A key aim of epidemiology is aetiology – determining causal effects of variation in population health and wellbeing. However, the ability to distinguish causal effects from non-causal association in all branches of epidemiology, including occupational epidemiology, is difficult. In this talk I will outline some novel approaches to testing causality, including using genetic instrumental variables (Mendelian randomization) and negative control studies, and how these can be integrated with more conventional approaches (multivariable regression analyses in observational data, randomised controlled trials and natural experiments) in a triangulation framework. I will used examples from perinatal and cardio-metabolic health (the main area in which I work) but also from occupational health to illustrate how these can be used to improve causal understanding of how occupational exposures affect health.
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