Annals of Applied Statistics

Quantifying the spatial inequality and temporal trends in maternal smoking rates in Glasgow

Duncan Lee and Andrew Lawson

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Abstract

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.

Article information

Source
Ann. Appl. Stat., Volume 10, Number 3 (2016), 1427-1446.

Dates
Received: July 2015
Revised: April 2016
First available in Project Euclid: 28 September 2016

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1475069613

Digital Object Identifier
doi:10.1214/16-AOAS941

Mathematical Reviews number (MathSciNet)
MR3553230

Zentralblatt MATH identifier
06775272

Keywords
Cluster detection maternal smoking spatial inequality spatio-temporal modelling

Citation

Lee, Duncan; Lawson, Andrew. Quantifying the spatial inequality and temporal trends in maternal smoking rates in Glasgow. Ann. Appl. Stat. 10 (2016), no. 3, 1427--1446. doi:10.1214/16-AOAS941. https://projecteuclid.org/euclid.aoas/1475069613


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Supplemental materials

  • Supplement A: Additional results and data analysis. Section 2 illustrates the use of the (non-data augmented) proposed model via the CARBayesST package on simulated data. Section 3 provides an additional simulation study that assesses the efficacy of the model with data augmentation. Section 4 presents example realisations of the simulated data. Section 5 presents posterior summaries of the hyperparameters from the Glasgow study, while Section 6 presents additional sensitivity analyses.
    Digital Object Identifier: doi:10.1214/16-AOAS941SUPP
    Supplemental PDF (575 KB)
  • Supplement B: Additional files for running the proposed model on simulated data. R code and data for running the model proposed in Section 3 on simulated data.
    Digital Object Identifier: doi:10.1214/16-AOAS941SUPP
    Supplemental ZIP File (5106 KB)

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