Epidemiologic studies have reported associations between air pollution levels and semen characteristics, which might in turn affect a couple's ability to achieve a live birth. Our aim was to characterize short-term effects of atmospheric pollutants on fecundability (the month-specific probability of pregnancy among noncontracepting couples).
Methods
For a cohort of births between 1994 and 1999 in Teplice (Czech Republic), we averaged fine particulate matter (PM2.5), carcinogenic polycyclic aromatic hydrocarbons, ozone, nitrogen dioxide (NO2), and sulfur dioxide levels estimated from a central measurement site over the 60-day period before the end of the first month of unprotected intercourse. We estimated changes in the probability of occurrence of a pregnancy during the first month of unprotected intercourse associated with exposure, using binomial regression and adjusting for maternal behaviors and time trends.
Results
Among the 1,916 recruited couples, 486 (25%) conceived during the first month of unprotected intercourse. Each increase of 10 µg/m in PM2.5 levels was associated with an adjusted decrease in fecundability of 22% (95% confidence interval = 6%-35%). NO2 levels were also associated with decreased fecundability. There was no evidence of adverse effects with the other pollutants considered. Biases related to pregnancy planning or temporal trends in air pollution were unlikely to explain the observed associations.
Conclusions
In this polluted area, we highlighted short-term decreases in a couple's ability to conceive in association with PM2.5 and NO2 levels assessed in a central monitoring station.
Russo LM et al., 2025·Ecotoxicol Environ Saf·
Open Access
Prior studies have observed impacts of air pollution on semen quality, but timing of exposure during developmental windows of spermatogenesis and impacts of low-to-moderate air pollution is less well understood. We examined the relation between air pollution and semen quality in the Folic Acid and Zinc Supplementation Trial (2013-2018), which enrolled male partners of couples seeking infertility treatment in the Salt Lake City, Utah region (n = 2015). Semen quality parameters were assessed at baseline, 2-, 4-, and 6-months follow-up. Measures of daily air pollutants at each participant's residence were abstracted from Community Multiscale Air Quality models (fine particulate matter: PM2.5, sulfur dioxide, nitrogen dioxide, and ozone: O3), linked to participants' residential addresses, and averaged across the 74-day spermatogenesis window prior to the sample collection date for each study visit, and across four developmental windows of spermatogenesis (mitosis, meiosis I-II, spermiogenesis, and spermiation). Generalized linear mixed models considered four repeated semen sample measures per participant and adjusted for co-pollutants, age, season, and income. In multi-pollutant models, O3 during early-to-mid spermatogenesis (meiosis I+II and spermiogenesis) was related to lower percent normal morphology (% difference -6.73, 95 % CI -9.82, -3.54 and % difference -3.83, 95 % CI -7.51, 0.00, respectively). Additionally, PM2.5 and O3 during late spermatogenesis (spermiation) were associated with lower count and concentration, and PM2.5 with lower progressive motility. These findings suggest that exposure to low-to-moderate levels of air pollution may negatively impact semen quality and indicate that exposure to O3 during meiosis and spermiogenesis may particularly affect normal sperm morphological development.
Understanding and mitigating health risks from poor indoor air quality, particularly fine particulate matter (PM2.5), is critical, yet conventional monitoring methods are costly and require skilled operators. Low-cost sensors (LCS) offer an accessible alternative; however, their accuracy under varying environmental conditions remains uncertain. This study evaluates how humidity, temperature, deployment duration, and concentration levels affect the calibration accuracy of low-cost PM2.5 monitors. Nineteen Plantower PMS 3003 sensors deployed in 11 Salt Lake County homes participating in the Green & Healthy Homes Initiative were calibrated before and after residential deployment using a TSI DustTrak aerosol monitor. Linear and Lasso regression analyses were performed to evaluate the influence of environmental factors on calibration parameters. Significant variability was observed in environmental conditions. Higher humidity (p = 0.0197) and longer deployment durations (p = 0.0178) significantly altered calibration slopes, while mean PM2.5 exposure (p = 0.0040) was strongly associated with intercept adjustments. These findings emphasize the need to account for environmental factors in calibration models to improve LCS accuracy and reliability. Environmental conditions significantly impact the performance of low-cost PM2.5 sensors. Modeling these impacts can streamline the calibration process, making it more efficient and cost-effective. Future research should focus on refining calibration models and exploring additional environmental factors to optimize LCS performance.
Palmore M et al., 2025·Environ Epigenet·
Open Access
Prenatal exposure to air pollution is an important risk factor for child health outcomes, including asthma. Identification of DNA methylation changes associated with air pollutant exposure can provide new intervention targets to improve children's health. The aim of this study is to test the association between prenatal air pollutant exposure and DNA methylation in developmental and asthma-/allergy-relevant biospecimens (placenta, buccal, cord blood, nasal mucosa, and lavage). A subset of 2294 biospecimens collected from 1906 child participants enrolled in the Environmental Influences on Child Health Outcomes program with prenatal air pollutant and high-quality Illumina Asthma&Allergy DNA methylation array measures (n = 37 197 probes) were included. Prenatal ozone, nitrogen dioxide, and fine particulate matter were derived using residential history during pregnancy and spatiotemporal models. For each pollutant, biospecimen type, and prenatal exposure window, we estimated the effects of air pollution on gene DNA methylation levels. We compared results across pollutants, biospecimen types, and trimesters and tested for critical months of exposure using distributed lag models. DNA methylation levels at 154 out of 4746 tested genes were associated with air pollution; over 95% were exposure window, pollutant, and biospecimen-type specific. The fewest gene associations were detected in trimester 2, relative to other exposure windows. A variety of trends in methylation patterns were observed in response to lagged monthly pollution levels. Child DNA methylation changes at specific respiratoryand immune-relevant genes are associated with prenatal air pollutant exposures. Future studies should examine the relationship between these pollution-sensitive genes and child health.