to diagnose hypertension, especially among men, and initiate or comply with treatment, especially among women. These results suggest a considerable burden of undiagnosed hypertension, and poor levels of control in those treated, in a deprived urban area of Lima, Peru

Long term cost effectiveness of interventions for obesity:A Mendelian randomisation study

Background The prevalence of obesity has increased in the United Kingdom, and reliably measuring the impact on quality of life and the total healthcare cost from obesity is key to informing the cost-effectiveness of interventions that target obesity, and determining healthcare funding. Current methods for estimating cost-effectiveness of interventions for obesity may be subject to confounding and reverse causation. The aim of this study is to apply a new approach using mendelian randomisation for estimating the cost-effectiveness of interventions that target body mass index (BMI), which may be less affected by confounding and reverse causation than previous approaches. Methods and findings We estimated health-related quality-adjusted life years (QALYs) and both primary and secondary healthcare costs for 310,913 men and women of white British ancestry aged between 39 and 72 years in UK Biobank between recruitment (2006 to 2010) and 31 March 2017. We then estimated the causal effect of differences in BMI on QALYs and total healthcare costs using mendelian randomisation. For this, we used instrumental variable regression with a polygenic risk score (PRS) for BMI, derived using a genome-wide association study (GWAS) of BMI, with age, sex, recruitment centre, and 40 genetic principal components as covariables to estimate the effect of a unit increase in BMI on QALYs and total healthcare costs. Finally, we used simulations to estimate the likely effect on BMI of policy relevant interventions for BMI, then used the mendelian randomisation estimates to estimate the cost-effectiveness of these interventions. A unit increase in BMI decreased QALYs by 0.65% of a QALY (95% confidence interval [CI]: 0.49% to 0.81%) per year and increased annual total healthcare costs by £42.23 (95% CI: £32.95 to £51.51) per person. When considering only health conditions usually considered in previous cost-effectiveness modelling studies (cancer, cardiovascular disease, cerebrovascular disease, and type 2 diabetes), we estimated that a unit increase in BMI decreased QALYs by only 0.16% of a QALY (95% CI: 0.10% to 0.22%) per year. We estimated that both laparoscopic bariatric surgery among individuals with BMI greater than 35 kg/m2, and restricting volume promotions for high fat, salt, and sugar products, would increase QALYs and decrease total healthcare costs, with net monetary benefits (at £20,000 per QALY) of £13,936 (95% CI: £8,112 to £20,658) per person over 20 years, and £546 million (95% CI: £435 million to £671 million) in total per year, respectively. The main limitations of this approach are that mendelian randomisation relies on assumptions that cannot be proven, including the absence of directional pleiotropy, and that genotypes are independent of confounders. Conclusions Mendelian randomisation can be used to estimate the impact of interventions on quality of life and healthcare costs. We observed that the effect of increasing BMI on health-related quality of life is much larger when accounting for 240 chronic health conditions, compared with only a limited selection. This means that previous cost-effectiveness studies have likely underestimated the effect of BMI on quality of life and, therefore, the potential cost-effectiveness of interventions to reduce BMI

Ethical considerations of use of hold-out sets in clinical prediction model management

Clinical prediction models are statistical or machine learning models used toquantify the risk of a certain health outcome using patient data. These can theninform potential interventions on patients, causing an effect called performativeprediction: predictions inform interventions which influence the outcome theywere trying to predict, leading to a potential underestimation of risk in somepatients if a model is updated on this data. One suggested resolution to this isthe use of hold-out sets, in which a set of patients do not receive model derivedrisk scores, such that a model can be safely retrained. We present an overview ofclinical and research ethics regarding potential implementation of hold-out setsfor clinical prediction models in health settings. We focus on the ethical principles of beneficence, non-maleficence, autonomy and justice. We also discussinformed consent, clinical equipoise, and truth-telling. We present illustrativecases of potential hold-out set implementations and discuss statistical issues arising from different hold-out set sampling methods. We also discuss differencesbetween hold-out sets and randomised control trials, in terms of ethics and statistical issues. Finally, we give practical recommendations for researchers interestedin the use hold-out sets for clinical prediction models

Common health conditions in childhood and adolescence, school absence, and educational attainment: Mendelian randomization study

Good health is positively related to children’s educational outcomes, but relationships may not be causal. Demonstrating a causal influence would strongly support childhood and adolescent health as important for education policy. We applied genetic causal inference methods to assess the causal relationship of common health conditions at age 10 (primary/elementary school) and 13 (mid-secondary/mid-high school) with educational attainment at 16 and school absence at 14–16. Participants were 6113 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). Exposures were symptoms of attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), depression, asthma, migraines and BMI. Genetic liability for these conditions and BMI was indexed by polygenic scores. In non-genetic, multivariate-adjusted models, all health conditions except asthma and migraines were associated with poorer attainment and greater school absence. School absence substantially mediated effects of BMI (39.9% for BMI at 13) and migraines (72.0% at 10), on attainment with more modest mediation for emotional and neurodevelopmental conditions. In genetic models, a unit increase in standardized BMI at 10 predicted a 0.19 S.D. decrease (95% CI: 0.11, 0.28) in attainment at 16, equivalent to around a 1/3 grade lower in all subjects, and 8.7% more school absence (95% CI:1.8%,16.1%). Associations were similar at 13. Genetic liability for ADHD predicted lower attainment but not more absence. Triangulation across multiple approaches supports a causal, negative influence on educational outcomes of BMI and ADHD, but not of ASD, depression, asthma or migraine. Higher BMI in childhood and adolescence may causally impair educational outcomes

Mental health selection : common mental disorder and migration between multiple states of deprivation in a UK cohort

Funding Funding for this work was received from Public Health Wales NHS Trust as part of a report on migration and health. Support for the report was also received from the National Centre for Population Health and Wellbeing Research (NCPHWR). The eCATALYsT multiagency dataset and the baseline survey was supported by the Wales Office of Research and Development (SCC99/1/105 and R00/1/017). The follow-up survey was supported by a Welsh Assembly Government/Medical Research Council Health Research Partnership Award (H07-3-030), and the electronic cohort is supported by a National Institute for Social Care and Health Research Welsh Assembly Government Translational Health Research Platform Award (TPR08-020). Data availability statement Data may be obtained from a third party and are not publicly available. The electronic cohort is securely stored and maintained on the Secure Anonymised Information Linkage (SAIL) databank at Swansea University Medical School. The authors welcome general enquiries and ideas for new collaborations. Readers with an interest in further details should contact Professor Shantini Paranjothy, Principal Investigator.Peer reviewedPublisher PD