Utilization of Census Tract-Based Neighborhood Poverty Rates to Predict Non-adherence to Screening Colonoscopy
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Efforts to improve colorectal cancer (CRC) screening rates include recognizing predictors of colonoscopy non-adherence and identifying these high-risk patient populations. Past studies have focused on individual-level factors but few have evaluated the influence of neighborhood-level predictors. We sought to assess the effect of census tract-based neighborhood poverty rates on scheduled screening colonoscopy non-adherence.
In this prospective observational cohort study, data from electronic medical records and appointment tracking software were collected in 599 patients scheduled to undergo outpatient CRC screening colonoscopy at two academic endoscopy centers between January 2011 and December 2012. Non-adherence was defined as failure to attend a colonoscopy appointment within 1 year of the date it was electronically scheduled. Neighborhood poverty rate was determined by matching patients’ self-reported home address with their corresponding US census tract. Individual factors including medical comorbidities and prior appointment adherence behavior were also collected.
Overall, 17% (65/383) of patients were non-adherent to scheduled colonoscopy at 1-year follow-up. Neighborhood poverty rate was a significant predictor of non-adherence to scheduled screening colonoscopy in multivariate modeling (OR 1.53 per 10% increase in neighborhood poverty rate, 95% CI 1.21–1.95, p < 0.001). By incorporating the neighborhood poverty rate, screening colonoscopy non-adherence was 31% at the highest quartile compared to 14% at the lowest quartile of neighborhood poverty rates (p = 0.006).
Census tract-based neighborhood poverty rates can be used to predict non-adherence to scheduled screening colonoscopy. Targeted efforts to increase CRC screening efficiency and completion among patients living in high-poverty geographic regions could reduce screening disparities and improve utilization of endoscopy unit resources.
KeywordsColonoscopy Geocoding Neighborhood socioeconomic status Organizational efficiency
American College of Gastroenterology
American Community Survey
Area under the receiver operating curve
Fecal immunochemical testing
US Preventative Services Task Force
PV collected and interpreted the data, contributed to statistical analysis, and drafted the manuscript. RS collected and interpreted the data. KM interpreted the data and drafted the manuscript. NS collected and interpreted the data. JM planned and conducted the study, interpreted the data, and edited the manuscript. All authors approved the final draft of this manuscript.
Some study support was provided by the American Cancer Society of Illinois (Grant No. 255086).
Compliance with ethical standards
Conflict of interest
Philip Vutien, Rucha Mehta, Karen Ma, Nasir Saleem have no conflicts of interest. Joshua Melson has received research grants from the American Cancer Society of Illinois (Grant No. 255086).
- 6.Centers for Disease Control and Prevention. Behavioral risk factor surveillance system survey data. Atlanta: U.S. Department of Health and Human Services; 2014.Google Scholar
- 13.Reid MW, Cohen S, Wang H, et al. Preventing patient absenteeism: validation of a predictive overbooking model. Am J Manag Care. 2015;21:902–910.Google Scholar
- 26.Krieger N, Chen JT, Waterman PD, et al. Geocoding and monitoring of US socioeconomic inequalities in mortality and cancer incidence: does the choice of area-based measure and geographic level matter?: the Public Health Disparities Geocoding Project. Am J Epidemiol. 2002;156:471–482.CrossRefGoogle Scholar
- 30.U.S. Census Bureau. Geographic Terms and Concepts. US Census Bureau Web site. https://www.census.gov/geo/reference/gtc/gtc_ct.html. Accessed March 10 2018.
- 31.U.S. Census Bureau. How the Census Bureau Measures Poverty. US Census Bureau Web site. https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html. Accessed March 10 2018.
- 32.U.S. Census Bureau. American Community Survey 2012 (5-year estimates). Prepared by Social Explorer. Accessed May 28 2016.Google Scholar
- 33.U.S. Census Bureau. 2014. American Community Survey Design and Methodology. US Census Bureau Web site. https://www.census.gov/programssurveys/acs/methodology/design_and_methodology/acs_design_methodology_report_2014.pdf. Accessed March 1 2018.
- 35.Centers for Disease Control and Prevention. Cancer screening—United States 2010. MMWR Morb Mortal Wkly Rep. 2012;61:41–45.Google Scholar