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Approved research

Examining the causal relationship between health outcomes and and socioeconomic status through Mendelian Randomization.

Principal Investigator: Dr Paul Auer
Approved Research ID: 40458
Approval date: August 23rd 2018

Lay summary

Public health researchers have long been aware that there is a statistical correlation between a person's health and his or her socioeconomic status, such that less well-off individuals are at a higher risk of a variety of health problems and generally have lower life expectancy. One possible explanation for this relationship is that being less well-off causes health problems, for example due to increased stress, or a lack of access to quality health care. Another explanation is that health problems make it difficult for people to achieve their educational potential or to fully participate in the workforce. If this is the case, then poor health would cause a loss of lifetime earnings. Another possible explanation is that there is a third factor that affects both health and income. Education is one possible candidate, because educational attainment is associated with both higher earnings and healthier behavior. The potential causal interrelations also have the potential to lead to feedbacks, resulting in self-reinforcing cycles of poor health and lower socioeconomic status. Researchers interested in the relationship between socioeconomic status and health have used a variety of techniques to try to untangle these complicated causal relationships, but with only limited success so far. Our proposed project would take advantage of genetic information to gain insight into the causal factors that drive the relationship between health and socioeconomic status. Prior research into genetic risk factors will allow us to identify profiles that are associated with greater risk of certain health problems, such as cancer. If genetic cancer risk is associated with decreased income, then the only pathway for that relationship is that cancer led to income loss (for example, by inducing an early retirement), because a person's income cannot affect his or her genome. There are many possible public health benefits that could come from this research. A clarified understand of the causal relationship at work will help policy makers target interventions where they are most useful, for example, by focusing on policies that can interrupt self-reinforcing cycles of poverty and disease. Our work can also help in demonstrating the potentially substantial direct economic benefits associated with particular public health expenditures.