社会环境邻里因素和类似精神病经历的暴露特征。

Benson Ku, Qingyue Yuan, Grace M Christensen, Lina Dimitrov, Benjamin Risk, Anke Huels
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引用次数: 0

摘要

重要性:最近的研究表明,健康的社会决定因素(SDOH)(如空气污染和社会环境)与精神病有关。然而,人们往往孤立地研究社会决定健康因素:目的:确定不同的暴露特征,估计它们与持续的类似精神病的痛苦经历(PLE)之间的关联,并评估参与体育活动是否能部分解释这种关联:这项基于人群的研究使用了青少年大脑和认知发展(ABCD)研究的数据。参与者是在 2016 年 9 月至 2022 年 1 月期间从美国 22 个地点招募的。研究纳入了基线数据和三次随访数据:使用自组织地图方法对跨越 SDOH 各领域(包括社会经济地位 (SES)、教育、犯罪、建筑环境、社会背景和犯罪)的地区级地理编码变量进行聚类,以确定暴露概况:持续困扰性 PLE 是根据儿童前驱症状问卷简明版得出的,时间跨度为四年。广义线性混合模型检验了暴露特征与持续困扰性 PLE 以及体育活动(即团队和个人运动)之间的关联,并调整了个人层面的协变量,包括年龄、性别、种族/民族、父母的最高教育水平、家庭相关性和研究地点:在 8145 名参与者(基线平均[标码]年龄为 9.92 [0.63]岁;女性 3868 人(47.5%);白人 5566 人(68.3%)、黑人 956 人(11.7%)、亚裔 159 人(2.0%)、西班牙裔 1480 人(18.4%))中,确定了五种暴露特征。与参考特征 1(郊区富裕地区,2521 名儿童,占 30.9%)相比,特征 3(步行率低、臭氧含量高的农村地区;1459 名儿童,占 17.9%;调整后 OR:1.34,95% CI:1.09-1.64)和特征 4(社会经济地位高、犯罪率高、污染严重的城市地区;715 名儿童,占 8.8%;调整后 OR:1.40,95% CI:1.08-1.81)与持续困扰性 PLE 相关。团队运动对特征 3 的关联起到了 6.14% 的中介作用:本研究发现,以步行便利性低的农村地区和社会经济贫困、空气污染和犯罪率高的城市地区为特征的社区与持续性令人痛苦的 PLE 相关。需要进一步研究探索不同环境因素可能影响精神病发展的途径。
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Exposure profiles of social-environmental neighborhood factors and psychotic-like experiences.

Importance: Recent research has demonstrated that domains of social determinants of health (SDOH) (e.g., air pollution and social context) are associated with psychosis. However, SDOHs have often been studied in isolation.

Objective: To identify distinct exposure profiles, estimate their associations with persistent distressing psychotic-like experiences (PLE), and evaluate whether involvement with physical activities partially explains this association.

Design setting and participants: This population-based study used data from the Adolescent Brain and Cognitive Development (ABCD) Study. Participants were recruited from 22 US sites between September 2016 and January 2022. Data from baseline and three follow-ups were included.

Exposures: Area-level geocoded variables spanning various domains of SDOH, including socioeconomic status (SES), education, crime, built environment, social context, and crime, were clustered using a self-organizing map method to identify exposure profiles.

Main outcomes and measures: Persistent distressing PLE was derived from the Prodromal Questionnaire-Brief Child Version across four years. Generalized linear mixed modeling tested the association between exposure profiles and persistent distressing PLE as well as physical activities (i.e., team and individual sports), adjusting for individual-level covariates including age, sex, race/ethnicity, highest level of parent education, family-relatedness, and study sites.

Results: Among 8,145 participants (baseline mean [SD] age, 9.92 [0.63] years; 3,868 (47.5%) females; 5,566 (68.3%) White, 956 (11.7%) Black, 159 (2.0%) Asian, and 1,480 (18.4%) Hispanic participants), five exposure profiles were identified. Compared to the reference Profile 1 (suburban affluent areas, 2521 children, 30.9%), Profile 3 (rural areas with low walkability and high ozone; 1459 children, 17.9%; adjusted OR: 1.34, 95% CI: 1.09-1.64) and Profile 4 (urban areas with high SES deprivation, high crime, and high pollution; 715 children, 8.8%; adjusted OR: 1.40, 95% CI: 1.08-1.81), were associated with persistent distressing PLE. Team sports mediated 6.14% of the association for Profile 3.

Conclusion and relevance: This study found that neighborhoods characterized by rural areas with low walkability and urban areas with high socioeconomic deprivation, air pollutants, and crime were associated with persistent distressing PLE. Further research is needed to explore the pathways through which different environmental factors may impact the development of psychosis.

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