Suppr超能文献

精神分裂症患者的失业、无家可归和其他社会后果:美国退伍军人健康管理局数据库的真实世界回顾性队列研究:美国退伍军人中的精神分裂症的社会负担。

Unemployment, homelessness, and other societal outcomes in patients with schizophrenia: a real-world retrospective cohort study of the United States Veterans Health Administration database : Societal burden of schizophrenia among US veterans.

机构信息

Janssen Scientific Affairs, LLC, Titusville, NJ, USA.

IQVIA, 4820 Emperor Blvd, Durham, NC, 27703, USA.

出版信息

BMC Psychiatry. 2022 Jul 8;22(1):458. doi: 10.1186/s12888-022-04022-x.

Abstract

BACKGROUND

The burden associated with schizophrenia is substantial. Impacts on the individual, healthcare system, and society may be particularly striking within the veteran population due to the presence of physical and mental health comorbidities. Disease burden is also influenced by a complex interplay between social determinants of health and health disparities. The objective of the current study was to compare non-healthcare societal outcomes between veterans with and without schizophrenia in the United States Veterans Health Administration (VHA).

METHODS

A retrospective cohort study was conducted using the VHA database (01/2013-09/2019; study period). Veterans with schizophrenia (≥2 diagnoses of ICD-9295.xx, ICD-10 F20.x, F21, and/or F25.x during the study period) were identified; the index date was the earliest observed schizophrenia diagnosis. Veterans with schizophrenia were propensity score-matched to those without schizophrenia using baseline characteristics. A 12-month baseline and variable follow-up period were applied. The frequency of unemployment, divorce, incarceration, premature death, and homelessness were compared between the matched cohorts using standardized mean difference (SMD). Risk of unemployment and homelessness were estimated using logistic regression models.

RESULTS

A total of 102,207 veterans remained in each cohort after matching (91% male; 61% White [per AMA]; median age, 59 years). Among veterans with schizophrenia, 42% had a substance use disorder and 30% had mental health-related comorbidities, compared with 25 and 15%, respectively, of veterans without schizophrenia. Veterans with schizophrenia were more likely to experience unemployment (69% vs. 41%; SMD: 0.81), divorce (35% vs. 28%; SMD: 0.67), homelessness (28% vs. 7%; SMD: 0.57), incarceration (0.4% vs. 0.1%; SMD: 0.47), and premature death (14% vs. 12%; SMD < 0.1) than veterans without schizophrenia. After further adjustments, the risk of unemployment and of homelessness were 5.4 and 4.5 times higher among veterans with versus without schizophrenia. Other predictors of unemployment included Black [per AMA] race and history of substance use disorder; for homelessness, younger age (18-34 years) and history of mental health-related comorbidities were additional predictors.

CONCLUSION

A greater likelihood of adverse societal outcomes was observed among veterans with versus without schizophrenia. Given their elevated risk for unemployment and homelessness, veterans with schizophrenia should be a focus of targeted, multifactorial interventions to reduce disease burden.

摘要

背景

精神分裂症的负担是巨大的。由于存在身心健康共病,退伍军人群体中的个人、医疗保健系统和社会可能会受到特别显著的影响。疾病负担还受到健康决定因素和健康差异之间复杂相互作用的影响。本研究的目的是比较美国退伍军人事务部(VHA)中患有和不患有精神分裂症的退伍军人之间非医疗保健的社会结果。

方法

使用 VHA 数据库(2013 年 1 月至 2019 年 9 月;研究期间)进行回顾性队列研究。患有精神分裂症的退伍军人(在研究期间至少有 2 次 ICD-9295.xx、ICD-10 F20.x、F21 和/或 F25.x 诊断);指数日期为最早观察到的精神分裂症诊断。使用基线特征对患有精神分裂症的退伍军人与不患有精神分裂症的退伍军人进行倾向评分匹配。应用 12 个月的基线和可变随访期。使用标准化均差(SMD)比较匹配队列之间的失业、离婚、监禁、过早死亡和无家可归的频率。使用 logistic 回归模型估计失业和无家可归的风险。

结果

匹配后,每个队列中仍有 102207 名退伍军人(91%为男性;61%为白人[按 AMA];中位年龄 59 岁)。患有精神分裂症的退伍军人中,42%有物质使用障碍,30%有心理健康相关共病,而没有精神分裂症的退伍军人中分别为 25%和 15%。患有精神分裂症的退伍军人更有可能失业(69% vs. 41%;SMD:0.81)、离婚(35% vs. 28%;SMD:0.67)、无家可归(28% vs. 7%;SMD:0.57)、监禁(0.4% vs. 0.1%;SMD:0.47)和过早死亡(14% vs. 12%;SMD<0.1)比没有精神分裂症的退伍军人。进一步调整后,与没有精神分裂症的退伍军人相比,患有精神分裂症的退伍军人失业和无家可归的风险分别高 5.4 倍和 4.5 倍。失业的其他预测因素包括非裔美国人[按 AMA]种族和物质使用障碍史;对于无家可归,年龄较小(18-34 岁)和心理健康相关共病史是其他预测因素。

结论

与没有精神分裂症的退伍军人相比,患有精神分裂症的退伍军人更有可能出现不良的社会结果。鉴于他们失业和无家可归的风险较高,患有精神分裂症的退伍军人应成为有针对性的多因素干预措施的重点,以减轻疾病负担。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f797/9264584/b71bffdfd04f/12888_2022_4022_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验