Libuy Nicolás, Fitzsimons Emla, Church David
Centre for Longitudinal Studies, Social Research Institute, University College London, UK.
Int J Popul Data Sci. 2024 Apr 25;9(1):2132. doi: 10.23889/ijpds.v9i1.2132. eCollection 2024.
Enhancing longitudinal cohort studies by linking routine external data to them is increasingly used to evaluate how local environments impact participants' outcomes (e.g. crime on adolescents' perception of security and victimisation).
To describe the geographical linkage between the UK Millennium Cohort Study (MCS) and street-level crime incidents reported to the Police in England and Wales, and to estimate crime count and rates around MCS participants' residences.
Eight years of monthly street-level police data were linked to the residential postcodes of MCS participants living in England and Wales in surveys 5, 6 and 7 to create individual-level variables of neighbourhood crime counts and rates (28,724 surveys and 11,365 individuals). Radial buffers around participants' residences were created at ages 11, 14 and 17. Crime counts and rates were created prior to the month of interview (at 1, 3, 6, 9, and 12 months prior). A homogenisation of crime categories reported in the police data was conducted to evaluate changes over time and areas. Multivariate models were used to study the association between MCS participants' demographic characteristics and derived measures of neighbourhood crime.
While total crime rates and counts around MCS participants remain stable over the period, they hide heterogeneous upward and downward trends in specific sub-categories, with violence and sexual offences showing a larger increase. We observe a negative socioeconomic gradient between household income deciles, recorded at age 11, and subsequent exposure to neighbourhood crime.
Linking routine crime data to longitudinal studies, such as the MCS, which follow children and their families through a critical period of development, can provide a new resource to understand how local crime impacts child and adolescent outcomes.
通过将常规外部数据与之相联系来加强纵向队列研究,越来越多地用于评估当地环境如何影响参与者的结果(例如犯罪对青少年安全感和受害情况的影响)。
描述英国千禧队列研究(MCS)与英格兰和威尔士警方报告的街道层面犯罪事件之间的地理联系,并估计MCS参与者住所周围的犯罪数量和犯罪率。
将八年的月度街道层面警方数据与居住在英格兰和威尔士的MCS参与者在第5、6和7次调查中的居住邮政编码相联系,以创建邻里犯罪数量和犯罪率的个体层面变量(28724次调查和11365名个体)。在参与者11岁、14岁和17岁时,在其住所周围创建了径向缓冲区。犯罪数量和犯罪率是在访谈月份之前(提前1、3、6、9和12个月)创建的。对警方数据中报告的犯罪类别进行了同质化处理,以评估随时间和地区的变化。使用多变量模型研究MCS参与者的人口特征与邻里犯罪衍生指标之间的关联。
虽然在此期间MCS参与者周围的总犯罪率和犯罪数量保持稳定,但它们掩盖了特定子类别中不同的上升和下降趋势,暴力和性犯罪的增加幅度更大。我们观察到,在11岁时记录的家庭收入十分位数与随后接触邻里犯罪之间存在负社会经济梯度。
将常规犯罪数据与纵向研究(如MCS)相联系,该研究在儿童及其家庭的关键发育时期对其进行跟踪,可以提供一种新的资源,以了解当地犯罪如何影响儿童和青少年的结果。