Associations of per- and polyfluoroalkyl substances (PFAS) on lipid metabolism have been documented but research remains scarce regarding effect of PFAS on lipid variability. To deeply understand their relationship, a step-forward in causal inference is expected. To address these, we conducted a longitudinal study with three repeated measurements involving 201 participants in Beijing, among which 100 eligible participants were included for the present study. Twenty-three PFAS and four lipid indicators were assessed at each visit. We used linear mixed models and quantile g-computation models to investigate associations between PFAS and blood lipid levels. A latent class growth model described PFAS serum exposure patterns, and a generalized linear model demonstrated associations between these patterns and lipid variability. Our study found that PFDA was associated with increased TC (β = 0.083, 95% CI: 0.011, 0.155) and HDL-C (β = 0.106, 95% CI: 0.034, 0.178). The PFAS mixture also showed a positive relationship with TC (β = 0.06, 95% CI: 0.02, 0.10), with PFDA contributing most positively. Compared to the low trajectory group, the middle trajectory group for PFDA was associated with VIM of TC (β = 0.756, 95% CI: 0.153, 1.359). Furthermore, PFDA showed biological gradients with lipid metabolism. This is the first repeated-measures study to identify the impact of PFAS serum exposure pattern on the lipid metabolism and the first to estimate the association between PFAS and blood lipid levels in middle-aged and elderly Chinese and reinforce the evidence of their causal relationship through epidemiological studies.
Keywords: Causal inference; Lipid metabolism; Per- and polyfluoroalkyl substances; Serum exposure pattern.
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