Unravelling the dynamics of mental health inequalities in England: A 12-year nationwide longitudinal spatial analysis of recorded depression prevalence

Tsimpida, Dialechti ORCID: 0000-0002-3709-5651, Tsakiridi, Anastasia, Daras, Konstantinos ORCID: 0000-0002-4573-4628, Corcoran, Rhiannon ORCID: 0000-0001-8900-9199 and Gabbay, Mark ORCID: 0000-0002-0126-8485 (2024) Unravelling the dynamics of mental health inequalities in England: A 12-year nationwide longitudinal spatial analysis of recorded depression prevalence SSM - Population Health, 26. p. 101669. ISSN 2352-8273, 2352-8273

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Abstract

Background: Depression is one of the most significant public health issues, but evidence of geographic patterns and trends of depression is limited. We aimed to examine the spatio-temporal patterns and trends of depression prevalence among adults in a nationwide longitudinal spatial study in England and evaluate the influence of neighbourhood socioeconomic deprivation in explaining patterns. Methods: Information on recorded depression prevalence was obtained from the indicator Quality and Outcomes Framework: Depression prevalence that measured the annual percentage of adults diagnosed with depression for Lower Super Output Areas (LSOA) from 2011 to 2022. We applied Cluster and Outlier Analysis using the Local Moran's I algorithm. Local effects of deprivation on depression in 2020 examined with Geographically Weighted Regression (GWR). Inequalities in recorded prevalence were presented using Prevalence Rate Ratios (PRR). Results: The North West Region of England had the highest concentration of High-High clusters of depression, with 17.4% of the area having high values surrounded by high values in both space and time and the greatest percentage of areas with a high rate of increase (43.1%). Inequalities widened among areas with a high rate of increase in prevalence compared to those with a lower rate of increase, with the PRR increasing from 1.66 (99% CI 1.61–1.70) in 2011 to 1.81 (99% CI 1.76–1.85) by 2022. Deprivation explained 3%–39% of the variance in depression in 2020 across the country. Conclusions: It is crucial to monitor depression's spatial patterns and trends and investigate mechanisms of mental health inequalities. Our findings can help identify priority areas and target prevention and intervention strategies in England. Evaluating mental health interventions in different geographic contexts can provide valuable insights to policymakers on the most effective and context-sensitive strategies, enabling them to allocate resources towards preventing the worsening of mental health inequalities.

Item Type:	Article
Uncontrolled Keywords:	Depression, Geographically weighted regression, Inequalities, Mental health, Morans' I, Spatial statistics
Divisions:	Faculty of Health & Life Sciences Faculty of Health & Life Sciences > Inst. Population Health
Depositing User:	Symplectic Admin
Date Deposited:	19 Apr 2024 08:37
Last Modified:	23 Jan 2026 00:47
DOI:	10.1016/j.ssmph.2024.101669
Open Access URL:	https://doi.org/10.1016/j.ssmph.2024.101669
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3180451
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