Multilevel predictors of colorectal cancer screening use in California

Am J Manag Care. 2013;19(3):205-16.

Abstract

Background: Screening can detect colorectal cancer (CRC) early, yet its uptake needs to be improved. Social determinants of health (SDOH) may be linked to CRC screening use but are not well understood.

Objectives: To examine geographic variation in CRC screening and the extent to which multilevel SDOH explain its use in California, the most populous and racially/ethnically diverse state in the United States.

Study design: Analysis of individual and neighborhood data on 20,626 adult respondents aged >50 years from the 2005 California Health Interview Survey.

Methods: We used multilevel logistic regression models to estimate the effects of individual characteristics and area-level segregation, socioeconomic status (SES), and healthcare resources at 2 different geographic levels on CRC screening use.

Results: We confirmed that individual-level factors (eg, race/ethnicity, income, insurance) were strong predictors and found that area-level healthcare resources were associated with CRC screening. Primary care shortage in the Medical Service Study Area was associated with CRC screening for any modality (odds ratio [OR] = 0.89; 95% confidence interval [CI], 0.80-1.00). County-level HMO penetration (OR = 1.85; 95% CI, 1.47-2.33) and primary care shortage (OR = 0.73; 95% CI, 0.53-0.99) were associated with CRC screening with flexible sigmoidoscopy.

Conclusions: Contextual factors including locality, primary care resources, and HMO membership are important determinants of CRC screening uptake; SES and segregation did not explain variation in screening behavior. More studies of contextual factors and varying geographic scales are needed to further elucidate their impact on CRC screening uptake.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • California / epidemiology
  • Colorectal Neoplasms / diagnosis*
  • Early Detection of Cancer / statistics & numerical data*
  • Ethnicity / statistics & numerical data
  • Female
  • Health Care Surveys
  • Health Maintenance Organizations / statistics & numerical data
  • Humans
  • Income / statistics & numerical data
  • Insurance Coverage / statistics & numerical data
  • Insurance, Health / statistics & numerical data
  • Logistic Models
  • Male
  • Middle Aged
  • Racial Groups / statistics & numerical data
  • Sigmoidoscopy / statistics & numerical data
  • Socioeconomic Factors