HRSNs and CRC screening recommendation in NHIS

Background: Health-related social needs (HRSNs), including food insecurity, housing instability, and financial hardship, are increasingly recognized as barriers to preventive care. Clinician recommendation is a primary driver of colorectal cancer (CRC) screening uptake. However, little is known about how specific HRSNs and co-occurring social risk patterns relate to clinician recommendations in nationally representative populations. Methods We analyzed pooled 2021 and 2023 National Health Interview Survey (NHIS) cross-sections among adults 45-75 years without cancer history (unweighted n = 6,500; weighted = 27.6 million). Survey-weighted logistic regression estimated adjusted odds ratios (aORs) for clinician recommendations in the past 12 months. We examined granular food insecurity categories, HRSN burden counts, and latent social-risk subgroups using latent class analysis (LCA). Analyses were stratified by race/ethnicity and nativity; interaction terms tested effect modification. Results: Overall, roughly 16% of adults reported a clinician's screening recommendation in the past 12 months. Among non-Hispanic White adults, financial hardship was associated with increased odds (aOR = 1.32, 95% CI: 1.11-1.56). Among Hispanic adults, food insecurity was associated with higher odds (aOR = 2.94, 95% CI: 1.59-5.42) while housing instability was associated with lower odds (aOR = 0.38, 95% CI: 0.16-0.88). LCA identified three distinct HRSN configurations: Low/No HRSN (85%), Moderate/Mixed (5%), and High HRSN Burden (10%). High-burden adults had marginally higher odds of recommendation (aOR = 1.33, 95% CI: 0.99-1.78). Race-by-HRSN interactions were statistically significant for housing instability. Conclusions Specific and clustered social needs are associated with clinician recommendations for CRC screening, with differential patterns by race/ethnicity and nativity. Social risk assessment may support more equitable preventive care engagement. Disclosure: During the preparation of this work, the author used OpenAI ChatGPT to assist with wording and clarity. After using this tool, the author reviewed and edited the content and takes full responsibility for the accuracy and integrity of the abstract.