Exposome Models

Research models that provide a holistic view of the risk of chronic health conditions, from molecules to populations.

Using obesity as a pilot primary clinical outcome, LongITools researchers have developed three complementary models that provide a holistic view of the risk of chronic health conditions, from molecules (determining the main drivers of health) to populations (investigating the potential effect of an intervention on health). These models include:

• Integrative Structural Causal: investigating the main exposures and their biological signatures that are jointly contributing to obesity development;
• Bayesian Life-course Structural Equation Models (BLSEM): investigating causal linkages, mediation and pathways between exposures and health outcomes;
• Microsimulation: investigating the effect of potential interventions on the prevalence and incidence of obesity in different populations and evaluating the costs and benefits of these potential interventions (more here).

The first two models generated and tested hypotheses on external factors and investment choices impacting the development of obesity, their biological embodiment, and their joint effect on health, and which policy levers can be used to modify these investment choices. They also identified critical life stages at which these exposures are more likely to exert their joined and marginal effects and therefore when policies and interventions might be more effective. The results of these analyses provided a potential target for obesity prevention.

These hypotheses were then taken forward in the microsimulation model to estimate the potential effect of a (counterfactual) intervention at the population level and its health and economic impact.

Access

Coming soon

Status

Completed

Interview

Professor Marc Chadeau-Hyam explains the models and their future development.