Exposure to ambient PM2.5 during pregnancy and preterm birth in metropolitan areas of the state of Georgia

Impact of Climate Change on Reproductive Health and Pregnancy Outcomes: A Systematic Review

Climate change has emerged as a significant global health challenge, with growing evidence linking environmental factors to adverse reproductive health outcomes. The primary objective of this review is to assess the effects of climate change-driven environmental factors, such as air pollution and temperature extremes, on reproductive health outcomes, including fertility rates, miscarriage, preterm birth, and congenital anomalies. A comprehensive search of PubMed, Google Scholar, and Web of Science was conducted until July 2024. Studies included in the review were observational, experimental, and randomized controlled trials that reported quantitative data on reproductive outcomes in relation to climate-related environmental exposures. A total of 49 studies were selected for qualitative synthesis. The review found that increased exposure to particulate matter (PM2.5), extreme temperatures, and proximity to traffic were consistently associated with reduced fertility, increased risks of miscarriage, preterm birth, and low birth weight. Adverse effects were particularly pronounced among vulnerable populations, such as pregnant women of lower socioeconomic status and those living in disaster-prone areas. The studies also highlighted potential transgenerational effects, with prenatal exposure to environmental stressors influencing the long-term health of offspring. The findings underscore the urgent need for public health interventions and policies to mitigate environmental exposures that negatively impact reproductive health. Future research should focus on longitudinal and interventional studies to establish causal relationships and inform effective public health strategies.

Predicting ambient PM2.5 concentrations via time series models in Anhui Province, China

Due to rapid expansion in the global economy and industrialization, PM2.5 (particles smaller than 2.5 µm in aerodynamic diameter) pollution has become a key environmental issue. The public health and social development directly affected by high PM2.5 levels. In this paper, ambient PM2.5 concentrations along with meteorological data are forecasted using time series models, including random forest (RF), prophet forecasting model (PFM), and autoregressive integrated moving average (ARIMA) in Anhui province, China. The results indicate that the RF model outperformed the PFM and ARIMA in the prediction of PM2.5 concentrations, with cross-validation coefficients of determination R2, RMSE, and MAE values of 0.83, 10.39 µg/m3, and 6.83 µg/m3, respectively. PFM achieved the average results (R2 = 0.71, RMSE = 13.90 µg/m3, and MAE = 9.05 µg/m3), while the predicted results by ARIMA are comparatively poorer (R2 = 0.64, RMSE = 15.85 µg/m3, and MAE = 10.59 µg/m3) than RF and PFM. These findings reveal that the RF model is the most effective method for predicting PM2.5 and can be applied to other regions for new findings.

Structural racism, air pollution and the association with adverse birth outcomes in the United States: the value of examining intergenerational associations

Structurally racist policies and practices of the past are likely to be a driving factor in current day differences in exposure to air pollution and may contribute to observed racial and ethnic disparities in adverse birth outcomes in the United States (U.S.). Non-Hispanic Black women in the U.S. experience poorer health outcomes during pregnancy and throughout the life course compared to non-Hispanic White women. This disparity holds even among non-Hispanic Black women with higher socioeconomic status. Reasons for this finding remain unclear, but long-term environmental exposure, either historical exposure or both historical and ongoing exposure, may contribute. Structural racism likely contributes to differences in social and environmental exposures by race in the U.S. context, and these differences can affect health and wellbeing across multiple generations. In this paper, we briefly review current knowledge and recommendations on the study of race and structural racism in environmental epidemiology, specifically focused on air pollution. We describe a conceptual framework and opportunities to use existing historical data from multiple sources to evaluate multi-generational influences of air pollution and structurally racist policies on birth and other relevant health outcomes. Increased analysis of this kind of data is critical for our understanding of structural racism's impact on multiple factors, including environmental exposures and adverse health outcomes, and identifying how past policies can have enduring legacies in shaping health and well-being in the present day. The intended purpose of this manuscript is to provide an overview of the widespread reach of structural racism, its potential association with health disparities and a comprehensive approach in environmental health research that may be required to study and address these problems in the U.S. The collaborative and methodological approaches we highlight have the potential to identify modifiable factors that can lead to effective interventions for health equity.

A preliminary analysis of global neonatal disorders burden attributable to PM2.5 from 1990 to 2019

BACKGROUND

Prenatal fine particulate matter (PM_2.5) exposure is related to various neonatal diseases (ND). However, data and studies assessing the neonatal disease burden caused by PM_2.5 at the global level are limited, especially comparing countries with various socioeconomic development levels. We, therefore, assessed three-decades spatiotemporal changes in neonatal disease burden from 1990 at a national level, combined with the socio-demographic index (SDI).

METHODS

We extracted statistics from the Global Burden of Disease Study database for this retrospective study, and analyzed differences in the age-standardized mortality rate (ASMR) of ND and five sub-causes related to PM_2.5 by gender, nationality, and SDI. To describe the trend of ASMR, the Joinpoint model was adopted to predict the annual percentage change (APC) and the average annual percentage changes (AAPCs). We executed the Gaussian process regression model to predict the relevance between SDI and ASMR.

RESULTS

The ND burden associated with PM_2.5 kept rising since 1990, especially in low-middle SDI regions, South Asia, and Sub-Saharan Africa, and the sex ratio of ASMR was >1 at the global level and all five SDI regions. The leading cause of death was neonatal preterm birth. The global ASMR level of ND was 2.09 per 100,000 population in 2019 and AAPCs was 0.91 (98 % CI: 0.28, 1.55) meanwhile AAPCs decreased with rising SDI levels. The decreasing trend of ASMR in ND was detected in regions with higher SDI, such as North America, Europe, and Australasia.

CONCLUSIONS

In the past three decades, the global burden of ND related to PM_2.5 has ascended considerably in lower SDI regions hence PM_2.5 is still considered a notable environmental hazard factor for newborn diseases.

Systematic review of climate change effects on reproductive health

Climate change is a major risk factor for overall health, including reproductive health, and well-being. Increasing temperatures, due mostly to increased greenhouse gases trapping excess heat in the atmosphere, result in erratic weather patterns, wildfires, displacement of large communities, and stagnant water resulting in vector-borne diseases that, together, have set the stage for new and devastating health threats across the globe. These conditions disproportionately affect disadvantaged and vulnerable populations, including women, pregnant persons, young children, the elderly, and the disabled. This review reports on the evidence for the adverse impacts of air pollution, wildfires, heat stress, floods, toxic chemicals, and vector-borne diseases on male and female fertility, the developing fetus, and obstetric outcomes. Reproductive health care providers are uniquely positioned and have an unprecedented opportunity to educate patients and policy makers about mitigating the impact of climate change to assure reproductive health in this and future generations.

Ambient fine particulate matter air pollution and the risk of preterm birth: A multicenter birth cohort study in China

Preterm birth (PTB), defined as live birth before the 37th week of gestation, is believed to have profound impacts on the infant's health in later life. Air pollution has been suggested to be a potential risk factor of PTB, but the evidence was inconsistent. In this multicenter birth cohort study, we aimed to examine the association between fine particulate matter (PM_2.5) exposure during pregnancy and PTB in China. A total of 5976 live births were identified between Jan. 2009 and Feb. 2011 from 8 provinces in China. Residential exposures to PM_2.5 were assigned based on satellite remote sensing estimates. Cox proportional hazards regressions were employed to explore the correlation for each trimester as well as the entire pregnancy. A total of 443 (7.4%) preterm births were observed. The average PM_2.5 during pregnancy was 57.2 ± 8.8 μg/m³. We found exposure to PM_2.5 during the whole pregnancy (hazard ratio, HR = 1.262; 95% CI: 1.087-1.465) and in the first trimester (HR = 1.114; 95% CI: 1.007-1.232) was associated with higher risk of PTB. The associations of PM_2.5 were stronger for subjects with older maternal or paternal age, lower maternal pre-pregnancy BMI, and lower family income. This study adds supports to the cumulating evidence linking PM_2.5 exposure and elevated PTB risk. Measures of air pollution reduction are needed during pregnancy, especially at early stage of pregnancy to prevent adverse birth outcomes.

Long-term impact of ambient air pollution on preterm birth in Xuzhou, China: a time series study

Accumulating evidence witnesses the negative influence of air pollution on human health, but the relationship between air pollution and premature babies has been inconsistent. In this study, the association between weekly average concentration of air pollutants and preterm birth (PTB) was conducted in Xuzhou, a heavy industry city, in China. We constructed a distributed lag non-linear model (DLNM), an ecological study, to access the associations between ambient air pollutants and PTB in this study. Totally, 5408 premature babies were included, and the weekly average levels of PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO were 61.24, 110.21, 22.55, 40.55, 104.45, and 1.04 mg/m³, respectively. We found that PM_2.5, PM₁₀, SO₂, and NO₂ significantly increased the risk of PTB, and the susceptibility windows of these contaminants were the second trimester and third trimester (from 12 to 29 weeks). Every 10 μg/m³ increase of PM_2.5, PM₁₀, SO₂, and NO₂, the greatest relative risk (RR) values and 95% confidence interval (CI) on PTB were 1.0075 [95% CI, 1.0019-1.0131], 1.0053 [95% CI, 1.0014-1.0092], 1.0203 [95% CI, 1.0030-1.0379], and 1.0170 [95% CI, 1.0052-1.0289] in lag 16th, 18th, 19th, and 20th gestational weeks, respectively. No significant influence of O₃ and CO were found on preterm birth. Subgroup analysis showed that the risk of premature delivery was higher for younger pregnant women and in warm season. This finding shows that prenatal exposure to ambient air pollutants is associated with preterm birth, and there existed an exposure window period.

Commuter PM exposure and estimated life-expectancy loss across multiple transportation modes in Xi'an, China

Commuters are reportedly exposed to severe traffic-related air pollution (TRAP) during their commuting trips. This study was designed and implemented to (1) compare particulate matter (PM) exposure across four common transportation modes; (2) examine and analyze various determining factors; and (3) estimate public health effects caused by commuting exposure to PM. All analyses and calculations were based on the experimental data collected from 13 volunteers, including heart-rate data on 336 commuting trips in four travel modes in Xi'an China. The results indicate highest PM exposure associated with cycling (average PM₁₀, PM_2.5 and PM_1.0 of 114.35, 72.37 and 56.51 μg/m³, respectively), followed by riding transit buses (116.29, 67.60 and 51.12 μg/m³ for the same pollutants, respectively), then taking a taxi (97.61, 58.87 and 45.11 μg/m³), and the lowest exposure onboard subways (55.86, 46.20 and 40.20 μg/m³). A multivariable linear regression model was used to examine major influences on PM concentration variations, with results corroborating significant PM variance across commuting modes, which is also affected by background pollution concentration and relative humidity. Further, years of life expectancy (YLE) loss were estimated using an inhalation dose model together with the life table method: cycling commuters experienced the greatest YLE loss (5.51-6.43 months per capita for the studied age group). During severe pollution periods, substituting other modes (like subway) for cycling could effectively avoid acute exposure. PM_2.5 levels in taxi cabins powered by CNG or methanol were comparatively lower, indicating that implementing alternative energy strategies could effectively lower traffic emissions and population exposure.

In Utero Exposure to Fine Particles Decreases Early Birth Weight of Rat Offspring and TLR4/NF-κB Expression in Lungs

Particulate matter (PM2.5) exposure is reported to have deleterious effects on health. Maternal PM2.5 exposure has been confirmed to damage the growth of somatic cells and enhance the incidence of chronic respiratory diseases in children. Here we aim to investigate the impact of in utero PM2.5 exposure on early birth weight and postnatal lung development. Pregnant Sprague-Dawley rats were administered PM2.5 (0.1, 0.5, 2.5, or 7.5 mg/kg) intraperitoneally every 3 days until birth. Maternal and birth outcomes and somatic growth were monitored. Lungs were collected on PND1 (where PND = postnatal day) and PND28; the lung wet-to-dry weight ratio (W/D) was analyzed, and reactive oxygen species (ROS) levels were measured. Expression of Toll-like receptor 4 (TLR4) and NF-κB were evaluated by Western blotting and quantitative RT-PCR. There were no significant intergroup differences for maternal outcomes; however, offspring exposed in utero to 2.5 and 7.5 mg/kg PM2.5 were significantly smaller in litter weight than the controls. In utero exposure to 2.5 and 7.5 mg/kg PM2.5 led to lower body weight after birth and disrupted lung development during infancy. ROS levels were significantly increased in the 7.5 mg/kg PM2.5 group. PM2.5-treated rats showed upregulated pulmonary expression of TLR4 and NF-κB. Maternal PM2.5 exposure enhances the risk of low birth weight and affects lung alveolar development. The underlying molecular mechanisms may involve TLR4/NF-κB signaling.

Source-related components of fine particulate matter and risk of adverse birth outcomes in Northern Italy

BACKGROUND/AIM

The aim of the present study was to assess the association between PM_2.5, its sources, and preterm birth (PTB), low birth weight (LBW), and small for gestational age (SGA) in a large open residential cohort (Supersito Project in the Emilia-Romagna Region - Northern Italy).

METHODS

We collected 2012-2014 pregnancy and childbirth data from Birth Assistance Certificates and selected the pregnancies of interest. PTBs (gestational age < 37 weeks), LBW (weight < 2500 g), and SGA (newborns weighing ≤ 10th age and pregnancy week-specific percentile) were considered. Three-year measurements of daily concentrations and constituents of PM_2.5 were available at four sites and were analyzed through a source apportionment approach identifying 6 sources (traffic, biomass burning, oil combustion, anthropogenic mix, and two secondary factors). Exposure to PM_2.5 and sources was calculated at address level. Using logistic regression models, associations between exposure and outcomes were derived, applying single-pollutant and two-pollutant models, to verify the independent effect of each source.

RESULTS

The study included 23,708 neonates born to 23,415 women, among whom 1,311 PTB, 424 LBW, and 1,354 SGA occurred. PTB was the only outcome associated with PM_2.5 mass (OR 1.03, 95% CI 1.002-1.058 per 1 μg/m³). Traffic, oil combustion and secondary sulfates and organics showed independent effects on PTB. Exposure to secondary nitrates was associated with a lower risk of PTB. There was no association between LBW or SGA and source-specific PM_2.5 components or the residual PM_2.5 related to all other sources.

CONCLUSION

This study found an association between PTB and PM_2.5. Traffic, secondary sulfates, and organic and oil combustion were the sources with most consistent association.

Maternal PM2.5 exposure triggers preterm birth: a cross-sectional study in Wuhan, China

Background

Most of the studies regarding air pollution and preterm birth (PTB) in highly polluted areas have estimated the exposure level based on fixed-site monitoring. However, exposure assessment methods relying on monitors have the potential to cause exposure misclassification due to a lack of spatial variation. In this study, we utilized a land use regression (LUR) model to assess individual exposure, and explored the association between PM_2.5 exposure during each time window and the risk of preterm birth in Wuhan city, China.

Methods

Information on 2101 singleton births, which were ≥ 20 weeks of gestation and born between November 1, 2013 and May 31, 2014; between January 1, 2015 and August 31, 2015, was obtained from the Obstetrics Department in one 3A hospital in Wuhan. Air quality index (AQI) data were accessed from the Wuhan Environmental Protection Bureau website. Individual exposure during pregnancy was assessed by LUR models and Kriging interpolation. Logistic regression analyses were conducted to determine the association between women exposure to PM_2.5 and the risk of different subtypes of PTB.

Results

During the study period, the average individual exposure concentration of PM_2.5 during the entire pregnancy was 84.54 μg/m³. A 10 μg/m³ increase of PM_2.5 exposure in the first trimester (OR: 1.169; 95% CI: 1.077, 1.262), the second trimester (OR: 1.056; 95% CI: 1.015, 1.097), the third trimester (OR: 1.052; 95% CI: 1.002, 1.101), and the entire pregnancy (OR: 1.263; 95% CI: 1.158, 1.368) was significantly associated with an increased risk of PTB. For the PTB subgroup, the hazard of PM_2.5 exposure during pregnancy was stronger for very preterm births (VPTB) than moderate preterm births (MPTB). The first trimester was the most susceptible exposure window. Moreover, women who had less than 9 years of education or who conceived during the cold season tended to be more susceptible to the PM_2.5 exposure during pregnancy.

Conclusions

Maternal exposure to PM_2.5 increased the risk of PTB, and this risk was stronger for VPTB than for MPTB, especially during the first trimester.

Acute Effects of Exposure to Ambient Air Pollutants on Preterm Birth in Xiamen City (2015-2018), China

Backgrounds: Urban energy consumption is one of the important causes of air pollution. The epidemiological risk assessment guided by air pollution is of great significance to the promotion of urban environmental protection. Objectives: The work researched the acute impact of exposure to air pollution on preterm birth (PTB) in Xiamen city from 2015 to 2018. Furthermore, the economic losses were assessed as well. Methods: Association of air pollution and PTB with economic losses were assessed using the generalized additive model. Results: A total of 1991 PTB visits, who are inhabitant in Xiamen, have been investigated. An interquartile range (IQR) (10 μg/m³) increase of PM₁₀, NO₂, and SO₂ in the current day corresponded to the increase of 0.64% [95% CI: -1.22, 2.54%], 0.52% [95% CI: -5.21, 6.61%], and 2.33% [95% CI: -6.41, 11.58%] in daily PTB visits. Especially, PTB visits were significantly related with PM₁₀ and NO₂ in Lag 1 and NO₂ and SO₂ in Lag 2. Furthermore, for multipollutants, an IQR increase in PM_2.5, O₃, and CO, after adjustment with SO₂, was related with 5.04% [95% CI: -5.90, 17.24], 2.49% [95% CI: -6.07, 11.81], and 7.10% [95% CI: -2.79, 18.00] increase of PTB morbidity, respectively. The estimates of the number of excess PTBs attributed to typical pollutants PM₁₀ and SO₂ were ∼2400 and 1200 people, respectively, every year. The highest excess PTBs was estimated to occur as a result of PM₁₀ and SO₂ effects. Conclusions: Although Xiamen has a relatively low level of air pollution, short-term exposure to NO₂, SO₂, and PM₁₀ was linked to the increase of PTB visits.

Short-term PM2.5 forecasting based on CEEMD-RF in five cities of China

The development of industrial civilization has greatly enriched the material and spiritual life of human beings, but it is accompanied by the intensification of the consumption of earth resources and environmental pollution. The smog that has emerged in various parts of China in recent years is a typical problem, which not only endangers human health but also affects normal human work and life. It is difficult to control smog in a short time productively, so people need to understand the rule of smog formation gradually, and effectively predict the PM2.5 index to help people continuously analyze relevant mechanisms and timely protect-related hazards. This paper proposes a hybrid model that uses the Complementary Ensemble Empirical Modal Decomposition algorithm to mine the information in the original PM2.5 sequence and then predicts the pertinent random forests. The trend of PM2.5 concentration during the decomposition process is effectively reflected, and the decomposition sequence is modeled by the high tolerance of the random forest to the noise data and the good fitting ability. In the modeling process, the parameters are optimized according to the evaluation function of the model on the verification set, and eventually, the prediction sequences are superimposed to obtain the final predicted PM2.5 concentration value. The validity of the model is verified by the data of several Chinese cities with different geographical features in the past 5 years. The results show that the recommendation model is higher than other comparison models in terms of model stability and prediction accuracy.

Maternal exposure to benzene and toluene and preterm birth. A longitudinal study

BACKGROUND

Exposure to air pollutants has several effects on human health, including during pregnancy.

OBJECTIVE

To identify whether exposure to benzene and toluene among pregnant women contributes to preterm delivery.

DESIGN AND SETTING

Longitudinal study using data on newborns from mothers living in São José dos Campos (SP) in 2016, who had been exposed to benzene and toluene.

METHODS

A logistic regression model with three hierarchical levels was constructed using maternal variables relating to newborns, and using benzene and toluene concentrations in quartiles. Occurrences of cesarean births, twins or malformations were excluded. Maternal exposure windows of 5, 10, 15, 30, 60 and 90 days prior to delivery were considered.

RESULTS

Out of the 9,562 live births, 3,671 newborns were included and 343 newborns were born at less than 37 weeks of gestation (9.3%). The average birth weight was 3,167.2 g. Exposure to benzene and toluene was significantly associated (P = 0.04) with preterm delivery in the five-day window. There was no association in any of the other exposure windows.

CONCLUSIONS

It was possible to identify that maternal exposure to benzene and toluene has an acute effect on preterm delivery.