Examining determinants of geographic variation in colorectal cancer mortality in North Carolina: A spatial analysis approach. (April 2019)

• Record Type: Journal Article
• Authors: Kuo, Tzy-Mey; Meyer, Anne Marie; Baggett, Christopher D.; Olshan, Andrew F.
• Is Part Of: Cancer epidemiology. Volume 59(2019:Apr.)
• Page Start: 8
• Page End: 14
• Publication Date: 2019-04
• Subjects: Keywords: Geographic variation -- Spatial regression -- Colorectal cancer mortality -- Spatial diffusion; Cancer -- Epidemiology -- Periodicals; Cancer -- Prevention -- Periodicals; Cancer -- Diagnosis -- Periodicals; Carcinogenesis -- Periodicals; 616.994005
• DOI: 10.1016/j.canep.2019.01.002
• Languages: English
• ISSNs: 1877-7821

Abstract

Highlights: Clusters of high colorectal cancer mortality were found in North Carolina counties. Spatial lag model explained geographic patterns of county-level mortality rates. The impact of socioeconomic factors on colorectal cancer mortality differed by risk factors. Counties of high colorectal cancer mortality were also deprived in several risk factors. Intervention should focus on multifaceted factors to reduce colorectal cancer mortality. Abstract: Purpose: A recent study using national data from 2000 to 2009 identified colorectal cancer (CRC) mortality "hotspots" in 11 counties of North Carolina (NC). In this study, we used more recent, state-specific data to investigate the county-level determinants of geographic variation in NC through a geospatial analytic approach. Method: Using NC CRC mortality data from 2003 to 2013, we first conducted clustering analysis to confirm spatial dependence. Spatial economic models were then used to incorporate spatial structure to estimate the association between determinants and CRC mortality. We included county-level data on socio-demographic characteristics, access and quality of healthcare, behavioral risk factors (CRC screening, obesity, and cigarette smoking), and urbanicity. Due to correlation among screening, obesity and quality of healthcare, we combined these factors to form a cumulative risk group variable in the analysis. Results: We confirmed the existence of spatial dependence and identified clusters of elevated CRC mortality rates in NC counties. Using a spatial lag model, we found significant interaction effect between CRC risk groups and socioeconomic deprivation. Higher CRC mortality rates were also associated with rural counties with large towns compared to urban counties. Conclusion: Our findings depicted a spatial diffusion process of CRC mortality rates across NC counties, demonstrated intertwined effects between SES deprivation and behavioral risks in shaping CRC mortality at area-level, and identified counties with high CRC mortality that were also deprived in multiple factors. These results suggest interventions to reduce geographic variation in CRC mortality should develop multifaceted strategies and work through shared resources in neighboring areas.