ArticleInternational journal of environmental research and public health2019
Spatial Analysis of Industrial Benzene Emissions and Cancer Incidence Rates in Texas.
Article in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.
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Who cites it
5 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Impact of Pollution on Cancer: A Systematic Review and Meta-Analysis with Focus on Air Pollution.International journal of environmental research and public health · 2026Pooled it
- A systematic review of spatial and temporal epidemiological approaches, focus on lung cancer risk associated with particulate matter.BMC public health · 2024Pooled it
- Spatial analysis of air pollution and cancer prevalence in Texas: a machine learning approach using satellite remote sensing data.Environmental monitoring and assessment · 2026Article
- Cancer patterns in Iran: a gender-specific spatial modelling of cancer incidence during 2014-2017.BMC cancer · 2024Article
- Characterization and exposure assessment to urban air toxics across Middle Eastern and North African countries: a review.Environmental monitoring and assessment · 2021Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents a spatial analysis of the association between industrial benzene emissions and the 10-year incidence rates of cancers likely to be associated with benzene exposure (Lymphohematopoietic, lung and lip cancers) at the county level in Texas. The spatial distribution of incident cases of the above cancers between 2004 and 2013 was assessed at the county level and found to have positive spatial auto-correlation. Subsequently, point pattern analysis was performed on industrial emissions of benzene reported to the Toxic Release Inventory (TRI), revealing a non-random spatial pattern. Universal kriging was performed using the industrial emissions data to derive estimates of ambient benzene levels at the county level. An ordinary linear regression model was fitted using the incidence rates as the outcome and the estimated benzene level along with chosen covariates and the residuals were assessed for lingering spatial auto-correlation. As the residuals showed that spatial auto-correlation persists, a spatial conditional auto-regression (CAR) model was fitted instead. In the spatial CAR linear regression model, estimated levels of ambient benzene were not found to be significantly associated with the 10-year incidence rates of lymphohematopoietic, lung and lip cancers at the county level.
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Registered trials
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