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<p>This study aimed to examine the association between phthalate exposure and urine flow rate (UFR). Data from 6951 adult participants across five consecutive NHANES cycles (2009–2018) were analyzed. High-performance liquid chromatography–electrospray ionization tandem mass spectrometry was used to measure urinary concentrations of 10 highly detectable phthalate metabolites (PMs). Associations between PMs and UFR were investigated using various analytical approaches, including weighted linear regression, weighted quantile sum regression (WQS), quantile g-computation (qgcomp), restricted cubic spline (RCS), and Bayesian kernel-machine regression (BKMR) models. Each quartile increase in the WQS index for PM mixtures was associated with a − 0.042 lower ln-transformed UFR (95% CI − 0.07, − 0.014). The qgcomp regression model yielded consistent results. In BKMR analysis, PM mixtures showed a significant negative association with ln-transformed UFR, with mono-2-ethyl-5-carboxypentyl phthalate (MECPP) and mono-benzyl phthalate (MBzP) identified as potential key contributors. In addition, the RCS results showed an inverted s-type nonlinear relationship between MECPP and MBzP, and UFR. Exposure to phthalates is associated with lower UFR.</p>

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Association between phthalates exposure and urine flow rate

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月7日

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  • Shuai Zhang,
  • Hanhan Tang,
  • Minglian Zhou

摘要

This study aimed to examine the association between phthalate exposure and urine flow rate (UFR). Data from 6951 adult participants across five consecutive NHANES cycles (2009–2018) were analyzed. High-performance liquid chromatography–electrospray ionization tandem mass spectrometry was used to measure urinary concentrations of 10 highly detectable phthalate metabolites (PMs). Associations between PMs and UFR were investigated using various analytical approaches, including weighted linear regression, weighted quantile sum regression (WQS), quantile g-computation (qgcomp), restricted cubic spline (RCS), and Bayesian kernel-machine regression (BKMR) models. Each quartile increase in the WQS index for PM mixtures was associated with a − 0.042 lower ln-transformed UFR (95% CI − 0.07, − 0.014). The qgcomp regression model yielded consistent results. In BKMR analysis, PM mixtures showed a significant negative association with ln-transformed UFR, with mono-2-ethyl-5-carboxypentyl phthalate (MECPP) and mono-benzyl phthalate (MBzP) identified as potential key contributors. In addition, the RCS results showed an inverted s-type nonlinear relationship between MECPP and MBzP, and UFR. Exposure to phthalates is associated with lower UFR.