Life-course pathways in healthy ageing and wellbeing


Supervisor: Marjo-Riitta Jarvelin

Non-accademic partner: Beta Technology LTD Barcley Court, Heavens Walk Doncaster Carr Doncaster DN4 5Z, UK

Studentship start date: October 2022

Application deadline: Monday 28th February 2022

Application details: 

Dynamic interpersonal, biological, psychological and behavioural (health) systems interact with broader contextual factors (“micro/macro-systems”, e.g. family’s social circumstances and functioning, wealth, health care, work environments, poverty), to shape health over the life span. We seek to unravel pathways through which psychosocial factors impact the ageing process throughout the lifecourse. We will approach health as a dynamic system and capture fluctuation over time from prenatal period until middle age. We hypothesise that socio-economic distress and psychosocial adversities (e.g. poverty, low education, mental distress) may be both risk factors for, and consequences of, metabolic adversities such as obesity promoting risks of developing long-term health conditions, such as adult-onset diabetes (type 2 diabetes, T2D). This is creating a vicious cycle of ill health affecting people’s wellbeing, quality of life and can lead to accelerated ageing process and premature mortality. The importance of bio-psychosocial model, in theory and practice, will be investigated to promote healthy ageing. The project will be embedded in social science conceptual framework, it’s theories that will be reviewed for the project. Ageing represents the accumulation of changes in a human being over lifespan and can encompass physical, psychological, behavioural and social changes. The mechanisms of ageing process are not well understood but are assigned to the damage in the body that may lead to biological systems to fail. In clinical medicine and social science context ageing can be defined and assessed in multiple ways e.g. by cognition, perception of health and wellbeing and disease development. Ageing will be assessed broadly and will not only include ageing associated diseases and their intermediate markers (e.g. T2D, glucose levels, obesity) but also physical and cognitive function as an indicator of mental deterioration, subjective wellbeing and mental health (particularly depression), quality of life (QoL) indicators, life-satisfaction, socioeconomic circumstances and participation in the work force. The newly developed and novel Bayesian statistics based analytical approach that we adopt, embedded in dynamic systems, allows integration of hundreds – thousands of factors. Depending on the context the same factor maybe an outcome or it can be an exposure in the pathway analysis. In this project, we will restrict disease exploration on conditions essential for public health, i.e. T2D and related factors (glucose, body mass index) known to contribute to or mimic the ageing process. T2D that is exponentially increasing in the populations is a good “model disease” in this context. High glucose level for example may contribute to vascular damage and lead to dementia.