Despite the effectiveness of screenings in reducing colorectal cancer (CRC) mortality, ~25% of US adults do not adhere to screening guidelines. Prior studies associate socioeconomic status (SES) with low screening adherence and suggest that neighborhood deprivation can influence CRC outcomes. We comprehensively investigated the effect of neighborhood SES circumstances (nSES), individual SES, and race/ethnicity on adherence to CRC screening in a multiethnic cross-sectional study. Participant surveys assessing 32 individual-level socioeconomic and healthcare access measures were administered from 2017 to 2018. Participant data were joined with nine nSES measures from the US Census at the census tract level. Univariate, LASSO, and multivariable mixed-effect logistic regression models were used for variable reduction and evaluation of associations. The total study population included 526 participants aged 50–85; 29% of participants were non-adherent. In the final multivariable model, age (p = 0.02) and Non-Hispanic Black race (p = 0.02) were associated with higher odds of adherence. Factors associated with lower adherence were home rental (vs. ownership) (p = 0.003), perception of low healthcare quality (p = 0.006), no routine checkup within two years (p = 0.002), perceived discrimination (p = 0.02), and nSES deprivation (p = 0.02). After comprehensive variable methods were applied, socioeconomic indicators at the neighborhood and individual level were found to contribute to low CRC screening adherence.

Background: Chronic kidney disease (CKD) and diabetes disproportionately affect the American Indian or Alaska Native population but understanding of major adverse kidney events (MAKE) in this population is limited. Methods: Electronic health records from the Providence health system identified the American Indian or Alaska Native adult population with diabetes during 2013-2022. A one-year window surrounding diabetes cohort entry was used to collect baseline data. Kaplan-Meier analyses assessed MAKE (≥40% estimated glomerular filtration rate [eGFR] decline, eGFR <15 mL/min/1.73 m ² , dialysis or kidney transplant, and all-cause death) with propensity score matching (1:3) of American Indian or Alaska Native people to reference individuals (non-Hispanic White) by demographics and clinical characteristics. Cox proportional hazards modeling estimated associations between demographic, clinical, social, and healthcare utilization variables and MAKE. Results: The American Indian or Alaska Native population (N=6,103) was younger (mean±standard deviation age 54±15 years) with higher HbA1c (mean 7.4±2.2 mg/dL) compared to the reference population (N=354,283; age 62±14 years; HbA1c 6.9%±1.8%). During a median follow-up of 4.1 (interquartile range 2.0-6.4) years, the American Indian or Alaska Native population experienced a higher frequency of MAKE (26%, n=1,614) than the reference population (24%, n=85,920). With propensity score matching, MAKE survival estimates were significantly lower in the American Indian or Alaska Native population (p <0.0001). In the adjusted Cox model, increased MAKE risk was observed for the American Indian or Alaska Native population (versus reference population, hazard ratio [HR] 1.20, 95% confidence interval [CI] 1.15-1.27), higher social vulnerability index (HR 1.05, 95% CI 1.05-1.05), and hospitalization (HR 1.98, 95% CI 1.95-2.01), while more primary care visits were associated with lower MAKE risk (HR 0.78, 95% CI 0.77-0.79). Conclusion: The risk of MAKE was significantly increased in the American Indian or Alaska Native population with diabetes. Social factors and healthcare utilization importantly contributed to risk prediction for MAKE.