{"title":"揭示英格兰心理健康不平等的动态变化：对记录在案的抑郁症发病率进行为期 12 年的全国性纵向空间分析","authors":"Dialechti Tsimpida , Anastasia Tsakiridi , Konstantinos Daras , Rhiannon Corcoran , Mark Gabbay","doi":"10.1016/j.ssmph.2024.101669","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>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.</p></div><div><h3>Methods</h3><p>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).</p></div><div><h3>Results</h3><p>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.</p></div><div><h3>Conclusions</h3><p>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.</p></div>","PeriodicalId":47780,"journal":{"name":"Ssm-Population Health","volume":"26 ","pages":"Article 101669"},"PeriodicalIF":3.6000,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352827324000703/pdfft?md5=98ec94353f2320d1d985476abdd18089&pid=1-s2.0-S2352827324000703-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Unravelling the dynamics of mental health inequalities in England: A 12-year nationwide longitudinal spatial analysis of recorded depression prevalence\",\"authors\":\"Dialechti Tsimpida , Anastasia Tsakiridi , Konstantinos Daras , Rhiannon Corcoran , Mark Gabbay\",\"doi\":\"10.1016/j.ssmph.2024.101669\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>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.</p></div><div><h3>Methods</h3><p>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).</p></div><div><h3>Results</h3><p>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.</p></div><div><h3>Conclusions</h3><p>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.</p></div>\",\"PeriodicalId\":47780,\"journal\":{\"name\":\"Ssm-Population Health\",\"volume\":\"26 \",\"pages\":\"Article 101669\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2352827324000703/pdfft?md5=98ec94353f2320d1d985476abdd18089&pid=1-s2.0-S2352827324000703-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ssm-Population Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352827324000703\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ssm-Population Health","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352827324000703","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
摘要
背景抑郁症是最重要的公共卫生问题之一，但有关抑郁症的地理模式和趋势的证据却很有限。我们旨在研究英格兰一项全国性纵向空间研究中成人抑郁症患病率的时空模式和趋势，并评估邻里社会经济贫困对解释这种模式的影响：抑郁症患病率的记录信息来自 "质量与成果框架：抑郁症患病率 "指标，该指标衡量了 2011 年至 2022 年期间，每年被诊断患有抑郁症的成年人在低产出区（LSOA）所占的百分比。我们使用地方莫兰 I 算法进行了聚类和离群值分析。利用地理加权回归（GWR）分析了 2020 年贫困对当地抑郁症的影响。结果英格兰西北部地区的抑郁症 "高-高 "集群最为集中，17.4%的地区在空间和时间上都被高值所包围，且高增长率地区的比例最高（43.1%）。与增长率较低的地区相比，患病率增长率较高的地区之间的不平等有所扩大，PRR 从 2011 年的 1.66（99% CI 1.61-1.70）上升到 2022 年的 1.81（99% CI 1.76-1.85）。2020 年，全国抑郁症患者的差异中，3%-39% 是由贫困造成的。我们的研究结果可以帮助英格兰确定优先领域，并有针对性地制定预防和干预策略。对不同地理环境下的心理健康干预措施进行评估，可以为政策制定者提供有关最有效和对环境敏感的策略的宝贵见解，使他们能够分配资源，防止心理健康不平等现象的恶化。
Unravelling the dynamics of mental health inequalities in England: A 12-year nationwide longitudinal spatial analysis of recorded depression prevalence
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.
期刊介绍：
SSM - Population Health. The new online only, open access, peer reviewed journal in all areas relating Social Science research to population health. SSM - Population Health shares the same Editors-in Chief and general approach to manuscripts as its sister journal, Social Science & Medicine. The journal takes a broad approach to the field especially welcoming interdisciplinary papers from across the Social Sciences and allied areas. SSM - Population Health offers an alternative outlet for work which might not be considered, or is classed as ''out of scope'' elsewhere, and prioritizes fast peer review and publication to the benefit of authors and readers. The journal welcomes all types of paper from traditional primary research articles, replication studies, short communications, methodological studies, instrument validation, opinion pieces, literature reviews, etc. SSM - Population Health also offers the opportunity to publish special issues or sections to reflect current interest and research in topical or developing areas. The journal fully supports authors wanting to present their research in an innovative fashion though the use of multimedia formats.
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