A Multidisciplinary, Data Analytics and Public Participatory Approach to Better Understanding the Risks of Dementia in Ageing

This inter-disciplinary project focuses on cognitive health in ageing, using existing TUDA data (Trinity, Ulster, Department of Agriculture Study) linking nutrition, biomarker, lifestyle, health, and geo-referenced data with cognition as people age.


  Project Funders

  • HSCB eHealth Directorate
  • eHealth and Data Analytics Dementia Pathfinder Programme

  Funding Amount

£99,905

About the Project

This inter-disciplinary project focuses on cognitive health in ageing, using existing TUDA data (Trinity, Ulster, Department of Agriculture Study) linking nutrition, biomarker, lifestyle, health, and geo-referenced data with cognition as people age.

The project seeks to address healthcare challenges by identifying effective dietary and lifestyle intervention options in order to promote health and wellness in our ageing population through the use of data analytics technologies applied to the TUDA dataset.

This project will apply data analytics to the cleansed and prepared TUDA dataset from the scoping round of the project to enable the discovery of patterns and trends that are pertinent to future health policies aimed to promote better brain health in ageing populations across various socioeconomic status (SES).

Various modelling techniques will be applied and upon building the models that produce the highest quality knowledge from the data analysis perspective, the models will be evaluated to ensure they are robust and achieve the business objectives. The knowledge gained from the models will then be presented to stakeholders in an actionable way.

The involvement of patients, carers and professionals in the design, monitoring, delivery and reporting of the project is essential. The team propose an innovate approach to how this project element is delivered on, by ensuring endorsement of the approach, monitoring progress and evaluating the outcomes, not only in respect of the teams defined outcomes, but also against the wider PPI expectations.

Projected key outcomes

  • Development of actionable models using data analytics techniques
  • Identification of factors contributing to cognitive dysfunction
  • Identification of potential interventions to promote health and wellness in our ageing population
  • Co-creation with involvement from patients, carers and professionals in the design and evaluation of the project