Spatial Analysis of Industrial Benzene Emissions and Cancer Incidence Rates in Texas
Bibliographic Data
| ID | 15494152 |
|---|---|
| Authors | Chinmay Mungi (The University of Texas Health Science Center at Houston), Dejian Lai (0000-0001-9459-1072, The University of Texas Health Science Center at Houston, corresponding author), Xianglin L Du (0000-0003-0119-5252, The University of Texas Health Science Center at Houston) |
| Year | 2019 |
| Volume | 16 |
| Issue | 15 |
| Pages | 2627-2627 |
| Publication date | 2019-07-24 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph16152627 |
| PMID | 31344779 |
| OpenAlex | W2962705077 |
| Language | EN |
| Citations received | 1 |
| References cited | 22 |
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
Benzene · Incidence (geometry · Kriging · Linear regression · Regression analysis · Spatial analysis · Spatial correlation · Spatial dependence · Spatial distribution · Spatial variability · Statistics · Air Quality and Health Impacts · Chemistry · Environmental Justice and Health Disparities · Environmental Science · Mathematics · Urban Transport and Accessibility
Statistics for Spatial Data
Applied Spatial Statistics for Public Health Data
A spatial scan statistic
Spatial Analysis of Air Pollution and Mortality in Los Angeles
Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine Particulate Air Pollution
The Contiguity Ratio and Statistical Mapping
Notes on Continuous Stochastic Phenomena
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |