Project description
Economics of obesity and population-based prevention
Obesity is a major contributor to the disease burden in Europe, leading to substantial healthcare expenses and productivity loss. Cost-effective obesity prevention strategies are needed to ensure the sustainability of healthcare and social security systems. Implementing population-based interventions (PBIs) aimed at changing the economic, social, and environmental context shows promise, yet robust evidence on their health and economic impact is lacking. The ERC-funded EcIMPACT project will measure the health and economic impact of two policy-relevant PBIs and determine the effects of excess body weight on long-term health and economic outcomes. The project will use and combine innovative methods across several academic disciplines to provide evidence for decision-makers regarding the value of PBIs to ultimately improve population health in an efficient way.
Objective
Overweight and obesity account for one eighth of the disease burden and five percent of health care expenditures in Europe and cause large societal productivity losses. Thus, cost-effective strategies for the prevention of overweight and obesity are urgently needed to assure the financial sustainability of health and social security systems. Population-based interventions (PBIs) that change the social and environmental context are promising strategies, however, robust evidence on their health and economic impact is lacking. This uncertainty might lead to inefficient resource allocation and harm for patients and society. In EcIMPACT, I aim to 1) quantify the real-world causal effect of two policy relevant PBIs on body weight, 2) estimate the causal effect of excess body weight on health and economic outcomes, and 3) model the long-term health and economic impact of PBIs by combining results from Aims 1 and 2. I will do so by combining innovative methods from economics, public health, and epidemiology. Specifically, I will pool data from large cohort studies, surveillance initiatives, and household panels across Europe and use econometric methods that exploit natural policy experiments (Aim 1), link primary and secondary data sources that comprise granular genetic, phenotypic, and socio-economic information and apply cutting-edge Mendelian Randomization techniques (Aim 2), and build a simulation model that integrates those estimated parameters in a novel model type (Aim 3). Synthesizing cutting-edge methods from different academic disciplines, EcIMPACT will provide urgently needed evidence for decision makers on the value of PBIs that will ultimately improve population health. EcIMPACT will advance public health research substantially by showing that combinations of innovative quasi-experimental and model-based techniques, which leverage the full potential of modern data infrastructures, can guide health policy in an efficient and timely manner.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. This project's classification has been validated by the project's team.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. This project's classification has been validated by the project's team.
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
80333 Muenchen
Germany