Principal Investigator: Dr Neil Davies
Institution: University of BristolTags: 8786, causal inference, education, health, morbidity, mortality
1a: Research question: what are the causal effects of education on morbidity and cause specific mortality? Outcomes: all-cause and cause-specific mortality, coronary heart disease, lung cancer and income.
Synopsis: On average people with more years of education live longer and are healthier. We do not know whether this is because more educated people are less likely to engage in risky behaviours such as smoking, or if there are other differences, such as cognition or social class, which cause some people to be both healthier and more educated.
We will address this hypothesis using statistical techniques for differentiating causation and correlation.
1b: Low education is a major risk factor for a wide range of diseases.
We will use data from the UK Biobank to improve our understanding of how individuals’ educational choices early in life affect their long term health outcomes.
Ultimately, knowledge from this project will help policy makers and
practitioners mitigate these differences. Furthermore, our results will
provide evidence about the consequences of the recent decisions to further increase the minimum school leaving age to 18 and to widen access to higher education.
1c: We will use data on all individuals from UK Biobank with information on date and country of birth and age at which they left full time education. We will investigate differences in health outcomes by duration of education. We will present adjusted results adjusted for known confounders (such as income, cognition).
We will use the raising of the school leaving age in 1972 and genetic variants known to associate with education as a natural experiment (instrumental variable) for educational achievement to identify the causal effects of education.
1d: We will use participants born outside the UK as a negative control
population to provide further validation of our methods (1). We do not
expect the changing of the school leaving age to affect the educational
attainment of individuals born outside of the UK.
Project extension: We will conduct a GWAS using the imputed data and will include the following covariates – sex, standardised age at the time of assessment, age squared, the 15 principal components of population stratification and indicators for genotyping array. We will restrict the analysis to unrelated white British individuals – the 112,338 individuals recommended by the imputation documentation. We do not need any further data for this extension.
Project extension: We would like to investigate the relationship between a genetic risk score for ADHD and educational attainment and socioeconomic position. This research involves Evie Stergiakouli, at Bristol University. This project would not require any additional data.
Research Project Extension – Approved by UK Biobank 13.10.2015
“Our paper proposes methods for estimating the causal effects of risk factors or exposures using individual genetic variants as instrumental variables. The method allows for unbiased estimation when some of the instruments are invalid.
We would like to investigate the effects of BMI on educational attainment, using the 97 variants published in Locke et al. (2015) as instrumental variables for BMI.”
PROJECT EXTENSION – Approved 21.01.2016:
“Collider bias – an illustration within Biobank – effects from artefact – Collider bias is appearing as a pervasive factor in the analysis of complex phenotypes and is of particular concern where analysts were preferentially turning to genetic data for properties of inter-variable independence (often quoting Mendel’s laws to justify such manoeuvres). It is of course sensible to think of the utility of phenotypic adjustment for the clarification of otherwise opaque genetic association signals, however the implications of adjusting for an additional phenotype which has a non-independent biological contribution to outcomes of interest may have the knock on effect of stratifying (and thereby correlating) otherwise independent genotypes. In studies of transgenerational effects adjusted for child genotype, comparisons of genetic sharing across phenotypes, or other analytical scenarios (Aschard et al ASHG 2015) these effects have the potential to be just as complicating as the original position before adjustment despite the aim to gain additional clarity. We propose in to undertake an investigation of this within the UKBiobank data, in a manner nor dissimilar to that already seen (Day et al BioRXiv 2015), but where spurious associations are shown to be delivered through the undertaking of analyses adjusted for pertinent colliders. This will be based not he analysis of confounder traits and cardiometabolic phenotypes and be for the purpose of demonstrating the potential impact of collider bias, man important analytical phenomenon.”
The relationship between myopia and educational attainment.
Educated individuals are more likely to be short sighted. However, we do not know why this association occurs, it may be because educated individuals spend more time studying, and reading, or alternatively, short sighted individuals may be less likely to engage in non-academic activities like sports. We will apply a bidirectional Mendelian randomisation approach to investigate whether recently discovered genetic variants, which are known to associate with educational attainment, are associated with myopia, and whether genetic variants which are known to associate with myopia are also associated with educational attainment. This will allow us to determine whether education causes myopia or if myopia causes educational attainment.
The relationship between fatty acids and educational attainment.
Fatty acids are thought to be vital for normal brain development, in utero and in infancy. Fish consumption provides a major source of fatty acids, and has been found to be associated with IQ. However, there are substantial socioeconomic differences in fish consumption, and the observational association of fish consumption may be due to residual confounding. During this project we will use genetic variants, which have been found to be associated with fatty acid levels in metabolic studies, as instrumental variables for fatty acid levels in biobank participants. We will conduct a two sample study to maximise our statistical power.