MentalSEP · Exploring the interplay between socioeconomic position and mental health through familial and genetic measures

There is robust evidence that low socioeconomic position is associated with an elevated risk of subsequent mental disorders, but the validity of these findings is debated. This association could be causal or could be the result of failing to adjust for underlying risk factors that cause both a lower socioeconomic position and a higher risk of mental disorders. Existing studies (i) do not fully account for familial and genetic underlying factors, (ii) do not use measures of socioeconomic position at different levels (e.g., individual and neighborhood), and/or (iii) do not consider mental health beyond clinically diagnosed mental disorders. MentalSEP addresses these fundamental gaps by developing a novel approach to estimate the association between childhood socioeconomic position and subsequent mental health in a comprehensive way using Danish population-based data (~11 million persons). I plan to consider both genetic and familial susceptibility and different aspects of socioeconomic position and mental health. Additionally, I propose two important methodological developments to overcome the limitations of current techniques: (i) to adapt new measures of familial susceptibility through the health and socioeconomic history of family members, and (ii) to develop data-driven methods capable of combining data sources from non-overlapping sample populations. The broad guiding hypothesis of this project is that innovative methods bridging different disciplines will reveal more meaningful information on the potential effect of socioeconomic position on mental health. MentalSEP is ground-breaking both in relation to the methods it will develop and their application. The project will deliver cutting-edge knowledge about social inequalities in mental health, helping us better guide policies aimed at reducing their impact. In addition, the project will explore pioneering methodological approaches that have the potential to be a major advancement in the field of epidemiology.