Related Experiment Video
Updated: Oct 25, 2025

A Modified QuEChERS-HPLC Method for Detection of Polycyclic Aromatic Hydrocarbons in Zebrafish Embryos Exposed to Fine Particulate Matter
Published on: June 13, 2025
Maternal PM10 Exposure Increases Risk for Spina Bifida: A Population-Based Case-Control Study
Huan Li1, Yan-Hong Huang2, Jing Li3
1Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Limited studies have focused on the impact of ambient air pollution on spina bifida. A population-based case-control study was conducted in Liaoning Province, China to assess the associations between maternal PM10 exposures in various exposure windows and spina bifida risk. Data on spina bifida cases born between 2010 and 2015 were available from the Maternal and Child Health Certificate Registry of Liaoning Province. Controls were a random sample of healthy livebirths without any birth defects delivered in the selected five cities during 2010-2015. Ambient air monitoring data for PM10 were obtained from 75 monitoring stations in Liaoning Province. The multivariable logistic regression models were established to calculate adjusted odds ratios (OR) and 95% confidence intervals (CI). We further performed sensitivity analyses by using three propensity score methods. A total of 749 spina bifida cases and 7,950 controls were included. After adjusting for potential confounders, spina bifida was associated with a 10 μg/m3 increment in PM10 during the first trimester of pregnancy (adjusted OR = 1.06, 95% CI: 1.00-1.12) and the 3 months before pregnancy (adjusted OR = 1.12, 95% CI: 1.06-1.19). The adjusted ORs in the final model for the highest vs. the lowest quartile were 1.51 (95% CI: 1.04-2.19) for PM10 during the first trimester of pregnancy and 2.01 (95% CI: 1.43-2.81) for PM10 during the 3 months before pregnancy. Positive associations were found between PM10 exposures during the single month exposure windows and spina bifida. Sensitivity analyses based on two propensity score methods largely reported similar positive associations. Our findings support the evidence that maternal PM10 exposure increases the risk of spina bifida in offspring. Further, validation with a prospective design and a more accurate exposure assessment is warranted.
Limited studies have focused on the impact of ambient air pollution on spina bifida. A population-based case-control study was conducted in Liaoning Province, China to assess the associations between maternal PM10 exposures in various exposure windows and spina bifida risk. Data on spina bifida cases born between 2010 and 2015 were available from the Maternal and Child Health Certificate Registry of Liaoning Province. Controls were a random sample of healthy livebirths without any birth defects delivered in the selected five cities during 2010-2015. Ambient air monitoring data for PM10 were obtained from 75 monitoring stations in Liaoning Province. The multivariable logistic regression models were established to calculate adjusted odds ratios (OR) and 95% confidence intervals (CI). We further performed sensitivity analyses by using three propensity score methods. A total of 749 spina bifida cases and 7,950 controls were included. After adjusting for potential confounders, spina bifida was associated with a 10 μg/m3 increment in PM10 during the first trimester of pregnancy (adjusted OR = 1.06, 95% CI: 1.00-1.12) and the 3 months before pregnancy (adjusted OR = 1.12, 95% CI: 1.06-1.19). The adjusted ORs in the final model for the highest vs. the lowest quartile were 1.51 (95% CI: 1.04-2.19) for PM10 during the first trimester of pregnancy and 2.01 (95% CI: 1.43-2.81) for PM10 during the 3 months before pregnancy. Positive associations were found between PM10 exposures during the single month exposure windows and spina bifida. Sensitivity analyses based on two propensity score methods largely reported similar positive associations. Our findings support the evidence that maternal PM10 exposure increases the risk of spina bifida in offspring. Further, validation with a prospective design and a more accurate exposure assessment is warranted.
More Related Videos
Related Concept Videos
Teratogenicity
Testing a Claim about Mean: Known Population SD
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...

