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OP18 What explains the effect of education on cardiovascular disease? Applying mendelian randomisation to identify the consequences of education inequality
  1. A Carter1,
  2. D Gill2,
  3. N Davies1,
  4. A Taylor3,
  5. G Davey Smith1,
  6. M Holmes4,5,1,
  7. I Tzoulaki2,6,7,
  8. L Howe1,
  9. A Dehghan2,6
  1. 1MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK
  2. 2Department of Biostatistics and Epidemiology, Imperial College London, London, UK
  3. 3NIHR Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
  4. 4Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
  5. 5Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, UK
  6. 6MRC-PHE Centre for Environment, School of Public Health, Imperial College London, London, UK
  7. 7Department of Hygiene and Epidemiology, University of Ioannina, Ioannina, Greece


Background Studies have demonstrated causal effects of educational attainment on cardiovascular disease (CVD). We aimed to investigate the role of body mass index (BMI), systolic blood pressure (SBP) and smoking in explaining the effect of education on risk of CVD outcomes triangulating across multivariable regression analysis of observational data and one- and two-sample Mendelian randomisation (MR) analysis; an instrumental variable approach more robust to bias from confounding and reverse causation.

Methods Individual level data from UK Biobank (N=217 013) was used for multivariable analyses and one-sample MR. Summary statistics from genome-wide association studies were used in two-sample MR.

The total effect of education on risk of coronary heart disease (CHD), CVD (all subtypes), myocardial infarction (MI) and stroke (all measured in odds ratio, OR) was assessed using multivariable regression and univariable Mendelian randomization (MR).

The degree to which this effect is mediated through BMI, SBP and smoking respectively (the indirect effect and proportion mediated) was estimated using the product of coefficients method, where the effect of education on each mediator, and each mediator on each outcome was assessed using multivariable regression and Network MR. The joint contribution of all three risk factors was assessed via the difference method, using multivariable regression or multivariable MR.

Results Each additional standard deviation of education (3.6 years) associated with 13% lower risk of coronary heart disease (OR 0.87, 95% confidence interval [CI] 0.84 to 0.89) in observational analysis and 37% lower risk (OR 0.63, 95% CI 0.60 to 0.67) in MR analysis. As a proportion of the total risk reduction, BMI mediated 15% (95% CI 13% to 17%) and 18% (95% CI 14% to 23%) in the observational and MR estimates respectively. Corresponding estimates for SBP were 11% (95% CI 9% to 13%) and 21% (95% CI 15% to 27%), and for smoking, 19% (15% to 22%) and 34% (95% CI 17% to 50%). All three risk factors combined mediated 42% (95% CI 36% to 48%) and 36% (95% CI 16% to 63%) of the effect of education on CHD in observational and MR respectively. Similar results were obtained for risk of stroke, MI and all-cause CVD.

Conclusion BMI, SBP and smoking mediate a substantial proportion of the protective effect of education on risk of cardiovascular outcomes. Intervening on these would reduce cases of CVD attributable to lower education. However, more than half of the protective effect of education remains unexplained.

  • Education
  • Mendelian randomisation
  • mediation analysis

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