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. 2025 Jun 27:13:1597489.
doi: 10.3389/fpubh.2025.1597489. eCollection 2025.

Associations of urinary phthalate metabolites with Circadian Syndrome: evidence from NHANES

Affiliations

Associations of urinary phthalate metabolites with Circadian Syndrome: evidence from NHANES

Chunxing Yi et al. Front Public Health. .

Abstract

Background: The relationship between phthalate exposure and circadian rhythm disruption lacks epidemiological evidence. This study investigated the association between exposure to ten phthalates (PAEs) and Circadian Syndrome (CircS) among American adults.

Methods: Data from the 2013-2018 United States National Health and Nutritional Health Surveys (N = 2519) were analyzed using logistic regression to assess associations between individual phthalate exposure and CircS. Restricted cubic splines (RCS) evaluated dose-response relationships, while Bayesian kernel machine regression (BKMR) and g-computation models assessed the effects of phthalate mixtures.

Results: The prevalence of CircS in the study population was 45.14%. Participants in the fourth quartile of exposure to MECP phthalate (OR = 1.632, 95% CI: 1.159-2.300), MEHP phthalate (OR = 1.830, 95% CI: 1.301-2.573), mono-benzyl phthalate (OR = 1.699, 95% CI: 1.156-2.496), and MEOH phthalate (OR = 1.560, 95% CI: 1.065-2.279) had an increased risk of CircS compared to those in the first quartile of exposure. RCS analysis indicated a linear positive association between exposure to MECP, MEHP, and mono-benzyl phthalate and CircS risk. BKMR and quantile g-computation analyses demonstrated that combined phthalate exposure was positively associated with CircS.

Conclusion: Individual and mixed exposures to certain phthalates may increase the risk of CircS, providing evidence for prevention strategies targeting endocrine-disrupting chemicals.

Keywords: BKMR; Circadian Syndrome; NHANES; phthalates; quantile g-computation.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow chart for inclusion of study participants.
Figure 2
Figure 2
Association between single urinary phthalate metabolite concentration and CircS (N = 2519). NHANES, USA, 2013–2018. Model 1: The unadjusted model. Model 2: Adjusted for age, gender, educational attainment, race, alcohol consumption, physical activity, and cotinine levels.
Figure 3
Figure 3
Non-linear dose–response analysis on PAEs and CircS. Restricted cubic spline regression with 3 knots at the 10th, 50th, and 90th percentiles was used to explore the potential dose–response relationship between log10-transformed PAEs and CircS, with the 25th percentile serving as the reference. Model adjusted for age, gender, educational attainment, race, alcohol consumption, physical activity, and cotinine levels. Solid lines indicate OR, and the shadow shapes indicate 95% CIs. L: P for overall; N: P for nonlinearity.
Figure 4
Figure 4
Joint effect (95% CI) of the mixture on CircS when all the PAEs at particular percentiles were compared to all the PAEs at their 25th percentile. The results were assessed by the BKMR model, adjusted for age, gender, educational attainment, race, alcohol consumption, physical activity, and cotinine levels.
Figure 5
Figure 5
Joint effect of PAEs mixture on CircS and weight of each phthalate according to quantile g-computation.

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