Association between composite dietary antioxidant index and cognitive function impairment in the elderly: evidence from NHANES 2011–2014

Objective Antioxidant-rich diets are posited as protective factors against cognitive function impairment. The Composite Dietary Antioxidant Index (CDAI) serves as a pivotal measure of antioxidant intake, yet its relationship with cognitive function impairment has been sparsely investigated. Herein, the purpose of this study was to investigate the relationship between CDAI and cognitive function impairment. Methods An analysis of data from the National Health and Nutrition Examination Survey (NHANES) spanning 2011 to 2014 was conducted to examine the relationship between the CDAI and cognitive function impairment by multivariate logistic regression, and its nonlinearity was verified by restricted cubic spline (RCS) regression. Moreover, a risk prediction nomogram model containing the key factors determined by logistic regression methods was constructed to estimate the probability of cognitive function impairment in older adults. Results Compared with participants with normal cognitive performance, those with low cognitive performance were likely to have higher age, lower education, lower household income, and lower CDAI score. In a multivariate logistic regression model adjusted for confounding variables, the CDAI score was associated with the CERAD word learning subtest was still significant, the adjusted odds ratios (ORs) with 95% confidence intervals (CIs) was 0.94 (0.90,0.98), while the association with AFT and DSST was not statistically significant. The RCS curves indicate that there was a smooth L-shaped correlation between CDAI index and cognitive performance. Moreover, the nomogram model based on the key factors determined by logistic regression has a good predictive value for cognitive function impairment (AUC = 0.747, 95%CI:0.726–0.768). Conclusion Our study determined a nonlinear and negative association between CDAI and cognitive function impairment in the US elderly population. And a risk prediction nomogram model was constructed to estimate the probability of cognitive function impairment in older adults.