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Multilevel Predictors of Colorectal Cancer Screening Use in California

Salma Shariff-Marco, PhD, MPH; Nancy Breen, PhD; David G. Stinchcomb, MS, MA; and Carrie N. Klabunde, PhD
We studied contextual factors and found that locality, availability of primary care, and HMO membership influenced use of colorectal cancer screening in California.
Limitations of our study include use of cross-sectional data, which does not allow causal inference. While our study findings are specific to California, the contextual factors we examined are not unique to California and could be studied in a similar fashion in other geographic locations. Although self-report of CRC screening tests may overestimate prevalence of CRC screening use, there is mixed evidence about the extent of this problem.64-66 A recent study showed that data from the 2007 CHIS overestimated being up-to-date by 6% to 14% across racial/ethnic groups.65 Skip patterns in the CHIS survey made analysis of CRC screening measures difficult. As a result of our study, CRC screening measures in CHIS were improved. Finally, adding data on additional resources (eg, endoscopy) as well as other contexts (eg, workplace) would offer a more extensive range of factors that may influence CRC screening use.

Our multilevel analysis showed that contextual factors including locality, availability of primary care, and HMO membership influenced use of CRC screening in California. Our results show that both levels of residential geography influence CRC screening use and suggest that multilevel analysis is a promising line of research for cancer screening. Accounting for contextual factors at different geographic scales can provide a richer characterization of the healthcare  resources and market characteristics that influence individual behaviors. Moreover, insights from this study could guide interventions aimed at increasing CRC screening uptake by prioritizing appropriate subgroups and geographic areas. A better understanding of contextual factors of the healthcare and social environment will be important in informing policy decisions for healthcare resource allocation and delivery. Future studies on CRC screening that address multilevel predictors should account for the hierarchical structure of the data by using multilevel analysis or by accounting for clustering within neighborhoods when multilevel analysis is not possible. More experimentation to find the appropriate geographic areas is needed in order to evaluate policy and interventions that address factors to improve screening.

Acknowledgments
We would like to acknowledge the Cancer Prevention Fellowship Program, Office of Preventive Oncology, National Cancer Institute for providing financial support for Salma Shariff-Marco in her postdoctoral fellowship. We would also like to acknowledge Tim McNeel, William Waldron, and Jeremy Lyman at Information Management Services, Inc, for their support in merging our data sets, developing programs for the descriptive analysis, and generating the maps for the Figure; and Penny Randall-Levy of the Scientific Consulting Group, Inc, for her help with the references. Finally, we would like to acknowledge Drs Martin L. Brown and Rachel Ballard-Barbash for their thoughtful reviews.


Author Affiliations: From Cancer Prevention Institute of California (SSM), Freemont, CA; Division of Cancer Control and Population Sciences (NB, CNK), National Cancer Institute, Rockville, MD; Westat, Inc (DOS), Rockville, MD.


Funding Source: All authors were employed at the National Cancer Institute.


Author Disclosures: The authors (SS-M, NB, DGS, CNK) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.


Authorship Information: Concept and design (SS-M, NB, DGS, CNK); acquisition of data (SS-M); analysis and interpretation of data (SS-M, NB, DGS, CNK); drafting of the manuscript (SS-M, NB, DGS, CNK); critical revision of the manuscript for important intellectual content (SS-M, NB, DGS, CNK); statistical analysis (SS-M, DGS); obtaining funding (SS-M); administrative, technical, or logistic support (SS-M, NB); and supervision (SS-M, NB).


Address correspondence to: Salma Shariff-Marco, PhD, MPH, Cancer Prevention Institute of California, 2201 Walnut Ave, Ste 300, Fremont, CA 94538. E-mail: salma.shariff-marco@cpic.org.
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