This study estimates the return to education in Britain using two instrumental variable (IV) estimators: one exploits variation in schooling associated with early smoking, the other uses the raising of the school leaving age; both affect a sizeable proportion of the sample. Early smoking is found to be a strong and valid IV and unlike previous IV strategies uses variations in education at numerous points across the distributions of (i) education, and (ii) ability. Thus whilst still a ‘local average treatment effect’ the estimate is closer to the average effect of additional education, akin to least squares but corrected for endogeneity.

1 On average, educated people are healthier, wealthier and have higher life expectancy than those with less education. Numerous studies have attempted to determine whether these differences are caused by education, or are merely correlated with it and are ultimately caused by another factor. Previous studies have used a range of natural experiments to provide causal evidence. Here we exploit two natural experiments, perturbation of germline genetic variation associated with education which occurs at conception, known as Mendelian randomization, and a policy reform, the raising of the school leaving age in the UK in 1972. Previous studies have suggested that the differences in outcomes associated with education may be due to confounding. However, the two independent sources of variation we exploit largely imply consistent causal effects of education on outcomes much later in life.

The reduction of hospital deaths is a policy priority in most developed countries. However, health and social care systems experience difficulties in delivering this outcome. Moreover, studies of place of death fail to identify barriers to dying in the community. To address this gap, this study estimates the unique effects of disease diagnosis and care provider type on the probability that ill adults aged 50 and older die in a private home, care home, hospital, or hospice. It does so by applying multinomial logistic regression analysis to data from the English Longitudinal Study of Ageing. Crucially, the analysis controls for sociodemographic factors, disability, and prognostic uncertainty by accounting for whether relatives anticipated the death. Cancer predicts hospice death, while non-cancer diagnosis and care provision by a partner predict hospital death. Dementia is a barrier to dying in a private home, while it is associated with a care home death. This suggests that community palliative care referral pathways cater to cancer diagnoses, while private home-based palliative care services struggle to support adults with dementia to die at home, regardless of prognostic accuracy. Including cancer-free adults in community palliative care referral pathways, and supporting their partners in care provision, would likely reduce hospital deaths.

Objectives: To estimate the causal effect of health conditions and risk factors on social and socioeconomic outcomes in UK Biobank. Evidence on socioeconomic impacts is important to understand because it can help governments, policy-makers and decision-makers allocate resources efficiently and effectively. Design: We used Mendelian randomization to estimate the causal effects of eight health conditions (asthma, breast cancer, coronary heart disease, depression, eczema, migraine, osteoarthritis, type 2 diabetes) and five health risk factors (alcohol intake, body mass index [BMI], cholesterol, systolic blood pressure, smoking) on 19 social and socioeconomic outcomes. Setting: UK Biobank. Participants: 337,009 men and women of white British ancestry, aged between 39 and 72 years. Main outcome measures: Annual household income, employment, deprivation (measured by the Townsend deprivation index [TDI]), degree level education, happiness, loneliness, and 13 other social and socioeconomic outcomes. Results: Results suggested that BMI, smoking and alcohol intake affect many socioeconomic outcomes. For example, smoking was estimated to reduce household income (mean difference = −£24,394, 95% confidence interval (CI): −£33,403 to −£15,384), the chance of owning accommodation (absolute percentage change [APC] = −21.5%, 95% CI: −29.3% to −13.6%), being satisfied with health (APC = −32.4%, 95% CI: −48.9% to −15.8%), and of obtaining a university degree (APC = −73.8%, 95% CI: −90.7% to −56.9%), while also increasing deprivation (mean difference in TDI = 1.89, 95% CI: 1.13 to 2.64, approximately 236% of a decile of TDI). There was evidence that asthma increased deprivation and decreased both household income and the chance of obtaining a university degree, and migraine reduced the chance of having a weekly leisure or social activity, especially in men. For other associations, estimates were null. Conclusions: Higher BMI, alcohol intake and smoking were all estimated to adversely affect multiple social and socioeconomic outcomes. Effects were not detected between health conditions and socioeconomic outcomes using Mendelian randomization, with the exceptions of depression, asthma and migraines. This may reflect true null associations, selection bias given the relative health and age of participants in UK Biobank, and/or lack of power to detect effects. What is known?: Studies have shown associations between poor health and adverse social (e.g. wellbeing, social contact) and socioeconomic (e.g. educational attainment, income, employment) outcomes, but there is also strong evidence that social and socioeconomic factors influence health. These bidirectional relationships make it difficult to establish whether health conditions and health risk factors have causal effects on social and socioeconomic outcomes. Mendelian randomization is a technique that uses genetic variants robustly related to an exposure of interest (here, health conditions and risk factors for poor health) as a proxy for the exposure. Since genetic variants are randomly allocated at conception, they tend to be unrelated to the factors that typically confound observational studies, and are less likely to suffer from reverse causality, making causal inference from Mendelian randomization analyses more plausible. What this study adds: This study suggests causal effects of higher BMI, smoking and alcohol use on a range of social and socioeconomic outcomes, implying that population-level improvements in these risk factors may, in addition to the well-known health benefits, have social and socioeconomic benefits for individuals and society. There was evidence that asthma increased deprivation, decreased household income and the chance of having a university degree, migraine reduced the chance of having a weekly leisure or social activity, especially in men, and depression increased loneliness and decreased happiness. There was little evidence for causal effects of cholesterol, systolic blood pressure or breast cancer on social and socioeconomic outcomes.