QUANTIFYING THE SPATIAL INEQUALITY AND TEMPORAL TRENDS IN MATERNAL SMOKING RATES IN GLASGOW

• 成果类型: Article
• 署名作者: Lee, Duncan; Lawson, Andrew
• 署名单位: University of Glasgow; Medical University of South Carolina
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/16-AOAS941
• 发表日期: 2016
• 页码: 1427-1446
• 关键词: bayesian detection; disease; pregnancy; MODEL; PREVALENCE; cessation; clusters; mixture; women

摘要

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.