The Application of Spatial Regression Analysis in Examining the Relationship Between Drinking Water Contaminants and Cancer Incidence Rates in Iowa and Illinois Restricted; Files Only
Munir, Sabah (Spring 2021)
Published
Abstract
Abstract
The Application of Spatial Regression Analysis in Examining the Relationship Between Drinking Water Contaminants and Cancer Incidence Rates in Iowa and Illinois
By Sabah Munir
Background: Past studies have examined the relationships between drinking water contaminants and cancer risk or incidence. However, many of these previous designs limited their scope to just one state, and the use of GIS techniques was restricted to only studying cancer incidence patterns. The current study sought to use spatial regression analysis to study the relationships between drinking water contaminants and cancer incidence in two Upper Midwest states (i.e., Iowa and Illinois).
Materials and Methods: Gaussian GAMs were used to conduct exploratory analyses between contaminants and cancer incidence rates while controlling for state and county urbanicity identifiers. SAR models helped study the associations between contaminants and cancer incidence rates while controlling for state and county urbanicity and examining the significance of spatial dependency on contaminant data.
Results: Both Illinois and Iowa reported fewer variations in concentration values for nitrates and arsenic. Higher radium values clustered in eastern Iowa and northern Illinois, and high haloacetic acids and total trihalomethane concentrations occurred in the southern halves of each state. Cancer incidence rates for all four cancers were varied across both states, and a cluster of higher prostate incidence was identified in western Iowa. Based on spatial analysis, for the incidence rates of both colon and rectal cancer and lung and bronchial cancer, radium yielded negative associations while total trihalomethanes yielded positive associations. Exploratory analysis also yielded significant positive associations between radium and female breast cancers and between haloacetic acids and lung and bronchial cancers. No significant associations were found between any contaminants and prostate cancer.
Discussion and Conclusions: The findings regarding radium’s association with cancer incidence supported only past literature for female breast cancer. Likewise, the findings regarding haloacetic acids and total trihalomethanes partly supported past literature for colon and rectal and lung and bronchial cancers. Spatial regression was useful in identifying relationships between contaminant exposure and cancer incidence while controlling for state and urbanicity classifications, although only one model demonstrated significant second-order spatial dependence. The existing model can be expanded further by including additional variables, stratifying the dependent variable by socio-demographic factors, or including more states in the sample data.
Table of Contents
Table of Contents
1. Introduction…………………………………………………………………………………..…1
2. Materials and Methods
2.1 Data Sources
2.1.1 Drinking Water Contaminant Data………………………………………….4
2.1.2 Cancer Incidence Data………………………………………………………5
2.1.3 Urbanicity Identification………………………………………………….…7
2.2 Statistical Analysis
2.2.1 Gaussian Generalized Additive Model…………………...…………………7
2.2.2 Simultaneous Autoregressive Model………………………………..………8
3. Results
3.1 Spatial Visualizations
3.1.1 Distributions of Mean Contaminant Concentrations From 2010-2017……..9
3.1.2 Distributions of Five-Year Cancer Incidence Rates From 2013-2017………10
3.2 Exploratory Analyses……………………………………………………..………….12
3.3 SAR Modeling……………………………………………………………………......16
4. Discussion and Conclusions………………………………………………….………………..19
References………………………………………………………………………………………..24
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File download under embargo until 21 May 2025 | 2021-04-26 11:29:39 -0400 | File download under embargo until 21 May 2025 |
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