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城市化对社区精神病患病率的因果影响。

The causal impact of urbanicity on neighbourhood psychosis prevalence.

作者信息

Congdon Peter

机构信息

School of Geography, Queen Mary University of London, London E1 4NS, United Kingdom.

出版信息

Spat Spatiotemporal Epidemiol. 2025 Aug;54:100739. doi: 10.1016/j.sste.2025.100739. Epub 2025 Jul 29.

Abstract

There is considerable evidence of elevated psychosis rates in more urban settings. However, the urbanicity effect is confounded with other neighbourhood contextual effects, such as from deprivation and crime. To assess the nature of the underlying urbanicity effect, removing distorting effects of confounders, we consider a novel method to assessing causality in spatial applications: a propensity weight approach, with weights obtained by entropy optimization, and adjusting for the spatial overlap in the urbanicity effect via a bivariate exposure approach. The application is to the effect of urbanicity on psychosis prevalence in 6856 English neighbourhoods. We use a measure of urbanicity adapted to represent aspects of urban form, rather than simply population density or a binary indicator. The overlap effect in the psychosis outcome model is shown to outweigh the local effect, and we find a clear urbanicity gradient with a relative risk of 1.91 comparing the most and least urban areas, after adjustment for confounding through propensity weighting.

摘要

有大量证据表明,在城市化程度较高的地区,精神病发病率有所上升。然而,城市化效应与其他邻里环境效应相互混淆,比如来自贫困和犯罪的影响。为了评估潜在城市化效应的本质,消除混杂因素的扭曲效应,我们考虑一种在空间应用中评估因果关系的新方法:倾向权重法,通过熵优化获得权重,并通过双变量暴露法调整城市化效应中的空间重叠。该应用针对的是城市化对6856个英国邻里地区精神病患病率的影响。我们使用一种经过调整的城市化度量来代表城市形态的各个方面,而不是简单的人口密度或二元指标。结果表明,在精神病结局模型中,重叠效应超过了局部效应,并且在通过倾向加权调整混杂因素后,我们发现了一个明显的城市化梯度,比较最城市化和最不城市化地区的相对风险为1.91。

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