Rurality and Area-based Socioeconomic Status of Patients' Residence as Predictors of Screening Colonoscopy Utilization

Background: Cancer is the second cause of deaths in the United States. Colorectal cancer mortality ranks third among all types of cancer. Medical care is a tremendous burden for cancer patients. It is well established that colorectal cancer screening is cost effective and life saving. Recent guidelines by the American Cancer Society (ACS) recommend that adults aged over 50 years receive colorectal cancer screening. Colonoscopy is the most preferred method for colorectal cancer screening. However, little is known about the relationship between rural residence and socioeconomic status and the likelihood of colonoscopy utilization. We explore associations between completing screening colonoscopy and level of rurality and area-based socioeconomic status of patients in South Carolina.

Data collection: The study uses data collected for a project funded by the National Cancer Institute, through the South Carolina Cancer Disparities Community Network (one of 25 Cancer Network Programs). We conducted patient chart reviews at seven colonoscopy-trained and five untrained primary care physician offices (selected by convenience sampling) in South Carolina. Consecutive patient charts of patients aged ≥50 years were retrieved using the billing databases. We conducted chart reviews of 2,272 patients aged ≥50 years who were established patients of 12 primary care physicians. Based on inclusion and exclusion criteria, 1643 patients were eligible for the study.

Data Analysis: The Rural Urban Commuting Areas (RUCA 2.0) classification system was used to classify patients' residence zip code into urban and rural. The U.S. Census 2000 was used to retrieve for each zip code the area-based SES data, including percent African American population, percent households below federal poverty, percent households with any adult aged ≥ 25 years who have completed college, median housing value, percent households with dividend, rental or interest income, percent employed persons aged ≥ 16 years in blue-collar occupations. A composite SES index was calculated as documented by Rosenberg et al. The composite scores were classified into four quartiles (highest=highest area SES). Fixed effects logistic regression model will be used to assess the likelihood of receipt of colonoscopy by rurality and area-based SES, controlling for patient demographics, insurance source, frequency of visiting their primary care doctor, and presence of serious co-morbidities. Variable recoding and model specification trials are underway. Results and implications for policy will be presented.

Implications: Because this study is based on primary data, it affords a closer look into the role of rural residence and SES on screening colonoscopy access.