Diabetes could impact many ocular tissues. However, the association of the serum aldehydes with diabetes-related eye diseases (DED) remains unclear. Thus, we aimed to examine the above relationship from the general US population of 2013-2014 National Health and Nutrition Examination Survey (NHANES). The multivariable logistic regression and Bayesian kernel machine regression (BKMR) were used to analyze the effect of serum aldehydes on the risk of DED. Pearson's correlation analysis, the restricted cubic spline (RCS) model, and the linear regression were performed to explore the association between the serum aldehydes and other parameters. The multivariable linear regression was conducted to further underlie the relationship between the serum aldehydes and the glycohemoglobin A1c (HbA1c) in DED participants. Although no significant association was observed between the serum aldehydes and the risk of DED by the multivariable logistic regression and BKMR, the Pearson correlation revealed a positive association between the HbA1c level and the serum level of heptanaldehyde and isopentanaldehyde in DED participants. The RCS model confirmed the above linear correlation. After adjusting for the cofounding factor of smoking, the multivariable linear regression revealed a significant association between the serum level of heptanaldehyde and the HbA1c level in DED participants. Our results suggest that aldehyde exposure did not significantly increase the risk of DED, while heptanaldehyde was the risk factor for increased HbA1c in DED population.
Keywords: Aldehydes; Diabetes; Diabetes-related eye diseases; HbA1c; Multivariable linear regression.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.