Population Data Science, Swansea University Medical School, Swansea, United Kingdom.
PLoS One. 2021 Mar 29;16(3):e0248195. doi: 10.1371/journal.pone.0248195. eCollection 2021.
Physical housing and household composition have an important role in the lives of individuals and drive health and social outcomes, and inequalities. Most methods to understand housing composition are based on survey or census data, and there is currently no reproducible methodology for creating population-level household composition measures using linked administrative data.
Using existing, and more recent enhancements to the address-data linkage methods in the SAIL Databank using Residential Anonymised Linking Fields we linked individuals to properties using the anonymised Welsh Demographic Service data in the SAIL Databank. We defined households, household size, and household composition measures based on adult to child relationships, and age differences between residents to create relative age measures.
Two relative age-based algorithms were developed and returned similar results when applied to population and household-level data, describing household composition for 3.1 million individuals within 1.2 million households in Wales. Developed methods describe binary, and count level generational household composition measures.
Improved residential anonymised linkage field methods in SAIL have led to improved property-level data linkage, allowing the design and application of household composition measures that assign individuals to shared residences and allow the description of household composition across Wales. The reproducible methods create longitudinal, household-level composition measures at a population-level using linked administrative data. Such measures are important to help understand more detail about an individual's home and area environment and how that may affect the health and wellbeing of the individual, other residents, and potentially into the wider community.
物理住房和家庭结构在个人生活中起着重要作用,并影响健康和社会结果以及不平等。大多数理解家庭结构的方法都是基于调查或人口普查数据,目前还没有使用链接行政数据创建人群层面家庭构成度量的可重复方法。
我们使用 SAIL 数据库中现有的和最近增强的地址数据链接方法,以及使用住宅匿名链接字段,使用 SAIL 数据库中的匿名威尔士人口服务数据将个人与房产相关联。我们根据成人与儿童的关系以及居民之间的年龄差异定义家庭、家庭规模和家庭构成指标,以创建相对年龄指标。
开发了两种基于相对年龄的算法,当应用于人群和家庭层面的数据时,它们返回了相似的结果,描述了威尔士 120 万户家庭中的 310 万人的家庭构成。开发的方法描述了二进制和计数级别的代际家庭构成指标。
SAIL 中改进的住宅匿名链接字段方法导致了更好的房产层面数据链接,允许设计和应用家庭构成指标,将个人分配到共享住所,并描述威尔士各地的家庭构成。可重复的方法使用链接的行政数据在人群层面创建纵向家庭层面的构成指标。这些措施对于了解个人家庭和居住环境的更多细节以及如何影响个人、其他居民甚至更广泛社区的健康和幸福感非常重要。