How is city living associated with psychosis? Findings from a novel data linkage of 612,988 people from an urban and ethnically diverse area
Objectives UK cities show higher incidence of psychotic disorders, but the reasons remain unclear. This case-control study uses data from one of the first and largest person-level data linkages between mental health records and the UK census to explore associations previously only assessed using ec...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Swansea University
2023-09-01
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| Series: | International Journal of Population Data Science |
| Online Access: | https://ijpds.org/article/view/2264 |
| _version_ | 1797410068311834624 |
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| author | Rosanna Hildersley Jayati Das-Munshi Peter Schofield Lukasz Cybulski Milena Wuerth |
| author_facet | Rosanna Hildersley Jayati Das-Munshi Peter Schofield Lukasz Cybulski Milena Wuerth |
| author_sort | Rosanna Hildersley |
| collection | DOAJ |
| description |
Objectives
UK cities show higher incidence of psychotic disorders, but the reasons remain unclear. This case-control study uses data from one of the first and largest person-level data linkages between mental health records and the UK census to explore associations previously only assessed using ecological or smaller studies in England.
Methods
The SocioEconomic Predictors of Mental Disorders (SEP-MD) project dataset comprises of data extracted from electronic health records (EHR) from the South London and Maudsley NHS Foundation trust (SLaM). These EHRs were linked to the 2011 UK census as a collaboration between SLaM, the ONS and King’s College London.
Cases with clinical diagnoses of non-affective (schizophrenia-spectrum) and affective psychoses (bipolar disorder, depression with psychosis) were identified. Population controls were sampled from the locality.
Logistic regression models were used to calculate weighted adjusted (age and sex) odds ratios (waOR) to assess associations. Robust standard errors were used to account for clustering.
Results
16,863 linked cases with psychosis (affective n=5,694; non-affective n=11,169) were identified alongside 596,125 population controls.
Cases with psychosis were more likely to live in areas with the highest population density (waOR 1.17 (1.05, 1.30)) when comparing the lowest quintile to the highest. Non-affective disorders showed the highest association with population density.
Being born within the UK was associated with a higher risk of psychosis, and migrants living in the country for longer were at a significantly higher risk than those living in the UK for less time. Socioeconomic predictors, including education, occupation and tenure, were all associated with higher psychosis risk. Racialised minorities were at higher risk of specifically non-affective psychoses. Indicators of isolation (marital status and living alone) were highly associated with psychosis risk.
Conclusions
Our findings regarding urbanicity, ethnicity, migration socioeconomic position and social circumstances both confirm and provide further depth to previously identified associations. Novel findings relating to migration and interactions with ethnicity will require further investigation.
These insights will provide valuable information for future public health and policy development.
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| first_indexed | 2024-03-09T04:24:30Z |
| format | Article |
| id | doaj.art-0bb3605c0e214ff68ea2cdb4bee5a712 |
| institution | Directory Open Access Journal |
| issn | 2399-4908 |
| language | English |
| last_indexed | 2024-03-09T04:24:30Z |
| publishDate | 2023-09-01 |
| publisher | Swansea University |
| record_format | Article |
| series | International Journal of Population Data Science |
| spelling | doaj.art-0bb3605c0e214ff68ea2cdb4bee5a7122023-12-03T13:41:51ZengSwansea UniversityInternational Journal of Population Data Science2399-49082023-09-018210.23889/ijpds.v8i2.2264How is city living associated with psychosis? Findings from a novel data linkage of 612,988 people from an urban and ethnically diverse areaRosanna Hildersley0Jayati Das-Munshi1Peter Schofield2Lukasz Cybulski3Milena Wuerth4King's College London, London, United KingdomKing's College London, London, United KingdomKing's College London, London, United KingdomKing's College London, London, United KingdomKing's College London, London, United Kingdom Objectives UK cities show higher incidence of psychotic disorders, but the reasons remain unclear. This case-control study uses data from one of the first and largest person-level data linkages between mental health records and the UK census to explore associations previously only assessed using ecological or smaller studies in England. Methods The SocioEconomic Predictors of Mental Disorders (SEP-MD) project dataset comprises of data extracted from electronic health records (EHR) from the South London and Maudsley NHS Foundation trust (SLaM). These EHRs were linked to the 2011 UK census as a collaboration between SLaM, the ONS and King’s College London. Cases with clinical diagnoses of non-affective (schizophrenia-spectrum) and affective psychoses (bipolar disorder, depression with psychosis) were identified. Population controls were sampled from the locality. Logistic regression models were used to calculate weighted adjusted (age and sex) odds ratios (waOR) to assess associations. Robust standard errors were used to account for clustering. Results 16,863 linked cases with psychosis (affective n=5,694; non-affective n=11,169) were identified alongside 596,125 population controls. Cases with psychosis were more likely to live in areas with the highest population density (waOR 1.17 (1.05, 1.30)) when comparing the lowest quintile to the highest. Non-affective disorders showed the highest association with population density. Being born within the UK was associated with a higher risk of psychosis, and migrants living in the country for longer were at a significantly higher risk than those living in the UK for less time. Socioeconomic predictors, including education, occupation and tenure, were all associated with higher psychosis risk. Racialised minorities were at higher risk of specifically non-affective psychoses. Indicators of isolation (marital status and living alone) were highly associated with psychosis risk. Conclusions Our findings regarding urbanicity, ethnicity, migration socioeconomic position and social circumstances both confirm and provide further depth to previously identified associations. Novel findings relating to migration and interactions with ethnicity will require further investigation. These insights will provide valuable information for future public health and policy development. https://ijpds.org/article/view/2264 |
| spellingShingle | Rosanna Hildersley Jayati Das-Munshi Peter Schofield Lukasz Cybulski Milena Wuerth How is city living associated with psychosis? Findings from a novel data linkage of 612,988 people from an urban and ethnically diverse area International Journal of Population Data Science |
| title | How is city living associated with psychosis? Findings from a novel data linkage of 612,988 people from an urban and ethnically diverse area |
| title_full | How is city living associated with psychosis? Findings from a novel data linkage of 612,988 people from an urban and ethnically diverse area |
| title_fullStr | How is city living associated with psychosis? Findings from a novel data linkage of 612,988 people from an urban and ethnically diverse area |
| title_full_unstemmed | How is city living associated with psychosis? Findings from a novel data linkage of 612,988 people from an urban and ethnically diverse area |
| title_short | How is city living associated with psychosis? Findings from a novel data linkage of 612,988 people from an urban and ethnically diverse area |
| title_sort | how is city living associated with psychosis findings from a novel data linkage of 612 988 people from an urban and ethnically diverse area |
| url | https://ijpds.org/article/view/2264 |
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