In our first blog, we explained the story of our project and the method used to link data from South London and Maudsley NHS Foundation Trust to the 2011 UK Census. After several months of data analysis, we can now share some preliminary findings which were presented bypost-doctoral researcher Dr. Lukasz Cybulski at the Congress of the Schizophrenia International Research Society. The findings highlight inequalities across the study sample and potential risk factors for unemployment, poor health, and disability.
Our dataset: a refresher
As explained in our second blog, our project – the Social and Economic Predictors of the Severe Mental Disorders: The SEP-MD Data Linkage Study – led by our team, in collaboration with the Office for National Statistics (ONS), is linking or connecting electronic hospital records from one of the nation’s largest secondary mental health trusts with data from the 2011 Census. The records were linked and then anonymised by the ONS, before being stored in a secure environment for analysis by our specially accredited research team.
This linkage allows us to explore associations between health outcomes and social or economic factors, including employment and household characteristics. The size and diversity of this cohort has allowed us to explore and adjust for individual-level socioeconomic indicators usually not included in routinely collected healthcare records.
For this study, we used a sample of 8,930 patient records from individuals diagnosed with schizophrenia spectrum or bipolar disorders. Using statistical methods, we explored the relationship between social, economic, and clinical indicators and unemployment, poor health, and disability outcomes.
The data showed several trends:
1. Unemployment (80.4%), disability (67.4%) and poor health (60.5%) were very high in the cohort of people with severe mental health conditions.
This is not unexpected, but still striking when compared with the general population; in the 2011 census of England and Wales found unemployment at 7.1%, disability at 18%, and poor health at 6% overall. High levels of unemployment, disability, and poor health among those with severe mental illness have been explored in previous studies. The SEP-MD data, however, shows just how disproportionately this cohort experiences different forms of social disadvantage, compared to the general population.
It has been hypothesised that this could be evidence of a ‘social gradient’ affecting those with severe mental illness, whereby people of lower social status experience poorer health. Most studies so far have not been sufficiently large or representative to draw conclusions about potential cause-effect relationships (although associations have been shown). The findings from our large, linked dataset suggests that, in fact, those with severe mental illness may experience even worse outcomes than people residing in the most deprived areas, on average. Unemployment, poor health, and disability amongst those living in the most deprived areas are estimated to be higher, compared to the least deprived, but still much lower than in our study cohort.
2. Members of Black Caribbean, African and South Asian communities were more likely to be unemployed than the White British majority.
This difference is evidence of inequalities within the cohort of people with severe mental illness, with particularly high unemployment in the Black Caribbean group relative to the White British group. This gap may suggest a ‘double disadvantage’ for this group in particular.
We have also found evidence that length of stay in the UK makes a difference for people from minority ethnic groups, with the risk of poor health increasing for those who have stayed in the UK longer. This difference could reflect the effects of stigma or discrimination over time, or a variety of other factors. These are all still hypotheses, which must be more rigorously tested before conclusions can be drawn; still, the overall finding is broadly consistent with other studies that have previously been conducted in this area.
3. After taking into account individual-level socioeconomic factors, living alone was strongly associated with each outcome.
Out of the measures available in the 2011 Census, we used ‘living alone’ to indicate those people who may be more socially isolated. The association between social isolation and mental disorders has been explored mostly from sociological perspectives, with very few epidemiological studies to date. It is possible that more resources to support people who are isolated could help improve health outcomes, and our team is planning further studies to investigate this.