Department of Clinical, Educational and Health Psychology, University College London, London, UK
Division of Psychiatry, University College London, London, UK.
BMJ Open. 2019 Sep 18;9(9):e030448. doi: 10.1136/bmjopen-2019-030448.
To determine whether neighbourhood-level socioenvironmental factors including deprivation and inequality predict variance in psychotic symptoms after controlling for individual-level demographics.
A cross-sectional design was employed.
Data were originally collected from secondary care services within the UK boroughs of Ealing, Hammersmith and Fulham, Wandsworth, Kingston, Richmond, Merton, Sutton and Hounslow as part of the West London First-Episode Psychosis study.
Complete case analyses were undertaken on 319 participants who met the following inclusion criteria: aged 16 years or over, resident in the study's catchment area, experiencing a first psychotic episode, with fewer than 12 weeks' exposure to antipsychotic medication and sufficient command of English to facilitate assessment.
Symptom dimension scores, derived from principal component analyses of the Scale for the Assessment of Positive Symptoms and Scale for the Assessment of Negative Symptoms, were regressed on neighbourhood-level predictors, including population density, income deprivation, income inequality, social fragmentation, social cohesion, ethnic density and ethnic fragmentation, using multilevel regression. While age, gender and socioeconomic status were included as individual-level covariates, data on participant ethnicity were not available.
Higher income inequality was associated with lower negative symptom scores (coefficient=-1.66, 95% CI -2.86 to -0.46, p<0.01) and higher levels of ethnic segregation were associated with lower positive symptom scores (coefficient=-2.32, 95% CI -4.17 to -0.48, p=0.01) after adjustment for covariates.
These findings provide further evidence that particular characteristics of the environment may be linked to specific symptom clusters in psychosis. Longitudinal studies are required to begin to tease apart the underlying mechanisms involved as well as the causal direction of such associations.
在控制个体水平人口统计学因素的情况下,确定邻里环境因素(包括贫困和不平等)是否可预测精神病症状的变化。
采用横断面设计。
数据最初是从英国伊灵、汉默史密斯和富勒姆、旺兹沃思、金斯敦、里士满、默顿、萨顿和豪恩斯洛等区的二级保健服务中收集的,作为伦敦西部首发精神病研究的一部分。
符合以下纳入标准的 319 名参与者进行了完整病例分析:年龄在 16 岁及以上、居住在研究的覆盖范围内、经历首次精神病发作、抗精神病药物暴露时间少于 12 周、有足够的英语水平以方便评估。
使用多层回归,根据人口密度、收入贫困、收入不平等、社会分裂、社会凝聚力、族裔密度和族裔分裂等邻里水平预测因素,对来自阳性症状评定量表和阴性症状评定量表的主要成分分析得出的症状维度得分进行回归。虽然将年龄、性别和社会经济地位作为个体水平的协变量进行了纳入,但参与者种族的数据不可用。
这些发现进一步表明,环境的某些特征可能与精神病的特定症状群有关。需要进行纵向研究,以开始梳理相关的潜在机制以及这些关联的因果关系方向。