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We aimed to spatially describe mental illness prevalence in England at small-area geographical level, as measured by prevalence of depression, severe mental illness (SMI) and antidepressant prescription volume in primary care records, and how much of their variation was explained by deprivation, social fragmentation and sociodemographic characteristics.
Information on prevalence of depression and SMI was obtained from the Quality and Outcomes Framework (QOF) administrative dataset for 2015/16 and the national dispensing dataset for 2015/16. Linear regression models were fitted to examine ecological associations between deprivation, social fragmentation, other sociodemographic characteristics and mental illness prevalence.
Mental illness prevalence varied within and between regions, with clusters of high prevalence identified across England. Our models explained 33.4–68.2% of variability in prevalence, but substantial variability between regions remained after adjusting for covariates. People in socially cohesive and socially deprived areas were more likely to be diagnosed with depression, while people in more socially fragmented and more socially deprived areas were more likely to be diagnosed with SMI.
Our findings suggest that to tackle mental health inequalities, attention needs to be targeted at more socially deprived localities. The role of social fragmentation warrants further investigation, and it is possible that depression remains undiagnosed in more socially fragmented areas. The wealth of routinely collected data can provide robust evidence to aid optimal resource allocation. If comparable data are available in other countries, similar methods could be deployed to identify high prevalence clusters and target funding to areas of greater need.
Pay-for-performance policies aim to improve population health by incentivising improvements in quality of care.
To assess the relationship between general practice performance on severe mental illness (SMI) and depression indicators under a national incentivisation scheme and suicide risk in England for the period 2006–2014.
Longitudinal spatial analysis for 32 844 small-area geographical units (lower super output areas, LSOAs), using population-structure adjusted numbers of suicide as the outcome variable. Negative binomial models were fitted to investigate the relationship between spatially estimated recorded quality of care and suicide risk at the LSOA level. Incidence rate ratios (IRRs) were adjusted for deprivation, social fragmentation, prevalence of depression and SMI as well as other 2011 Census variables.
No association was found between practice performance on the mental health indicators and suicide incidence in practice localities (IRR=1.000, 95% CI 0.998–1.002). IRRs indicated elevated suicide risks linked with area-level social fragmentation (1.030; 95% CI 1.027–1.034), deprivation (1.013, 95% CI 1.012–1.014) and rurality (1.059, 95% CI 1.027–1.092).
Primary care has an important role to play in suicide prevention, but we did not observe a link between practices' higher reported quality of care on incentivised mental health activities and lower suicide rates in the local population. It is likely that effective suicide prevention needs a more concerted, multiagency approach. Better training in suicide prevention for general practitioners is also essential. These findings pertain to the UK but have relevance to other countries considering similar programmes.
Declaration of interest
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