Using epidemiology data towards causal inference
Results from observational data in epidemiological studies are very seldom used in risk assessment of chemicals. One reason for this is that such data most often is deemed as not causal since they don´t follow gold standard for randomized control trial designs. This is of course true, however, with new approaches, environmental epidemiology can move towards causal inference. In this seminar, Professor Carl-Gustaf Bornehag will present a scientific platform based on the Swedish SELMA study, a pregnancy cohort following about 2,000 mother-child pairs from early pregnancy over birth and up in school age of the children.
SELMA is focusing on early life exposure for risk and resilience factors for health and developmental outcomes in the children. In focus are e.g., exposure for mixtures of chemicals with suspected or proven endocrine disrupting properties (EDCs), maternal diet and nutrition during pregnancy as well as epigenetic mechanisms as potential explanations for the associations between exposure and outcomes. Outcomes in focus are asthma and allergy, metabolism and growth, sexual development, and neurodevelopment including cognitive function and behavioral disorders. Finally, we are introducing new statistical approaches such as g-computation to conduct causal inference with counterfactuals for assumed changes in either EDC exposures or improved nutrition. Evaluation of such a strategy may support decision makers for risk management of EDCs and individual choices for improving dietary nutrition.
Carl-Gustaf Bornehag is Professor in Public Health Sciences and works at the Department of Health Sciences at Karlstad University, and also at the Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.