Lee Duncan, Lawson Andrew
School of Mathematics and Statistics, University of Glasgow, Glasgow, UK, G12 8QQ.
Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA, 29401-8350.
Ann Appl Stat. 2016 Sep 28;10(3):1427-1446. doi: 10.1214/16-AOAS941.
Maternal smoking is well known to adversely affect birth outcomes, and there is considerable spatial variation in the rates of maternal smoking in the city of Glasgow, Scotland. This spatial variation is a partial driver of health inequalities between rich and poor communities, and it is of interest to determine the extent to which these inequalities have changed over time. Therefore in this paper we develop a Bayesian hierarchical model for estimating the spatio-temporal pattern in smoking incidence across Glasgow between 2000 and 2013, which can identify the changing geographical extent of clusters of areas exhibiting elevated maternal smoking incidences that partially drive health inequalities. Additionally, we provide freely available software via the R package CARBayesST to allow others to implement the model we have developed. The study period includes the introduction of a ban on smoking in public places in 2006, and the results show an average decline of around 11% in maternal smoking rates over the study period.
众所周知,孕妇吸烟会对分娩结果产生不利影响,而且在苏格兰格拉斯哥市,孕妇吸烟率存在相当大的空间差异。这种空间差异是贫富社区之间健康不平等的部分驱动因素,确定这些不平等现象随时间变化的程度很有意义。因此,在本文中,我们开发了一种贝叶斯分层模型,用于估计2000年至2013年格拉斯哥市吸烟发生率的时空模式,该模型可以识别出孕妇吸烟发生率较高的区域集群不断变化的地理范围,这些区域集群是造成健康不平等的部分原因。此外,我们通过R包CARBayesST提供免费软件,以便其他人能够应用我们开发的模型。研究期间包括2006年实施的公共场所禁烟令,结果显示,在研究期间,孕妇吸烟率平均下降了约11%。