Abstract Rationale Persistent disparities in cystic fibrosis outcomes remain under-explored in ethnically diverse populations. We evaluated whether Hispanic ethnicity, treated as a social construct linked to structural and clinical inequities rather than biology, associates with low lung function after adjustment for age, insurance category, and modulator exposure. Methods We performed a cross-sectional analysis of 138 individuals with cystic fibrosis from a single center. The primary outcome was worst recorded FEV1% (forced expiratory volume in 1 second percentage) predicted; primary endpoint was FEV1% 70. Sensitivity analyses used thresholds of FEV1% 60 and 40. Primary exposure was Hispanic ethnicity. Covariates included age (per 10-year increase), any modulator exposure, and insurance category. We used logistic regression with robust standard errors and reported adjusted odds ratios. We also inspected linear models and robust regression for consistency. Results We analyzed 138 participants with cystic fibrosis. Race distribution among those with race data was 92.8% White, 2.2% Black, 1.5% Asian, and 3.6% Other. Hispanic ethnicity represented 10% of the analytic sample. In the adjusted FEV1% 70 model, Hispanic ethnicity was associated with higher odds of low FEV1% predicted (adjusted OR 10.08; 95% CI 2.69- 37.81; p = 0.001). Older age was associated with low FEV1% (OR per 10 years 1.67, 95% CI 1.07-2.61). Any modulator exposure showed an elevated point estimate but was not statistically significant (OR 4.43; 95% CI 0.79-24.85; p = 0.091). Insurance category showed no association. Sensitivity analysis for FEV1% 60 reproduced the direction and significance for ethnicity and age with statistically significant estimates (Hispanic: OR 4.33, 95% CI 1.28-14.60; age per 10 years: OR 1.52, 95% CI 1.01- 2.27). Models of continuous FEV1% showed consistent directions. Conclusions Hispanic participants in this cohort had higher adjusted odds of low FEV1% predicted, independent of age, modulator exposure, and insurance type. This difference reflects inequity rather than innate biology. Likely drivers include later presentation and treatment, differences in language, nutritional risk, neighborhood exposures, and measurement bias from percent-predicted equations. These data support targeted actions: earlier detection and referral, proactive outreach for Spanish-speaking families, rapid initiation of appropriate modulators, and standardized follow-up. Future work will use absolute FEV1 liters and z-scores, incorporate neighborhood-level measures, and capture time to modulator initiation and interruptions to clarify mechanisms and target interventions. This abstract is funded by: None
Lo et al. (2026) studied this question.