Association between ambient particulate matter concentration and fetal growth restriction stratified by maternal employment

Meta-analysis of fine particulate matter exposure during pregnancy and birth weight: Exploring sources of heterogeneity

BACKGROUND

Several meta-analyses assessed the relationship between exposure to PM with aerodynamic diameter ≤ 2.5 μm (PM2.5) during pregnancy and birth weight (BW), but results were inconsistent and substantial unexplained heterogeneity was reported. We aimed to investigate the above association and to explore sources of heterogeneity across studies.

METHODS

We systematically reviewed the current worldwide evidence examining the association between PM2.5 and BW. The review protocol was registered on the PROSPERO website (CRD42020188996) and followed PRISMA guidelines. We extracted association measures for BW and low birth weight (LBW, BW < 2500 g) from each study to evaluate pooled summary measures and to explore sources of between-study heterogeneity.

FINDINGS

Of the 2677 articles identified, 84 met the inclusion criteria (~42 M births). Our random effects meta-analyses revealed substantial heterogeneity among included studies (I2 = 98.4 % and I2 = 77.7 %, for BW and LBW respectively). For LBW, the heterogeneity decreased (I2 = 59.7 %) after excluding four outlying studies, with a pooled odds ratio 1.07 (95 % confidence interval, CI: 1.05, 1.09) per a 10-μg/m3 increase in mean PM2.5 exposure over the entire pregnancy. Further subgroup analysis revealed geographic heterogeneity with higher association in Europe (1.34, (1.16, 1.55)) compared to Asia (1.06, (1.03, 1.10)) and US (1.07, (1.04, 1.10)).

CONCLUSION

The association between PM2.5 and birth weight varied depending on several factors. The sources of heterogeneity between studies included modifiers such as study region and period. Hence, it is advisable not to pool summary measures of PM2.5-BW associations and that policy would be informed by local evidence.

Health effects of exposure to urban ambient particulate matter: A spatial-statistical study on 3rd-trimester pregnant women

Pregnant women are highly vulnerable to environmental stressors such as ambient particulate matter (PM). Particularly during their 3rd trimester, their bodies undergo significant oxidative stresses. To further consolidate this dialogue into practice, the current study evaluated healthy pregnant women (n = 150 housewives; 18-40 years old; gestation age >36 weeks) from the highly polluted city of Yazd, Iran, from September to November 2021. The aerosol optical depth (AOD) data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) were employed as influencing variables and validated using field-collected PM10 data (r = 0.62, p-value <0.01). The links between blood platelet count, enzymes (SGOT, SGPT, LDH, bilirubin), metabolic products (urea and acid uric) and different combinations of AOD data were assessed using the Generalized Additive Model. The results showed a high temporal variability in AOD (0.94 ± 0.51) but a spatially stable distribution pattern. The mean AOD during the 3rd trimester, followed by that of the three-month peak, were identified as the most significant non-linear predictors, while the mean AOD during the 1st trimester and throughout the entire pregnancy showed no significant associations with any of the biomarkers. Considering the associations found between AOD variables and maternal oxidative stresses, urgent planning is required to improve the urban air quality for sensitive subpopulations.

Gestational exposure to 1-NP induces ferroptosis in placental trophoblasts via CYP1B1/ERK signaling pathway leading to fetal growth restriction

Fetal growth restriction (FGR) is a prevalent complication in obstetrics, yet its exact aetiology remains unknown. Numerous studies suggest that the degradation of the living environment is a significant risk factor for FGR. 1-Nitropyrene (1-NP) is a widespread environmental pollutant as a representative substance of nitro-polycyclic aromatic hydrocarbons. In this study, we revealed that 1-NP induced FGR in fetal mice by constructing 1-NP exposed pregnant mice models. Intriguingly, we found that placental trophoblasts of 1-NP exposed mice exhibited significant ferroptosis, which was similarly detected in placental trophoblasts from human FGR patients. In this regard, we established a 1-NP exposed cell model in vitro using two human trophoblast cell lines, HTR8/SVneo and JEG-3. We found that 1-NP not only impaired the proliferation, migration, invasion and angiogenesis of trophoblasts, but also induced severe cellular ferroptosis. Meanwhile, the ferroptosis inhibitor ferrostatin-1 (Fer-1) effectively rescued 1-NP-induced trophoblast biological function impairment. Mechanistically, we revealed that 1-NP regulated ferroptosis by activating the ERK signaling pathway. Moreover, we innovatively revealed that CYP1B1 was essential for the activation of ERK signaling pathway induced by 1-NP. Overall, our study innovatively identified ferroptosis as a significant contributor to 1-NP induced trophoblastic functional impairment leading to FGR and clarified the specific mechanism by which 1-NP induced ferroptosis via the CYP1B1/ERK signaling pathway. Our study provided novel insights into the aetiology of FGR and revealed new mechanisms of reproductive toxicity of environmental pollutants.

Mother-level random effect in the association between PM2.5 and fetal growth: A population-based pregnancy cohort

BACKGROUND

A growing body of literature reports associations between exposure to particulate matter with diameter ≤2.5 μm (PM_2.5) during pregnancy and birth outcomes. However, findings are inconsistent across studies.

OBJECTIVES

To assess the association between PM_2.5 and birth outcomes of fetal growth in a cohort with high prevalence of siblings by multilevel models accounting for geographical- and mother-level correlations.

METHODS

In Israel, we used Maccabi Healthcare Services data to establish a population-based cohort of 381,265 singleton births reaching 24-42 weeks' gestation and birth weight of 500-5000 g (2004-2015). Daily PM_2.5 predictions from a satellite-based spatiotemporal model were linked to the date of birth and maternal residence. We generated mean PM_2.5 values for the entire pregnancy and for exposure periods during pregnancy. Associations between exposure and birth outcomes were modeled by using multilevel logistic regression with random effects for maternal locality of residence, administrative census area (ACA) and mother.

RESULTS

In fully adjusted models with a mother-level random intercept only, a 10-μg/m³ increase in PM_2.5 over the entire pregnancy was positively associated with term low birth weight (TLBW) (Odds ratio, OR = 1.25, 95% confidence interval, CI: 1.09,1.43) and small for gestational age (SGA) (OR = 1.15, 95% CI: 1.06,1.26). Locality- and ACA-level effects accounted for <0.4% of the variance while mother-level effects explained ∼50% of the variability. Associations varied by exposure period, infants' sex, birth order, and maternal pre-pregnancy BMI.

CONCLUSIONS

Consideration of mother-level variability in a region with high fertility rates provides new insights on the strength of associations between PM_2.5 and birth outcomes.

Impact of limited residential address on health effect analysis of predicted air pollution in a simulation study

BACKGROUND

Recent epidemiological studies of air pollution have adopted spatially-resolved prediction models to estimate air pollution concentrations at people's homes. However, the benefit of these models was limited in many studies that used existing health data relying on incomplete addresses resulting from confidentiality concerns or lack of interest when designed.

OBJECTIVE

This simulation study aimed to understand the impact of incomplete addresses on health effect estimation based on the association between particulate matter with diameter ≤10 µm (PM₁₀) and low birth weight (LBW).

METHODS

We generated true annual average concentrations of PM₁₀ at 46,007 mothers' homes and their LBW status, using the parameters obtained from our data analysis and a previous study in Seoul, Korea. Then, we hypothesized that mothers' address information is limited to the district and compared the properties of their health effect estimates of PM₁₀ with those using complete addresses. We performed this comparison across eight environmental scenarios that represent various spatial distributions of PM₁₀ and nine exposure prediction methods that provide different sets of predicted PM₁₀ concentrations of mothers.

RESULTS

We observed increased bias and root mean square error consistently across all environmental scenarios and prediction methods using incomplete addresses compared to complete addresses. However, the bias related to incomplete addresses decreased when we used population-representative exposures averaged to the district from predicted PM₁₀ at census tract centroids.

SIGNIFICANCE

Our simulation study suggested that individual exposure estimated by prediction approaches and averaged across population-representative points can provide improved accuracy in health effect estimates when complete address data are unavailable.

IMPACT STATEMENT

Our simulation study focused on a common and practical challenge of limited address information in air pollution epidemiology, and investigated its impact on health effect analysis. Cohort studies of air pollution have developed advanced exposure prediction model to allow the estimation of individual-level long-term air pollution concentrations at people's addresses. However, it is common that address information of existing health data is available at the coarse spatial scale such as city, district, and zip code area. Our findings can help understand the possible consequences of limited address information and provide practical guidance in achieving the accuracy in health effect analysis.

Ambient Air Pollution and Kawasaki Disease in Korean Children: A Study of the National Health Insurance Claim Data

Background

Kawasaki disease (KD) is a systemic vasculitis of unknown etiology that primarily affects children under 5 years of age. Some researchers suggested a potential triggering effect of air pollution on KD, but the findings are inconsistent and limited by small sample size. We investigated the association between ambient air pollution and KD among the population of South Korea younger than 5 years using the National Health Insurance claim data between 2007 and 2019.

Methods and Results

We obtained the data regarding particulate matter ≤10 or 2.5 µm in diameter, nitrogen dioxide, sulfur dioxide, carbon monoxide, and ozone from 235 regulatory monitoring stations. Using a time‐stratified case‐crossover design, we performed conditional logistic regression to estimate odds ratios (OR) of KD according to interquartile range increases in each air pollutant concentration on the day of fever onset after adjusting for temperature and relative humidity. We identified 51 486 children treated for KD during the study period. An interquartile range increase (14.67 μg/m³) of particulate matter ≤2.5 µm was positively associated with KD at lag 1 (OR, 1.016; 95% CI, 1.004–1.029). An interquartile range increase (2.79 ppb) of sulfur dioxide concentration was associated with KD at all lag days (OR, 1.018; 95% CI, 1.002–1.034 at lag 0; OR, 1.022; 95% CI, 1.005–1.038 at lag 1; OR, 1.017; 95% CI, 1.001–1.033 at lag 2). Results were qualitatively similar in the second scenario of different fever onset, 2‐pollutant model and sensitivity analyses.

Conclusions

In a KD‐focused national cohort of children, exposure to particulate matter ≤2.5 µm and sulfur dioxide was positively associated with the risk of KD. This finding supports the triggering role of ambient air pollution in the development of KD.

Maternal Secondhand Smoke Exposure Enhances Macrosomia Risk Among Pregnant Women Exposed to PM2.5: A New Interaction of Two Air Pollutants in a Nationwide Cohort

Background: Fine particulate matter (PM_2.5) is one of the most common outdoor air pollutants, and secondhand smoking (SHS) is an important source of inhalable indoor air pollution. Previous studies were controversial and inconsistent about PM_2.5 and SHS air pollutants on neonatal birth weight outcomes, and no studies assessed the potential interactive effects between PM_2.5 and SHS on birth weight outcomes. Purpose: To investigate the interaction between gestational PM_2.5 and SHS air pollution exposure on the risk of macrosomia among pregnant women and examine the modifying effect of SHS exposure on the association of PM_2.5 air pollution and birth weight outcomes during pregnancy. Methods: Research data were derived from the National Free Preconception Health Examination Project (NFPHEP), which lasted 3 years from January 1, 2010, to December 31, 2012. At least 240,000 Chinese women from 220 counties were enrolled in this project. PM_2.5 exposure concentration was obtained using a hindcast model specific for historical PM_2.5 estimation from satellite-retrieved aerosol optic depth. Different interaction models about air pollution exposure on birth weight outcomes were established, according to the adjustment of different confounding factors and different pregnancy stages. The establishment of interaction models was based on multivariable logistic regression, and the main confounding factors were maternal age at delivery and pre-pregnancy body mass index (BMI) of participants. SHS subgroups analysis was conducted to further confirm the results of interaction models. Results: In total, 197,877 participants were included in our study. In the full-adjusted interaction model, maternal exposure to PM_2.5 was associated with an increased risk of macrosomia in whole, the first-, second-, and third trimesters of pregnancy (p < 0.001). The interactive effect was statistically significant between maternal exposure to PM_2.5 and SHS on the risk of macrosomia in the whole (interaction p < 0.050) and the first-trimester pregnancy (interaction p < 0.050), not in the second (interaction p > 0.050) or third trimester (interaction p > 0.050) of pregnancy. The higher frequency of SHS exposure prompted the stronger interaction between the two air pollutants in the whole pregnancy and the first-trimester pregnancy. Conclusions: In the whole and first-trimester pregnancy, maternal exposure to SHS during pregnancy enhanced the risk of macrosomia among pregnant women exposed to PM_2.5 air pollutants, and the interaction became stronger with the higher frequency of SHS exposure.

Environmental air pollution: respiratory effects

Environmental air pollution is a major risk factor for morbidity and mortality worldwide. Environmental air pollution has a direct impact on human health, being responsible for an increase in the incidence of and number of deaths due to cardiopulmonary, neoplastic, and metabolic diseases; it also contributes to global warming and the consequent climate change associated with extreme events and environmental imbalances. In this review, we present articles that show the impact that exposure to different sources and types of air pollutants has on the respiratory system; we present the acute effects-such as increases in symptoms and in the number of emergency room visits, hospitalizations, and deaths-and the chronic effects-such as increases in the incidence of asthma, COPD, and lung cancer, as well as a rapid decline in lung function. The effects of air pollution in more susceptible populations and the effects associated with physical exercise in polluted environments are also presented and discussed. Finally, we present the major studies on the subject conducted in Brazil. Health care and disease prevention services should be aware of this important risk factor in order to counsel more susceptible individuals about protective measures that can facilitate their treatment, as well as promoting the adoption of environmental measures that contribute to the reduction of such emissions.

Spatial heterogeneity in the association between particulate matter air pollution and low birth weight in South Korea

As many studies showed the spatial heterogeneity in the association between particulate matter (PM) air pollution and low birth weight (LBW), few studies focused on the variation of local associations at the national scale and related areal characteristics. This study aimed to explore different approaches to estimating local effects of PM with an aerodynamic diameter ≤10 μm (PM₁₀) on LBW across 235 districts in South Korea, to investigate the spatial pattern of local associations, and to examine the relationship with local socio-demographic and environmental characteristics. LBW was identified in 5,692,650 mothers from birth certificate data for 2001-2013. We estimated individual annual-average concentrations of PM₁₀ at centroids of mothers' residential districts by using a previously-validated prediction model. Then, we estimated district-specific odds ratios of LBW for PM₁₀ using modified geographically weighted logistic regression. Here, we applied four approaches with different neighborhood definitions: the distance-based approach within 20- and 40-km bandwidth and the hybrid approach replacing with adjacent districts for urban districts <100 km². In addition, we compared district-specific socioeconomic indicators and emission estimates across three groups of districts that showed significantly positive, no, and significantly negative associations. Medians of district-specific estimates of four approaches were similar to the global estimate and between each other. However, their variability differed with some unreasonably high estimates when a small distance was applied as the neighborhood definition, although spatial pattern was generally similar among the four. The hybrid approach based on the different neighborhood definition by urban and rural areas provided stable risk estimates. Higher risk districts in rural areas were found in more socioeconomically-deprived areas, whereas urban areas showed higher risk districts when their air pollution emissions were higher. Our approach and findings will help identify high risk areas and enhance understanding of geographic determinants.

Nighttime environmental noise and semen quality: A single fertility center cohort study

With increased population and urban development, there are growing concerns regarding health impacts of environmental noise. We assessed the relationship between nighttime environmental noise and semen quality of men who visited for fertility evaluation. This is a retrospective cohort study of 1,972 male patient who had undertaken semen analysis between 2016-2018 at a single fertility center of Seoul, South Korea. We used environmental noise data of National Noise Information System (NNIS), Korea. Using semiannual nighttime noise measurement closest to the time of semen sampling, individual noise exposures at each patient's geocoded address were estimated with empirical Bayesian kriging method. We explored the association between environmental noise and semen quality indicators (volume, concentration, % of progressive motility, vitality, normal morphology, total motile sperm count, oligozoospermia, asthenozoospermia, and severe teratozoospermia) using multivariable regression and generalized additive models. Estimated exposure to nighttime environmental noise level in the study population was 58.3±2.2 Leq. Prevalence of oligozoospermia, asthenozoospermia, and severe teratozoospermia were 3.3%, 14.0%, and 10.1%. Highest quartile nighttime noise was associated with 3.5 times higher odds of oligozoospermia (95% CI: 1.18, 10.17) compared to lowest quartile. In men whose noise exposure is in 3rd quartile, odds ratio (OR) of severe teratozoospermia was 0.57 (95% CI: 0.33, 0.98). The OR for 4th quartile noise were toward null. In generalized additive model, the risk of oligozoospermia increases when the nighttime noise is 55 Leq dB or higher. Our study adds an evidence of potential impact of environmental noise on semen quality in men living in Seoul. Additional studies with more refined noise measurement will confirm the finding.

Maternal exposure to air pollution and the risk of low birth weight: A meta-analysis of cohort studies

Previous studies have evaluated the relationship between prenatal air pollution exposure and low birth weight, but the results are inconsistent. The purpose of this meta-analysis is to quantitatively analyze the relationship between maternal air pollutant exposure and low birth weight (LBW). PubMed and Web of Science databases were searched to obtain the studies on the relationship between the prenatal exposure of air pollutants and LBW that published as of June 2020. The pooled effects of air pollutant exposure and LBW were calculated using random-effect model (for studies with significant heterogeneity) or fixed-effect model (for studies without significant heterogeneity). Totally, 54 studies were included in this meta-analysis. The pooled effect of PM_2.5, PM₁₀, NO₂, CO, SO₂, and O₃ exposure on LBW were 1.081 (95% CI: 1.043, 1.120), 1.053 (95% CI: 1.030, 1.076), 1.030 (95% CI: 1.008, 1.053), 1.007 (95% CI: 1.001, 1.014), 1.125 (95% CI: 1.017, 1.244), and 1.045 (95% CI: 1.005, 1.086), respectively. NO₂ (per 10 ppb increase) and CO (per 100 ppb increase) exposure in the first trimester were positively correlated with LBW, of which the pooled effect was 1.022 (95% CI: 1.009, 1. 035) and 1.008 (95% CI: 1.004, 1.012), respectively. PM_2.5 (per 10 μg/m³ increase) exposure in the third trimester significantly affected the LBW, of which the pooled effect was 1.053 (95% CI: 1.010, 1.097). In addition, PM₁₀ (per 10 μg/m³ increase) exposure in the second trimester also significantly affected the LBW, with the pooled effect of 1.011 (95% CI: 1.005, 1.017). Prenatal exposure of the major air pollutants during the entire pregnancy could increase the risk of LBW, while the susceptible window of the pollutants varied.