Estimation of exposure to atmospheric pollutants during pregnancy integrating space-time activity and indoor air levels: Does it make a difference?

Long-term exposure to air pollution and risk of insulin resistance: A systematic review and meta-analysis

OBJECTIVE

The effects of air pollution on metabolism have become a popular research topic, and a large number of studies had confirmed that air pollution exposure could induce insulin resistance (IR) to varying degrees, but the results were inconsistent, especially for the long-term exposures. The aim of the current study was to further investigate the potential effects of air pollution on IR.

METHODS

A systematic review and meta-analysis of four electronic databases, including PubMed, Embase, Web of Science and Cochrane were conducted, searching for relevant studies published before June 10, 2023, in order to explore the potential relationships between long-term exposure to air pollution and IR. A total of 10 studies were included for data analysis, including seven cohort studies and three cross-sectional studies. Four major components of air pollution, including PM2.5 (particulate matter with an aerodynamic diameter of 2.5 µm or less), PM10 (particulate matter with an aerodynamic diameter of 10 µm or less), NO2, and SO2 were selected, and each analyzed for the potential impacts on insulin resistance, in the form of adjusted percentage changes in the homeostasis assessment model of insulin resistance (HOMA-IR).

RESULTS

This systematic review and meta-analysis showed that for every 1 μg/m³ increase in the concentration of selected air pollutants, PM2.5 induced a 0.40% change in HOMA-IR (95%CI: -0.03, 0.84; I2 =67.4%, p = 0.009), while PM10 induced a 1.61% change (95%CI: 0.243, 2.968; I2 =49.1%, p = 0.001). Meanwhile, the change in HOMA-IR due to increased NO2 or SO2 exposure concentration was only 0.09% (95%CI: -0.01, 0.19; I2 =83.2%, p = 0.002) or 0.01% (95%CI: -0.04, 0.06; I2 =0.0%, p = 0.638), respectively.

CONCLUSIONS

Long-term exposures to PM2.5, PM10, NO2 or SO2 are indeed associated with the odds of IR. Among the analyzed pollutants, inhalable particulate matters appear to exert greater impacts on IR.

Systematic review of best practices for GPS data usage, processing, and linkage in health, exposure science and environmental context research

Global Positioning System (GPS) technology is increasingly used in health research to capture individual mobility and contextual and environmental exposures. However, the tools, techniques and decisions for using GPS data vary from study to study, making comparisons and reproducibility challenging.

OBJECTIVES

The objectives of this systematic review were to (1) identify best practices for GPS data collection and processing; (2) quantify reporting of best practices in published studies; and (3) discuss examples found in reviewed manuscripts that future researchers may employ for reporting GPS data usage, processing and linkage of GPS data in health studies.

DESIGN

A systematic review.

DATA SOURCES

Electronic databases searched (24 October 2023) were PubMed, Scopus and Web of Science (PROSPERO ID: CRD42022322166).

ELIGIBILITY CRITERIA

Included peer-reviewed studies published in English met at least one of the criteria: (1) protocols involving GPS for exposure/context and human health research purposes and containing empirical data; (2) linkage of GPS data to other data intended for research on contextual influences on health; (3) associations between GPS-measured mobility or exposures and health; (4) derived variable methods using GPS data in health research; or (5) comparison of GPS tracking with other methods (eg, travel diary).

DATA EXTRACTION AND SYNTHESIS

We examined 157 manuscripts for reporting of best practices including wear time, sampling frequency, data validity, noise/signal loss and data linkage to assess risk of bias.

RESULTS

We found that 6% of the studies did not disclose the GPS device model used, only 12.1% reported the per cent of GPS data lost by signal loss, only 15.7% reported the per cent of GPS data considered to be noise and only 68.2% reported the inclusion criteria for their data.

CONCLUSIONS

Our recommendations for reporting on GPS usage, processing and linkage may be transferrable to other geospatial devices, with the hope of promoting transparency and reproducibility in this research.

PROSPERO REGISTRATION NUMBER

CRD42022322166.

The methodology of quantitative risk assessment studies

Once an external factor has been deemed likely to influence human health and a dose response function is available, an assessment of its health impact or that of policies aimed at influencing this and possibly other factors in a specific population can be obtained through a quantitative risk assessment, or health impact assessment (HIA) study. The health impact is usually expressed as a number of disease cases or disability-adjusted life-years (DALYs) attributable to or expected from the exposure or policy. We review the methodology of quantitative risk assessment studies based on human data. The main steps of such studies include definition of counterfactual scenarios related to the exposure or policy, exposure(s) assessment, quantification of risks (usually relying on literature-based dose response functions), possibly economic assessment, followed by uncertainty analyses. We discuss issues and make recommendations relative to the accuracy and geographic scale at which factors are assessed, which can strongly influence the study results. If several factors are considered simultaneously, then correlation, mutual influences and possibly synergy between them should be taken into account. Gaps or issues in the methodology of quantitative risk assessment studies include 1) proposing a formal approach to the quantitative handling of the level of evidence regarding each exposure-health pair (essential to consider emerging factors); 2) contrasting risk assessment based on human dose-response functions with that relying on toxicological data; 3) clarification of terminology of health impact assessment and human-based risk assessment studies, which are actually very similar, and 4) other technical issues related to the simultaneous consideration of several factors, in particular when they are causally linked.

PM2.5 constituents associated with childhood obesity and larger BMI growth trajectory: A 14-year longitudinal study

BACKGROUND

The association of specific PM2.5 chemical constituents with childhood overweight or obesity (OWOB) remain unclear. Furthermore, the long-term impacts of PM2.5 exposure on the trajectory of children's body mass index (BMI) have not been explored.

METHODS

We conducted a longitudinal study among 1,450,830 Chinese children aged 6-19 years from Beijing and Zhongshan in China during 2005-2018 to examine the associations of PM2.5 and its chemical constituents with incident OWOB risk. We extracted PM2.5 mass and five main component exposure from Tracking Air Pollution in China (TAP) dataset. Cox proportional hazards models were applied to quantify exposure-response associations. We further performed principal component analysis (PCA) to handle the multi-collinearity and used quantile g-computation (QGC) approach to analyze the impacts of exposure mixtures. Additionally, we selected 125,863 children with at least 8 physical examination measurements and combined group-based trajectory models (GBTM) with multinomial logistic regression models to explore the impacts of exposure to PM2.5 mass and five constituents on BMI and BMI Z-score trajectories during 6-19 years.

RESULTS

We observed each interquartile range increment in PM2.5 exposure was significantly associated with a 5.1 % increase in the risk of incident OWOB (95 % confidence Interval [CI]: 1.036-1.066). We also found black carbon, sulfate, organic matter, often linked to fossil combustion, had comparable or larger estimates of the effect (HR = 1.139-1.153) than PM2.5. Furthermore, Exposure to PM2.5 mass, sulfate, nitrate, ammonium, organic matter and black carbon was significantly associated with an increased odds of being in a larger BMI trajectory and being assigned to persistent OWOB trajectory.

CONCLUSIONS

Our findings provide evidence that the constituents mainly from fossil fuel combustion may have a perceptible influence on increased OWOB risk associated with PM2.5 exposure in China. Moreover, long-term exposure to PM2.5 contributes to an increased odds of being in a lager BMI and a persistent OWOB trajectories.

Extreme Temperature Exposure and Risks of Preterm Birth Subtypes Based on a Nationwide Survey in China

BACKGROUND

Previous studies have reported that ambient temperature may affect perinatal outcomes. However, whether extreme temperature affects the risk of preterm birth (PTB) remains controversial. Studies on the associations of extreme temperature with PTB subtypes are lacking.

OBJECTIVES

We aimed to investigate the associations of extreme climate events with the risks of PTB and its subtypes, discerning possible modifiers.

METHODS

Data on all singleton deliveries were obtained from the China Labor and Delivery Survey (CLDS), a nationwide investigation implemented in 2015 and 2016. PTB was defined as gestational weeks < 37 and then categorized as early (24-34 wk) and late PTBs (35-36 wk), and clinical subtypes [spontaneous PTB, preterm premature rupture of the fetal membranes (PPROM), iatrogenic PTB]. Ambient temperature data were provided by the China National Weather Data Sharing System. Five heat indexes and five cold indexes were used to define heat waves and cold spells. Generalized linear mixed models with a random term by hospital unit were used to assess the associations of short-term prenatal extreme temperature exposure. The Cox proportional hazard regression model was applied to assess the nonlinear associations of low- or high-temperature exposure at the whole and different trimesters of pregnancy with the risk of PTB. Stratified analyses were conducted to assess the possible modification by geographic region and fetal sex.

RESULTS

A total of 70,818 singleton births from 96 hospitals in China were included, among which 4,965 (7.01%) were PTBs. Exposure to extreme cold events 1 wk before delivery was associated with an increased PTB risk, with an adjusted odds ratio (aOR) [95% confidence intervals (CIs)] of 1.07 (95% CI: 1.04, 1.10) and 1.06 (1.04, 1.09) for the total days when the daily average temperature below the fifth percentile (fifth-days) and the 10th percentile (10th-days), 1.18 (1.04, 1.34) for the cold spells when the daily average temperature below the fifth percentile for two consecutive days (fifth-2D), 1.09 (1.03, 1.16) and 1.12 (1.06, 1.19) for the cold spells when the daily average temperature below the 10th percentile for three and two consecutive days (10th-3D and 10th-2D), respectively. Results of extreme temperature exposure during 2 weeks before delivery showed similarly significant associations. The association between cold spells and PTB tended to be stronger for late PTB than for early PTB. Cold spells were mainly associated with spontaneous PTB and late PPROM. A stratified analysis indicated that pregnant women in western and northern regions tended to be more sensitive to cold spells, and pregnant women with a female fetus appeared to be at a higher risk of PTB when exposed to cold spells. Pregnant women in late pregnancy were more susceptible to extreme temperatures. No significant or stable association was found between heat waves and preterm birth.

DISCUSSION

Exposure to cold spells was associated with an increased risk of PTB, especially late, spontaneous PTB and PPROM. The associations appeared to be more pronounced in the north and west regions and in pregnancies with female fetuses. https://doi.org/10.1289/EHP10831.

Pre-natal exposure to NO2 and PM2.5 and newborn lung function: An approach based on repeated personal exposure measurements

CONTEXT

While strong evidence supports adverse effects of pre-natal air pollution on child's lung function, previous studies rarely considered fine particulate matter (PM_2.5) or the potential role of offspring sex and no study examined the effects of pre-natal PM_2.5 on the lung function of the newborn.

AIM

We examined overall and sex-specific associations of personal pre-natal exposure to PM_2.5 and nitrogen (NO₂) with newborn lung function measurements.

METHODS

This study relied on 391 mother-child pairs from the French SEPAGES cohort. PM_2.5 and NO₂ exposure was estimated by the average concentration of pollutants measured by sensors carried by the pregnant women during repeated periods of one week. Lung function was assessed with tidal breathing analysis (TBFVL) and nitrogen multiple breath washout (N₂MBW) test, performed at 7 weeks. Associations between pre-natal exposure to air pollutants and lung function indicators were estimated by linear regression models adjusted for potential confounders, and then stratified by sex.

RESULTS

Mean exposure to NO₂ and PM_2.5 during pregnancy was 20.2 μg/m³ and 14.3 μg/m³, respectively. A 10 μg/m³ increase in PM_2.5 maternal personal exposure during pregnancy was associated with an adjusted 2.5 ml (2.3%) decrease in the functional residual capacity of the newborn (p-value = 0.11). In females, functional residual capacity was decreased by 5.2 ml (5.0%) (p = 0.02) and tidal volume by 1.6 ml (p = 0.08) for each 10 μg/m³ increase in PM_2.5. No association was found between maternal NO₂ exposure and newborns lung function.

CONCLUSIONS

Personal pre-natal PM_2.5 exposure was associated with lower lung volumes in female newborns, but not in males. Our results provide evidence that pulmonary effects of air pollution exposure can be initiated in utero. These findings have long term implications for respiratory health and may provide insights into the underlying mechanisms of PM_2.5 effects.

Organophosphate Flame Retardants in Pregnant Women: Sources, Occurrence, and Potential Risks to Pregnancy Outcomes

Organophosphate flame retardants (OPFRs) are found in various environmental matrixes and human samples. Exposure to OPFRs during gestation may interfere with pregnancy, for example, inducing maternal oxidative stress and maternal hypertension during pregnancy, interfering maternal and fetal thyroid hormone secretion and fetal neurodevelopment, and causing fetal metabolic abnormalities. However, the consequences of OPFR exposure on pregnant women, impact on mother-to-child transmission of OPFRs, and harmful effects on fetal and pregnancy outcomes have not been evaluated. This review describes the exposure to OPFRs in pregnant women worldwide, based on metabolites of OPFRs (mOPs) in urine for prenatal exposure and OPFRs in breast milk for postnatal exposure. Predictors of maternal exposure to OPFRs and variability of mOPs in urine have been discussed. Mother-to-child transmission pathways of OPFRs have been scrutinized, considering the levels of OPFRs and their metabolites in amniotic fluid, placenta, deciduae, chorionic villi, and cord blood. The results showed that bis(1,3-dichloro-2-propyl) phosphate (BDCIPP) and diphenyl phosphate (DPHP) were the two predominant mOPs in urine, with detection frequencies of >90%. The estimated daily intake (EDI_M) indicates low risk when infants are exposed to OPFRs from breast milk. Furthermore, higher exposure levels of OPFRs in pregnant women may increase the risk of adverse pregnancy outcomes and influence the developmental behavior of infants. This review summarizes the knowledge gaps of OPFRs in pregnant women and highlights the crucial steps for assessing health risks in susceptible populations, such as pregnant women and fetuses.

Cellular mechanisms linking to outdoor and indoor air pollution damage during pregnancy

Pregnancies are a critical window period for environmental influences over the mother and the offspring. There is a growing body of evidence associating indoor and outdoor air pollution exposure to adverse pregnancy outcomes such as preterm birth and hypertensive disorders of pregnancy. Particulate matter (PM) could trigger oxi-inflammation and could also reach the placenta leading to placental damage with fetal consequences. The combination of strategies such as risk assessment, advise about risks of environmental exposures to pregnant women, together with nutritional strategies and digital solutions to monitor air quality can be effective in mitigating the effects of air pollution during pregnancy.

Prenatal Exposure to PM2.5 Oxidative Potential and Lung Function in Infants and Preschool- Age Children: A Prospective Study

BACKGROUND

Fine particulate matter (PM 2.5 ) has been found to be detrimental to respiratory health of children, but few studies have examined the effects of prenatal PM 2.5 oxidative potential (OP) on lung function in infants and preschool children.

OBJECTIVES

We estimated the associations of personal exposure to PM 2.5 and OP during pregnancy on offspring objective lung function parameters and compared the strengths of associations between both exposure metrics.

METHODS

We used data from 356 mother-child pairs from the SEPAGES cohort. PM filters collected twice during a week were analyzed for OP, using the dithiothreitol (DTT) and the ascorbic acid (AA) assays, quantifying the exposure of each pregnant woman. Lung function was assessed with tidal breathing analysis (TBFVL) and nitrogen multiple-breath washout (N 2 MBW ) test, performed at 6 wk, and airwave oscillometry (AOS) performed at 3 y. Associations of prenatal PM 2.5 mass and OP with lung function parameters were estimated using multiple linear regressions.

RESULTS

In neonates, an interquartile (IQR) increase in OP v DTT (0.89  nmol / min / m 3 ) was associated with a decrease in functional residual capacity (FRC) measured by N 2 MBW [β = - 2.26 mL ; 95% confidence interval (CI): - 4.68 , 0.15]. Associations with PM 2.5 showed similar patterns in comparison with OP v DTT but of smaller magnitude. Lung clearance index (LCI) and TBFVL parameters did not show any clear association with the exposures considered. At 3 y, increased frequency-dependent resistance of the lungs (Rrs 7 - 19 ) from AOS tended to be associated with higher OP v DTT (β = 0.09  hPa × s / L ; 95% CI: - 0.06 , 0.24) and OP v AA (IQR = 1.14  nmol / min / m 3 ; β = 0.12  hPa × s / L ; 95% CI: - 0.04 , 0.27) but not with PM 2.5 (IQR = 6.9   μ g / m 3 ; β = 0.02  hPa × s / L ; 95% CI: - 0.13 , 0.16). Results for FRC and Rrs 7 - 19 remained similar in OP models adjusted on PM 2.5 .

DISCUSSION

Prenatal exposure to OP v DTT was associated with several offspring lung function parameters over time, all related to lung volumes. https://doi.org/10.1289/EHP11155.

Time series of transcriptome analysis in entire lung development stages provide insights into the origin of NO2 related lung diseases

Lung growth is a critical window, when exposure to various pollutants can disturb the finely-tuned lung development and enhance risk of long-term structural and functional sequelae of lung. In this study, pregnant C57/6 mice were treated with NO2, and lungs of fetus/offspring were collected at different developmental windows and dynamic lung development was determined. The results showed that maternal NO2 exposure suppressed fetal weight, implying that fetal development can be disturbed. The time-series RNA-seq analysis of lungs showed that maternal NO2 exposure induced significant time-dependent changes in the expression profiles of genes associated with lung vein myocardium development in fetus/offspring. Most of these genes in NO2 exposure group were suppressed at middle gestation and at birth. Our results also indicated that the gene expressions of Nkx2.5 in NO2 exposure were suppressed to 0.27- and 0.44-fold of the corresponding Air group at E13.5 and PND1, and restored at later time points. This indicated that the transcription factor Nkx2.5 played an important role in abnormal lung development in fetus/offspring caused by maternal NO2 exposure. Importantly, gene expressions of lung vein myocardium development were related to transcription factors (TFs) and lung functions, and TFs showed similar trends with lung function. These results provide a comprehensive view of the adverse effects of maternal NO2 exposure on fetal lung development by uncovering molecular targets and related signaling pathways at the transcriptional level.

Early pregnancy PM2.5 exposure and its inorganic constituents affect fetal growth by interrupting maternal thyroid function

Early pregnancy is crucial for fetal growth. Maternal thyroid hormone is critical for fetal growth and can be disturbed under exogenous exposure. However, it's uncertain whether exposure to PM_2.5 and inorganic constituents during early pregnancy can affect TH and fetal growth. We focused on the associations of early-pregnancy PM_2.5 and inorganic constituents with fetal growth and maternal THs. PM_2.5 concentration was estimated using a satellite-based spatiotemporal model. Fetal biparietal diameter (BPD), head circumference (HC), femur length (FL), and humerus length (HL) were measured by ultrasonography at median 15.6, 22.2, and 33.1 gestational weeks. Levels of 28 PM_2.5 constituents were measured in a sub-group of 329 pregnancies. Maternal serum free thyroxine (fT4), free triiodothyronine, and thyroid-stimulating hormone levels were measured at 14 weeks of gestation. Mixed-effect models and multiple linear regression were applied to evaluate the associations of PM_2.5 and its constituents with fetal growth measures. Mediation analysis was used to examine the mediating role of the THs. Results showed that each 10 μg/m³ increase in PM_2.5 was associated with 0.20 mm reductions in BPD (95%CI: 0.33, -0.01), 0.27 mm decreases in FL (95%CI: 0.40, -0.13), and 0.36 decreases in HL (95%CI: 0.49, -0.23). Per 10 μg/m³ increment in PM_2.5 was correlated with 5.82% decreases in the fT4 level (95% CI: 8.61%, -2.96%). FT4 accounted for 14.3% of PM_2.5 exposure-induced change in BPD at first follow-up. Al (β = -2.91, 95%CI: 5.17, -0.66), Si (β = -1.20, 95%CI: 2.22, -0.19), K (β = -3.09, 95%CI: 5.41, -0.77), Mn (β = -47.20, 95%CI: 83.68, -10.79) and Zn (β = -3.02, 95%CI: 5.55, -0.49) were associated with decreased fetal BPD, especially in first follow-up. Zn (β = -38.12%, 95% CI: 58.52%, -8.61%) was also associated with decreased fT4 levels. Overall, early pregnancy exposure to PM_2.5 and its constituents was associated with fetal growth restriction and decreased maternal fT4 levels might mediate the effect of PM_2.5.

Time-activity and daily mobility patterns during pregnancy and early postpartum - evidence from the MADRES cohort

INTRODUCTION

Pregnant women's daily time-activity and mobility patterns determine their environmental exposures and subsequently related health effects. Most studies ignore these and assess pregnancy exposures using static residential measures.

METHODS

We conducted 4-day continuous geo-location monitoring in 62 pregnant Hispanic women, during pregnancy and early post-partum then derived trips by mode and stays, classified by context (indoor/outdoor, type). Generalized mixed-effect models were used to examine whether these patterns changed over time.

RESULTS

Women spent on average 17.3 h/day at home. Commercial and service locations were the most popular non-home destinations, while parks and open spaces were seldom visited. Women made 3.5 daily trips (63.7 min/day and approximately 25% were pedestrian-based). Women were less likely to visit commercial and services locations and make vehicle-based trips postpartum compared to the 3^rd trimester.

CONCLUSION

Our findings suggest time-activity patterns vary across pregnancy and postpartum, thus assessing exposures at stationary locations might introduce measurement error.

Effects of household environmental exposure and ventilation in association with adverse birth outcomes: A prospective cohort study in rural China

Prenatal exposure to outdoor air pollution have been associated with birth outcomes. However, there is limited evidence on the adverse effects of household indoor air pollution worldwide, much less in rural areas of China. This study aimed to explore the associations of household environmental factors (primary cooking fuel, housing renovation, and home ventilation) with four adverse birth outcomes (preterm birth (PTB), small for gestational age (SGA), low birth weight (LBW), and term low birth weight (T-LBW)). We conducted a cohort study involving 10,324 pregnancies in women who delivered a live-born infant from 2015 to 2018 in Guangxi, China. Risk ratios and 95% confidence intervals (CI) were estimated with control for reproductive history, lifestyle, home environmental confounders, and other potential confounders. A total of 5.4% of the infants were PTB, 10.7% were SGA, 5.5% had LBW, and 3.0% had T-LBW. Household-use induction cookers as the primary cooking fuel during pregnancy was associated with SGA (RR = 1.31, 95% CI: 1.07-1.60), LBW (1.41, 1.09-1.82), and T-LBW(1.62, 1.16-2.26), as compared with household-use gas as the primary cooking fuel. Housing renovation within one year before pregnancy was associated with PTB (1.45, 1.06-1.98) and LBW (1.56, 1.17-2.09), while housing renovation during pregnancy was associated with a higher risk of SGA only in moderate home ventilation conditions (3.74, 1.69-8.28). Our findings suggested that household-use induction cookers as the primary cooking fuel increased the risks of SGA, LBW, and T-LBW. In addition, housing renovation within one year before pregnancy increased the risks of PTB and LBW. Proper home ventilation may reduce the effect on the association between housing renovation during pregnancy and SGA.

Vitamin D intake modifies the association of household air pollution exposure with maternal disorders of pregnancy

To date, only three studies have investigated the association of household air pollution (HAP) exposure with pregnancy disorders. The ameliorating role of diet and nutrition in the association has never been explored. We conducted a cross-sectional study among 799 mothers who had recently given singleton birth in the Cape Coast Metropolis, Ghana. Structured questionnaire and semi-quantitative food frequency questionnaire were used to assess HAP exposure (from use of biomass fuels for cooking and garbage burning at home) and vitamin D (vitD) intake, respectively. Multivariable binary logistic regression was used to investigate the association between HAP exposure and pregnancy disorders. HAP exposure due to cooking with biomass fuels and garbage burning at home was associated with two fold (AOR = 2.15; 95% confidence interval [CI]: 1.05, 4.43) and six fold (AOR = 6.35; 95% CI: 2.43, 16.58) increased odds of hypertensive disorders of pregnancy (HDP). For gestational diabetes (GDM), the increased odds were two folds for both exposures but the 95% CI included the null value. Stove stacking was also associated with two folds increased odds of GDM (AOR = 1.83; 95% CI: 0.91, 3.68). In stratified analysis, the odds of HDP and GDM associated with biomass fuels use decreased with increasing vitD intake. All the interaction p values were, however, greater than 0.05. We provide the first evidence on the ameliorating role of vitD intake on the effect of HAP exposure on pregnancy disorders. In LMICs where solid fuel use and garbage burning at home is widespread, health workers should advise mothers during antenatal care visits to increase intake of vitamin D rich foods.

Acute ambient air pollution exposure and placental Doppler results in the NICHD fetal growth studies - Singleton cohort

BACKGROUND

Increased placental vascular resistance is a proposed mechanism by which air pollution exposure during pregnancy lowers birth weight and increases pregnancy-induced hypertensive disorders.

OBJECTIVE

To examine the impact of acute air pollution exposure during pregnancy on uterine and umbilical artery Doppler indicators of placental vascular resistance.

METHODS

After a first ultrasound to confirm gestational age, 2562 pregnant women recruited in 12 clinics throughout the United States underwent up to five standardized ultrasounds with Doppler measurements. Exposures to 11 air pollutants were estimated for the hour of ultrasound and each of the 2 h prior to ultrasound at the clinics using the National Air Quality Forecast Capability reanalysis products. We used mixed logistic regression to study the longitudinal odds ratio (OR) of any, uni- or bi-lateral systolic and diastolic uterine artery notching compared to no notching and the longitudinal OR of abnormal end diastolic flow of the umbilical artery compared to forward flow. Uterine and umbilical artery resistance indexes were studied using linear mixed models.

RESULTS

Each inter-quartile range (IQR) increase of particulate matter < 2.5 μm, nitrate, ammonium, primary organic matter (POM) and nitrogen dioxide during the hour of ultrasound was associated with a decreased risk of unilateral systolic notch and with increased resistance index of the left uterine artery. For the umbilical artery, each IQR increase in ozone was associated with decreased resistance index (b: -0.26, 95 % CI: -0.52, -0.01) and with a decreased risk of abnormal end diastolic flow (OR: 0.36, 95 % CI: 0.14, 0.94); while each IQR increase of elemental carbon and POM was associated with increased risk of abnormal end diastolic flow (OR: 1.47, 95 % CI: 1.02, 2.13 and OR: 1.67, 95 % CI: 1.17, 2.39, respectively).

DISCUSSION

Our results suggest acute air pollution exposure may influence placental vascular resistance.

Maternal Ambient Exposure to Atmospheric Pollutants during Pregnancy and Offspring Term Birth Weight in the Nationwide ELFE Cohort

Background: Studies have reported associations between maternal exposure to atmospheric pollution and lower birth weight. However, the evidence is not consistent and uncertainties remain. We used advanced statistical approaches to robustly estimate the association of atmospheric pollutant exposure during specific pregnancy time windows with term birth weight (TBW) in a nationwide study. Methods: Among 13,334 women from the French Longitudinal Study of Children (ELFE) cohort, exposures to PM_2.5, PM₁₀ (particles < 2.5 µm and <10 µm) and NO₂ (nitrogen dioxide) were estimated using a fine spatio-temporal exposure model. We used inverse probability scores and doubly robust methods in generalized additive models accounting for spatial autocorrelation to study the association of such exposures with TBW. Results: First trimester exposures were associated with an increased TBW. Second trimester exposures were associated with a decreased TBW by 17.1 g (95% CI, −26.8, −7.3) and by 18.0 g (−26.6, −9.4) for each 5 µg/m³ increase in PM_2.5 and PM₁₀, respectively, and by 15.9 g (−27.6, −4.2) for each 10 µg/m³ increase in NO₂. Third trimester exposures (truncated at 37 gestational weeks) were associated with a decreased TBW by 48.1 g (−58.1, −38.0) for PM_2.5, 38.1 g (−46.7, −29.6) for PM₁₀ and 14.7 g (−25.3, −4.0) for NO₂. Effects of pollutants on TBW were larger in rural areas. Conclusions: Our results support an adverse effect of air pollutant exposure on TBW. We highlighted a larger effect of air pollutants on TBW among women living in rural areas compared to women living in urban areas.

The association of prenatal exposure to particulate matter with infant growth: A birth cohort study in Beijing, China

Limited studies examined the associations of prenatal exposure to particulate matter (PM) and children's growth with inconsistent results, and no study focused on PM₁. We matched a birth cohort (10,547 children) with daily PM₁ and PM_2.5 concentrations by maternal home addresses. Air pollution concentrations were predicted by satellite remote sensing data, meteorological factors, and land use information. The weight and length of children in the birth cohort were measured at approximately one year old. We calculated the Z-score of weight for length (WFL) and body mass index (BMI) and then defined overweight and obesity (OWOB) based on WHO Standards. Generalized linear regression and modified Poisson regression were used to identify the association of prenatal exposure to PM₁ or PM_2.5 with anthropometric measurements and risk of OWOB. We also determined the mediation effect of preterm birth on the associations. Results showed that a 10 μg/m³ increase in prenatal exposure to PM₁ and PM_2.5 was significantly associated with a 0.105 [95% confidence interval (CI): 0.067, 0.144] and 0.063 (95% CI: 0.029, 0.097) increase in WFL Z-score for one-year-old children. Similar associations were found for BMI Z-score. A 10 μg/m³ increase in prenatal PM₁ and PM_2.5 exposure was significantly associated with 1.012 (95%CI: 1.003, 1.021) and 1.010 (95%CI: 1.002, 1.018) times higher risk of OWOB. . Preterm birth mediated 7.5% [direct effect (DE) = 0.106, P < 0.001; indirect effect (IE) = 0.009, P < 0.001)] and 9.9% (DE = 0.064, P < 0.001; IE = 0.007, P < 0.001) of the association between prenatal PM₁ and PM_2.5 exposure and WFL Z-score of the children. The association of prenatal PM₁ and PM_2.5 exposure with BMI Z-score of children was also mediated by preterm birth by 6.6% (DE = 0.111, P < 0.001; IE = 0.008, P < 0.001) and 9.1% (DE = 0.064, P < 0.001; IE = 0.006, P < 0.001). These results remained robust in the sensitivity analyses. In conclusion, prenatal exposure to PM₁ and PM_2.5 increased WFL, BMI Z-scores and higher risk of OWOB for one-year-old children. The associations were partially mediated by preterm birth. These findings call for the urgent action on air pollution regulation to protect early-life health among children.

Joint effects of ethnic enclave residence and ambient volatile organic compounds exposure on risk of gestational diabetes mellitus among Asian/Pacific Islander women in the United States

BACKGROUND

Asian/Pacific Islander (API) communities in the United States often reside in metropolitan areas with distinct social and environmental attributes. Residence in an ethnic enclave, a socially distinct area, is associated with lower gestational diabetes mellitus (GDM) risk, yet exposure to high levels of air pollution, including volatile organic compounds (VOCS), is associated with increased GDM risk. We examined the joint effects of ethnic enclaves and VOCs to better understand GDM risk among API women, the group with the highest prevalence of GDM.

METHODS

We examined 9069 API births in the Consortium on Safe Labor (19 hospitals, 2002-2008). API ethnic enclaves were defined as areas ≥66th percentile for percent API residents, dissimilarity (geographic dispersal of API and White residents), and isolation (degree that API individuals interact with another API individual). High levels of 14 volatile organic compounds (VOC) were defined as ≥75th percentile. Four joint categories were created for each VOC: Low VOC/Enclave (reference group), Low VOC/No Enclave, High VOC/Enclave, High VOC/No Enclave. GDM was reported in medical records. Hierarchical logistic regression estimated odds ratios (OR) and 95% confidence intervals (95%CI) between joint exposures and GDM, adjusted for maternal factors and area-level poverty. Risk was estimated for 3-months preconception and first trimester exposures.

RESULTS

Enclave residence was associated with lower GDM risk regardless of VOC exposure. Preconception benzene exposure was associated with increased risk when women resided outside enclaves [High VOC/No Enclave (OR:3.45, 95%CI:1.77,6.72)], and the effect was somewhat mitigated within enclaves, [High VOC/Enclave (OR:2.07, 95%:1.09,3.94)]. Risks were similar for 12 of 14 VOCs during preconception and 10 of 14 during the first trimester.

CONCLUSIONS

API residence in non-enclave areas is associated with higher GDM risk, regardless of VOC level. Ethnic enclave residence may mitigate effects of VOC exposure, perhaps due to lower stress levels. The potential benefit of ethnic enclaves warrants further study.

The Impact of Individual Mobility on Long-Term Exposure to Ambient PM2.5: Assessing Effect Modification by Travel Patterns and Spatial Variability of PM2.5

The impact of individuals' mobility on the degree of error in estimates of exposure to ambient PM2.5 concentrations is increasingly reported in the literature. However, the degree to which accounting for mobility reduces error likely varies as a function of two related factors-individuals' routine travel patterns and the local variations of air pollution fields. We investigated whether individuals' routine travel patterns moderate the impact of mobility on individual long-term exposure assessment. Here, we have used real-world time-activity data collected from 2013 participants in Erie/Niagara counties, New York, USA, matched with daily PM2.5 predictions obtained from two spatial exposure models. We further examined the role of the spatiotemporal representation of ambient PM2.5 as a second moderator in the relationship between an individual's mobility and the exposure measurement error using a random effect model. We found that the effect of mobility on the long-term exposure estimates was significant, but that this effect was modified by individuals' routine travel patterns. Further, this effect modification was pronounced when the local variations of ambient PM2.5 concentrations were captured from multiple sources of air pollution data ('a multi-sourced exposure model'). In contrast, the mobility effect and its modification were not detected when ambient PM2.5 concentration was estimated solely from sparse monitoring data ('a single-sourced exposure model'). This study showed that there was a significant association between individuals' mobility and the long-term exposure measurement error. However, the effect could be modified by individuals' routine travel patterns and the error-prone representation of spatiotemporal variability of PM2.5.

An Empirical Validation of the Within-subject Biospecimens Pooling Approach to Minimize Exposure Misclassification in Biomarker-based Studies

BACKGROUND

Within-subject biospecimens pooling can theoretically reduce bias in dose-response functions from biomarker-based studies when exposure assessment suffers from classical-type error. However, collecting many urine voids each day is cumbersome. We evaluated the empirical validity of a within-subject pooling approach and compared several options to avoid sampling each void.

METHODS

In 16 pregnant women who collected a spot of each urine void over several nonconsecutive weeks, we compared concentrations of 10 phenols in daily, weekly, and pregnancy within-subject pools. We pooled either three or all daily samples. In a simulation study using these data, we quantified bias in dose-response functions when using one to 20 urine samples per subject to assess methylparaben (a compound with moderate within-subject variability) and bisphenol A (high variability) exposures.

RESULTS

Correlations between exposure estimates from pools of all and of only three voids per day were above 0.80 for all time windows and compounds, except for benzophenone-3 and triclosan in the daily time window (correlations, 0.57-0.68). With one spot sample to assess pregnancy exposure, correlations were all below 0.74. Using only one biospecimen led to attenuation bias in the dose-response functions of 29% (methylparaben) and 69% (bisphenol A); four samples for methylparaben and 18 for bisphenol A decreased bias to 10%.

CONCLUSIONS

For nonpersistent chemicals, collecting and pooling three samples per day instead of all daily samples efficiently estimates exposures over a week or more. Collecting around 20 biospecimens can strongly limit attenuation bias for nonpersistent chemicals such as bisphenol A.

Methodological Considerations for Epidemiological Studies of Air Pollution and the SARS and COVID-19 Coronavirus Outbreaks

BACKGROUND

Studies have reported that ambient air pollution is associated with an increased risk of developing or dying from coronavirus-2 (COVID-19). Methodological approaches to investigate the health impacts of air pollution on epidemics should differ from those used for chronic diseases, but the methods used in these studies have not been appraised critically.

OBJECTIVES

Our study aimed to identify and critique the methodological approaches of studies of air pollution on infections and mortality due to COVID-19 and to identify and critique the methodological approaches of similar studies concerning severe acute respiratory syndrome (SARS).

METHODS

Published and unpublished papers of associations between air pollution and developing or dying from COVID-19 or SARS that were reported as of 10 May 2020 were identified through electronic databases, internet searches, and other sources.

RESULTS

All six COVID-19 studies and two of three SARS studies reported positive associations. Two were time series studies that estimated associations between daily changes in air pollution, one was a cohort that assessed associations between air pollution and the secondary spread of SARS, and six were ecological studies that used area-wide exposures and outcomes. Common shortcomings included possible cross-level bias in ecological studies, underreporting of health outcomes, using grouped data, the lack of highly spatially resolved air pollution measures, inadequate control for confounding and evaluation of effect modification, not accounting for regional variations in the timing of outbreaks' temporal changes in at-risk populations, and not accounting for nonindependence of outcomes.

DISCUSSION

Studies of air pollution and novel coronaviruses have relied mainly on ecological measures of exposures and outcomes and are susceptible to important sources of bias. Although longitudinal studies with individual-level data may be imperfect, they are needed to adequately address this topic. The complexities involved in these types of studies underscore the need for careful design and for peer review. https://doi.org/10.1289/EHP7411.

Derivation of Time-Activity Data Using Wearable Cameras and Measures of Personal Inhalation Exposure among Workers at an Informal Electronic-Waste Recovery Site in Ghana

OBJECTIVES

Approximately 2 billion workers globally are employed in informal settings, which are characterized by substantial risk from hazardous exposures and varying job tasks and schedules. Existing methods for identifying occupational hazards must be adapted for unregulated and challenging work environments. We designed and applied a method for objectively deriving time-activity patterns from wearable camera data and matched images with continuous measurements of personal inhalation exposure to size-specific particulate matter (PM) among workers at an informal electronic-waste (e-waste) recovery site.

METHODS

One hundred and forty-two workers at the Agbogbloshie e-waste site in Accra, Ghana, wore sampling backpacks equipped with wearable cameras and real-time particle monitors during a total of 171 shifts. Self-reported recall of time-activity (30-min resolution) was collected during the end of shift interviews. Images (N = 35,588) and simultaneously measured PM2.5 were collected each minute and processed to identify activities established through worker interviews, observation, and existing literature. Descriptive statistics were generated for activity types, frequencies, and associated PM2.5 exposures. A kappa statistic measured agreement between self-reported and image-based time-activity data.

RESULTS

Based on image-based time-activity patterns, workers primarily dismantled, sorted/loaded, burned, and transported e-waste materials for metal recovery with high variability in activity duration. Image-based and self-reported time-activity data had poor agreement (kappa = 0.17). Most measured exposures (90%) exceeded the World Health Organization (WHO) 24-h ambient PM2.5 target of 25 µg m-3. The average on-site PM2.5 was 81 µg m-3 (SD: 94). PM2.5 levels were highest during burning, sorting/loading and dismantling (203, 89, 83 µg m-3, respectively). PM2.5 exposure during long periods of non-work-related activities also exceeded the WHO standard in 88% of measured data.

CONCLUSIONS

In complex, informal work environments, wearable cameras can improve occupational exposure assessments and, in conjunction with monitoring equipment, identify activities associated with high exposures to workplace hazards by providing high-resolution time-activity data.

Air Pollution Exposure Monitoring among Pregnant Women with and without Asthma

Background: We monitored exposure to fine particulates (PM_2.5), ozone, nitrogen dioxide (NO₂), and ambient temperature for pregnant women with and without asthma. Methods: Women (n = 40) from the Breathe—Well-Being, Environment, Lifestyle, and Lung Function Study (2015–2018) were enrolled during pregnancy and monitored for 2–4 days. Daily pollutants were measured using personal air monitors, indoor air monitors, and nearest Environmental Protection Agency’s stationary monitors based on GPS tracking and home address. Results: Personal-monitor measurements of PM_2.5, ozone, and NO₂ did not vary by asthma status but exposure profiles significantly differed by assessment methods. EPA stationary monitor-based methods appeared to underestimate PM_2.5 and temperature exposure and overestimate ozone and NO₂ exposure. Higher indoor-monitored PM_2.5 exposures were associated with smoking and the use of gas appliances. The proportion of waking-time during which personal monitors were worn was ~56%. Lower compliance was associated with exercise, smoking, being around a smoker, and the use of a prescription drug. Conclusions: Exposure did not vary by asthma status but was influenced by daily activities and assessment methods. Personal monitors may better capture exposures but non-compliance merits attention. Meanwhile, larger monitoring studies are warranted to further understand exposure profiles and the health effects of air pollution during pregnancy.

Use of personal care products during pregnancy in relation to urinary concentrations of select phenols: A longitudinal analysis from the SEPAGES feasibility study

BACKGROUND

Exposure to certain synthetic phenols is of growing concern, in particular among pregnant women, because of their endocrine disrupting nature. Many phenols are still authorized in personal care products (PCP). We aimed to assess if use of PCPs, by pregnant women could influence their urinary concentrations of synthetic phenols.

METHODS

We used a panel design with intense urine sample collection. Eight women completed a diary with exact time and use of PCPs in three weeks. We measured the concentrations of phenols (four parabens, bisphenol A and S, two dichlorophenols, triclosan, and benzophenone-3) in 178 urine samples, collected during 7 consecutive days at 3 time points during pregnancy. We characterized PCP use as the total number of PCP applications or as a single PCP use (yes/no) in three time windows (0-6, 6 to 12 and 12 to 24h before each urine sample collection). We used adjusted linear and Tobit regressions to assess associations between PCP use and phenol urinary concentrations.

RESULTS

The total number of PCP applications was positively associated with ethylparaben, propylparaben and butylparaben concentrations. We observed a peak in urinary concentration of ethylparaben, butylparaben and propylparaben at 2.86, 2.55 and 2.67 h since last PCP use, respectively and twelve different types of PCPs were positively associated with at least one of these parabens. The bisphenol S concentration increased by 12.4% (95%CI: confidence interval: 5.9; 19.3) for each additional PCP application in the 12 to 24 time window and use of specific PCPs such as anti-stretchmarks cream, facial cleanser and shower gel. Associations varied by time window.

CONCLUSION

Our study showed that PCP use was associated with a short-term increase in the urinary concentration of ethylparaben, butylparaben and propylparaben, but not methylparaben. This study also reported a positive association between the use of PCPs and the bisphenol S concentration, a finding that warrants further investigation in cohorts with repeated collection of urine samples and detailed information on PCP use.

PM2.5 and NO2 exposure errors using proxy measures, including derived personal exposure from outdoor sources: A systematic review and meta-analysis

BACKGROUND

The use of proxy exposure estimates for PM_2.5 and NO₂ in air pollution studies instead of personal exposures, introduces measurement error, which can produce biased epidemiological effect estimates. Most studies consider total personal exposure as the gold standard. However, when studying the effects of ambient air pollution, personal exposure from outdoor sources is the exposure of interest.

OBJECTIVES

We assessed the magnitude and variability of exposure measurement error by conducting a systematic review of the differences between personal exposures from outdoor sources and the corresponding measurements for ambient concentrations in order to increase understanding of the measurement error structures of the pollutants.

DATA SOURCES AND ELIGIBILITY CRITERIA

We reviewed the literature (ISI Web of Science, Medline, 2000-2016) for English language studies (in any age group in any location (NO₂) or Europe and North America (PM_2.5)) that reported repeated measurements over time both for personal and ambient PM_2.5 or NO₂ concentrations. Only a few studies reported personal exposure from outdoor sources. We also collected data for infiltration factors and time-activity patterns of the individuals in order to estimate personal exposures from outdoor sources in every study.

STUDY APPRAISAL AND SYNTHESIS METHODS

Studies using modelled rather than monitored exposures were excluded. Type of personal exposure monitor was assessed. Random effects meta-analysis was conducted to quantify exposure error as the mean difference between "true" and proxy measures.

RESULTS

Thirty-two papers for PM_2.5 and 24 for NO₂ were identified. Outdoor sources were found to contribute 44% (range: 33-55%) of total personal exposure to PM_2.5 and 74% (range: 57-88%) to NO₂. Overall estimates of personal exposure (24-hour averages) from outdoor sources were 9.3 μg/m³ and 12.0 ppb for PM_2.5 and NO₂ respectively, while the corresponding difference between these exposures and the ambient concentrations (i.e. the measurement error) was 5.72 μg/m³ and 7.17 ppb. Our findings indicated also higher error variability for NO₂ than PM_2.5. Large heterogeneity was observed which was not explained sufficiently by geographical location or age group of the study sample.

LIMITATIONS, CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS

Relying only on information available in published studies led to some limitations: the contribution of outdoor sources to total personal exposure for NO₂ had to be inferred, individual variation in exposure misclassification was unavailable and instrument error could not be addressed. The larger magnitude and variability of errors for NO₂ compared with PM_2.5 has implications for biases in the health effect estimates of multi-pollutant epidemiological models. Results suggest that further research is needed regarding personal exposure studies and measurement error bias in epidemiological models.

Estimating exposure to fine particulate matter emissions from vehicle traffic: Exposure misclassification and daily activity patterns in a large, sprawling region

Vehicle traffic is responsible for a significant portion of toxic air pollution in urban areas that has been linked to a wide range of adverse health outcomes. Most vehicle air quality analyses used for transportation planning and health effect studies estimate exposure from the measured or modeled concentration of an air pollutant at a person's home. This study evaluates exposure to fine particulate matter from vehicle traffic and the magnitude and cause of exposure misclassification that result from not accounting for population mobility during the day in a large, sprawling region. We develop a dynamic exposure model by integrating activity-based travel demand, vehicle emission, and air dispersion models to evaluate the magnitude, components and spatial patterns of vehicle exposure misclassification in the Atlanta, Georgia metropolitan area. Overall, we find that population exposure estimates increase by 51% when population mobility is accounted for. Errors are much larger in suburban and rural areas where exposure is underestimated while exposure may be overestimated near high volume roadways and in the urban core. Exposure while at work and traveling account for much of the error. We find much larger errors than prior studies, all of which have focused on more compact urban regions. Since many people spend a large part of their day away from their homes and vehicle emissions are known to create "hotspots" along roadways, home-based exposure is unlikely to be a robust estimator of a person's actual exposure. Accounting for population mobility in vehicle emission exposure studies may reveal more effective mitigation strategies, important differences in exposure between population groups with different travel patterns, and reduce exposure misclassification in health studies.

Can atmospheric pollutants influence menstrual cycle function?

A few experimental studies suggest that atmospheric pollutants could affect the endocrine system, and in particular stress hormones and the hypothalamic-hypophyseal-ovarian axis, which could in turn influence menstrual cycle function. We aimed to study the possible short-term effects of atmospheric pollutants on the length of the follicular and luteal phases and on the duration of the menstrual cycle in humans. To do so, from a nation-wide study on couples' fecundity, we recruited 184 women not using contraception who collected urine samples at least every other day during one menstrual cycle, from which a progesterone metabolite was assayed, allowing estimation of the duration of the follicular and luteal phases of the cycle. Atmospheric pollution (nitrogen dioxide and particulate matter with an aerodynamical diameter below 10 μm, PM₁₀) levels were estimated from a dispersion model with a 1-km resolution combined with permanent monitoring stations measurements, allowing to estimate exposures in the 30-day, 1-10 and 11-30-day periods before the start of the menstrual cycle. Regression models allowed to quantify the change in cycle duration associated with atmospheric pollutants and adjusted for potential confounders. Follicular phase duration increased on average by 0.7 day (95% confidence interval, CI, 0.2; 1.3) for each increase by 10 μg/m³ in NO₂ concentration averaged over the 30 days before the cycle and by 1.6 day (95% CI, 0.3; 2.9) for each increase by 10 μg/m³ in PM₁₀. There was no strong evidence of associations of exposures in this time window with luteal phase or with total menstrual cycle durations (p > 0.2). Exposures in the 1-10 day period before the cycle start were also associated with increased follicular phase duration. This study is one of the first prospective studies to suggest short-term alterations in follicular phase duration following atmospheric pollutants exposure.

Deciphering the Impact of Early-Life Exposures to Highly Variable Environmental Factors on Foetal and Child Health: Design of SEPAGES Couple-Child Cohort

In humans, studies based on Developmental Origins of Health and Disease (DOHaD) concept and targeting short half-lived chemicals, including many endocrine disruptors, generally assessed exposures from spot biospecimens. Effects of early-life exposure to atmospheric pollutants were reported, based on outdoor air pollution levels. For both exposure families, exposure misclassification is expected from these designs: for non-persistent chemicals, because a spot biospecimen is unlikely to capture exposure over windows longer than a few days; for air pollutants, because indoor levels are ignored. We developed a couple-child cohort relying on deep phenotyping and extended personal exposure assessment aiming to better characterize the effects of components of the exposome, including air pollutants and non-persistent endocrine disruptors, on child health and development. Pregnant women were included in SEPAGES couple-child cohort (Grenoble area) from 2014 to 2017. Maternal and children exposure to air pollutants was repeatedly assessed by personal monitors. DNA, RNA, serum, plasma, placenta, cord blood, meconium, child and mother stools, living cells, milk, hair and repeated urine samples were collected. A total of 484 pregnant women were recruited, with excellent compliance to the repeated urine sampling protocol (median, 43 urine samples per woman during pregnancy). The main health outcomes are child respiratory health using early objective measures, growth and neurodevelopment. Compared to former studies, the accuracy of assessment of non-persistent exposures is expected to be strongly improved in this new type of birth cohort tailored for the exposome concept, with deep phenotyping and extended exposure characterization. By targeting weaknesses in exposure assessment of the current approaches of cohorts on effects of early life environmental exposures with strong temporal variations, and relying on a rich biobank to provide insight on the underlying biological pathways whereby exposures affect health, this design is expected to provide deeper understanding of the interplay between the Exposome and child development and health.

Time-Varying Exposure to Air Pollution and Outcomes of in Vitro Fertilization among Couples from a Fertility Clinic

BACKGROUND

A few studies suggest that air pollution may decrease fertility, but prospective studies and examinations of windows of susceptibility remain unclear.

OBJECTIVE

We aimed to examine the association between time-varying exposure to nitrogen dioxide ([Formula: see text]), ozone ([Formula: see text]), fine particulate matter [Formula: see text] ([Formula: see text]), and black carbon (BC) on in vitro fertilization (IVF) outcomes.

METHODS

We included 345 women (522 IVF cycles) for the [Formula: see text], [Formula: see text], and [Formula: see text] analyses and 339 women (512 IVF cycles) for the BC analysis enrolled in a prospective cohort at a Boston fertility center (2004–2015). We used validated spatiotemporal models to estimate daily residential exposure to [Formula: see text], [Formula: see text], [Formula: see text], and BC. Multivariable discrete time Cox proportional hazards models with four periods [ovarian stimulation (OS), oocyte retrieval to embryo transfer (ET), ET to implantation, implantation to live birth] estimated odds ratios (OR) and 95% confidence intervals (CI) of failing at IVF. Time-dependent interactions were used to identify vulnerable periods.

RESULTS

An interquartile range (IQR) increase in [Formula: see text], [Formula: see text], and BC throughout the IVF cycle was associated with an elevated odds of failing at IVF prior to live birth ([Formula: see text], 95% CI: 0.95, 1.23 for [Formula: see text]; [Formula: see text], 95% CI: 0.88, 1.28 for [Formula: see text]; and [Formula: see text], 95% CI: 0.96, 1.41 for BC). This relationship significantly varied across the IVF cycle such that the association with higher exposure to air pollution during OS was strongest for early IVF failures. An IQR increase in [Formula: see text], [Formula: see text], and BC exposure during OS was associated with 1.42 (95% CI: 1.20, 1.69), 1.26 (95% CI: 0.96, 1.67), and 1.23 (95% CI: 0.96, 1.59) times the odds of failing prior to oocyte retrieval, and 1.32 (95% CI: 1.13, 1.54), 1.27 (95% CI: 0.98, 1.65), and 1.32 (95% CI: 1.10, 1.59) times the odds of failing prior to ET.

CONCLUSION

Increased exposure to traffic-related pollutants was associated with higher odds of early IVF failure. https://doi.org/10.1289/EHP4601.

Maternal Exposure to Indoor Air Pollution and Birth Outcomes

There is a growing body of research on the association between ambient air pollution and adverse birth outcomes. However, people in high income countries spend most of their time indoors. Pregnant women spend much of that time at home. The aim of this study was to investigate if indoor air pollutants were associated with poor birth outcomes. Pregnant women were recruited prior to 18 weeks gestation. They completed a housing questionnaire and household chemical use survey. Indoor pollutants, formaldehyde (HCHO), nitrogen dioxide (NO2) and volatile organic compounds (VOCs), were monitored in the women's homes at 34 weeks gestation. Gestational age (GA), birth weight (BW) and length (BL) and head circumference (HC) were collected from birth records. The associations between measured pollutants, and pollution surrogates, were analysed using general linear models, controlling for maternal age, parity, maternal health, and season of birth. Only HCHO was associated with any of the birth outcomes. There was a 0.044 decrease in BW z-score (p = 0.033) and 0.05 decrease in HC z-score (p = 0.06) for each unit increase in HCHO. Although HCHO concentrations were very low, this finding is consistent with other studies of formaldehyde and poor birth outcomes.

Ambient air pollution and fetal growth restriction: Physician diagnosis of fetal growth restriction versus population-based small-for-gestational age

BACKGROUND

Ambient air pollution may affect fetal growth restriction (FGR) through several mechanisms. However, prior studies of air pollution and small-for-gestational age (SGA), a common proxy for FGR, have reported inconsistent findings.

OBJECTIVE

We assessed air pollution in relation to physician-diagnosed FGR and population-based SGA in the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Consecutive Pregnancy Study (2002-2010).

METHODS

Among 50,005 women (112,203 singleton births), FGR was captured from medical records and ICD-9 codes, and SGA determined by population standards for birthweight <10th, <5th and <3rd percentile. Community Multiscale Air Quality models estimated ambient levels of seven criteria pollutants for whole pregnancy, 3-months preconception, and 1st, 2nd and 3rd trimesters. Generalized estimating equations with robust standard errors accounted for interdependency of pregnancies within participant. Models adjusted for maternal age, race/ethnicity, pre-pregnancy body mass index, smoking, alcohol, parity, insurance, marital status, asthma and temperature.

RESULTS

FGR was diagnosed in 1.5% of infants, and 6.7% were <10th, 2.7% <5th and 1.5% <3rd percentile for SGA. Positive associations of SO2, NO2 and PM10 and negative associations of O3 with FGR were observed throughout preconception and pregnancy. For example, an interquartile increase in whole pregnancy SO2 was associated with 16% (95% CI 8%, 25%) increased FGR risk, 17% for NO2 (95% CI 9%, 26%) and 12% for PM10 (95% CI 6%, 19%). Associations with SGA were less clear.

CONCLUSIONS

Chronic exposure to air pollution may be associated with FGR but not SGA in this low-risk population.

Ambient Volatile Organic Compounds and Racial/Ethnic Disparities in Gestational Diabetes Mellitus: Are Asian/Pacific Islander Women at Greater Risk?

US Asian/Pacific Islander (API) communities experience high air pollution levels. APIs may be predisposed to pancreatic β-cell dysfunction and have the highest prevalence of gestational diabetes mellitus (GDM) compared with other racial/ethnic groups. Exposure to high levels of volatile organic compounds (VOCs) impairs pancreatic β-cell function, leading to insulin resistance, but racial/ethnic differences in this association are unexamined. We analyzed singleton deliveries (n = 220,065) from the Consortium on Safe Labor (2002-2008). Exposure to 14 VOCs in each hospital referral region was based on modified Community Multiscale Air Quality models. Logistic regression estimated odds ratios for GDM associated with high (≥75th percentile) versus low (<75th percentile) VOC exposure 3 months before conception and during the first trimester of pregnancy. Preconception and first-trimester exposure to high VOC levels was associated with increased odds of GDM among whites and APIs. GDM risk was significantly higher for APIs than whites for most VOCs. Preconception benzene exposure was associated with 29% (95% confidence interval: 12, 47) increased odds of GDM among whites compared with 45% (95% confidence interval: 16, 81) increased odds among APIs. These findings highlight environmental health disparities affecting pregnant women. Increased focus on GDM risk in US API communities is warranted.

Towards an integrated framework for air quality monitoring and exposure estimation-a review

For the health and safety of the public, it is essential to measure spatiotemporal distribution of air pollution in a region and thus monitor air quality in a fine-grain manner. While most of the sensing-based commercial applications available until today have been using fixed environmental sensors, the use of personal devices such as smartphones, smartwatches, and other wearable devices has not been explored in depth. These kinds of devices have an advantage of being with the user continuously, thus providing an ability to generate accurate and well-distributed spatiotemporal air pollution data. In this paper, we review the studies (especially in the last decade) done by various researchers using different kinds of environmental sensors highlighting related techniques and issues. We also present important studies of measuring impact and emission of air pollution on human beings and also discuss models using which air pollution inhalation can be associated to humans by quantifying personal exposure with the use of human activity detection. The overarching aim of this review is to provide novel and key ideas that have the potential to drive pervasive and individual centric and yet accurate pollution monitoring techniques which can scale up to the future needs.

Impacts of Personal Mobility and Diurnal Concentration Variability on Exposure Misclassification to Ambient Pollutants

Appreciating the uncertainty margins of exposure assessment to air pollution requires good understanding of its variability throughout the daily activities. This study describes a modeling framework for estimating exposure to air pollutants for a representative sample of working Israeli adults ( N ∼ 168 000) for which both the residence and workplace addresses were available. Individual daily trajectories were simulated by accounting for five generic daily activities: at home, at work, while in commute from home to work and back, and during out-of-home leisure activities. The integrated daily exposure to nitrogen dioxide (NO₂) was estimated for each individual by tracking the daily trajectory through an NO₂ concentration map, obtained using a dynamic and highly resolved dispersion-like model (temporal resolution, half-hourly; spatial resolution, 500 m). Accounting for the subjects' daily mobility was found to affect their exposure more significantly than accounting solely for the diurnal concentration variability, yet a synergistic effect was noted when accounting for both factors simultaneously. Exposure misclassification varies along the day, with the work microenvironment found to contribute the most to it. In particular, regardless of the high concentrations encountered during the commute, their contribution to the integrated daily exposure is small due to the relatively short time spent in this activity by most people.

Spatial and Temporal Dynamics in Air Pollution Exposure Assessment

Analyzing individual exposure in urban areas offers several challenges where both the individual's activities and air pollution levels demonstrate a large degree of spatial and temporal dynamics. This review article discusses the concepts, key elements, current developments in assessing personal exposure to urban air pollution (seventy-two studies reviewed) and respective advantages and disadvantages. A new conceptual structure to organize personal exposure assessment methods is proposed according to two classification criteria: (i) spatial-temporal variations of individuals' activities (point-fixed or trajectory based) and (ii) characterization of air quality (variable or uniform). This review suggests that the spatial and temporal variability of urban air pollution levels in combination with indoor exposures and individual's time-activity patterns are key elements of personal exposure assessment. In the literature review, the majority of revised studies (44 studies) indicate that the trajectory based with variable air quality approach provides a promising framework for tackling the important question of inter- and intra-variability of individual exposure. However, future quantitative comparison between the different approaches should be performed, and the selection of the most appropriate approach for exposure quantification should take into account the purpose of the health study. This review provides a structured basis for the intercomparing of different methodologies and to make their advantages and limitations more transparent in addressing specific research objectives.

Within-Day, Between-Day, and Between-Week Variability of Urinary Concentrations of Phenol Biomarkers in Pregnant Women

BACKGROUND

Toxicology studies have shown adverse effects of developmental exposure to industrial phenols. Evaluation in humans is challenged by potentially marked within-subject variability of phenol biomarkers in pregnant women, which is poorly characterized.

OBJECTIVES

We aimed to characterize within-day, between-day, and between-week variability of phenol urinary biomarker concentrations during pregnancy.

METHODS

In eight French pregnant women, we collected all urine voids over a 1-wk period (average, 60 samples per week per woman) at three occasions (15±2, 24±2, and 32±1 gestational weeks) in 2012-2013. Aliquots of each day and of the whole week were pooled within-subject. We assayed concentrations of 10 phenols in these pools, and, for two women, in all spot (unpooled) samples collected during a 1-wk period. We characterized variability using intraclass correlation coefficients (ICCs) with spot samples (within-day variability), daily pools (between-day variability), and weekly pools (between-week variability).

RESULTS

For most biomarkers, the within-day variability was high (ICCs between 0.03 and 0.50). The between-day variability, based on samples pooled within each day, was much lower, with ICCs >0.60 except for bisphenol S (0.14, 95% confidence interval [CI]: 0.00, 0.39). The between-week variability differed between compounds, with triclosan and bisphenol S having the lowest ICCs (<0.3) and 2,5-dichlorophenol the highest (ICC >0.9).

CONCLUSION

During pregnancy, phenol biomarkers showed a strong within-day variability, while the variability between days of a given week was more limited. One biospecimen is not enough to efficiently characterize exposure; collecting biospecimens during a single week may be enough to represent well the whole pregnancy exposure for some but not all phenols. https://doi.org/10.1289/EHP1994.

Walker occupancy has an impact on changing airborne bacterial communities in an underground pedestrian space, as small-dust particles increased with raising both temperature and humidity

Although human occupancy is a source of airborne bacteria, the role of walkers on bacterial communities in built environments is poorly understood. Therefore, we visualized the impact of walker occupancy combined with other factors (temperature, humidity, atmospheric pressure, dust particles) on airborne bacterial features in the Sapporo underground pedestrian space in Sapporo, Japan. Air samples (n = 18; 4,800L/each sample) were collected at 8:00 h to 20:00 h on 3 days (regular sampling) and at early morning / late night (5:50 h to 7:50 h / 22:15 h to 24:45 h) on a day (baseline sampling), and the number of CFUs (colony forming units) OTUs (operational taxonomic units) and other factors were determined. The results revealed that temperature, humidity, and atmospheric pressure changed with weather. The number of walkers increased greatly in the morning and evening on each regular sampling day, although total walker numbers did not differ significantly among regular sampling days. A slight increase in small dust particles (0.3–0.5μm) was observed on the days with higher temperature regardless of regular or baseline sampling. At the period on regular sampling, CFU levels varied irregularly among days, and the OTUs of 22-phylum types were observed, with the majority being from Firmicutes or Proteobacteria (γ-), including Staphylococcus sp. derived from human individuals. The data obtained from regular samplings reveled that although no direct interaction of walker occupancy and airborne CFU and OTU features was observed upon Pearson's correlation analysis, cluster analysis indicated an obvious lineage consisting of walker occupancy, CFU numbers, OTU types, small dust particles, and seasonal factors (including temperature and humidity). Meanwhile, at the period on baseline sampling both walker and CFU numbers were similarly minimal. Taken together, the results revealed a positive correlation of walker occupancy with airborne bacteria that increased with increases in temperature and humidity in the presence of airborne small particles. Moreover, the results indicated that small dust particles at high temperature and humidity may be a crucial factor responsible for stabilizing the bacteria released from walkers in built environments. The findings presented herein advance our knowledge and understanding of the relationship between humans and bacterial communities in built environments, and will help improve public health in urban communities.

A critical review of the ESCAPE project for estimating long-term health effects of air pollution

The European Study of Cohorts for Air Pollution Effects (ESCAPE) is a13-nation study of long-term health effects of air pollution based on subjects pooled from up to 22 cohorts that were intended for other purposes. Twenty-five papers have been published on associations of various health endpoints with long-term exposures to NOx, NO2, traffic indicators, PM10, PM2.5 and PM constituents including absorbance (elemental carbon). Seven additional ESCAPE papers found moderate correlations (R2=0.3-0.8) between measured air quality and estimates based on land-use regression that were used; personal exposures were not considered. I found no project summaries or comparisons across papers; here I conflate the 25 ESCAPE findings in the context of other recent European epidemiology studies. Because one ESCAPE cohort contributed about half of the subjects, I consider it and the other 18 cohorts separately to compare their contributions to the combined risk estimates. I emphasize PM2.5 and confirm the published hazard ratio of 1.14 (1.04-1.26) per 10μg/m3 for all-cause mortality. The ESCAPE papers found 16 statistically significant (p<0.05) risks among the125 pollutant-endpoint combinations; 4 each for PM2.5 and PM10, 1 for PM absorbance, 5 for NO2, and 2 for traffic. No PM constituent was consistently significant. No significant associations were reported for cardiovascular mortality; low birthrate was significant for all pollutants except PM absorbance. Based on associations with PM2.5, I find large differences between all-cause death estimates and the sum of specific-cause death estimates. Scatterplots of PM2.5 mortality risks by cause show no consistency across the 18 cohorts, ostensibly because of the relatively few subjects. Overall, I find the ESCAPE project inconclusive and I question whether the efforts required to estimate exposures for small cohorts were worthwhile. I suggest that detailed studies of the large cohort using historical exposures and additional cardiovascular risk factors might be productive.

Multi-pollutant exposure profiles associated with term low birth weight in Los Angeles County

Research indicates that multiple outdoor air pollutants and adverse neighborhood conditions are spatially correlated. Yet health risks associated with concurrent exposure to air pollution mixtures and clustered neighborhood factors remain underexplored. Statistical models to assess the health effects from pollutant mixtures remain limited, due to problems of collinearity between pollutants and area-level covariates, and increases in covariate dimensionality. Here we identify pollutant exposure profiles and neighborhood contextual profiles within Los Angeles (LA) County. We then relate these profiles with term low birth weight (TLBW). We used land use regression to estimate NO2, NO, and PM2.5 concentrations averaged over census block groups to generate pollutant exposure profile clusters and census block group-level contextual profile clusters, using a Bayesian profile regression method. Pollutant profile cluster risk estimation was implemented using a multilevel hierarchical model, adjusting for individual-level covariates, contextual profile cluster random effects, and modeling of spatially structured and unstructured residual error. Our analysis found 13 clusters of pollutant exposure profiles. Correlations between study pollutants varied widely across the 13 pollutant clusters. Pollutant clusters with elevated NO2, NO, and PM2.5 concentrations exhibited increased log odds of TLBW, and those with low PM2.5, NO2, and NO concentrations showed lower log odds of TLBW. The spatial patterning of pollutant cluster effects on TLBW, combined with between-pollutant correlations within pollutant clusters, imply that traffic-related primary pollutants influence pollutant cluster TLBW risks. Furthermore, contextual clusters with the greatest log odds of TLBW had more adverse neighborhood socioeconomic, demographic, and housing conditions. Our data indicate that, while the spatial patterning of high-risk multiple pollutant clusters largely overlaps with adverse contextual neighborhood cluster, both contribute to TLBW while controlling for the other.