Related Experiment Video

Updated: May 2, 2026

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Published on: April 18, 2019

Association of per- and polyfluoroalkyl substances with gout risk: a cross-sectional analysis of NHANES 2007-2018

Haixin Feng¹, Siran Li¹, Shiqing Huang¹

¹Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Medical University, Dongguan, China.

Frontiers in Public Health

|February 25, 2025

Abstract

Objective:

This study examined associations between serum concentrations of per- and polyfluoroalkyl substances (PFASs) and gout risk in the U.S. adult population using the National Health and Nutrition Examination Survey (NHANES) 2007-2018 data. And assessing the potential intermediary effect of uric acid.

Methods:

The study included 8,494 participants, with 385 having gout. Four PFAS compounds (PFOA, PFOS, PFHxS, PFNA) were measured. PFOS is the most prevalent PFAS in the environment, biota, and human tissues. It is rapidly absorbed and accumulates in the liver, kidneys, and blood, binding to serum albumin and low-density lipoprotein. PFOA is highly persistent in the body, mainly accumulating in the kidneys and liver through enterohepatic circulation, posing risks due to its difficulty in metabolism and excretion. PFHxS has the longest metabolic half-life in humans (7.3 years) and bioaccumulates in the endocrine, immune, nervous, and reproductive systems. PFNA is the second most detected PFAS in human serum after PFOS. It is more likely to accumulate and express toxicity in the reproductive organs, liver, and immune system compared to PFOS and PFOA. Multivariate logistic regression and weighted quantile sum regression were used to assess individual and mixture effects. Mediation analysis was conducted to estimate effect of uric acid.

Results:

In fully adjusted model, the associations were nonsignificant, with PFOA showing a marginally positive association. Mixture analysis revealed a significant positive association with gout risk across all models. PFOS was the largest contributor to the mixture effect. Stronger associations were observed in old people and females. Sensitivity analyses confirmed the robustness of these findings. Mediation analysis indicated significant intermediary effect of uric acid in the associations of PFAS with risk of gout, with the mediated proportion ranging from 48 to 77%.

Conclusion:

This study provides evidence for a potential link between PFAS exposure and gout risk, particularly when considering mixtures. While associations with individual PFASs are largely explained by demographic and lifestyle factors, the persistent association of mixtures with gout risk highlights the importance of considering combined exposures in environmental health research. Uric acid level plays a crucial intermediary effect.

Keywords:

PFAS (per- and polyfluoroalkyl substances)WQS regression gout logistic regression mixture exposure

More Related Videos

Investigating Long-Distance Transport of Perfluoroalkyl Acids in Wheat via a Split-Root Exposure Technique

Investigating Long-Distance Transport of Perfluoroalkyl Acids in Wheat via a Split-Root Exposure Technique

Published on: September 28, 2022

Synthesis of a Borylated Ibuprofen Derivative Through Suzuki Cross-Coupling and Alkene Boracarboxylation Reactions

Synthesis of a Borylated Ibuprofen Derivative Through Suzuki Cross-Coupling and Alkene Boracarboxylation Reactions

Published on: November 30, 2022

Related Concept Videos

Chi-square Analysis

Chi-square Analysis

The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...

Factors Affecting Illness

Factors Affecting Illness

When a person's physical, emotional, intellectual, social development or spiritual functioning is compromised, this deviation from a healthy normal state is called illness. Illness creates stress that in turn harms individuals. Irritation, anger, denial, hopelessness, and fear are behavioral and emotional changes an individual experiences in the phases of illness. A variety of factors influence a person's health and well-being.
For instance, risk factors are connected to illness,...

Combined Effects of Drugs: Antagonism

Combined Effects of Drugs: Antagonism

The combined effects of drugs can result in various interactions, of which an important type is antagonism. Antagonism is a mechanism where one drug inhibits or counteracts the effects of another drug. Antagonism can occur through various means, including receptor binding, allosteric modulation, functional interaction, chemical reactions, and pharmacokinetic processes.
The most common type is receptor antagonism, where one drug acts as an antagonist to block the effects of another drug by...

Combined Effects of Drugs: Synergism

Combined Effects of Drugs: Synergism

Synergism is a useful mechanism where combining two or more drugs is more effective than each constituent used alone. Such combinations are also called supra-additive interactions. The drugs collectively enhance the final therapeutic effect by acting on different targets. Another advantage is that the low dose of each constituent drug is sufficient to achieve the desired effect. This helps reduce the duration of therapy and lower the adverse effects of these drugs.
Such synergistic combinations...

Local Anesthetics: Differential Sensitivity of Nerve Fibers

Local Anesthetics: Differential Sensitivity of Nerve Fibers

Local anesthetics (LAs) block the sodium channels of nerve trunks, sensory nerve endings, and neuromuscular junctions. Although LAs can block all kinds of nerves, the sensitivity of nerve fibers differs according to nerve types and structures. LAs are known to block myelinated fibers faster than unmyelinated ones. Also, they block pain or sensory neurons at low concentrations without affecting the motor neurons involved in muscle contractions. This helps relieve labor pain without affecting the...

Bias in Epidemiological Studies

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:

Articles linked to this work by shared authors, journal, and citation graph.

Artificial Intelligence in Model-Informed Drug Development: Augmentation, Acceleration, and Regulatory Preparation.

Clinical and translational science·2026

AI Cautionary Guide: Pitfalls and Strategies for the Use of Machine Learning in Medical Research.

Clinical pharmacology and therapeutics·2026

Cyclic(silyl)(amino)carbenes as Ambiphilic Platforms for Small-Molecule Activation and Skeletal Si-C Bond Reorganization: A DFT Study.

Inorganic chemistry·2026

Efficient Synthesis of N-Bridged Annulenes.

Journal of the American Chemical Society·2026

Machine Learning-Enabled Layer-Wise Melting Quality Recognition for Laser Powder Bed Fusion Process via In Situ Monitoring.

Materials (Basel, Switzerland)·2026

Stereocontrolled Substitution at P(III) Centers Enabled by Pyridine N-Oxide Catalysis.

Organic letters·2026

See all related articles