biostudies-literatureRomeo-Cervera PInstituto de Salud Carlos III and co-financed by the European Regional Development Fund (ERDF)3940https://www.ebi.ac.uk/biostudies/studies/S-EPMC11640264biostudies-literatureUnknown16(23)<b>Background/Objectives:</b> An individual socioeconomic status index (ISESI) was used to analyse inequalities in participation and colonoscopy acceptance in the Valencia Region Colorectal Cancer Screening Programme (VR-CRCSP). <b>Methods:</b> This is a cross-sectional study of men and women aged 50-69 who had been invited to participate in the VR-CRCSP as of February 2020 (N = 1,066,763). The variables included in the ISESI were nationality, employment status, disability, healthcare coverage, risk of vulnerability, and family size. The ISESI was categorised into quartiles (Qs), with Q4 corresponding to the lowest socioeconomic status (SES). Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using mixed logistic regression models. <b>Results:</b> The results showed that QCancersAnalysing Inequalities in Colorectal Cancer Screening Using an Individual Socioeconomic Status Index.PMC11640264PI18/01669Romeo-Cervera PMartin-Pozuelo JPinto-Carbo MMolina-Barcelo ACastan-Cameo SVanaclocha-Espi MSalas DfalseAnalysing Inequalities in Colorectal Cancer Screening Using an Individual Socioeconomic Status Index.<b>Background/Objectives:</b> An individual socioeconomic status index (ISESI) was used to analyse inequalities in participation and colonoscopy acceptance in the Valencia Region Colorectal Cancer Screening Programme (VR-CRCSP). <b>Methods:</b> This is a cross-sectional study of men and women aged 50-69 who had been invited to participate in the VR-CRCSP as of February 2020 (N = 1,066,763). The variables included in the ISESI were nationality, employment status, disability, healthcare coverage, risk of vulnerability, and family size. The ISESI was categorised into quartiles (Qs), with Q4 corresponding to the lowest socioeconomic status (SES). Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using mixed logistic regression models. <b>Results:</b> The results showed that Q2024-01-01T00:00:00Z2024 Nov2025-04-18T13:03:19.194Z2025-04-06T22:33:18.559ZS-EPMC116402643968212810.3390/cancers16233940