Using large data sets to explore the population-level long-term effects of social factors
We use advanced statistical analyses to explore associations between social factors and the prevention and management of mental and physical illness at a population level. We work with datasets including international cohort studies, patient electronic medical records, and bespoke large-scale datasets such as the COVID-19 Social Study that we recruit ourselves. Our work has identified associations between social factors including the arts, cultural engagement, volunteering, and social networks and reduced incidence of depression, childhood behavioural problems, chronic pain, frailty, cognitive decline, age-related disability and premature mortality as well as higher wellbeing, self-esteem and healthy behaviours. We’ve also shown how social deficits such as social isolation and loneliness are related to the incidence and management of chronic diseases. Notably our findings are independent of factors that could explain such associations such as wealth, education, health behaviours and other leisure activities. We’ve additionally undertaken in-depth research into the psychosocial impact of the COVID-19 pandemic, identifying how and why people have been differently affected. Through all of our epidemiology work, we specialise in looking at biological and clinical outcomes, showing the relationship between the arts and neuroendocrine and immune response, the relationship between different types of social deficits and health service utilisation, and the interplay between social engagement, social connections, genetic propensity for social and health traits, and health outcomes.
Examples of our epidemiology work include EpiArts, COVID-19 Social Study, and Arts, Society and Public Health.