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种族密度效应作为生态疾病模型中的一种情境影响:确定其定量表达。

The ethnic density effect as a contextual influence in ecological disease models: Establishing its quantitative expression.

作者信息

Congdon Peter

机构信息

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

出版信息

Health Place. 2023 Sep;83:103083. doi: 10.1016/j.healthplace.2023.103083. Epub 2023 Aug 4.

Abstract

Research suggests higher neighbourhood ethnic minority density to be associated with lessened chances of ethnic group illness. We focus on the density effect on psychosis, arguing that (at higher ethnic concentrations) it acts as a contextual influence attenuating the compositional influence whereby minority ethnicity is associated with higher psychosis risk. In terms of ecological disease regression, the ethnic density effect will then be apparent in nonlinear impacts of minority concentration. Contextual effects may also be evident in spatially varying regression coefficient models for psychosis. Nonlinearity or heterogeneity may be associated with other contextual processes where geography modifies demography (e.g. deprivation amplification). We illustrate these issues with an analysis of psychosis prevalence in 4835 London neighbourhoods. The data are collected in primary care (during 2019/20) using clinical diagnosis (e.g. based on referrals to specialists or psychosis hospitalisation), and refer to patients currently under care: such care may extend retrospectively over several years. The data offer a complete population perspective in contrast to survey data, which typically offer limited geographic perspectives. We consider impacts on psychosis prevalence of non-white ethnicity, as well as those of deprivation, social fragmentation and urbanicity. We find evidence suggesting nonlinear impacts of non-white ethnicity on psychosis (essentially flat risk above a threshold concentration), but find no evidence for deprivation amplification.

摘要

研究表明,邻里少数民族密度越高,族群患病几率越低。我们关注密度对精神病的影响,认为(在较高的族群集中度下)它作为一种背景影响,减弱了构成影响,即少数族裔与较高的精神病风险相关联。就生态疾病回归而言,族群密度效应将在少数族裔集中度的非线性影响中显现出来。在精神病的空间变化回归系数模型中,背景效应也可能很明显。非线性或异质性可能与其他背景过程相关,在这些过程中地理因素会改变人口统计学特征(例如贫困加剧)。我们通过对伦敦4835个街区的精神病患病率进行分析来说明这些问题。数据是在初级保健中(2019/20年期间)使用临床诊断(例如基于转诊至专科医生或精神病住院治疗)收集的,并且涉及目前正在接受治疗的患者:这种治疗可能会追溯到过去几年。与通常提供有限地理视角的调查数据相比,这些数据提供了完整的总体视角。我们考虑非白人种族、贫困、社会分裂和城市化对精神病患病率的影响。我们发现有证据表明非白人种族对精神病有非线性影响(在阈值集中度以上风险基本平稳),但没有发现贫困加剧的证据。

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