ArticleSSM - population health2024
Unravelling the dynamics of mental health inequalities in England: A 12-year nationwide longitudinal spatial analysis of recorded depression prevalence.
Article in SSM - population health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Urban-rural dichotomy of emergency medical service demand: spatiotemporal patterns and heterogeneous driving mechanisms.BMC public health · 2026Article
- Prevalence and experiences of presenteeism in the workplace: a cross-sectional survey of an English National Health Service Mental Health Trust.Frontiers in health services · 2026Article
- From fragmentation to integration: can social prescribing bridge the gap between multimorbidity and mental health in an ageing population?BMJ public health · 2026Review
- Mental health within ESG frameworks: a narrative and descriptive cross-national analysis.Frontiers in public health · 2026Review
- Assessing hearing health inequalities using routine health information systems.Journal of public health policy · 2025Article
- Introduction to the special issue collection, How and why are health inequalities changing over time?SSM - population health · 2025Article
- Estimating the prevalence, socioeconomic determinants, and health seeking behavior of individuals with depression in Ghana.Scientific reports · 2025Article
- The Relationship between Noise Pollution and Depression and Implications for Healthy Aging: A Spatial Analysis Using Routinely Collected Primary Care Data.Journal of urban health : bulletin of the New York Academy of Medicine · 2025Article
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Authors and funding
5 authors.
Funding
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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.
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