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Hierarchical spatial modeling of uncertainty in air pollution and birth weight study.

Publication ,  Journal Article
Gray, SC; Gelfand, AE; Miranda, ML
Published in: Statistics in medicine
July 2011

In environmental health studies air pollution measurements from the closest monitor are commonly used as a proxy for personal exposure. This technique assumes that air pollution concentrations are spatially homogeneous in the neighborhoods associated with the monitors and consequently introduces measurement error into a resultant model. To model the relationship between maternal exposure to air pollution and birth weight, we build a hierarchical model that accounts for the associated measurement error. We allow four possible scenarios, with increasing flexibility, for capturing this uncertainty. In the two simplest cases, we specify models with a constant variance term and a variance component that allows uncertainty in the exposure measurements to increase as the distance between maternal residence and the location of the closest monitor increases. In the remaining two models, we introduce spatial dependence using random effects. The models are illustrated using Bayesian hierarchical modeling techniques that relate pregnancy outcomes from the North Carolina Detailed Birth Records to air pollution data from the U.S. Environmental Protection Agency.

Duke Scholars

Published In

Statistics in medicine

DOI

EISSN

1097-0258

ISSN

0277-6715

Publication Date

July 2011

Volume

30

Issue

17

Start / End Page

2187 / 2198

Related Subject Headings

  • Statistics & Probability
  • Pregnancy
  • Particulate Matter
  • North Carolina
  • Models, Statistical
  • Maternal Exposure
  • Infant, Newborn
  • Humans
  • Female
  • Environmental Monitoring
 

Citation

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Gray, S. C., Gelfand, A. E., & Miranda, M. L. (2011). Hierarchical spatial modeling of uncertainty in air pollution and birth weight study. Statistics in Medicine, 30(17), 2187–2198. https://doi.org/10.1002/sim.4234
Gray, Simone C., Alan E. Gelfand, and Marie Lynn Miranda. “Hierarchical spatial modeling of uncertainty in air pollution and birth weight study.Statistics in Medicine 30, no. 17 (July 2011): 2187–98. https://doi.org/10.1002/sim.4234.
Gray SC, Gelfand AE, Miranda ML. Hierarchical spatial modeling of uncertainty in air pollution and birth weight study. Statistics in medicine. 2011 Jul;30(17):2187–98.
Gray, Simone C., et al. “Hierarchical spatial modeling of uncertainty in air pollution and birth weight study.Statistics in Medicine, vol. 30, no. 17, July 2011, pp. 2187–98. Epmc, doi:10.1002/sim.4234.
Gray SC, Gelfand AE, Miranda ML. Hierarchical spatial modeling of uncertainty in air pollution and birth weight study. Statistics in medicine. 2011 Jul;30(17):2187–2198.
Journal cover image

Published In

Statistics in medicine

DOI

EISSN

1097-0258

ISSN

0277-6715

Publication Date

July 2011

Volume

30

Issue

17

Start / End Page

2187 / 2198

Related Subject Headings

  • Statistics & Probability
  • Pregnancy
  • Particulate Matter
  • North Carolina
  • Models, Statistical
  • Maternal Exposure
  • Infant, Newborn
  • Humans
  • Female
  • Environmental Monitoring