Quantifying geographic regions of excess stillbirth risk in the presence of spatial and spatio-temporal heterogeneity

Zahrieh, David; Oleson, Jacob J.; Romitti, Paul A.

doi:10.1016/j.sste.2019.01.002

i

Quantifying geographic regions of excess stillbirth risk in the presence of spatial and spatio-temporal heterogeneity

Supporting Files

6 2019
By Zahrieh, David ; Oleson, Jacob J. ; Romitti, Paul A.

File Language:

English

Details

Alternative Title:

Spat Spatiotemporal Epidemiol
Personal Author:

Zahrieh, David ; Oleson, Jacob J. ; Romitti, Paul A.
Description:

Motivated by population-based geocoded data for Iowa stillbirths and live births delivered during 2005-2011, we sought to identify spatio-temporal variation of stillbirth risk. Our high-quality data consisting of point locations of these delivery events allows use of a Bayesian Poisson point process approach to evaluate the spatial pattern of events. With this large epidemiologic dataset, we implemented the integrated nested Laplace approximation (INLA) to fit the conditional formulation of the point process via a Bayesian hierarchical model and empirically showed that INLA, compared to Markov chain Monte Carlo (MCMC) sampling, is an attractive approach. Furthermore, we modeled the temporal variability in stillbirth to better understand how stillbirths are geographically linked over the seven-year study period and demonstrate the similarity between the conditional formulation of the spatio-temporal model and a log Gaussian Cox process governed by discrete space-time random fields. After controlling for important features of the data, the Bayesian temporal relative risk maps identified areas of increasing and decreasing stillbirth risk over the birth period, which may warrant further public health investigation in the regions identified.
Subjects:

Demography Female Humans Infant, Newborn Iowa Maternal Health Services Pregnancy Risk Factors Spatio-Temporal Analysis Stillbirth
Keywords:

Bayesian Point Process Spatio-temporal Heterogeneity
Source:

Spat Spatiotemporal Epidemiol. 29:97-109
Pubmed ID:

31128635
Pubmed Central ID:

PMC7156247
Document Type:

Journal Article
Funding:

U01 DD001223/DD/NCBDD CDC HHSUnited States/ ; P30 ES005605/ES/NIEHS NIH HHSUnited States/ ; U01 DD001035/DD/NCBDD CDC HHSUnited States/ ; U01DD001035/ACL/ACL HHSUnited States/ ; U50 DD000730/DD/NCBDD CDC HHSUnited States/
Volume:

29
Collection(s):

CDC Public Access
Main Document Checksum:

urn:sha256:db9575be0fcd3e7e6de3747ca123889c566e8a8b3c3bfc806e3fe7fc0781e297
Download URL:

https://stacks.cdc.gov/view/cdc/86804/cdc_86804_DS1.pdf
File Type:

[PDF - 1.26 MB ]

File Language:

English

ON THIS PAGE

Details Supporting Files

CDC STACKS serves as an archival repository of CDC-published products including scientific findings, journal articles, guidelines, recommendations, or other public health information authored or co-authored by CDC or funded partners.

As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.