Division of Epidemiology, University of California Berkeley School of Public Health, Berkeley, California, USA
Division of Epidemiology, University of California Berkeley School of Public Health, Berkeley, California, USA.
J Epidemiol Community Health. 2019 Jun;73(6):577-584. doi: 10.1136/jech-2018-211230. Epub 2019 Mar 20.
Studies suggest that racial discrimination impacts health via biological dysregulation due to continual adaptation to chronic psychosocial stress. Therefore, quantifying chronicity is critical for operationalising the relevant aetiological exposure and hence maximising internal validity. Using one of the most common discrimination scales in the epidemiological literature, we develop a novel approach for more accurately assessing chronicity and compare it with conventional approaches to determine whether coding influences differential exposure classification and associations with hypertension and depression among African American women.
Data are from a socioeconomically diverse cross section of 208 mid-life African American women in Northern California (data collection: 2012-2013). Racial discrimination was assessed using the Everyday Discrimination Scale (α=0.95), and was coded using two conventional approaches: (1) : number of different situations ever experienced; (2) : sum of Likert scale responses ranging from 'never' to 'almost everyday'; and (3) a new approach: sum of responses, weighted to capture annual chronicity (eg, 'a few times a month'=3×12=36×/year). Outcomes are hypertension and depressive symptomatology (10-item Center for Epidemiologic Studies-Depression Scale).
Exposure classification differed by coding approach, by up to 41%. There was a positive association between racial discrimination and hypertension prevalence for chronicity coding only (prevalence ratio=1.61, 95% CI 1.03 to 2.49). For depressive symptoms, a dose-response relationship of similar magnitude was observed for all three coding approaches.
Scale coding is an important methodological consideration for valid exposure assessment in epidemiological research. Coding can impact exposure classification and associations with important indicators of African American women's mental and physical health.
研究表明,由于持续适应慢性心理社会压力,种族歧视会通过生物失调对健康产生影响。因此,量化慢性是将相关发病暴露因素操作化的关键,从而最大限度地提高内部有效性。本文使用流行病学文献中最常用的歧视量表之一,开发了一种更准确评估慢性的新方法,并将其与传统方法进行比较,以确定编码是否会影响差异暴露分类以及与非裔美国女性高血压和抑郁之间的关联。
数据来自北加州 208 名中年非裔美国女性的社会经济多样化横断面研究(数据收集:2012-2013 年)。使用日常歧视量表(α=0.95)评估种族歧视,并使用两种传统方法进行编码:(1):经历过的不同情况的数量;(2):从“从不”到“几乎每天”的李克特量表反应之和;(3):一种新的方法:反应之和,加权以捕捉年度慢性(例如,“每月几次”=3×12=36×/年)。结果是非裔美国女性的高血压和抑郁症状(10 项中心流行病学研究抑郁量表)。
暴露分类因编码方法而异,最多相差 41%。只有慢性编码与高血压患病率之间存在正相关(患病率比=1.61,95%CI 1.03 至 2.49)。对于抑郁症状,三种编码方法都观察到了类似大小的剂量-反应关系。
量表编码是流行病学研究中有效暴露评估的一个重要方法学考虑因素。编码会影响暴露分类以及与非裔美国女性心理和身体健康的重要指标的关联。