Bayesian distributed lag models: Estimating effects of particulate matter air pollution on daily mortality

L. J. Welty, Roger Peng, Scott Zeger, F. Dominici

Research output: Contribution to journalArticle

Abstract

A distributed lag model (DLagM) is a regression model that includes lagged exposure variables as covariates; its corresponding distributed lag (DL) function describes the relationship between the lag and the coefficient of the lagged exposure variable. DLagMs have recently been used in environmental epidemiology for quantifying the cumulative effects of weather and air pollution on mortality and morbidity. Standard methods for formulating DLagMs include unconstrained, polynomial, and penalized spline DLagMs. These methods may fail to take full advantage of prior information about the shape of the DL function for environmental exposures, or for any other exposure with effects that are believed to smoothly approach zero as lag increases, and are therefore at risk of producing suboptimal estimates. In this article, we propose a Bayesian DLagM (BDLagM) that incorporates prior knowledge about the shape of the DL function and also allows the degree of smoothness of the DL function to be estimated from the data. We apply our BDLagM to its motivating data from the National Morbidity, Mortality, and Air Pollution Study to estimate the short-term health effects of particulate matter air pollution on mortality from 1987 to 2000 for Chicago, Illinois. In a simulation study, we compare our Bayesian approach with alternative methods that use unconstrained, polynomial, and penalized spline DLagMs. We also illustrate the connection between BDLagMs and penalized spline DLagMs. Software for fitting BDLagM models and the data used in this article are available online.

Original languageEnglish (US)
Pages (from-to)282-291
Number of pages10
JournalBiometrics
Volume65
Issue number1
DOIs
StatePublished - Mar 2009

Fingerprint

Particulate Matter
Air Pollution
air pollution
Air pollution
Mortality
particulates
Splines
Penalized Splines
Morbidity
morbidity
Polynomial Splines
Bayes Theorem
Environmental Exposure
Weather
Polynomials
Epidemiology
Environmental Epidemiology
Software
Model
epidemiology

Keywords

  • Air pollution
  • Bayes
  • Distributed lag
  • Mortality
  • NMMAPS
  • Penalized splines
  • Smoothing
  • Time series

ASJC Scopus subject areas

  • Applied Mathematics
  • Statistics and Probability
  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Medicine(all)

Cite this

Bayesian distributed lag models : Estimating effects of particulate matter air pollution on daily mortality. / Welty, L. J.; Peng, Roger; Zeger, Scott; Dominici, F.

In: Biometrics, Vol. 65, No. 1, 03.2009, p. 282-291.

Research output: Contribution to journalArticle

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