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一项减少多族裔人群焦虑不平等的假设性干预措施:模拟针对童年逆境的干预。

A hypothetical intervention to reduce inequities in anxiety for Multiracial people: simulating an intervention on childhood adversity.

作者信息

Lam-Hine Tracy, Bradshaw Patrick T, Allen Amani M, Omi Michael, Riddell Corinne A

机构信息

Stanford University School of Medicine, Division of Epidemiology & Population Health, Palo Alto CA.

University of California Berkeley School of Public Health, Division of Epidemiology, Berkeley, CA.

出版信息

medRxiv. 2023 Jun 6:2023.06.04.23290940. doi: 10.1101/2023.06.04.23290940.

Abstract

Multiracial people report higher mean Adverse Childhood Experiences (ACEs) scores and prevalence of anxiety than other racial groups. Studies using statistical interactions to estimate racial differences in ACEs-anxiety associations do not show stronger associations for Multiracial people. Using data from Waves 1 (1995-97) through 4 (2008-09) of the National Longitudinal Study of Adolescent to Adult Health (Add Health), we simulated a stochastic intervention over 1,000 resampled datasets to estimate the race-specific cases averted per 1,000 of anxiety if all racial groups had the same exposure distribution of ACEs as Whites. Simulated cases averted were greatest for the Multiracial group, (median = -4.17 cases per 1,000, 95% CI: -7.42, -1.86). The model also predicted smaller risk reductions for Black participants (-0.76, 95% CI: -1.53, -0.19). CIs around estimates for other racial groups included the null. An intervention to reduce racial disparities in exposure to ACEs could help reduce the inequitable burden of anxiety on the Multiracial population. Stochastic methods support consequentialist approaches to racial health equity, and can encourage greater dialogue between public health researchers, policymakers, and practitioners.

摘要

与其他种族群体相比,多种族人群报告的童年不良经历(ACEs)平均得分更高,焦虑症患病率也更高。使用统计交互作用来估计ACEs与焦虑症关联中的种族差异的研究并未显示多种族人群的关联更强。利用青少年到成人健康全国纵向研究(Add Health)第1波(1995 - 97年)至第4波(2008 - 09年)的数据,我们在1000个重新抽样的数据集中模拟了一种随机干预,以估计如果所有种族群体的ACEs暴露分布与白人相同,每1000例焦虑症中可避免的特定种族病例数。多种族群体模拟可避免的病例数最多(中位数 = 每1000例 - 4.17例,95%置信区间:-7.42,-1.86)。该模型还预测黑人参与者的风险降低幅度较小(-0.76,95%置信区间:-1.53,-0.19)。其他种族群体估计值的置信区间包含零值。减少ACEs暴露方面种族差异的干预措施有助于减轻多种族人群焦虑症的不公平负担。随机方法支持种族健康公平的结果主义方法,并可鼓励公共卫生研究人员、政策制定者和从业者之间进行更多对话。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d40d/10274983/cb4aff6b99de/nihpp-2023.06.04.23290940v1-f0001.jpg

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