Health disparities in clinical practice patterns for prostate cancer screening by geographic regions in the United States: a multilevel modeling analysis.

BACKGROUND: To our knowledge, no previous study has examined state-level geographic variability and its predictors in clinical practice patterns to screen for prostate cancer in the United States.

METHODS: We used the Behavioral Risk Factor Surveillance System 2010 data set to analyze geographic variability (by state) and its associated predictors in receiving a PSA test and/or a digital rectal examination (DRE). The study population consisted of men aged ≥50 years who responded as yes/no when asked about having a PSA test or DRE performed during the last year. We build two multilevel logistic regression models, differing in dependent variables, that is, (1) any prostate cancer screening (PCS) (either PSA and/or DRE), and (2) PCS based on PSA testing (PSAT). Individual characteristics (age, education, employment, marriage, income, race/ethnicity, self-reported health status, obesity, alcohol consumption, smoking status, personal physician presence, and health insurance coverage) were treated as level-1 variables and state characteristics (number of doctors per 100 000 persons per state, US regions and metropolitan statistical area (MSA) codes) were treated as level-2 variables.

RESULTS: We found significant geographic variability in receiving PCS and PSAT screening in the United States. For PCS, MSA code was an independent predictor, with men living in urban areas having lower odds of screening (odds ratio (OR)=0.8, 95% confidence interval (CI)=0.7-0.9). In PSAT, the number of doctors per 100 000 persons per state was an independent predictor, with lowest quartile states (0-25% quartile) having lower odds of PSA-based screening (OR=0.78, 95% CI=063-0.94). In both models, all level-1 variables were independent predictors (P<0.05) of PCS, except self-reported health status.

CONCLUSIONS: Men living in urban areas and states with lower prevalence of doctors have lower odds of screening for prostate cancer and PSAT, respectively, after adjusting for individual variables. Future studies should examine the reasons for these health disparities.