Background: Colorectal cancer screening participation is lower among recent immigrants than among Canadianborn individuals. We assessed whether this screening disparity is mediated by access to regular primary care physicians (PCP).Methods: Pooling years 2003 to 2014 of the Canadian Community Health Survey, lifetime screening in respondents aged 50 to 75 years of age who immigrated in the previous 10 years (n ¼ 1,067) was compared with Canadian-born respondents (N ¼ 102,366). Regression-and inverse probability weighting-based methods were used to estimate the total effect (TE) and controlled direct effect (CDE) of recent immigration on never having received either a stool-or endoscopic-based screening test. The proportion of the TE that would be eliminated if all had a PCP was computed using these estimates [proportion eliminated (PE) ¼ (TE À CDE)/(TE À 1)]. Analyses were stratified by visible minority status and adjusted for income, rurality, age, sex, marital status, education, and exposure to a provincially organized colorectal screening program.Results: The prevalence of never having been screened was 71% and 57% in visible minority and white recent immigrants, respectively, and 46% in white Canadian-born respondents. If all had regular PCPs, there would be no reduction in the screening inequality between white recent immigrants and Canadian-born (null PE), and the inequality between visible minority immigrants and white Canadian-born may increase by 6% to 13%.Conclusions: Ensuring all have regular PCPs may lead to greater screening gains among Canadian-born than recent immigrants.Impact: Improving access to PCPs may increase colorectal screening overall, but not reduce immigration-based disparities screening. Alternative interventions to reduce this disparity should be explored. a "Mar" indicates married; "Com. Law" indicates Common law relationship status; "Div." indicates divorced, "Widow." indicates widowed. b Stratified PR values represent stratified prevalence risk ratios estimated via Poisson log-linear regression models. Models were adjusted for age, sex, marital status, educational attainment, exposure to a provincial organized screening program, income quartile, and rural residence.Blair et al.