A general conceptual and statistical framework to model non-linear and delayed exposure-response relationships and combi

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Scientific studies which assess the health effects of various risk factors usually depend on statistical models, used to quantify the relationship between the dose people are exposed to, and the health outcome. This relationship should concisely and reliably summarize the association, in order to correctly inform about the health consequences of specific risk factors. This association is usually estimated in multiple comparable studies, whose evidence needs then to be combined in order to improve the knowledge about related health risks.Researchers at the London School of Hygiene and Tropical Medicine, in collaboration with the MRC-Cambridge and the University of Southern California, have promoted a project to provide the statistical tools suitable to describe complex relationships and combine them across studies. These methodologies will be implemented in statistical software, freely available and usable by all the researchers working in different biomedical fields. The aim of the project is to improve the analytical method to study the association between risk factors and human health.