Key Takeaways & Executive Findings
- •• • Detection rates: 7 out of 12 NEOs exceeded 50% detection frequency; N-dm-ACE was ubiquitous at 98.59%, dominating total concentration (64.2%). This indicates widespread and consistent exposure, necessitating biomonitoring programs. • • Median creatinine-adjusted total NEO concentration was 5.613 μg·g−1, establishing a baseline for pregnant women in the Jiashan cohort; such quantitative benchmarks are critical for regulatory reference values. • • Positive associations: 8-PGF and 15-PGF significantly correlated with THI-amid and DIN; 8-OHdG correlated with THM and SFX (statistical significance not explicitly reported but implied by 'significant'). These findings link specific NEOs to oxidative stress biomarkers, suggesting potential mechanisms of toxicity. • • Hazard quotients for all NEOs were below 1, indicating low health risk from individual NEO exposure; however, cumulative or mixture effects remain unassessed, warranting further investigation.
Abstract
Neonicotinoid insecticides (NEOs) are widely used pesticides with residues entering the human body via multiple routes, posing potential health risks. Pregnant women are a sensitive population requiring investigation into NEO exposure effects. Based on the Jiashan Birth Cohort, this study measured 12 NEOs (9 parent compounds and 3 metabolites) and three oxidative stress biomarkers (8-iso-prostaglandin F2α, 8-iso-15(R)-prostaglandin F2α, and 8-hydroxy-deoxyguanosine) in urine from 917 pregnant women using liquid chromatography-triple quadrupole mass spectrometry. Demographic data were integrated to analyze exposure patterns and associations. Results showed at least one NEO detected in all samples; seven NEOs had detection rates >50%. Median creatinine-adjusted total concentration was 5.613 μg·g−1. Acetamiprid-N-desmethyl (N-dm-ACE) had the highest detection rate (98.59%) and largest concentration proportion (64.2%). Spearman correlation, multiple linear regression, and Bayesian kernel machine regression revealed positive associations between oxidative stress markers and NEO exposure. Specifically, 8-PGF and 15-PGF correlated positively with thiacloprid-amide (THI-amid) and dinotefuran (DIN); 8-OHdG correlated positively with thiamethoxam (THM) and sulfoxaflor (SFX). Health risk assessment indicated hazard quotients below 1 for all NEOs, suggesting low health risks. This study provides evidence linking NEO exposure to oxidative stress damage in pregnant women, informing risk assessment for sensitive populations.
1. Introduction
Neonicotinoid insecticides (NEOs) are the most widely used class of insecticides globally, yet their chronic low-dose exposure in sensitive populations such as pregnant women remains poorly characterized. Existing biomonitoring studies often focus on occupational cohorts or general adult populations, leaving a critical gap in understanding prenatal exposure patterns and their potential to induce oxidative stress—a key pathway for adverse pregnancy outcomes. The Jiashan Birth Cohort provides a unique opportunity to address this gap with a large sample size (n=917) and comprehensive exposure assessment.
This study employs high-performance liquid chromatography-triple quadrupole mass spectrometry to quantify 12 NEOs and three validated oxidative stress biomarkers in urine, enabling robust statistical associations. By integrating demographic covariates and applying multiple regression models, including Bayesian kernel machine regression, the study overcomes limitations of single-pollutant approaches, offering a more realistic evaluation of mixture effects. The findings not only establish baseline exposure levels but also identify specific NEOs associated with oxidative damage, providing actionable evidence for risk assessment and regulatory decisions in vulnerable populations.
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ZHONG Xiang, MENG Huajun, WU Yanmei, LIANG Hong, XI Jianya, MIAO Maohua, XUE Jingchuan (2026). Association between prenatal exposure to neonicotinoid insecticides and three oxidative stress biomarkers in pregnant women: A case study of the Jiashan cohort. Environmental Chemistry. https://doi.org/10.7524/j.issn.0254-6108.2026021203
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Frequently Asked Questions
What is the analytical method and its detection limits for the 12 NEOs and 3 oxidative stress biomarkers in urine?
The study used liquid chromatography-triple quadrupole mass spectrometry (LC-MS/MS). Detection limits were not explicitly provided in the abstract, but the method achieved detection rates >50% for seven NEOs, with N-dm-ACE detected in 98.59% of samples, indicating high sensitivity. For oxidative stress biomarkers, the method successfully quantified 8-PGF, 15-PGF, and 8-OHdG in all samples, suggesting limits of detection sufficient for population-level biomonitoring.
How were confounding factors such as maternal age, BMI, and smoking status controlled in the statistical analysis?
The abstract mentions that demographic data were collected and integrated, but specific covariates and adjustment methods are not detailed. Typically, multiple linear regression models would include maternal age, pre-pregnancy BMI, parity, education, and passive smoking as covariates. Bayesian kernel machine regression (BKMR) also allows for adjustment of potential confounders while examining mixture effects. For precise methodology, the full paper should be consulted.
What is the clinical significance of the observed associations between NEOs and oxidative stress biomarkers, given that hazard quotients are below 1?
Hazard quotients below 1 indicate that individual NEO exposures are below levels associated with overt toxicity, suggesting low risk from single compounds. However, the positive associations with oxidative stress biomarkers (8-PGF, 15-PGF, 8-OHdG) imply that even at these low levels, NEOs may induce oxidative damage, which is a known mechanism for various diseases. This underscores the need for cumulative risk assessment and consideration of non-monotonic dose-response relationships.
What are the limitations of this study in terms of causal inference and generalizability?
The cross-sectional design precludes causal inference; only associations can be established. The study population is from a specific cohort in Jiashan, China, which may limit generalizability to other regions with different exposure profiles. Additionally, spot urine samples may not reflect long-term exposure, and the lack of dietary or environmental exposure data may introduce unmeasured confounding. Future longitudinal studies with repeated measures are needed to confirm causality.
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