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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/m.sup.2, 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., Author(s): Sean Harrison 1,2,*, Padraig Dixon 1,2, Hayley E. Jones 2, Alisha R. Davies 3, Laura D. Howe 1,2, Neil M. Davies 1,2,4 Introduction Between 1993 and 2017 in England, [...]

The article discusses the issue of researchers being compelled to make policy claims based on single studies, which can be misleading and distort evidence-based policy. The increasing emphasis on 'impact' in academia, along with financial and career incentives, has led to the use of hype and positive language in scientific articles and grant applications. The authors argue that drawing unfounded policy conclusions based on single studies undermines trust in science and suggest that researchers should report on policy claims more cautiously and provide a broader discussion of policy options. They also propose that policy discussion pieces should be valued separately from original research articles to promote evidence-based policy. [Extracted from the article]

Education policy in England has explicitly aimed to remodel state schools in the image of independent, private, schools. However, the body of research evidence on the operation of private schools is very small. Critics have frequently argued that, in contrast to state schools, private schools use resources efficiently because their autonomy gives them freedom to make efficient choices in response to market pressures. We investigated the resource allocation decisions of income private schools using data from their financial accounts. We report the associations of private school spending and performance and teacher and non-teacher numbers, teacher salaries and regional earnings. Schools with higher fees had more teachers and non-teachers per pupil, but similar average staff wages to schools with lower income. Yet we found little evidence that achievement was associated with resource use in English private schools. That is, we found no evidence to support the view that financial autonomy enabled flexibility in using resources to promote higher achievement.

This study examines ways in which economic and sociological explanations of higher education (HE) choices may intersect through student's use of information. We find substantial positive associations between intention to go to university in England and each of: (i) parents' education; (ii) cultural capital; and (iii) expectations of the size of the graduate premium. We also find an association between beliefs about the size of the graduate premium and cultural capital. These results support an integrated model of participation in HE in which social and economic factors are treated as complementary rather than competing explanations. The results run counter to previous research which has found that associations between participation in HE and socio-economic status (SES) largely disappear once students' attainment is taken into account. One policy implication of this research is that some indicators of SES (notably household income, eligibility for free school meals or parental occupation) are sub-optimal for interventions to widen participation in HE.

Objectives To estimate the impact of altering referral thresholds from out-of-hours services on older patients' further use of health services and risk of death. Design Cohort study using patient data from primary and specialised health services and demographic data from Statistics Norway and the Norwegian Cause of Death Registry. Setting Norway Participants 491 653 patients aged 65 years and older contacting Norwegian out-of-hours services between 2008 and 2016. Analysis Multivariable adjusted and instrumental variable associations between referrals to hospital from out-of-hours services and further health services use and death for up to 6 months. Physicians' proportions of acute referrals of older, unknown patients from out-of-hours work were used as an instrumental variable ('physician referral preference') for their threshold of referral for such patients whose clinical presentations were less clear cut. Results For older patients, whose referrals could be attributed to their physicians' threshold for referral, mean length of stay in hospital increased 3.30 days (95% CI 3.13 to 3.27) within the first 10 days, compared with non-referred patients. Such referrals also increased 6 months use of outpatient specialist clinics and primary care physicians. Importantly, patients with referrals attributable to their physicians' threshold had a substantially reduced risk of death the first 10 days (HR 0.53, 95% CI 0.31 to 0.91), an effect sustaining through the 6-month follow-up period (HR 0.72, 95% CI 0.54 to 0.97). Conclusions Out-of-hours patients whose referrals are affected by physician referral threshold contribute substantially to the use of health services. However, the referral seems protective by reducing the risk of death in the first 6 months after the referral. Thus, raising the threshold for referral to lower pressure on overcrowded emergency departments and hospitals should not be encouraged without ensuring the accuracy of the referral decisions, ideally through high-quality randomised controlled trial evidence. [ABSTRACT FROM AUTHOR]

Background: Traditionally, heritability has been estimated using family-based methods such as twin studies. Advancements in molecular genomics have facilitated the development of methods that use large samples of (unrelated or related) genotyped individuals.Methods: Here, we provide an overview of common methods applied in genetic epidemiology to estimate heritability, i.e. the proportion of phenotypic variation explained by genetic variation. We provide a guide to key genetic concepts required to understand heritability estimation methods from family-based designs (twin and family studies), genomic designs based on unrelated individuals [linkage disequilibrium score regression, genomic relatedness restricted maximum-likelihood (GREML) estimation] and family-based genomic designs (sibling regression, GREML-kinship, trio-genome-wide complex trait analysis, maternal-genome-wide complex trait analysis, relatedness disequilibrium regression).Results: We describe how heritability is estimated for each method and the assumptions underlying its estimation, and discuss the implications when these assumptions are not met. We further discuss the benefits and limitations of estimating heritability within samples of unrelated individuals compared with samples of related individuals.Conclusions: Overall, this article is intended to help the reader determine the circumstances when each method would be appropriate and why. [ABSTRACT FROM AUTHOR]