Perfluorononanoic acid as a risk factor for metabolic syndrome: A case-control study

Background

Current epidemiological results from studies linking per- and poly-fluoroalkyl substances (PFASs) to metabolic syndrome (MetS) remain inconsistent.

Objectives

We aim to investigate the association between serum PFASs and MetS using data from the National Health and Nutrition Examination Survey in the United States (US NHANES) 2017–2018.

Methods

The Bayesian kernel regression (BKMR) and weighted quantiles sum regression (WQS) models were used to assess the association of serum PFASs with MetS and calculate the weight of each substance. Stratification analysis and sensitivity analysis were used to study the effect modification and the robustness of the study results, respectively.

Results

All statistical models used in this study consistently indicated that serum perfluorononanoic acid (PFNA) was positively associated with an increased risk of MetS. The BKMR model revealed that serum PFASs mixtures had a combined toxic effect on MetS and its components, and serum PFNA could contribute the most to driving the overall association. Specifically, the combined exposure of PFASs was significantly associated with lipids (LP), among which serum PFNA contributed significantly to high density lipoprotein cholesterol (HDL-C), and serum perfluorodecanoate (PFDeA) was significantly positively correlated with triglyceride (TG). Besides, a nonlinear dose-response relationship between PFASs and MetS was observed. The final stratified analysis results underscore the critical importance of maintaining a healthy lifestyle, as obesity, smoking, and consume carryout/delivered foods exhibit effect modification on the association between PFASs and MetS.

Conclusion

Our findings point to PFNA as a risk factor for metabolic diseases, particularly affecting lipids.