Journal article
Causal decomposition maps: An exploratory tool for designing area-level interventions aimed at reducing health disparities
Biometrical journal, Vol.65(8), 2200213
12/2023
DOI: 10.1002/bimj.202200213
PMCID: PMC10795519
PMID: 37338305
Abstract
Methods for decomposition analyses have been developed to partition between-group differences into explained and unexplained portions. In this paper, we introduce the concept of causal decomposition maps, which allow researchers to test the effect of area-level interventions on disease maps before implementation. These maps quantify the impact of interventions that aim to reduce differences in health outcomes between groups and illustrate how the disease map might change under different interventions. We adapt a new causal decomposition analysis method for the disease mapping context. Through the specification of a Bayesian hierarchical outcome model, we obtain counterfactual small area estimates of age-adjusted rates and reliable estimates of decomposition quantities. We present two formulations of the outcome model, with the second allowing for spatial interference of the intervention. Our method is utilized to determine whether the addition of gyms in different sets of rural ZIP codes could reduce any of the rural–urban difference in age-adjusted colorectal cancer incidence rates in Iowa ZIP codes.
Details
- Title: Subtitle
- Causal decomposition maps: An exploratory tool for designing area-level interventions aimed at reducing health disparities
- Creators
- Melissa J SmithMary E Charlton - University of IowaJacob J Oleson - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Biometrical journal, Vol.65(8), 2200213
- DOI
- 10.1002/bimj.202200213
- PMID
- 37338305
- PMCID
- PMC10795519
- NLM abbreviation
- Biom J
- eISSN
- 1521-4036
- Grant note
- DOI: 10.13039/100000066, name: National Institute of Environmental Health Sciences, award: P30 ES005605; DOI: 10.13039/100000054, name: National Cancer Institute, award: HHSN261201800012I/HHSN26100001, P30 CA086862, U01CA258400
- Language
- English
- Electronic publication date
- 06/20/2023
- Date published
- 12/2023
- Academic Unit
- Epidemiology; Biostatistics
- Record Identifier
- 9984436287002771
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