Intersectional inequities in colorectal cancer screening attendance in Sweden: Using decision trees for intersectional matrix reduction

Colorectal cancer (CRC) represents a significant health burden worldwide, with existing inequities in incidence and mortality. In Sweden, CRC screening programmes have varied regionally since the mid-2000s, but the significance of organised screening for counteracting complex inequities in screening attendance has not been investigated. This study aimed to assess patterns of inequities in lifetime CRC screening attendance in the Swedish population aged 60–69 years by identifying intersectional strata at higher risk of never attending CRC screening. The research question is answered using decision trees to reduce the complexity of a full intersectional matrix into a reduced intersectional matrix for risk estimation. Participants were drawn from the cross-sectional 2019 European Health Interview Survey (N = 9,757, response rate: 32.52%). The Conditional Inference Tree (CIT) (AUC = 0.7489, F-score = 0.7912, depth = 4, significance level = 0.05) identified region of residence (opportunistic vs organised screening), country of origin, gender, age and income as relevant variables in explaining lifetime CRC screening attendance in Sweden. Then, Poisson regression with robust standard errors estimated that EU-born women living in opportunistic screening regions belonging to the 2nd income quintile had the highest risk of never attending CRC screening (PR = 8.54, p < 0.001), followed by EU-born men living in opportunistic screening regions (PR = 7.41, p < 0.001) compared to the reference category (i.e. people aged 65–69 living in organised screening regions). In contrast, only age-related differences in attendance were found in regions with organised screening (i.e. people aged 60–64 living in regions with organised screening (PR = 2.01, p < 0.05)). The AUC of the reduced intersectional matrix model (0.7489) was higher than the full intersectional matrix model (0.6959) and slightly higher than the main effects model (0.7483), demonstrating intersectional effects of the reduced intersectional matrix compared with the main effects model and better discriminatory accuracy than the full intersectional matrix. In conclusion, regions with long-established organised CRC screening programmes display more limited socio-demographic inequities than regions with opportunistic CRC screening. This suggests that organised screening may be a crucial policy instrument to improve equity in CRC screening, which, in the long run, has the potential to prevent inequities in colorectal cancer mortality. Moreover, decision trees appear to be valuable statistical tools for efficient data-driven simplification of the analytical and empirical complexity that epidemiological intersectional analysis conventionally entails.