Project description
Predicting lifestyle’s impact on diabetes
Despite WHO's recommendation of lifestyle changes to tackle diabetes, its prevalence continues to rise. However, there is a need for comprehensive intervention studies that consider the interplay of different factors such as diet, sleep and exercise. Funded by the Marie Skłodowska-Curie Actions programme, the DyNPI-T2D project aims to conduct a long-term intervention study involving 200 subjects with and without diabetes. Researchers will examine different lifestyle factors and record multimodal health data on a daily basis. Through a novel model, DyNPI-T2D aims to be able to precisely predict health trajectories, improving the health of individuals at risk.
Objective
The prevalence of type 2 diabetes (T2D) is projected to increase by 100 million within years. However, while lifestyle changes are recommended by the WHO to counter & mitigate diabetes, comprehensive intervention experiments that consider the interplay of different lifestyle factors are lacking, as are clinical tools to evaluate such interplay. The present project will address these outstanding issues through two major undertakings:
(1) A first long-term dynamic intervention experiment encompassing multiple lifestyle factors (diet, sleep & exercise) will be conducted in 200 subjects with & without T2D. The participants’ daily multimodal health data (biochemical markers, sleep, questionnaires, etc.) will be recorded, to form a high-resolution dynamic intervention database with unprecedented integrative & temporal resolution, which will be stored securely and made available for fellow scholars and the public to take advantage of.
(2) The project will, for the first time, use the concept “Order Parameters” from statistical physics to represent different health states treated as distinct “ordered statuses”. Thus, a novel multimodal model will be built to characterize the temporal evolution of health variables that the modelling pinpoints as being the most predictive longitudinal parameters. The project will thus enable personalized predictions for holistic health trajectory, by analyzing the general physical laws followed by the temporal evolution of model parameters, also in relevant T2D & healthy subgroups.
The two undertakings provide excellent quality control & risk assessment via six tailored work packages consisting of 32 milestones and 4 deliverables. This will provide an effective assessment tool for public health monitoring, at both the individual & policy level. More importantly, it will enable a paradigm shift from traditional group-level descriptive statistics, to precise quantitative assessment for longitudinal evaluation of key clinical health parameters.
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.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencesdatabases
- medical and health sciencesclinical medicineendocrinologydiabetes
- medical and health scienceshealth sciencesnutrition
- social scienceslaw
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Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinator
751 05 Uppsala
Sweden