Objective Neighbourhood socioeconomic status (nSES) and built environment features strongly influence diet, physical activity and cancer screening adherence, potentially affecting colorectal cancer (CRC) incidence and prognosis. The aim of this study is to assess the association between neighbourhood obesogenic environments (eg, nSES, restaurant and retail food indices, recreational facilities, and business district residence) and CRC risk and mortality. Design A secondary data analysis was performed using prospectively collected data from the Southern Community Cohort Study. Setting 12 states in the Southeastern USA. Participants We analysed data from 70 519 participants enrolled in the Southern Community Cohort Study. Outcomes The primary outcomes in this study are CRC risk and mortality. Data analysis We used multivariable Cox proportional hazards models, adjusting for individual-level factors to investigate neighbourhood-level risk factors associated with CRC risk and mortality. We further performed race-stratified analyses (Black/White) to examine potential disparities in CRC risk. Results Among 70 519 participants (69.49% Black, 30.51% White), 927 (1.31%) were diagnosed with CRC (1.37% Black and 1.19% White participants). Of these, 255 (27.5%) died from CRC.
Objective Neighbourhood socioeconomic status (nSES) and built environment features strongly influence diet, physical activity and cancer screening adherence, potentially affecting colorectal cancer (CRC) incidence and prognosis. The aim of this study is to assess the association between neighbourhood obesogenic environments (eg, nSES, restaurant and retail food indices, recreational facilities, and business district residence) and CRC risk and mortality. Design A secondary data analysis was performed using prospectively collected data from the Southern Community Cohort Study. Setting 12 states in the Southeastern USA. Participants We analysed data from 70 519 participants enrolled in the Southern Community Cohort Study. Outcomes The primary outcomes in this study are CRC risk and mortality. Data analysis We used multivariable Cox proportional hazards models, adjusting for individual-level factors to investigate neighbourhood-level risk factors associated with CRC risk and mortality. We further performed race-stratified analyses (Black/White) to examine potential disparities in CRC risk. Results Among 70 519 participants (69.49% Black, 30.51% White), 927 (1.31%) were diagnosed with CRC (1.37% Black and 1.19% White participants). Of these, 255 (27.5%) died from CRC. Compared with participants residing in the highest (fifth) nSES quintile, those residing in the wealthier (fourth) quintile of nSES exhibited a higher CRC risk (adjusted HR (aHR) 1.27 (95% CI 1.03 to 1.57)). The Retail Food Environment Index was associated with an increased risk of CRC among participants residing in the fifth (wealthiest) nSES quintile (aHR 3.07 (95% CI 1.23 to 7.61) for Tertile 1 vs None; aHR 3.06 (95% CI 1.23 to 7.60) for Tertile 2 vs None). Similar associations were observed among both Black participants (aHR 3.65 (95% CI 1.19 to 11.20) for Tertile 1 vs None) and White participants (aHR 5.20 (95% CI 1.29 to 20.97) for Tertile 2 vs None) living in the same neighbourhoods, although these subgroup estimates should be interpreted cautiously due to wide CIs. Living in a low-walkability neighbourhood was associated with a higher risk of CRC (aHR 2.42 (95% CI 1.09 to 3.56)) among residents in the second-lowest nSES quintile, particularly among Black participants (aHR 3.41 (95% CI 1.29 to 9.02)). Compared with residents of the most walkable neighbourhoods, those in the least walkable (aHR 2.23 (95% CI 1.10 to 4.54)), below-average walkable (aHR 2.10 (95% CI 1.08 to 4.07)) and above-average walkable areas (aHR 2.33 (95% CI 1.24 to 4.39)) had significantly higher CRC mortality risk. Conclusion Our findings suggest that nSES and unhealthy food environments are associated with CRC risk, while less walkable environments were associated with higher CRC mortality. These findings highlight the need for a more detailed assessment of neighbourhood-level deprivation and support enhanced public policies targeting neighbourhood deprivation in low-income populations in the Southeastern USA.