Scottish Longitudinal Study
Development & Support Unit
Project Extension: Social inequalities in chronic disease trajectories in mid and later life: taking account of multimorbidities
Dr Katherine Keenan, University of St Andrews
Prof Hill Kulu, University of St Andrews
Genevieve Cezard, University of St Andrews
The aims of the original project remain the same: Briefly,
To investigate social and demographic factors that predict differential trajectories of chronic disease among adults in mid-and later-life living in Scotland, taking into account multimorbidities.
Detailed research questions / aims:
- To develop methods for characterising common longitudinal trajectories of multimorbidity of chronic diseases by exploring possibilities of sequence analysis, Markov state modelling and/ or survival analysis.
- Investigate how such trajectories are associated with cross-sectional/ non time varying measures of socio-economic and demographic factors derived from census data, including household structure and size, marital status, SIMD, ethnicity, fertility history.
- Through sequential SLS waves investigate how changes in family and social factors may be associated with more negative trajectories.
We wish to add some aims specifically relating to Covid-19 risk, multimorbidities and household inequalities ( this was encouraged by the funder AMS) :
- Using our existing linked data, we will investigate how covid-19 health risks and particularly multimorbidity relates to individual and household level social inequalities. Using hospitalisation and prescription data, we will identify individuals with high risk health conditions, who either need to shield, or who are high risk for covid-19 complications. We will characterise their socio-demographic, socio-economic and household characteristics based on 2011 census records. The aim is to understand the co-occurrence of social and health risks in the population. We may do the same analyses using 2001 to check that the relationships remain similar.
- We will construct indices of Covid-19 vulnerability (using principle components analysis or multiple correspondence analysis) by taking into account multiple indicators at individual and household level (employment, housing characteristics, income, deprivation, household structures, health) and assess how their co-occurrence, are distributed by deprivation, geography and household structure. This is to replicate/extend analysis conducted using understanding society https://osf.io/preprints/socarxiv/4wtz8/, but with a better identification of individuals with high risk conditions relating to Covid-19.
The available analysis so far of the impact of Covid-19 on social inequalities has been relatively limited, and the conceptualization of risk and vulnerability has so far been at the individual, rather than household level. This research will aim to demonstrate to policy makers that one has to think at a household scale too. This will provide evidence and possible projections for how covid-19 vulnerabilities cluster at various scales: the household, geographically and within social groups. This may be of interest to policy makers who may wish to target alleviation strategies to particular areas or particular social groups. We will ensure policy makers understand the research and its implications by producing a policy brief for the Centre for Population Change and Population Europe, and will share the results with NRS and NHS Scotland. We will present the results at an upcoming CPC research seminar to which NRS and other policy makers are invited.