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Predoctoral Researcher at University of Ghent

University of Ghent, Belgium is inviting excellent candidates to apply for a PhD position in communicable diseases. The deadline to apply is November 30, 2019.

You will be responsible for the organization, implementation and reporting of the research project 'Relative contribution of excess weight status as risk factor for non-communicable disease, disability and multimorbidity'. Your research results contribute to the preparation and defense of a PhD in Statistical Data Analysis. The research project will be conducted in collaboration with Sciensano and Ghent University, and is part of the WaIST project - 'Contribution of excessive weight status to the social impact of non-communicable diseases, multimorbidity and disability in Belgium: past, present, and future'.

Excess weight status is one of the primary metabolic risk factors for non-communicable diseases. In Belgium, as in many high-income countries, average BMI has continuously increased over the past decades among both children and adults. Despite the increasing attention at the international level, there is currently no national nutrition and physical activity health plan in Belgium. More than ever, the further development and implementation of evidence-based health policies for the prevention of excessive weight gain therefore requires proactive policy support.

The overall objective of WaIST is to valorise available Sciensano data sources in an integrated framework to assess the past, present and future contribution of excess weight status to the societal impact of non-communicable diseases, multimorbidity and disability in Belgium.

In the context of this project, the following PhD project will be funded: Relative contribution of excess weight status as risk factor for non-communicable disease, disability and multimorbidity.

The relative health impact of excess weight status among a set of simultaneous (non-modifiable, lifestyle, metabolic, and environmental) exposures and health determinants will be assessed using attribution models. Outcome indicators will include disability, multimorbidity and cause specific mortality. Microdata from different waves of the Belgian Health Interview Survey (HIS) will allow to assess the evolution of the relative contribution of excess weight status over time. To support this activity, 1) HIS data will be enriched with environmental exposure data, and 2) a statistical approach will be developed to assess the contribution of risk factors to health outcomes using complex, cross-sectional data and taking account of mediation and interaction.


Summary:

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