Pain and Rehabilitation Centre and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Mol Psychiatry. 2022 Aug;27(8):3510-3519. doi: 10.1038/s41380-022-01586-8. Epub 2022 Apr 28.
Numerous risk factors for mental disorders have been identified. However, we do not know how many disorders we could prevent and to what extent by modifying these risk factors. This study quantifies the Population Attributable Fraction (PAF) of potentially modifiable risk factors for mental disorders. We conducted a PRISMA 2020-compliant (Protocol: https://osf.io/hk2ag ) meta-umbrella systematic review (Web of Science/PubMed/Cochrane Central Register of Reviews/Ovid/PsycINFO, until 05/12/2021) of umbrella reviews reporting associations between potentially modifiable risk factors and ICD/DSM mental disorders, restricted to highly convincing (class I) and convincing (class II) evidence from prospective cohorts. The primary outcome was the global meta-analytical PAF, complemented by sensitivity analyses across different settings, the meta-analytical Generalised Impact Fraction (GIF), and study quality assessment (AMSTAR). Seven umbrella reviews (including 295 meta-analyses and 547 associations) identified 28 class I-II risk associations (23 risk factors; AMSTAR: 45.0% high-, 35.0% medium-, 20.0% low quality). The largest global PAFs not confounded by indication were 37.84% (95% CI = 26.77-48.40%) for childhood adversities and schizophrenia spectrum disorders, 24.76% (95% CI = 13.98-36.49%) for tobacco smoking and opioid use disorders, 17.88% (95% CI = not available) for job strain and depression, 14.60% (95% CI = 9.46-20.52%) for insufficient physical activity and Alzheimer's disease, 13.40% (95% CI = 7.75-20.15%) for childhood sexual abuse and depressive disorders, 12.37% (95% CI = 5.37-25.34%) for clinical high-risk state for psychosis and any non-organic psychotic disorders, 10.00% (95% CI = 5.62-15.95%) for three metabolic factors and depression, 9.73% (95% CI = 4.50-17.30%) for cannabis use and schizophrenia spectrum disorders, and 9.30% (95% CI = 7.36-11.38%) for maternal pre-pregnancy obesity and ADHD. The GIFs confirmed the preventive capacity for these factors. Addressing several potentially modifiable risk factors, particularly childhood adversities, can reduce the global population-level incidence of mental disorders.
已经确定了许多精神障碍的风险因素。然而,我们不知道通过改变这些风险因素可以预防多少种疾病,以及在多大程度上可以预防。本研究量化了精神障碍潜在可改变风险因素的人群归因分数 (PAF)。我们进行了一项符合 PRISMA 2020 指南(方案:https://osf.io/hk2ag)的元 umbrella 系统综述(Web of Science/PubMed/Cochrane 中央评论注册处/Ovid/PsycINFO,截至 2021 年 12 月 5 日),综述了潜在可改变的风险因素与 ICD/DSM 精神障碍之间的关联,仅限于前瞻性队列研究中具有高度说服力(I 类)和说服力(II 类)的证据。主要结果是全球荟萃分析的 PAF,辅以不同环境下的敏感性分析、荟萃分析的广义影响分数 (GIF) 和研究质量评估 (AMSTAR)。7 项 umbrella 综述(包括 295 项荟萃分析和 547 项关联)确定了 28 项 I-II 级风险关联(23 个风险因素;AMSTAR:45.0%高、35.0%中、20.0%低质量)。未被指征混淆的最大全球 PAF 为 37.84%(95%CI=26.77-48.40%),用于童年逆境和精神分裂症谱系障碍;24.76%(95%CI=13.98-36.49%),用于吸烟和阿片类药物使用障碍;17.88%(95%CI=不可用),用于工作压力和抑郁;14.60%(95%CI=9.46-20.52%),用于体力活动不足和阿尔茨海默病;13.40%(95%CI=7.75-20.15%),用于童年性虐待和抑郁障碍;12.37%(95%CI=5.37-25.34%),用于精神病的临床高危状态和任何非器质性精神病障碍;10.00%(95%CI=5.62-15.95%),用于三种代谢因素和抑郁;9.73%(95%CI=4.50-17.30%),用于大麻使用和精神分裂症谱系障碍;9.30%(95%CI=7.36-11.38%),用于母亲孕前肥胖和注意力缺陷多动障碍。GIF 证实了这些因素的预防能力。针对一些潜在可改变的风险因素,特别是儿童逆境,可以降低精神障碍在全球人群中的发病率。