Journal article
Restricted spatial models for the analysis of geographic and racial disparities in the incidence of low birthweight in Pennsylvania
Spatial and spatio-temporal epidemiology, v 49, 100649
Jun 2024
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The incidence of low birthweight is a common measure of public health due to the increased risk of complications associated with infants having low and very low birthweights. Moreover, many factors that increase the risk of an infant having a low birthweight can be linked to the mother’s socioeconomic status, leading to large racial/ethnic disparities in its incidence. Our objective is thus to analyze the incidence of low and very low birthweight in Pennsylvania counties by race/ethnicity. Due to the small number of births in many Pennsylvania counties when stratified by race/ethnicity, our methods must walk a fine line: While we wish to leverage spatial structure to improve the precision of our estimates, we also wish to avoid oversmoothing the data, which can yield spurious conclusions. As such, we develop a framework by which we can measure (and control) the informativeness of our spatial model. To analyze the data, we first model the Pennsylvania birth data using the conditional autoregressive model to demonstrate the extent to which it can lead to oversmoothing. We then reanalyze the data using our proposed framework and highlight its ability to detect (or not detect) evidence of racial/ethnic disparities in the incidence of low birthweight.
•The CAR model of Besag et al. (1991) often produces overly informative models.•We developed a simple approach to measure and control the CAR model’s informativeness.•When left unchecked, the CAR model dominated the data, leading to oversmoothing.•Our proposed restricted model produces estimates more consistent with the data.
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Details
- Title
- Restricted spatial models for the analysis of geographic and racial disparities in the incidence of low birthweight in Pennsylvania
- Creators
- Guangzi Song - Drexel UniversityLoni Philip Tabb - Drexel UniversityHarrison Quick - Drexel University
- Publication Details
- Spatial and spatio-temporal epidemiology, v 49, 100649
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Urban Health Collaborative; Epidemiology and Biostatistics
- Web of Science ID
- WOS:001221237400001
- Scopus ID
- 2-s2.0-85189549456
- Other Identifier
- 991021866433504721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Public, Environmental & Occupational Health