Prevalence of mental illness in primary care and its association with deprivation and social fragmentation at small-area level: a spatial analysis in EnglandCitation formats

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@article{42d02e604aab477580e3edf83127c65c,
title = "Prevalence of mental illness in primary care and its association with deprivation and social fragmentation at small-area level: a spatial analysis in England",
abstract = "Background: 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.Methods: 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.Results: Mental illness prevalence varied within and between regions, with clusters of high prevalence identified across England. Our models explained 33.4% to 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.Conclusions: 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.",
keywords = "Mental illness, depression, severe mental illness, deprivation, social fragmentation, antidepressant prescribing",
author = "Christos Grigoroglou and Luke Munford and Roger Webb and Nav Kapur and Darren Ashcroft and Evangelos Kontopantelis",
year = "2019",
doi = "10.1017/s0033291719000023",
language = "English",
journal = "Psychological Medicine",
issn = "0033-2917",
publisher = "Cambridge University Press",

}

RIS

TY - JOUR

T1 - Prevalence of mental illness in primary care and its association with deprivation and social fragmentation at small-area level: a spatial analysis in England

AU - Grigoroglou, Christos

AU - Munford, Luke

AU - Webb, Roger

AU - Kapur, Nav

AU - Ashcroft, Darren

AU - Kontopantelis, Evangelos

PY - 2019

Y1 - 2019

N2 - Background: 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.Methods: 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.Results: Mental illness prevalence varied within and between regions, with clusters of high prevalence identified across England. Our models explained 33.4% to 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.Conclusions: 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.

AB - Background: 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.Methods: 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.Results: Mental illness prevalence varied within and between regions, with clusters of high prevalence identified across England. Our models explained 33.4% to 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.Conclusions: 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.

KW - Mental illness

KW - depression

KW - severe mental illness

KW - deprivation

KW - social fragmentation

KW - antidepressant prescribing

U2 - 10.1017/s0033291719000023

DO - 10.1017/s0033291719000023

M3 - Article

JO - Psychological Medicine

JF - Psychological Medicine

SN - 0033-2917

ER -