Maternal PM2.5 exposure during gestation and offspring neurodevelopment: Findings from a prospective birth cohort study

A scoping review and quality assessment of machine learning techniques in identifying maternal risk factors during the peripartum phase for adverse child development

Maternal exposure to environmental risk factors (e.g., heavy metal exposure) or mental health problems during the peripartum phase has been shown to lead to negative and lasting impacts on child development and life in adulthood. Given the importance of identifying early markers within highly complex and heterogeneous perinatal factors, machine learning techniques emerge as a promising tool. The main goal of the current scoping review was to summarize the evidence on the application of machine learning techniques in predicting or identifying risk factors during peripartum for child development. A critical appraisal was also conducted to evaluate various aspects, including representativeness, data leakage, validation, performance metrics, and interpretability. A systematic search was conducted in PubMed, Web of Science, Scopus, and Google Scholar to identify studies published prior to the 14th of January 2025. Review selection and data extraction were performed by three independent reviewers. After removing duplicates, the searches yielded 10,336 studies, of which 60 studies were included in the final report. Among these 60 machine learning studies, a majority were pattern-focused, using machine learning primarily as a tool to more accurately describe associations between variables, while 16 studies were prediction-focused (26.7%), exploring the predictive performance of their models. For prediction-focused machine learning studies, a diverse range of methodologies was observed. The quality assessment showed that all studies had some important criteria that were not fully met, with deviations ranging from minor to major, limiting the interpretability and generalizability of the reported findings. Future research should aim at addressing these limitations to enhance the robustness and applicability of machine learning models in this field.

Association of early life exposure to PM2.5 and its components with offspring neurodevelopment: A prospective birth cohort study

Emerging data have explored early life fine particulate (PM2.5) exposure and its relationship with offspring neurodevelopment. However, the findings remain inconsistent, and the roles of specific PM2.5 components are unclear. We investigated these associations and explored the potential interactive role of children's physical activity (PA). A total of 1547 mother-child pairs from the Shenzhen Birth Cohort were included. Neurodevelopment was assessed at seven time points (1, 3, 6, 8, 12, 18, and 24 months) using the Ages and Stages Questionnaire. An established spatiotemporal model was used to estimate early life exposure to PM2.5 and five components [sulfate (SO42), nitrate (NO3-), ammonium (NH4+), organic matter (OM), and black carbon (BC)]. Associations of individual and joint exposure to components with neurodevelopment were analyzed using generalized estimating equation and quantile-based g-computation models with a binomial distribution. Most mothers (79.1%) were under 35 at delivery, and 43.6% of the children were boys. During the early postnatal period, a 5 μg/m3 increase in PM2.5 was associated with higher adjusted odds ratios (aORs) for developmental delays in gross motor (1.24, 95%CI:1.12, 1.37), fine motor (1.11, 95%CI:1.04, 1.20), and problem-solving (1.12, 95%CI:1.03, 1.22) domains. Similar associations were observed for individual PM2.5 components. Each quintile increase in early postnatal exposure to PM2.5 mixtures was correlated with higher aORs for these domains, with NO3- constituting the largest weight. No significant associations were found for the prenatal period. The children's PA showed no interaction. These findings underscore the need to reduce PM2.5 exposure, particularly its toxic components, to minimize developmental risks.

Associations of prenatal exposure to PM2.5 and its components with offsprings' neurodevelopmental and behavioral problems: A prospective cohort study from China

Prenatal exposure to fine particulate matter (PM2.5) has been linked with increased neurodevelopmental disorders. However, the most detrimental component of PM2.5 and the most vulnerable exposure time windows remain undetermined, especially in areas with high PM2.5 levels. In a prospective cohort study involving 4494 mother-child dyads, we examined the associations of prenatal exposure to PM2.5 and its four main components with children's neurodevelopmental and behavioral problems (NBPs), separately in three pregnancy trimesters. Poisson regression and generalized additive models were used to depict the linear and nonlinear associations, respectively. Weighted quantile sum and Bayesian kernel machine regression models were applied to examine the effects of exposure to both mixed and individual components. Results showed that exposure to PM2.5 and its components throughout the three trimesters increased the risk of children's NBPs (Risk ratio for PM2.5: 1.16, 95 % confidence interval 1.14-1.18 per μg/m3 in the first trimester; 1.15, 1.12-1.17 in the second trimester; 1.06, 1.04-1.08 in the third trimester), with associations gradually diminishing as pregnancy progressed (P values for trends < 0.05). Among the four main components of PM2.5, exposure to SO42- posed the highest risks on children's NBPs, while organic matter contributed the largest proportion to the overall impacts of PM2.5 exposure. These results underscore the significance of mitigating PM2.5 exposure in pregnant women to reduce the risk of neurodevelopmental disorders in offspring. Our findings would inform risk assessment of PM2.5 exposure and facilitate the development of precision preventive strategies targeting specific components of PM2.5 in similar areas with high levels of exposure.

Impact of Respiratory Dust on Health: A Comparison Based on the Toxicity of PM2.5, Silica, and Nanosilica

Respiratory dust of different particle sizes in the environment causes diverse health effects when entering the human body and makes acute or chronic damage through multiple systems and organs. However, the precise toxic effects and potential mechanisms induced by dust of different particle sizes have not been systematically summarized. In this study, we described the sources and characteristics of three different particle sizes of dust: PM2.5 (<2.5 μm), silica (<5 μm), and nanosilica (<100 nm). Based on their respective characteristics, we further explored the main toxicity induced by silica, PM2.5, and nanosilica in vivo and in vitro. Furthermore, we evaluated the health implications of respiratory dust on the human body, and especially proposed potential synergistic effects, considering current studies. In summary, this review summarized the health hazards and toxic mechanisms associated with respiratory dust of different particle sizes. It could provide new insights for investigating the synergistic effects of co-exposure to respiratory dust of different particle sizes in mixed environments.

Associations between particulate matter exposure during pregnancy and executive function of toddlers in a prospective cohort study

BACKGROUND

Exposure to particulate matter (PM) has been found to be associated with impaired cognitive function. However, limited evidence is available on the relationship between PM exposure in the prenatal period and toddler executive function (EF), and the potential influence of breastfeeding.

METHODS

The study included 1106 mother-toddler pairs recruited between 2015 and 2019. We assessed mothers' PM1, PM2.5, and PM10 prenatal exposure with a satellite-based dataset at a 1 × 1 km spatial resolution and assigned to participants based on residential addresses. Toddler EF was measured using the Behavior Rating Inventory of Executive Function for Preschoolers (BRIEF-P) questionnaire, higher BRIEF-P scores indicated poorer EF in toddlers. We determined the associations of PM exposure during pregnancy with BRIEF-P scores using multiple linear regression models.

RESULTS

In the first trimester, a 10 μg/m3 increase of PM was associated with 1.49 (95% confidence interval [CI]: 0.14-2.83; PM1), 0.68 (95% CI: 0.10-1.26; PM2.5), and 0.63 (95% CI: 0.07-1.20; PM10) elevated toddler global executive composite index scores, respectively. In the stratified analysis, a 10 μg/m3 increase in first trimester PM1 exposure was related to 0.54 (95% CI: 0.19-0.89) higher inhibition scores in toddlers who received complementary breastfeeding for less than six months and -0.15 (95% CI: 0.81-0.51) higher inhibition scores in toddlers who received complementary breastfeeding for six months or more (P for interaction: 0.046). Additionally, a 10 μg/m3 increment in first trimester PM1 exposure was related to 0.36 (95% CI: 0.13-0.59) higher emotional control scores in toddlers who received breastfeeding for less than 12 months and -0.54 (95% CI: 1.25-0.18) higher inhibition scores in toddlers who received breastfeeding for no less than 12 months (P for interaction: 0.043).

CONCLUSIONS

PM exposure during the first trimester, especially PM1, has been linked to lower toddler EF performance in toddlers; feeding with breast milk may be a potential protective measure.

Gestational Exposure to PM2.5 and Specific Constituents, Meconium Metabolites, and Neonatal Neurobehavioral Development: A Cohort Study

Exposure to fine particulate matter (PM2.5) during pregnancy has been inversely associated with neonatal neurological development. However, the associations of exposure to specific PM2.5 constituents with neonatal neurological development remain unclear. We investigated these associations and examined the mediating role of meconium metabolites in a Chinese birth cohort consisting of 294 mother-infant pairs. Our results revealed that exposure to PM2.5 and its specific constituents (i.e., organic matter, black carbon, sulfate, nitrate, and ammonium) in the second trimester, but not in the first or third trimester, was inversely associated with the total neonatal behavioral neurological assessment (NBNA) scores. The PM2.5 constituent mixture in the second trimester was also inversely associated with NBNA scores, and sulfate was identified as the largest contributor. Furthermore, meconium metabolome analysis identified four metabolites, namely, threonine, lysine, leucine, and saccharopine, that were associated with both PM2.5 constituents and NBNA scores. Threonine was identified as an important mediator, accounting for a considerable proportion (14.53-15.33%) of the observed inverse associations. Our findings suggest that maternal exposure to PM2.5 and specific constituents may adversely affect neonatal behavioral development, in which meconium metabolites may play a mediating role.

Associations between maternal exposure to air pollution during pregnancy and trajectories of infant growth: A birth cohort study

OBJECTIVE

We examined the relationships between infants' growth trajectories and prenatal exposure to air pollution, which is still under-investigated.

METHODS

A birth cohort study was constructed using medical records of pregnant women and infants born between 2015 and 2019 in Foshan, China. Using satellite-based spatial-temporal models, prenatal exposure to air pollutants including particulate matter with an aerodynamic dimension of < 2.5 µm (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) was assessed at each woman's residence. Latent class growth modeling was used to identify trajectories of physical (body length and weight) growth and neurodevelopment, which were repeatedly measured within 1 year after birth. Logistic regression models were used to investigate the associations between prenatal exposure to air pollution and the risks of growth disorders, adjusting for an array of potential confounders.

RESULTS

We identified two growth trajectories for body length [normal: 3829 (93%); retardation: 288 (7%)], three for weight [normal: 2475 (59.6%); retardation: 390 (9.4%); overgrowth: 1287 (31%)], and two for neurodevelopment [normal: 956 (66.1%); retardation: 491 (33.9%)]. For exposure over whole pregnancy, SO2 was associated with an increased risk of body length retardation (OR for per 1 µg/m3 increment: 1.09, 95%CI: 1.01-1.17); PM2.5 (OR: 1.05, 95%CI: 1.03-1.07), SO2 (OR: 1.15, 95%CI: 1.08-1.22), and NO2 (OR: 1.05, 95%CI: 1.03-1.07) were positively associated with neurodevelopmental retardation. Such associations appeared stronger for exposures over the first and second trimesters. No significant associations were detected for weight growth.

CONCLUSIONS

Maternal exposure to air pollution during pregnancy was associated with higher risks of impairments in both physical growth, particularly body length, and neurodevelopment.

Fine particulate matter and its constituent on ovarian reserve: Identifying susceptible windows of exposure

BACKGROUND

Little is known about the associations of exposure to fine particulate matter (PM2.5) and its constituents with ovarian reserve, and the potential susceptible window of exposure remains unclear.

METHODS

We performed a retrospective cohort study of 5189 women who attended a fertility center in Hubei, China, during 2019-2022, and estimated concentrations of PM2.5 and its major constituents during the development of follicles (4th-6th month [W1], 0-4th month [W2], 0-6th month [W3]) and 1-year before measurement (W4) based on Tracking Air Pollution in China database. We used multivariable linear regression and logistic regression models to examine the associations of PM2.5 and its constituent exposures with anti-Müllerian hormone (AMH), the preferred indicator of ovarian reserve.

RESULTS

We observed significantly decreased AMH levels associated with increasing PM2.5 concentrations, with the percent changes (95 % confidence intervals [CIs]) of 1.99 % (0.24 %-3.71 %) during W1 and 3.99 % (0.74 %-7.15 %) during W4 for per 10 μg/m3 increases in PM2.5.When PM2.5 exposure levels were equal to 50th percentile (32.6-42.3 μg/m3) or more, monotonically decreased AMH levels and increased risks of low AMH were seen with increasing PM2.5 concentrations during W1 and W4 (P < 0.05). Black carbon (BC), ammonium (NH4+), nitrate (NO3-), and organic matter (OM) during W1, and NH4+, NO3-, as well as sulfate (SO42-) during W4 were significantly associated with decreased AMH. Moreover, PM2.5 and SO42- exposures during W4 were positively associated with low AMH. Additionally, the associations were stronger among women aged <35 years, lived in urban regions, or measured AMH in cold-season (P for interaction <0.05).

CONCLUSION

PM2.5 and specific chemical components (particularly NH4+, NO3-, and SO42-) exposure during the secondary to antral follicle stage and 1-year before measurement were associated with diminished ovarian reserve (DOR), indicating the adverse impact of PM2.5 and its constituent exposures on female reproductive potential.

Ambient air pollution and infant health: a narrative review

The extensive evidence regarding the effects of ambient air pollution on child health is well documented, but limited review summarized their health effects during infancy. Symptoms or health conditions attributed to ambient air pollution in infancy could result in the progression of severe diseases during childhood. Here, we reviewed previous empirical epidemiological studies and/or reviews for evaluating the linkages between ambient air pollution and various infant outcomes including adverse birth outcomes, infant morbidity and mortality, early respiratory health, early allergic symptoms, early neurodevelopment, early infant growth and other relevant outcomes. Patterns of the associations varied by different pollutants (i.e., particles and gaseous pollutants), exposure periods (i.e., pregnancy and postpartum) and exposure lengths (i.e., long-term and short-term). Protection of infant health requires that paediatricians, researchers, and policy makers understand to what extent infants are affected by ambient air pollution, and a call for action is still necessary to reduce ambient air pollution.