PDF(Pubmed)
Abstract：
The collection of sexual orientation in routine data, generated either from contacts with health services or in infrastructure data resources designed and collected for policy and research, has improved substantially in the United Kingdom in the last decade. Inclusive measures of gender and transgender status are now also beginning to be collected. This viewpoint considers current data collections, and their strengths and limitations, including accessing data, sample size, measures of sexual orientation and gender, measures of health outcomes, and longitudinal follow-up. The available data are considered within both sociopolitical and biomedical models of health for individuals who are lesbian, gay, bisexual, transgender, queer, or of other identities including nonbinary (LGBTQ+). Although most individual data sets have some methodological limitations, when put together, there is now a real depth of routine data for LGBTQ+ health research. This paper aims to provide a framework for how these data can be used to improve health and health care outcomes. Four practical analysis approaches are introduced-descriptive epidemiology, risk prediction, intervention development, and impact evaluation-and are discussed as frameworks for translating data into research with the potential to improve health.
摘要：
在常规数据中收集性取向，从与卫生服务部门的联系或为政策和研究而设计和收集的基础设施数据资源中生成，在过去十年中，英国的情况有了很大改善。现在也开始收集关于性别和变性者地位的包容性措施。这个观点考虑了当前的数据收集，以及它们的优势和局限性，包括访问数据，样本量,衡量性取向和性别，健康结果的衡量标准，纵向随访。现有数据在社会政治和生物医学健康模型中都被认为是女同性恋，同性恋,双性恋,变性人,酷儿,或其他身份，包括非二进制(LGBTQ+)。尽管大多数单独的数据集都有一些方法论上的限制，当放在一起，现在有一个真正深度的LGBTQ+健康研究的常规数据。本文旨在为如何使用这些数据来改善健康和医疗保健结果提供一个框架。介绍了四种实用的分析方法-描述性流行病学，风险预测，干预发展，和影响评估-并被讨论为将数据转化为具有改善健康潜力的研究的框架。
