Investigating the Impact of Maternal Residential Mobility on Identifying Critical Windows of Susceptibility to Ambient Air Pollution During Pregnancy

Independent and joint effects of neighborhood-level environmental and socioeconomic exposures on body mass index in early childhood: The environmental influences on child health outcomes (ECHO) cohort

Past studies support the hypothesis that the prenatal period influences childhood growth. However, few studies explore the joint effects of exposures that occur simultaneously during pregnancy. To explore the feasibility of using mixtures methods with neighborhood-level environmental exposures, we assessed the effects of multiple prenatal exposures on body mass index (BMI) from birth to age 24 months. We used data from two cohorts: Healthy Start (n = 977) and Maternal and Developmental Risks from Environmental and Social Stressors (MADRES; n = 303). BMI was measured at delivery and 6, 12, and 24 months and standardized as z-scores. We included variables for air pollutants, built and natural environments, food access, and neighborhood socioeconomic status (SES). We used two complementary statistical approaches: single-exposure linear regression and quantile-based g-computation. Models were fit separately for each cohort and time point and were adjusted for relevant covariates. Single-exposure models identified negative associations between NO2 and distance to parks and positive associations between low neighborhood SES and BMI z-scores for Healthy Start participants; for MADRES participants, we observed negative associations between O3 and distance to parks and BMI z-scores. G-computations models produced comparable results for each cohort: higher exposures were generally associated with lower BMI, although results were not significant. Results from the g-computation models, which do not require a priori knowledge of the direction of associations, indicated that the direction of associations between mixture components and BMI varied by cohort and time point. Our study highlights challenges in assessing mixtures effects at the neighborhood level and in harmonizing exposure data across cohorts. For example, geospatial data of neighborhood-level exposures may not fully capture the qualities that might influence health behavior. Studies aiming to harmonize geospatial data from different geographical regions should consider contextual factors when operationalizing exposure variables.

Using Parametric g-Computation for Time-to-Event Data and Distributed Lag Models to Identify Critical Exposure Windows for Preterm Birth: An Illustrative Example Using PM2.5 in a Retrospective Birth Cohort Based in Eastern Massachusetts (2011-2016)

BACKGROUND

Parametric g-computation is an attractive analytic framework to study the health effects of air pollution. Yet, the ability to explore biologically relevant exposure windows within this framework is underdeveloped.

OBJECTIVES

We outline a novel framework for how to incorporate complex lag-responses using distributed lag models (DLMs) into parametric g-computation analyses for survival data. We call this approach "g-survival-DLM" and illustrate its use examining the association between PM 2.5 during pregnancy and the risk of preterm birth (PTB).

METHODS

We applied the g-survival-DLM approach to estimate the hypothetical static intervention of reducing average PM 2.5 in each gestational week by 20% on the risk of PTB among 9,403 deliveries from Beth Israel Deaconess Medical Center, Boston, Massachusetts, 2011-2016. Daily PM 2.5 was taken from a 1 -km grid model and assigned to address at birth. Models were adjusted for sociodemographics, time trends, nitrogen dioxide, and temperature. To facilitate implementation, we provide a detailed description of the procedure and accompanying R syntax.

RESULTS

There were 762 (8.1%) PTBs in this cohort. The gestational week-specific median PM 2.5 concentration was relatively stable across pregnancy at ∼ 7 μ g / m 3 . We found that our hypothetical intervention strategy changed the cumulative risk of PTB at week 36 (i.e., the end of the preterm period) by - 0.009 (95% confidence interval: - 0.034 , 0.007) in comparison with the scenario had we not intervened, which translates to about 86 fewer PTBs in this cohort. We also observed that the critical exposure window appeared to be weeks 5-20.

DISCUSSION

We demonstrate that our g-survival-DLM approach produces easier-to-interpret, policy-relevant estimates (due to the g-computation); prevents immortal time bias (due to treating PTB as a time-to-event outcome); and allows for the exploration of critical exposure windows (due to the DLMs). In our illustrative example, we found that reducing fine particulate matter [particulate matter (PM) with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 )] during gestational weeks 5-20 could potentially lower the risk of PTB. https://doi.org/10.1289/EHP13891.

High ambient temperature in pregnancy and risk of childhood acute lymphoblastic leukaemia: an observational study

BACKGROUND

High ambient temperature is increasingly common due to climate change and is associated with risk of adverse pregnancy outcomes. Acute lymphoblastic leukaemia is the most common malignancy in children, the incidence is increasing, and in the USA disproportionately affects Latino children. We aimed to investigate the potential association between high ambient temperature in pregnancy and risk of childhood acute lymphoblastic leukaemia.

METHODS

We used data from California birth records (children born from Jan 1, 1982, to Dec 31, 2015) and California Cancer Registry (those diagnosed with childhood cancer in California from Jan 1, 1988, to Dec 31, 2015) to identify acute lymphoblastic leukaemia cases diagnosed in infants and children aged 14 years and younger and controls matched by sex, race, ethnicity, and date of last menstrual period. Ambient temperatures were estimated on a 1-km grid. The association between ambient temperature and acute lymphoblastic leukaemia was evaluated per gestational week, restricted to May-September, adjusting for confounders. Bayesian meta-regression was applied to identify critical exposure windows. For sensitivity analyses, we evaluated a 90-day pre-pregnancy period (assuming no direct effect before pregnancy), adjusted for relative humidity and particulate matter less than 2·5 microns in aerodynamic diameter, and constructed an alternatively matched dataset for exposure contrast by seasonality.

FINDINGS

6849 cases of childhood acute lymphoblastic leukaemia were identified and, of these, 6258 had sufficient data for study inclusion. We also included 307 579 matched controls. Most of the study population were male (174 693 [55·7%] of the 313 837 included in the study) and of Latino ethnicity (174 906 [55·7%]). The peak association between ambient temperature and risk of acute lymphoblastic leukaemia was observed in gestational week 8, where a 5°C increase was associated with an odds ratio of 1·07 (95% CI 1·04-1·11). A slightly larger effect was seen among Latino children (OR 1·09 [95% CI 1·04-1·14]) than non-Latino White children (OR 1·05 [1·00-1·11]). The sensitivity analyses supported the results of the main analysis.

INTERPRETATION

Our findings suggest an association between high ambient temperature in early pregnancy and risk of childhood acute lymphoblastic leukaemia. Further replication and investigation of mechanistic pathways might inform mitigation strategies.

FUNDING

Yale Center on Climate Change and Health, The National Center for Advancing Translational Science, National Institutes of Health.

Ambient particulate matter and surrounding greenness in relation to sleep quality among pregnant women: A nationwide cohort study

Background

Particulate air pollution and residential greenness are associated with sleep quality in the general population; however, their influence on maternal sleep quality during pregnancy has not been assessed.

Objective

This cross-sectional study investigated the individual and interactive effects of exposure to particulate matter (PM) air pollution and residential greenness on sleep quality in pregnant women.

Methods

Pregnant women (n = 4933) enrolled in the Korean Children's Environmental Health Study with sleep quality information and residential address were included. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The average concentrations of PM (PM2.5 and PM10) during pregnancy were estimated through land use regression, and residential greenness in a 1000 m buffer area around participants' residences was estimated using the Normalized Difference Vegetation Index (NDVI1000-m). Modified Poisson regression models were used to estimate the associations between PM and NDVI and poor sleep quality (PSQI >5) after controlling for a range of covariates. A four-way mediation analysis was conducted to examine the mediating effects of PM.

Results

After adjusting for confounders, each 10 μg/m3 increase in PM2.5 and PM10 exposure was associated with a higher risk of poor sleep quality (relative risk [RR]: 1.06; 95% confidence interval [CI]: 1.01, 1.11; and RR: 1.09; 95% CI: 1.06, 1.13, respectively), and each 0.1-unit increase in NDVI1000-m was associated with a lower risk of poor sleep quality (RR: 0.97; 95% CI: 0.95, 0.99). Mediation analysis showed that PM mediated approximately 37%-56% of the association between residential greenness and poor sleep quality.

Conclusions

This study identified a positive association between residential greenness and sleep quality. Furthermore, these associations are mediated by a reduction in exposure to particulate air pollution and highlight the link between green areas, air pollution control, and human health.

Prenatal exposure to fine particulate matter chemical constituents and the risk of stillbirth and the mediating role of pregnancy complications: A cohort study

Evidence on the association of fine particulate matter (PM2.5) exposure with stillbirth is limited and inconsistent, which is largely attributed to differences in PM2.5 constituents. Studies have found that the hazards of certain PM2.5 constituents to the fetus are comparable to or even higher than total PM2.5 mass. However, few studies have linked PM2.5 constituents to stillbirth. Moreover, the mediating role of pregnancy complications in PM2.5-related stillbirth remains unclear. To our knowledge, this study was the first to explore the individual and mixed associations of PM2.5 and its constituents with stillbirth in China. After matching the concentrations of PM2.5 and its constituents (sulfate [SO42-], nitrate [NO3-], ammonium [NH4+], organic matter [OM], and black carbon [BC]) for participants according to their geographical location, there were 170,507 participants included in this study. We found that stillbirth was associated with exposure to PM2.5 and its constituents in the year before pregnancy and during the entire pregnancy, and the associations in trimester 1 were strongest. The risk of stillbirth increased sharply when PM2.5 and its constituents during pregnancy exceeded the median concentrations. Moreover, stillbirth was associated with exposure to the mixtures of SO42-, NO3-, NH4+, OM, and BC before and during pregnancy (trimesters 1 and 2). Meanwhile, two-pollutant models also suggested stillbirth was associated with PM2.5 and its constituents in the year before and during pregnancy. The associations of PM2.5 and its constituents with stillbirth were stronger in mothers with advanced age and without cesarean delivery history. Additionally, hypertensive disorders in pregnancy, gestational diabetes, and placental abruption mediated the association of PM2.5 with stillbirth. Therefore, enhanced protection against PM2.5 for pregnant women before and during pregnancy and targeted interventions for pregnancy complications and anthropogenic sources of PM2.5 constituents are important to reduce stillbirth risk.

Effects of air pollution on adverse birth outcomes and pregnancy complications in the U.S. state of Kansas (2000-2015)

Neonatal mortality and morbidity are often caused by preterm birth and lower birth weight. Gestational diabetes mellitus (GDM) and gestational hypertension (GH) are the most prevalent maternal medical complications during pregnancy. However, evidence on effects of air pollution on adverse birth outcomes and pregnancy complications is mixed. Singleton live births conceived between January 1st, 2000, and December 31st, 2015, and reached at least 27 weeks of pregnancy in Kansas were included in the study. Trimester-specific and total pregnancy exposures to nitrogen dioxide (NO2), particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5), and ozone (O3) were estimated using spatiotemporal ensemble models and assigned to maternal residential census tracts. Logistic regression, discrete-time survival, and linear models were applied to assess the associations. After adjustment for demographics and socio-economic status (SES) factors, we found increases in the second and third trimesters and total pregnancy O3 exposures were significantly linked to preterm birth. Exposure to the second and third trimesters O3 was significantly associated with lower birth weight, and exposure to NO2 during the first trimester was linked to an increased risk of GDM. O3 exposures in the first trimester were connected to an elevated risk of GH. We didn't observe consistent associations between adverse pregnancy and birth outcomes with PM2.5 exposure. Our findings indicate there is a positive link between increased O3 exposure during pregnancy and a higher risk of preterm birth, GH, and decreased birth weight. Our work supports limiting population exposure to air pollution, which may lower the likelihood of adverse birth and pregnancy outcomes.

Development of Spatio-Temporal Land Use Regression Models for Fine Particulate Matter and Wood-Burning Tracers in Temuco, Chile

Biomass burning is common in much of the world, and in some areas, residential wood-burning has increased. However, air pollution resulting from biomass burning is an important public health problem. A sampling campaign was carried out between May 2017 and July 2018 in over 64 sites in four sessions, to develop a spatio-temporal land use regression (LUR) model for fine particulate matter (PM) and wood-burning tracers levoglucosan and soluble potassium (Ksol) in a city heavily impacted by wood-burning. The mean (sd) was 46.5 (37.4) μg m-3 for PM2.5, 0.607 (0.538) μg m-3 for levoglucosan, and 0.635 (0.489) μg m-3 for Ksol. LUR models for PM2.5, levoglucosan, and Ksol had a satisfactory performance (LOSOCV R2), explaining 88.8%, 87.4%, and 87.3% of the total variance, respectively. All models included sociodemographic predictors consistent with the pattern of use of wood-burning in homes. The models were applied to predict concentrations surfaces and to estimate exposures for an epidemiological study.

Associations between weekly gestational exposure of fine particulate matter, ozone, and nitrogen dioxide and preterm birth in a North Carolina Birth Cohort, 2003-2015

Background

Preterm birth (PTB; <37 weeks completed gestation) is associated with exposure to air pollution, though variability in association magnitude and direction across exposure windows exists. We evaluated associations between weekly gestational exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) with PTB in a North Carolina Birth Cohort from 2003 to 2015 (N = 1,367,517).

Methods

Daily average PM2.5 and daily 8-hour maximum NO2 concentration estimates were obtained from a hybrid ensemble model with a spatial resolution of 1 km2. Daily 8-hour maximum census tract-level concentration estimates for O3 were obtained from the EPA's Fused Air Quality Surface Using Downscaling model. Air pollutant concentrations were linked by census tract to residential address at delivery and averaged across each week of pregnancy. Modified Poisson regression models with robust errors were used to estimate risk differences (RD [95% confidence intervals (CI)]) for an interquartile range increase in pollutants per 10,000 births, adjusted for potential confounders.

Results

Associations were similar in magnitude across weeks. We observed positive associations for PM2.5 and O3 exposures, but generally null associations with NO2. RDs ranged from 15 (95% CI = 11, 18) to 32 (27, 37) per 10,000 births for PM2.5; from -7 (-14, -1) to 0 (-5, 4) for NO2; and from 4 (1, 7) to 13 (10, 16) for O3.

Conclusion

Our results show that increased PM2.5 exposure is associated with an increased risk of PTB across gestational weeks, and these associations persist in multipollutant models with NO2 and/or O3.

Residential mobility in pregnancy and potential exposure misclassification of air pollution, temperature, and greenness

Introduction

Epidemiological studies commonly use residential addresses at birth to estimate exposures throughout pregnancy, ignoring residential mobility. Lack of consideration for residential mobility during pregnancy might lead to exposure misclassification that should be addressed in environmental epidemiology.

Methods

We investigated potential exposure misclassification from estimating exposure during pregnancy by residence at delivery utilizing a prospective cohort of pregnant women in New York, United States (n = 1899; 2016-2019). We calculated exposure during pregnancy corresponding to each address for fine particles (PM2.5), temperature, and greenness (Enhanced Vegetation Index [EVI]).

Results

Twenty-two percent of participants moved at least once during pregnancy; 82.3% of movers changed residences during the second or third trimesters. Participants with better health, lower parity, and higher socioeconomic status were more likely to move. Exposures based on address at delivery rather than residential history overestimated exposure for PM2.5 (exposure error: range -5.7 to 4.6 µg/m3, average -0.6 µg/m3) and EVI (range -0.305 to 0.307, average -0.013), but not temperature. Overestimations were significantly larger for mothers with higher socioeconomic status. Our findings indicate that the error for prenatal exposure can occur when residential mobility is not considered and is disproportional by maternal characteristics.

Conclusions

Epidemiological studies should consider residential mobility in exposure assessments based on geolocation when possible, and results based on mother's residence at birth should be interpreted with understanding of potential differential exposure misclassification.

Critical Windows of Maternal Exposure to Biothermal Stress and Birth Weight for Gestational Age in Western Australia

BACKGROUND

There is limited and inconsistent evidence on the risk of ambient temperature on small for gestational age (SGA) and there are no known related studies for large for gestational age (LGA). In addition, previous studies used temperature rather than a biothermal metric.

OBJECTIVES

Our aim was to examine the associations and critical susceptible windows of maternal exposure to a biothermal metric [Universal Thermal Climate Index (UTCI)] and the hazards of SGA and LGA.

METHODS

We linked 385,337 singleton term births between 1 January 2000 and 31 December 2015 in Western Australia to daily spatiotemporal UTCI. Distributed lag nonlinear models with Cox regression and multiple models were used to investigate maternal exposure to UTCI from 12 weeks preconception to birth and the adjusted hazard ratios (HRs) of SGA and LGA.

RESULTS

Relative to the median exposure, weekly and monthly specific exposures showed potential critical windows of susceptibility for SGA and LGA at extreme exposures, especially during late gestational periods. Monthly exposure showed strong positive associations from the 6th to the 10th gestational months with the highest hazard of 13% for SGA (HR = 1.13 ; 95% CI: 1.10, 1.14) and 7% for LGA (HR = 1.07 ; 95% CI: 1.03, 1.11) at the 10th month for the 1st UTCI centile. Entire pregnancy exposures showed the strongest hazards of 11% for SGA (HR = 1.11 ; 95% CI: 1.04, 1.18) and 3% for LGA (HR = 1.03 ; 95% CI: 0.95, 1.11) at the 99th UTCI centile. By trimesters, the highest hazards were found during the second and first trimesters for SGA and LGA, respectively, at the 99th UTCI centile. Based on estimated interaction effects, male births, mothers who were non-Caucasian, smokers, ≥ 35 years of age, and rural residents were most vulnerable.

CONCLUSIONS

Both weekly and monthly specific extreme biothermal stress exposures showed potential critical susceptible windows of SGA and LGA during late gestational periods with disproportionate sociodemographic vulnerabilities. https://doi.org/10.1289/EHP12660.

Heterogeneous Distributed Lag Models to Estimate Personalized Effects of Maternal Exposures to Air Pollution

Children's health studies support an association between maternal environmental exposures and children's birth outcomes. A common goal is to identify critical windows of susceptibility-periods during gestation with increased association between maternal exposures and a future outcome. The timing of the critical windows and magnitude of the associations are likely heterogeneous across different levels of individual, family, and neighborhood characteristics. Using an administrative Colorado birth cohort we estimate the individualized relationship between weekly exposures to fine particulate matter (PM 2.5) during gestation and birth weight. To achieve this goal, we propose a statistical learning method combining distributed lag models and Bayesian additive regression trees to estimate critical windows at the individual level and identify characteristics that induce heterogeneity from a high-dimensional set of potential modifying factors. We find evidence of heterogeneity in the PM 2.5 -birth weight relationship, with some mother-child dyads showing a 3 times larger decrease in birth weight for an IQR increase in exposure (5.9 to 8.5 PM 2.5 μg/m3) compared to the population average. Specifically, we find increased vulnerabilitity for non-Hispanic mothers who are either younger, have higher body mass index or lower educational attainment. Our case study is the first precision health study of critical windows.

Adverse effects of temperature on perinatal and pregnancy outcomes: methodological challenges and knowledge gaps

Evidence linking temperature with adverse perinatal and pregnancy outcomes is emerging. We searched for literature published until 30 January 2023 in PubMed, Web of Science, and reference lists of articles focusing on the outcomes that were most studied like preterm birth, low birth weight, stillbirth, and hypertensive disorders of pregnancy. A review of the literature reveals important gaps in knowledge and several methodological challenges. One important gap is the lack of knowledge of how core body temperature modulates under extreme ambient temperature exposure during pregnancy. We do not know the magnitude of non-modulation of body temperature during pregnancy that is clinically significant, i.e., when the body starts triggering physiologic counterbalances. Furthermore, few studies are conducted in places where extreme temperature conditions are more frequently encountered, such as in South Asia and sub-Saharan Africa. Little is also known about specific cost-effective interventions that can be implemented in vulnerable communities to reduce adverse outcomes. As the threat of global warming looms large, effective interventions are critically necessary to mitigate its effects.

Association of Antepartum and Postpartum Air Pollution Exposure With Postpartum Depression in Southern California

Importance

Women are especially vulnerable to mental health matters post partum because of biological, emotional, and social changes during this period. However, epidemiologic evidence of an association between air pollution exposure and postpartum depression (PPD) is limited.

Objective

To examine the associations between antepartum and postpartum maternal air pollution exposure and PPD.

Design, Setting, and Participants

This retrospective cohort study used data from Kaiser Permanente Southern California (KPSC) electronic health records and included women who had singleton live births at KPSC facilities between January 1, 2008, and December 31, 2016. Data were analyzed between January 1 and May 10, 2023.

Exposures

Ambient air pollution exposures were assessed based on maternal residential addresses using monthly averages of particulate matter less than or equal to 2.5 μm (PM2.5), particulate matter less than or equal to 10 μm (PM10), nitrogen dioxide (NO2), and ozone (O3) from spatial interpolation of monitoring station measurements. Constituents of PM2.5 (sulfate, nitrate, ammonium, organic matter, and black carbon) were obtained from fine-resolution geoscience-derived models based on satellite, ground-based monitor, and chemical transport modeling data.

Main Outcomes and Measures

Participants with an Edinburgh Postnatal Depression Scale score of 10 or higher during the 6 months after giving birth were referred to a clinical interview for further assessment and diagnosis. Ascertainment of PPD was defined using a combination of diagnostic codes and prescription medications.

Results

The study included 340 679 participants (mean [SD] age, 30.05 [5.81] years), with 25 674 having PPD (7.54%). Increased risks for PPD were observed to be associated with per-IQR increases in antepartum and postpartum exposures to O3 (adjusted odds ratio [AOR], 1.09; 95% CI, 1.06-1.12), PM10 (AOR, 1.02; 95% CI, 1.00-1.04), and PM2.5 (AOR, 1.02; 95% CI, 1. 00-1.03) but not with NO2; PPD risks were mainly associated with PM2.5 organic matter and black carbon. Overall, a higher risk of PPD was associated with O3 during the entire pregnancy and postpartum periods and with PM exposure during the late pregnancy and postpartum periods.

Conclusions and Relevance

The study findings suggest that long-term exposure to antepartum and postpartum air pollution was associated with higher PPD risks. Identifying the modifiable environmental risk factors and developing interventions are important public health issues to improve maternal mental health and alleviate the disease burden of PPD.

Traffic-Related Air Pollution and Ultrasound Parameters of Fetal Growth in Eastern Massachusetts

Previous studies have examined the association between prenatal nitrogen dioxide (NO2)-a traffic emissions tracer-and fetal growth based on ultrasound measures. Yet, most have used exposure assessment methods with low temporal resolution, which limits the identification of critical exposure windows given that pregnancy is relatively short. Here, we used NO2 data from an ensemble model linked to residential addresses at birth to fit distributed lag models that estimated the association between NO2 exposure (resolved weekly) and ultrasound biometric parameters in a Massachusetts-based cohort of 9,446 singleton births from 2011-2016. Ultrasound biometric parameters examined included biparietal diameter (BPD), head circumference, femur length, and abdominal circumference. All models adjusted for sociodemographic characteristics, time trends, and temperature. We found that higher NO2 was negatively associated with all ultrasound parameters. The critical window differed depending on the parameter and when it was assessed. For example, for BPD measured after week 31, the critical exposure window appeared to be weeks 15-25; 10-parts-per-billion higher NO2 sustained from conception to the time of measurement was associated with a lower mean z score of -0.11 (95% CI: -0.17, -0.05). Our findings indicate that reducing traffic emissions is one potential avenue to improving fetal and offspring health.

Maternal exposure to ambient air pollution mixture and premature rupture of membranes: Evidence from a large cohort in Southern California (2008-2018)

BACKGROUND

There is minimal evidence of relationships between maternal air pollution exposure and spontaneous premature rupture of membranes (SPROM), a critical obstetrical problem that can significantly increase maternal and fetal mortality and morbidity. No prior study has explored the PROM risk related to specific components of particulate matter with aerodynamic diameters of ≤ 2.5 µm (PM2.5). We examined associations between maternal exposure to nitrogen dioxide (NO2), ozone (O3), PM2.5, PM10, and PM2.5 constituents and SPROM.

METHODS

A large retrospective cohort study was conducted and included 427,870 singleton live births from Kaiser Permanente Southern California during 2008-2018. Monthly averages of NO2, O3 (8-h daily maximum), PM2.5, and PM10 were measured using empirical Bayesian kriging based on measurements from monitoring stations. Data on PM2.5 sulfate, nitrate, ammonium, organic matter, and black carbon were obtained from a fine-resolution model. A discrete time approach with pooled logistic regressions was used to estimate associations throughout the pregnancy and based on trimesters and gestational months. The quantile-based g-computation models were fitted to examine the effects of 1) the air pollution mixture of four pollutants of interest and 2) the mixture of PM2.5 components.

RESULTS

There were 37,857 SPROM cases (8.8%) in our study population. We observed relationships between SPROM and maternal exposure to NO2, O3, and PM2.5. PM2.5 sulfate, nitrate, ammonium, and organic matter were associated with higher SPROM risks in the single-pollutant model. Mixture analyses demonstrated that the overall effects of the air pollution mixture and PM2.5 mixture in this study were mainly driven by O3 and PM2.5 nitrate, respectively. Underweight mothers had a significantly higher risk of SPROM associated with NO2.

CONCLUSION

Our findings add to the literature on associations between air pollution exposure and SPROM. This is the first study reporting the impact of PM2.5 constituents on SPROM.

High Ambient Temperature in Pregnancy and Risk of Childhood Acute Lymphoblastic Leukemia

Background

High ambient temperature is increasingly common due to climate change and is associated with risk of adverse pregnancy outcomes. Acute lymphoblastic leukemia (ALL) is the most common malignancy in children, the incidence is increasing, and in the United States it disproportionately affects Latino children. We aimed to investigate the potential association between high ambient temperature in pregnancy and risk of childhood ALL.

Methods

We used data from California birth records (1982-2015) and California Cancer Registry (1988-2015) to identify ALL cases diagnosed <14 years and 50 times as many controls matched by sex, race/ethnicity, and date of last menstrual period. Ambient temperatures were estimated on a 1-km grid. Association between ambient temperature and ALL was evaluated per gestational week, restricted to May-September, adjusting for confounders. Bayesian meta-regression was applied to identify critical exposure windows. For sensitivity analyses, we evaluated a 90-day pre-pregnancy period (assuming no direct effect before pregnancy) and constructed an alternatively matched dataset for exposure contrast by seasonality.

Findings

Our study included 6,258 ALL cases and 307,579 controls. The peak association between ambient temperature and risk of ALL was observed in gestational week 8, where a 5 °C increase was associated with an odds ratio of 1.09 (95% confidence interval 1.04-1.14) and 1.05 (95% confidence interval 1.00-1.11) among Latino and non-Latino White children, respectively. The sensitivity analyses supported this.

Interpretation

Our findings suggest an association between high ambient temperature in early pregnancy and risk of childhood ALL. Further replication and investigation of mechanistic pathways may inform mitigation strategies.

Interaction effects of night-time temperature and PM2.5 on preterm birth in Huai River Basin, China

Nocturnal temperature is observed increasing with global warming. However, evidence on night-time non-optimal temperature on the risk of preterm birth (PTB) is limited, and the potential interactions with air pollution on PTB has not been well clarified. We therefore conducted a population-based retrospective cohort study to evaluate the effect of night-time temperature extremes on the risk of PTB and its interaction with air pollution. Records of 196,780 singleton births from 4 counties in Huai River Basin (2013-2018) were obtained. Gridded data on night-time temperature were collected from a high-quality Chinese Air Quality Reanalysis dataset. We used a multivariate logistic regression to evaluate the effects of night-time heat and cold exposure on the risk of PTB as well as its subtypes. Potential interactions between night-time temperature extremes and fine particulate matter < 2.5 µm (PM_2.5) were examined using the relative excess risk due to interaction (RERI). We found that the risk of PTB was positively associated with third trimester night-time extremely heat and cold exposure, with adjusted OR of 1.898 (95 %CI: 1.655-2.177) and 2.044 (95 %CI: 1.786-2.339). Similar effects were observed for PTB subtypes, moderately PTB (mPTB) and very PTB (vPTB). Synergistic effects (RERI greater than 0) of each trimester night-time temperature extremes exposure and PM_2.5 on PTB were observed. We identified consistent positive interactions between night-time temperature extremes and PM_2.5 on mPTB. No significant interaction of night-time temperature extremes and PM_2.5 on vPTB was found. In conclusion, this large retrospective cohort study found that third trimester night-time heat and cold exposure significantly increased the risk of PTB and its subtypes. There is a synergistic effect between night-time temperature extremes and high PM_2.5 levels on PTB and mPTB. In the context of climate warming, our results add new evidence to the current understanding of night-time non-optimal temperature exposure on PTB.

Ambient temperature during pregnancy and fetal growth in Eastern Massachusetts, USA

Background

Left unabated, rising temperatures pose an escalating threat to human health. The potential effects of hot temperatures on fetal health have been under-explored. Here, we examined the association between prenatal ambient temperature exposure and fetal growth measures in a Massachusetts-based pregnancy cohort.

Methods

We used ultrasound measurements of biparietal diameter (BPD), head circumference (HC), femur length and abdominal circumference (AC), in addition to birthweight (BW), from 9446 births at Beth Israel Deaconess Medical Center from 2011 to 2016. Ultrasound scans were classified into three distinct gestational periods: 16–23 weeks, 24–31 weeks, 32+ weeks; and z-scores were created for each fetal growth measure using the INTERGROWTH-21st standards. We fitted distributed lag models to estimate the time-varying association between weekly temperature and fetal growth, adjusting for sociodemographic characteristics, seasonal and long-term trends, humidity and particulate matter (PM2.5).

Results

Higher ambient temperature was associated with smaller fetal growth measures. The critical window of exposure appeared to be Weeks 1–20 for ultrasound parameters, and high temperatures throughout pregnancy were important for BW. Associations were strongest for head parameters (BPD and HC) in early to mid-pregnancy, AC late in pregnancy and BW. For example, a 5ºC higher cumulative temperature exposure was associated with a lower mean AC z-score of -0.26 (95% CI: -0.48, -0.04) among 24–31-Week scans, and a lower mean BW z-score of -0.32 (95% CI: -0.51, -0.12).

Conclusion

Higher temperatures were associated with impaired fetal growth. This has major health implications given that extreme temperatures are more common and escalating.

Exposure errors due to inaccurate residential addresses and their impact on epidemiological associations: Evidence from a national neonate dataset

BACKGROUND

Studies assessing the associations between prenatal air pollution exposures and birth outcomes commonly use maternal addresses at the time of delivery as a proxy for residency throughout pregnancy. Yet, in large-scale epidemiology studies, maternal addresses commonly originate from an administrative source.

OBJECTIVE

This study aimed to examine the use of population registry addresses to assign exposure estimations and to evaluate the impact of inaccurate addresses on exposure estimates and association measures of prenatal exposures with congenital hypothyroidism.

METHODS

We used morbidity data for congenital hypothyroidism from the national program for neonatal screening for 2009-2015 and address data from two sources: population registry and hospital records. We selected neonates with geocoded addresses from both sources (N = 685,491) and developed a comparison algorithm for these addresses. Next, we assigned neonates with exposures from ambient air pollution of PM and NO₂/NO_X, evaluated exposure assessment differences, and used multivariable logistic regression models to assess the impact that these differences have on association measures.

RESULTS

We found that most of the exposure differences between neonates with addresses from both sources were around zero and had a leptokurtic distribution density, with most values being zero. Additionally, associations between exposure and congenital hypothyroidism were comparable, regardless of address source and when we limited the model to neonates with identical addresses.

CONCLUSIONS

We found that ignoring residential inaccuracies results in only a small bias of the associations towards the null. These results strengthen the validity of addresses from population registries for exposure assessment, when detailed residential data during pregnancy are not available.

Ambient temperature and term birthweight in Latin American cities

BACKGROUND

Extreme temperatures may lead to adverse pregnancy and birth outcomes, including low birthweight. Studies on the impact of temperature on birthweight have been inconclusive due to methodological challenges related to operationalizing temperature exposure, the definitions of exposure windows, accounting for gestational age, and a limited geographic scope.

METHODS

We combined data on individual-level term live births (N≈15 million births) from urban areas in Brazil, Chile, and Mexico from 2010 to 2015 from the SALURBAL study (Urban Health in Latin America) with high-resolution daily air temperature data and computed average ambient temperature for every month of gestation for each newborn. Associations between full-term birthweight and average temperature during gestation were analyzed using multi-level distributed lag non-linear models that adjusted for newborn's sex, season of conception, and calendar year of child's birth; controlled for maternal age, education, partnership status, presence of previous births, and climate zone; and included a random term for the sub-city of mother's residence.

FINDINGS

Higher temperatures during the entire gestation are associated with lower birthweight, particularly in Mexico and Brazil. The cumulative effect of temperature on birthweight is mostly driven by exposure to higher temperatures during months 7-9 of gestation. Higher maternal education can attenuate the temperature-birthweight associations.

INTERPRETATION

Our work shows that climate-health impacts are likely to be context- and place-specific and warrants research on temperature and birthweight in diverse climates to adequately anticipate global climate change. Given the high societal cost of suboptimal birthweight, public health efforts should be aimed at diminishing the detrimental effect of higher temperatures on birthweight.

FUNDING

The Wellcome Trust.

Assessing Exposure to Unconventional Oil and Gas Development: Strengths, Challenges, and Implications for Epidemiologic Research

PURPOSE OF REVIEW

Epidemiologic studies have observed elevated health risks in populations living near unconventional oil and gas development (UOGD). In this narrative review, we discuss strengths and limitations of UOG exposure assessment approaches used in or available for epidemiologic studies, emphasizing studies of children's health outcomes.

RECENT FINDINGS

Exposure assessment challenges include (1) numerous potential stressors with distinct spatiotemporal patterns, (2) critical exposure windows that cover long periods and occur in the past, and (3) limited existing monitoring data coupled with the resource-intensiveness of collecting new exposure measurements to capture spatiotemporal variation. All epidemiologic studies used proximity-based models for exposure assessment as opposed to surveys, biomonitoring, or environmental measurements. Nearly all studies used aggregate (rather than pathway-specific) models, which are useful surrogates for the complex mix of potential hazards. Simple and less-specific exposure assessment approaches have benefits in terms of scalability, interpretability, and relevance to specific policy initiatives such as set-back distances. More detailed and specific models and metrics, including dispersion methods and stressor-specific models, could reduce exposure misclassification, illuminate underlying exposure pathways, and inform emission control and exposure mitigation strategies. While less practical in a large population, collection of multi-media environmental and biological exposure measurements would be feasible in cohort subsets. Such assessments are well-suited to provide insights into the presence and magnitude of exposures to UOG-related stressors in relation to spatial surrogates and to better elucidate the plausibility of observed effects in both children and adults.

CRITICAL WINDOW VARIABLE SELECTION FOR MIXTURES: ESTIMATING THE IMPACT OF MULTIPLE AIR POLLUTANTS ON STILLBIRTH

Understanding the role of time-varying pollution mixtures on human health is critical as people are simultaneously exposed to multiple pollutants during their lives. For vulnerable subpopulations who have well-defined exposure periods (e.g., pregnant women), questions regarding critical windows of exposure to these mixtures are important for mitigating harm. We extend critical window variable selection (CWVS) to the multipollutant setting by introducing CWVS for mixtures (CWVSmix), a hierarchical Bayesian method that combines smoothed variable selection and temporally correlated weight parameters to: (i) identify critical windows of exposure to mixtures of time-varying pollutants, (ii) estimate the time-varying relative importance of each individual pollutant and their first order interactions within the mixture, and (iii) quantify the impact of the mixtures on health. Through simulation we show that CWVSmix offers the best balance of performance in each of these categories in comparison to competing methods. Using these approaches, we investigate the impact of exposure to multiple ambient air pollutants on the risk of stillbirth in New Jersey, 2005-2014. We find consistent elevated risk in gestational weeks 2, 16-17, and 20 for non-Hispanic Black mothers, with pollution mixtures dominated by ammonium (weeks 2, 17, 20), nitrate (weeks 2, 17), nitrogen oxides (weeks 2, 16), PM2.5 (week 2), and sulfate (week 20). The method is available in the R package CWVSmix.

Assessing the effect of fine particulate matter on adverse birth outcomes in Huai River Basin, Henan, China, 2013-2018

Previous studies have indicated that maternal exposure to particles with aerodynamic diameter <2.5 μm (PM_2.5) is associated with adverse birth outcomes. However, the critical exposure windows remain inconsistent. A retrospective cohort study was conducted in Huai River Basin, Henan, China during 2013-2018. Daily PM_2.5 concentration was collected using Chinese Air Quality Reanalysis datasets. We calculated exposures for each participant based on the residential address during pregnancy. Binary logistic regression was used to examine the trimester-specific association of PM_2.5 exposure with preterm birth (PTB), low birth weight (LBW) and term LBW (tLBW), and we further estimated monthly and weekly association using distributed lag models. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for each 10 μg/m³ increase in PM_2.5 exposure. Stratified analyses were performed by maternal age, infant gender, parity, and socioeconomic status (SES). In total, 196,780 eligible births were identified, including 4257 (2.2%) PTBs, 3483 (1.8%) LBWs and 1770 (0.9%) tLBWs. Maternal PM_2.5 exposure during the second trimester were associated with the risk of PTB and LBW. At the monthly level, the PTB and LBW risks were associated with PM_2.5 exposure mainly in the 4th -6th month. By estimating the weekly-specific association, we observed that critical exposure windows of PM_2.5 exposure and PTB were in the 18th- 27th gestational weeks. Stronger associations were found in younger, multiparous mothers and those with a female baby and in low SES. In conclusion, the results indicate that maternal PM_2.5 exposure during the second trimester was associated with PTB and LBW. Younger, multiparous mothers and those with female babies and in low SES were susceptible.

Both parents matter: a national-scale analysis of parental race/ethnicity, disparities in prenatal PM2.5 exposures and related impacts on birth outcomes

BACKGROUND

Most U.S. studies that report racial/ethnic disparities in increased risk of low birth weight associated with air pollution exposures have been conducted in California or northeastern states and/or urban areas, limiting generalizability of study results. Few of these studies have examined maternal racial/ethnic groups other than Non-Hispanic Black, non-Hispanic White and Hispanic, nor have they included paternal race. We aimed to examine the independent effects of PM_2.5 on birth weight among a nationally representative sample of U.S. singleton infants and how both maternal and paternal race/ethnicity modify relationships between prenatal PM_2.5 exposures and birth outcomes.

METHODS

We used data from the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B), a longitudinal nationally representative cohort of 10,700 U.S. children born in 2001, which we linked to U.S.EPA's Community Multi-scale Air Quality (CMAQ)-derived predicted daily PM2.5 concentrations at the centroid of each Census Bureau Zip Code Tabulation Area (ZCTA) for maternal residences. We examined relationships between term birthweight (TBW)_, term low birthweight rate (TLBW) and gestational PM_2.5 pollutant using multivariate regression models. Effect modification of air pollution exposures on birth outcomes by maternal and paternal race was evaluated using stratified models. All analyses were conducted with sample weights to provide national-scale estimates.

RESULTS

The majority of mothers were White (61%). Fourteen percent of mothers identified as Black, 21% as Hispanic, 3% Asian American and Pacific Islander (AAPI) and 1% American Indian and Alaskan Native (AIAN). Fathers were also racially/ethnically diverse with 55% identified as White Non-Hispanic, 10% as Black Non-Hispanic, 19% as Hispanic, 3% as AAPI and 1% as AIAN. Results from the chi-square and ANOVA tests of significance for racial/ethnic differences indicate disparities in prenatal exposures and birth outcomes by both maternal and paternal race/ethnicity. Prenatal PM_2.5 was associated with reduced birthweights during second and third trimester and over the entire gestational period in adjusted regression models, although results did not reach statistical significance. In models stratified by maternal race and paternal race, one unit increase in PM_2.5 was statistically significantly associated with lower birthweights among AAPI mothers, -5.6 g (95% CI:-10.3, -1.0 g) and AAPI fathers, -7.6 g (95% CI: -13.1, -2.1 g) during 3^rd trimester and among births where father's race was not reported, -14.2 g (95% CI: -24.0, -4.4 g).

CONCLUSIONS

These data suggest that paternal characteristics should be used, in addition to maternal characteristics, to describe the risks of adverse birth outcomes. Additionally, our study suggests that serious consideration should be given to investigating environmental and social mechanisms, such as air pollution exposures, as potential contributors to disparities in birth outcomes among AAPI populations.

Prenatal air pollution exposure and neonatal health

Air pollution has been shown to have adverse effects on many health outcomes including respiratory effects, cardiovascular effects, and mortality. However, evidence on the effects of prenatal exposure is still limited. We investigate the causal impact of prenatal exposure to air pollution on neonatal health in Italy in the 2000s. We exploit variation in rainfall shocks to instrument for non-random air pollution exposure. Our empirical setting combines detailed information on mother's residential location from birth certificates with PM₁₀ concentrations from air pollution monitors. Ten additional units in the average PM₁₀ level (approximately one standard deviation) would decrease birth weight by about 0.5% and gestational age by 0.16%; it would increase the prevalence of low birth weight by 22% and of preterm birth by 16%. The effects are stronger in magnitude for third trimester exposure and for less educated mothers. These findings suggest that the health impacts of air pollution on newborns are unequally distributed in the population.

Pre- and Postnatal Fine Particulate Matter Exposure and Childhood Cognitive and Adaptive Function

Increasing evidence exists for an association between early life fine particulate matter (PM_2.5) exposure and several neurodevelopmental outcomes, including autism spectrum disorder (ASD); however, the association between PM_2.5 and adaptive and cognitive function remains poorly understood. Participants included 658 children with ASD, 771 with a non-ASD developmental disorder, and 849 population controls from the Study to Explore Early Development. Adaptive functioning was assessed in ASD cases using the Vineland Adaptive Behavior Scales (VABS); cognitive functioning was assessed in all groups using the Mullen Scales of Early Learning (MSEL). A satellite-based model was used to assign PM_2.5 exposure averages during pregnancy, each trimester, and the first year of life. Linear regression was used to estimate beta coefficients and 95% confidence intervals, adjusting for maternal age, education, prenatal tobacco use, race-ethnicity, study site, and season of birth. PM_2.5 exposure was associated with poorer VABS scores for several domains, including daily living skills and socialization. Associations were present between prenatal PM_2.5 and lower MSEL scores for all groups combined; results were most prominent for population controls in stratified analyses. These data suggest that early life PM_2.5 exposure is associated with specific aspects of cognitive and adaptive functioning in children with and without ASD.

Critical Time Windows for Air Pollution Exposure and Birth Weight in a Multicity Canadian Pregnancy Cohort

BACKGROUND

Maternal prenatal exposure to air pollution has been associated with adverse birth outcomes. However, previous studies focused on a priori time intervals such as trimesters reported inconsistent associations.

OBJECTIVES

We investigated time-varying vulnerability of birth weight to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) using flexible time intervals.

METHODS

We analyzed 1,300 live, full-term births from Maternal-Infant Research on Environmental Chemicals, a Canadian prospective pregnancy cohort spanning 10 cities (2008-2011). Daily PM2.5 and NO2 concentrations were estimated from ground-level monitoring, satellite models, and land-use regression, and assigned to participants from pre-pregnancy through delivery. We developed a flexible two-stage modeling method-using a Bayesian Metropolis-Hastings algorithm and empirical density threshold-to identify time-dependent vulnerability to air pollution without specifying exposure periods a priori. This approach identified critical windows with varying lengths (2-363 days) and critical windows that fell within, or straddled, predetermined time periods (i.e., trimesters). We adjusted the models for detailed infant and maternal covariates.

RESULTS

Critical windows associated with reduced birth weight were identified during mid- to late-pregnancy for both PM2.5 and NO2: -6 g (95% credible interval: -11, -1 g) and -5 g (-10, -0.1 g) per µg/m3 PM2.5 during gestational days 91-139 and 249-272, respectively; and -3 g (-5, -1 g) per ppb NO2 during days 55-145.

DISCUSSION

We used a novel, flexible selection method to identify critical windows when maternal exposures to air pollution were associated with decrements in birth weight. Our results suggest that air pollution impacts on fetal development may not be adequately captured by trimester-based analyses.

Maternal exposure to air pollution and congenital heart diseases in Henan, China: A register-based case-control study

BACKGROUND

Association between ambient air pollution and congenital heart diseases (CHDs) remains inconclusive, and the critical exposure windows has not been well studied.

OBJECTIVES

This case-control study aimed to assess the effect of ambient air pollution exposure on the risk of CHDs and the subtypes in Henan, China, and further to explore potential susceptible windows.

METHODS

Daily average particulate matter with an aerodynamic diameter of ≤2.5 µm (PM_2.5) and ≤10 µm (PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO) and ozone (O₃) were collected by Chinese Air Quality Reanalysis datasets. Binary logistic regression was used to examine trimester-specific associations between per 10 μg/m³ increase in air pollutants and CHDs as well as the major subtypes. Distributed lag models incorporating logistic regression were applied to explore weekly-specific associations.

RESULTS

A total of 196,069 singleton live births were included during 2013-2018, 643 CHDs were identified (3.3‰). We found that first and second trimester CO exposure increased overall CHDs risk, the adjusted odds ratio (aOR) and 95% confidence interval (CI) were 1.066 (1.010-1.125) and 1.065 (1.012-1.122). For CHDs subtypes, we observed that NO₂ and CO in first trimester, PM_2.5 and PM₁₀ in the second trimester exposure were associated with the risk of atrial septal defect (ASD), the susceptible windows of air pollutants and ASD mainly occurred in the 1st- 6th gestational weeks. No positive association was observed for air pollution and tetralogy of Fallot.

CONCLUSION

Our findings suggest that ambient air pollution exposure is associated with the risk of CHDs especially for ASD, and the susceptible windows generally occurred in first trimester. Further well-designed longitudinal studies are warranted to confirm our findings.

Exposure to PM2.5 during Pregnancy and Fetal Growth in Eastern Massachusetts, USA

BACKGROUND

Prior studies have examined the association between fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] and fetal growth with either limited spatial or temporal resolution.

OBJECTIVES

In this study, we examined the association between PM2.5 exposure during pregnancy and fetal growth measures (ultrasound parameters and birth weight) in a pregnancy cohort using spatiotemporally resolved PM2.5 in Eastern Massachusetts, USA.

METHODS

We used ultrasound measures of biparietal diameter (BPD), head circumference, femur length, and abdominal circumference (AC), in addition to birth weight, from 9,446 pregnancies that were delivered at the Beth Israel Deaconess Medical Center from 2011-2016. We used linear mixed-effects models to examine the associations of PM2.5 in two exposure windows (the first 16 wk of pregnancy and the cumulative exposure up until the assessment of fetal growth) with anatomic scans (ultrasound measures at<24 wk), growth scans (ultrasound measures at≥24wk), and birth weight. All models were adjusted for sociodemographic characteristics, long-term trends, and temperature.

RESULTS

Higher PM2.5 exposure in the first 16 wk was associated with smaller fetal growth measures, where associations were particularly strong for BPD, AC, and birth weight. For example, a 5-μg/m3 increase in PM2.5 was associated with a lower mean BPD z-score of -0.19 (95% CI: -0.31, -0.06) before 24 wk, a lower mean AC z-score of -0.15 (95% CI: -0.28, -0.01) after 24 wk, and a lower mean birth weight z-score of -0.11 (95% CI: -0.20, -0.01). Analyses examining the associations with cumulative PM2.5 exposure up until the assessment of fetal growth produced attenuated associations.

CONCLUSIONS

Higher gestational exposure to PM2.5 was associated with smaller fetal growth measures at levels below the current national standards. https://doi.org/10.1289/EHP9824.

Maternal and Childhood Ambient Air Pollution Exposure and Mental Health Symptoms and Psychomotor Development in Children: An Australian Population-Based Longitudinal Study

BACKGROUND

Accumulating evidence indicates early life exposure to air pollution, a suspected neurotoxicant, is negatively associated with children's neurodevelopment.

OBJECTIVES

To explore the role of multiple exposure periods to ambient particulate matter with diameter <2.5 μm (PM_2.5) and nitrogen dioxide (NO₂) on emotion and behaviour, and early development in children <13 years.

METHODS

We used data from Mothers and their Children's Health (MatCH) study, a 2016/17 sub-study from a prospective longitudinal study, the Australian Longitudinal Study on Women's Health. Annual PM_2.5 and NO₂ estimates since 1996 were obtained from a land-use regression model. Maternal residential proximity to roadways were used as a proxy measure of exposure to traffic-related air pollution. Child outcomes were maternal-rated emotional and behavioural problems (Strengths and Difficulties Questionnaire; SDQ, aged 2-12 years, n = 5471 children) and developmental delay in communication and gross motor skills (Ages and Stages Questionnaire; ASQ, aged 1-66 months, n = 1265 children). Defined exposure periods were early life exposure ('during pregnancy' and 'first year of life') and 'children's lifetime exposure'. Ambient air pollution was divided into tertiles and logistic regression was performed to estimate odds ratio (OR) for each child outcome, adjusting for potential confounders.

RESULTS

Children exposed to moderate and high PM_2.5 exposure, compared to low exposure, across all periods, had higher odds of emotional and behavioural problems, and gross motor delay. Children's lifetime exposure to moderate levels of PM_2.5 (5.9-7.1 µg/m³) was associated with 1.27 (95% confidence interval 1.03, 1.57) fold higher odds of emotional/behavioural problems. Similar associations were found for moderate PM_2.5 levels at 'first year of life' in a two-pollutant model only (OR: 1.30; 1.05, 1.60). However, there was insufficient evidence to suggest that NO₂ exposure or living within 200 m of major roads was associated with emotional and behaviour problems or developmental delay across any exposure periods.

CONCLUSION

We found isolated evidence that early life and childhood exposure to PM_2.5 may be associated with emotional and behavioural problems and delays in gross motor skills, but most associations were null. Due to the limited number of longitudinal studies on low-exposure settings, further studies with more temporally refined exposure assessment are warranted.

Congenital anomalies associated with ambient temperature variability during fetal organogenesis period of pregnancy: Evidence from 4.78 million births

BACKGROUNDS

Evidence for the effects of temperature variability on risk of congenital anomalies is lacking. We aimed to examine the association of temperature variability during fetal organogenesis period (weeks 3-8 post-conception) with major congenital anomalies.

METHODS

A retrospective cohort study comprising 4,787,356 singleton live-births and stillbirths in China was performed. We defined two temperature variability indices within gestational week i: the standard deviation (SD) of daily temperature (TVSD_i) and the maximum day-to-day temperature difference (TVD_i). At 6-week long timescales, we computed the SD of daily temperature (TVSD_3-8) and the average value of TVD_i (TVD_3-8). We matched two temperature variability indices, pollutant exposure levels over entire exposure window and data of each mother-infant pairs. An extended generalized estimating equation log-binomial regression model was constructed to explore their associations after adjusting for individual characters, temperature extremes and air pollutants. Stratified and sensitivity analyses were also performed.

RESULTS

59,571 neonates were registered as major congenital anomalies besides genetic and chromosomal anomalies. At weekly levels, the highest risk estimates of two temperature variability indices occurred at the 5th week for most anomaly groups. All TVSD₅, TVD₅, and maximum weekly TVSD and TVD were significantly associated with all anomaly groups; with the increment of 1 °C, the estimated risk ratio (RR) and corresponding 95% confidence interval (CI) ranges from 1.03 (1.01-1.05) to 1.19 (1.08-1.31). At 6-week scales, TVSD_3-8 and TVD_3-8 were associated with most anomaly subgroups. Overall, the strongest associations were estimated for isolated defects among morphology subgroups and cardiac defects among type subgroups.

CONCLUSIONS

Exposure to temperature variability during fetal organogenesis period of pregnancy is associated with increased risk of major congenital defects. Our findings provide a research foundation for public health policies, and further mechanism investigation.

Hyperlocalized Measures of Air Pollution and Preeclampsia in Oakland, California

Exposure to nitrogen dioxide (NO₂), black carbon (BC), and ultrafine particles (UFPs) during pregnancy may increase the risk of preeclampsia, but previous studies have not assessed hyperlocalized differences in pollutant levels, which may cause exposure misclassification. We used data from Google Street View cars with mobile air monitors that repeatedly sampled NO₂, BC, and UFPs every 30 m in Downtown and West Oakland neighborhoods during 2015-2017. Data were linked to electronic health records of pregnant women in the 2014-2016 Sutter Health population, who resided within 120 m of monitoring data (N = 1095), to identify preeclampsia cases. We used G-computation with log-binomial regression to estimate risk differences (RDs) associated with a hypothetical intervention reducing pollutant levels to the 25th percentile observed in our sample on preeclampsia risk, overall and stratified by race/ethnicity. Prevalence of preeclampsia was 6.8%. Median (interquartile range) levels of NO₂, BC, and UFPs were 10.8 ppb (9.0, 13.0), 0.34 μg/m³ (0.27, 0.42), and 29.2 # × 10³/cm³ (26.6, 32.6), respectively. Changes in the risk of preeclampsia achievable by limiting each pollutant to the 25th percentile were NO₂ RD = -1.5 per 100 women (95% confidence interval (CI): -2.5, -0.5); BC RD = -1.0 (95% CI: -2.2, 0.02); and UFP RD = -0.5 (95% CI: -1.8, 0.7). Estimated effects were the largest for non-Latina Black mothers: NO₂ RD = -2.8 (95% CI: -5.2, -0.3) and BC RD = -3.0 (95% CI: -6.4, 0.4).

The effect of prenatal temperature and PM2.5 exposure on birthweight: Weekly windows of exposure throughout the pregnancy

BACKGROUND

Birthweight is a strong predictor of normal growth, healthy development, and survival. Several studies have found associations between temperature, fine particulate matter (PM_2.5), and birth weight. However, the relevant timing of exposures varies between studies and is yet unclear. Therefore, we assessed the difference in term birthweight (TBW) associated with weekly exposure to temperature and PM_2.5 throughout 37 weeks of gestation.

METHODS

We included all singleton live term births in Massachusetts, U.S between 2004 and 2015 (n = 712,438). Weekly PM_2.5 and temperature predictions were estimated on a 1 km grid from satellite-based models. We utilized a distributed lag nonlinear model (DLNM) to estimate the difference in TBW associated with weekly exposures from the last menstrual period to 37 weeks of gestation.

RESULTS

We found a nonlinear association with prenatal temperature exposure. Larger effects were observed in warmer temperatures, where higher temperatures were negatively associated with TBW. Temperature effects were larger in the first and final weeks of gestation. We observed a negative difference in TBW associated with PM_2.5 exposure. Overall, a 1 µg/m³ increase in prenatal exposure was associated with 3.9 g lower TBW (95% CI -5.0 g; -2.9 g). PM_2.5 effects were larger in the final weeks of gestation.

CONCLUSION

We found heat and PM_2.5 exposure to be related to lower TBW. Our findings suggest that women are more susceptible to both exposures towards the end of pregnancy. Susceptibility to heat was higher in the initial weeks of pregnancy as well. These critical windows of susceptibility can be communicated to pregnant women during routine prenatal visits to increase awareness and target interventions to reduce exposures.

Quantifying the influence of bias in reproductive and perinatal epidemiology through simulation

PURPOSE

The application of simulated data in epidemiological studies enables the illustration and quantification of the magnitude of various types of bias commonly found in observational studies. This was a review of the application of simulation methods to the quantification of bias in reproductive and perinatal epidemiology and an assessment of value gained.

METHODS

A search of published studies available in English was conducted in August 2020 using PubMed, Medline, Embase, CINAHL, and Scopus. A gray literature search of Google and Google Scholar, and a hand search using the reference lists of included studies was undertaken.

RESULTS

Thirty-nine papers were included in this study, covering information (n = 14), selection (n = 14), confounding (n = 9), protection (n = 1), and attenuation bias (n = 1). The methods of simulating data and reporting of results varied, with more recent studies including causal diagrams. Few studies included code for replication.

CONCLUSIONS

Although there has been an increasing application of simulation in reproductive and perinatal epidemiology since 2015, overall this remains an underexplored area. Further efforts are required to increase knowledge of how the application of simulation can quantify the influence of bias, including improved design, analysis and reporting. This will improve causal interpretation in reproductive and perinatal studies.

Joint effects of ambient air pollution and maternal smoking on neonatal adiposity and childhood BMI trajectories in the Healthy Start study

Coexposure to air pollution and tobacco smoke may influence early-life growth, but few studies have investigated their joint effects. We examined the interaction between fetal exposure to maternal smoking and ozone (O₃) or fine particulate matter (PM_2.5) on birth weight, neonatal adiposity, and body mass index (BMI) trajectories through age 3 years.

Methods

Participants were 526 mother-child pairs, born ≥37 weeks. Cotinine was measured at ~27 weeks gestation. Whole pregnancy and trimester-specific O₃ and PM_2.5 were estimated via. inverse-distance weighted interpolation from stationary monitors. Neonatal adiposity (fat mass percentage) was measured via. air displacement plethysmography. Child weight and length/height were abstracted from medical records. Interaction was assessed by introducing cotinine (<31.5 vs. ≥31.5 ng/mL [indicating active smoking]), O₃/PM_2.5 (low [tertiles 1-2] vs. high [tertile 3]), and their product term in linear regression models for birth weight and neonatal adiposity and mixed-effects models for BMI trajectories.

Results

The rate of BMI growth among offspring jointly exposed to maternal smoking and high PM_2.5 (between 8.1 and 12.7 μg/m³) in the third trimester was more rapid than would be expected due to the individual exposures alone (0.8 kg/m² per square root year; 95% CI = 0.1, 1.5; P for interaction = 0.03). We did not detect interactions between maternal smoking and O₃ or PM_2.5 at any other time on birth weight, neonatal adiposity, or BMI trajectories.

Conclusions

Although PM_2.5 was generally below the EPA annual air quality standards of 12.0 μg/m³, exposure during the third trimester may influence BMI trajectories when combined with maternal smoking.

Early Life Exposure to Air Pollution and Autism Spectrum Disorder: Findings from a Multisite Case-Control Study

BACKGROUND

Epidemiologic studies have reported associations between prenatal and early postnatal air pollution exposure and autism spectrum disorder (ASD); however, findings differ by pollutant and developmental window.

OBJECTIVES

We examined associations between early life exposure to particulate matter ≤2.5 µm in diameter (PM2.5) and ozone in association with ASD across multiple US regions.

METHODS

Our study participants included 674 children with confirmed ASD and 855 population controls from the Study to Explore Early Development, a multi-site case-control study of children born from 2003 to 2006 in the United States. We used a satellite-based model to assign air pollutant exposure averages during several critical periods of neurodevelopment: 3 months before pregnancy; each trimester of pregnancy; the entire pregnancy; and the first year of life. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for study site, maternal age, maternal education, maternal race/ethnicity, maternal smoking, and month and year of birth.

RESULTS

The air pollution-ASD associations appeared to vary by exposure time period. Ozone exposure during the third trimester was associated with ASD, with an OR of 1.2 (95% CI: 1.1, 1.4) per 6.6 ppb increase in ozone. We additionally observed a positive association with PM2.5 exposure during the first year of life (OR = 1.3 [95% CI: 1.0, 1.6] per 1.6 µg/m increase in PM2.5).

CONCLUSIONS

Our study corroborates previous findings of a positive association between early life air pollution exposure and ASD, and identifies a potential critical window of exposure during the late prenatal and early postnatal periods.

The Dynamics of Infectious Diseases Associated With Injection Drug Use in Lawrence and Lowell, Massachusetts

Background

There are a wide variety of infectious complications of injection drug use. Understanding the trajectory of these complications might inform the development of an early warning system for human immunodeficiency virus (HIV) outbreaks that occur regularly among people who inject drugs (PWID).

Methods

A distributed lag Poisson regression model in the Bayesian setting was used to examine temporal patterns in the incidence of injection-associated infectious diseases and their association with HIV cases in Lawrence and Lowell, Massachusetts between 2005 and 2018.

Results

Current-month HIV counts are associated with fatal overdoses approximately 8 months prior, cases of infective endocarditis 10 months prior, and cases of skin and soft tissue infections and incision and drainage procedures associated with these infections 12 months prior.

Conclusions

Collecting data on these other complications associated with injection drug use by public health departments may be important to consider because these complications may serve as input to a sentinel system to trigger early intervention and avert potential outbreaks of HIV.

Association of maternal ozone exposure with term low birth weight and susceptible window identification

BACKGROUND

Ozone pollution keeps deteriorating in the context of climate change. Maternal ozone exposure may be associated with low birth weight (LBW), but the results are still inconsistent. The identification of the critical exposure windows, a specific period of particular susceptibility during pregnancy, remains unresolved. We aimed to evaluate whether ozone exposure was associated with term LBW and further identify the susceptible exposure windows.

METHODS

A retrospective cohort study was conducted in Guangzhou, a megacity in the most populous and economically developed city clusters in China. We included 444,096 singleton live births between January 2015 and July 2017. From 11 fixed stations, we collected daily 1-h maximum and 8-h maximum moving average ozone level (O₃-1 h and O₃-8 h) and calculated exposures for each participant based on their district of residence during pregnancy. We used traditional Logistic regression to estimate the trimester-specific association between ozone exposure and term LBW, and further estimated monthly- and weekly association by distributed lag models (DLMs) with Logistic regression. Odds ratios (ORs) and 95% confidence intervals (CIs) of term LBW were calculated for an interquartile range (IQR) increase in ozone exposure. Stratified analyses and heterogeneity tests were conducted by maternal age and infant sex.

RESULTS

The incidence of term LBW was 1.9%. During the study period, the mean O₃-1 h and O₃-8 h levels were 112.6 µg/m³ and 84.5 µg/m³, respectively. Increased O₃-1 h (IQR: 90 µg/m³) and O₃-8 h (73 µg/m³) exposure during the second trimester were associated with increased risk of term LBW. At a monthly level, the term LBW risk was associated with O₃-1 h exposure during the 4th-6th month and O₃-8 h exposure during the 6th month. By estimating the weekly-specific association, we observed that critical exposure windows were the 15th- 26th gestational weeks for O₃-1 h, and the 20th-26th weeks for O₃-8 h, respectively. Estimated ORs and 95% CIs ranged from 1.012 (1.000, 1.024) to 1.023 (1.007, 1.039). When examined by subgroups, the effects were present among women ≥ 35 years or < 25 years old and those with female babies.

CONCLUSIONS

This study provides compelling evidence that exposure to O₃ was associated with increased risk of term LBW, and gestational weeks 15th- 26th was found to be particularly susceptible. These findings provide a research basis for further mechanism examination, public health interventions, and targeted environmental policy-making.

Associations Between Ambient Air Pollutant Concentrations and Birth Weight: A Quantile Regression Analysis

INTRODUCTION

We investigated the extent to which associations of ambient air pollutant concentrations and birth weight varied across birth weight quantiles.

METHODS

We analyzed singleton births ≥27 weeks of gestation from 20-county metropolitan Atlanta with conception dates between January 1, 2002 and February 28, 2006 (N = 273,711). Trimester-specific and total pregnancy average concentrations for 10 pollutants, obtained from ground observations that were interpolated using 12-km Community Multiscale Air Quality model outputs, were assigned using maternal residence at delivery. We estimated associations between interquartile range width (IQRw) increases in pollutant concentrations and changes in birth weight using quantile regression.

RESULTS

Gestational age-adjusted associations were of greater magnitude at higher percentiles of the birth weight distribution. Pollutants with large vehicle source contributions (carbon monoxide, nitrogen dioxide, PM2.5 elemental carbon, and total PM2.5 mass), as well as PM2.5 sulfate and PM2.5 ammonium, were associated with birth weight decreases for the higher birth weight percentiles. For example, whereas the decrease in mean birthweight per IQRw increase in PM2.5 averaged over pregnancy was -7.8 g (95% confidence interval = -13.6, -2.0 g), the quantile-specific associations were: 10th percentile -2.4 g (-11.5, 6.7 g); 50th percentile -8.9 g (-15.7, -2.0g); and 90th percentile -19.3 g (-30.6, -7.9 g). Associations for the intermediate and high birth weight quantiles were not sensitive to gestational age adjustment. For some pollutants, we saw associations at the lowest quantile (10th percentile) when not adjusting for gestational age.

CONCLUSIONS

Associations between air pollution and reduced birth weight were of greater magnitude for newborns at relatively heavy birth weights.

Sex-specific influence of prenatal air pollutant exposure on neonatal neurobehavioral development and the sensitive window

Increasing evidence indicates the adverse effect of air pollution exposure during pregnancy on neurologic development among children. However, the impact on neurobehavioral development in fetus remains unknown. In 2017, a total of 1193 mother-newborns pairs were enrolled in a birth cohort study in Changsha, China. Exposures to PM_2.5, PM_10, SO₂, CO and NO₂ were determined by using inverse distance weighted method based on local monitoring station data. Neurobehavioral measure was administered at 48-72 h postpartum by utilizing the neonatal behavioral neurological assessment (NBNA). Basic information and covariates were collected by face to face interview. Generalized linear regression and multivariable restricted cubic spline function were performed to explore the trimester-specific association and dose-response relationship of maternal air pollution exposure with NBNA score, respectively. In adjusted three-pollutant model, PM_2.5 exposure in trimester 2 was negatively associated with behavior score (β, -0.003; 95% CI, -0.006, -0.001) and the inverse relation was more pronounced in male infants. In addition, PM_2.5 level in the 2nd trimester was negatively related to activetone score (β, -0.012; 95% CI, -0.021, -0.002) in a dose-dependent manner for both genders. Collectively, our results demonstrated that prenatal exposure to PM_2.5 was linked to poor neurobehavioral performance of newborns. The second trimester was the most sensitive time window for the developments of behavior and activetone, and male subject was more vulnerable as compared to females.

Quantile regression analysis of the socioeconomic inequalities in air pollution and birth weight

BACKGROUND

An association between maternal exposure to air pollution and the birth weight distribution has been reported, but the extent to which this relationship varies according to socioeconomic status (SES) is unknown. This study examined the relationship using the data from a Korean birth cohort.

METHODS

Data for singleton births in Seoul from 2007 to 2017 (n = 1739) were analyzed. Maternal exposures to particulate matter with an aerodynamic diameter <10 µm (PM₁₀) and <2.5 µm (PM_2.5), as well as to nitrogen dioxide (NO₂) and ozone (O₃) for each trimester and the entire pregnancy were estimated using residential address, gestational age, and the birth date. The associations between the interquartile range (IQR) increases in pollutant concentrations and the changes in birth weight were examined using linear regression and quantile regression models. The socioeconomic disparities in the associations were investigated using a derived SES variable based on the composite of parental education and occupation. This SES variable was then interacted with the air pollutant.

RESULTS

In the gestational age-adjusted models, particulate air pollutants (PM₁₀ and PM_2.5) and O₃ were associated with birth weight decreases for the lower birth weight percentiles. For example, the decrease in mean birthweight per IQR increase in PM_2.5 during second trimester was -21.1 g (95% confidence interval (CI) = -41.8, -0.4), whereas the quantile-specific associations were: 10th percentile -27.0 g (95% CI = -46.6, -7.3); 50th percentile -22.2 g (95% CI = -39.6, -4.8); and 90th percentile -22.9 g (95% CI = -45.5, -0.2). Particulate air pollutants and O₃ showed a pattern of socioeconomic inequalities; the reduced birth weight was of greater magnitude for children from a low SES group.

CONCLUSIONS

Negative associations between particulate air pollutants and O₃ and birth weight were consistently greater at the lower quantiles of the birth weight distribution, especially in lower SES group.

Fine particulate matter exposure and lipid levels among children in Mexico city

Background

Studies have identified associations between air pollution and lipid levels in adults, suggesting a mechanism by which air pollution contributes to cardiovascular disease. However, little is known about the association between early life air pollution exposure and lipid levels in children.

Methods

Participants included 465 mother-child pairs from a prospective birth cohort in Mexico City. Daily particulate matter <2.5 µm in diameter (PM_2.5) predictions were estimated using a satellite-based exposure model and averaged over trimesters, the entire pregnancy, and the first year of life. We assessed associations with several lipid measures at 4-6 years of age, including total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), non-HDL-C, high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG). Linear regression models were used to estimate change in lipid levels with each interquartile range increase in PM_2.5. We additionally assessed if associations between PM_2.5 and lipid levels varied across lipid quantiles using quantile regression. Models were adjusted for maternal education, body mass index, and age, child's age at study visit, prenatal environmental tobacco smoke, and season of conception.

Results

PM_2.5 exposure during the third trimester was associated with increases in childhood total cholesterol, LDL-C, and non-HDL-C, and decreases in HDL-C and triglycerides. There was additionally an increasing trend in the effect estimate across higher quantiles of total cholesterol, LDL-C, and non-HDL-C during the third trimester and entire pregnancy period. There were no consistent associations for first year of life exposures.

Conclusion

In this longitudinal birth cohort in Mexico City, associations between prenatal PM_2.5 and childhood lipid (total cholesterol, LDL-C, non-HDL-C) levels were greater for children at higher lipid quantiles.

A spatially varying distributed lag model with application to an air pollution and term low birth weight study

Distributed lag models have been used to identify critical pregnancy periods of exposure (i.e. critical exposure windows) to air pollution in studies of pregnancy outcomes. However, much of the previous work in this area has ignored the possibility of spatial variability in the lagged health effect parameters that may result from exposure characteristics and/or residual confounding. We develop a spatially varying Gaussian process model for critical windows called 'SpGPCW' and use it to investigate geographic variability in the association between term low birth weight and average weekly concentrations of ozone and PM_2:5 during pregnancy by using birth records from North Carolina. SpGPCW is designed to accommodate areal level spatial correlation between lagged health effect parameters and temporal smoothness in risk estimation across pregnancy. Through simulation and a real data application, we show that the consequences of ignoring spatial variability in the lagged health effect parameters include less reliable inference for the parameters and diminished ability to identify true critical window sets, and we investigate the use of existing Bayesian model comparison techniques as tools for determining the presence of spatial variability. We find that exposure to PM_2:5 is associated with elevated term low birth weight risk in selected weeks and counties and that ignoring spatial variability results in null associations during these periods. An R package (SpGPCW) has been developed to implement the new method.

Ambient Fine Particulate Matter and Preterm Birth in California: Identification of Critical Exposure Windows

Exposure to ambient fine particulate matter (particulate matter ≤2.5 μm in aerodynamic diameter (PM2.5)) during pregnancy is associated with preterm birth (PTB), a leading cause of infant morbidity and mortality. Results from studies attempting to identify etiologically relevant exposure periods of vulnerability have been inconsistent, possibly because of failure to consider the time-to-event nature of the outcome and lagged exposure effects of PM2.5. In this study, we aimed to identify critical exposure windows for weekly PM2.5 exposure and PTB in California using California birth cohort data from 2005-2010. Associations were assessed using distributed-lag Cox proportional hazards models. We assessed effect-measure modification by race/ethnicity by calculating the weekly relative excess risk due to interaction. For a 10-μg/m3 increase in PM2.5 exposure over the entire period of gestation, PTB risk increased by 11% (hazard ratio = 1.11, 95% confidence interval: 1.09, 1.14). Gestational weeks 17-24 and 36 were associated with increased vulnerability to PM2.5 exposure. We find that non-Hispanic black mothers may be more susceptible to effects of PM2.5 exposure than non-Hispanic white mothers, particularly at the end of pregnancy. These findings extend our knowledge about the existence of specific exposure periods during pregnancy that have the greatest impact on preterm birth.

A quantile regression approach to examine fine particles, term low birth weight, and racial/ethnic disparities

Background

Exposure to fine particulate matter (PM_2.5) during pregnancy has been shown to be associated with reduced birth weight and racial/ethnic minorities have been found to be more vulnerable. Previous studies have focused on the mean value of birth weight associated with PM_2.5, which may mask meaningful differences. We applied a quantile regression approach to investigate the variation by percentile of birth weight and compared non-Hispanic (NH) Black, NH White, and Hispanic mothers.

Methods

Data for singleton births in California from October 24, 2005 to February 27, 2010 were collected from the birth records accessed from the California Department of Public Health. Air pollution monitoring data collected by the California Air Resources Board and interpolated for each zip code using an inverse-distance weighting approach, and linked to maternal zip code of residence reported on the birth certificate. Multilevel linear regression models were conducted with mother's residential zip code tabulation area as a random effect. Multilevel quantile regression models were used to analyze the association at different percentiles of birth weight (5th, 10th, 25th, 50th, 75th, 90th, 95th), as well as examine the heterogeneity in this association between racial/ethnic groups.

Results

Linear regression revealed that a 10 μg/m³ increase in PM_2.5 exposure during pregnancy is associated with a mean birth weight decrease of 7.31 g [95% confidence interval (CI): 8.10, 6.51] and NH Black mothers are the most vulnerable. Results of the quantile regression are not constant across quantiles. For NH Black mothers whose infants had the lowest birthweight of less than 2673 g (5th percentile), a 10 μg/m³ increase in PM_2.5 exposure is associated with a decrease of 18.57 g [95% CI: 22.23, 14.91], while it is associated with a decrease of 7.77 g [95% CI: 8.73, 6.79] for NH White mothers and 7.76 [8.52, 7.00] decrease for Hispanic mothers at the same quantile.

Conclusion

Results of the quantile regression revealed greater disparities, particularly for infants with the lowest birth weight. By identifying vulnerable populations, we can promote and implement policies to confront these health disparities.

Statistical Approaches for Investigating Periods of Susceptibility in Children's Environmental Health Research

PURPOSE OF REVIEW

Children's environmental health researchers are increasingly interested in identifying time intervals during which individuals are most susceptible to adverse impacts of environmental exposures. We review recent advances in methods for assessing susceptible periods.

RECENT FINDINGS

We identified three general classes of modeling approaches aimed at identifying susceptible periods in children's environmental health research: multiple informant models, distributed lag models, and Bayesian approaches. Benefits over traditional regression modeling include the ability to formally test period effect differences, to incorporate highly time-resolved exposure data, or to address correlation among exposure periods or exposure mixtures. Several statistical approaches exist for investigating periods of susceptibility. Assessment of susceptible periods would be advanced by additional basic biological research, further development of statistical methods to assess susceptibility to complex exposure mixtures, validation studies evaluating model assumptions, replication studies in different populations, and consideration of susceptible periods from before conception to disease onset.

Economic Downturns and Inequities in Birth Outcomes: Evidence From 149 Million US Births

Using birth certificate data for nearly all registered US births from 1976 to 2016 and monthly data on state unemployment rates, we reexamined the link between macroeconomic variation and birth outcomes. We hypothesized that economic downturns reduce exposure to work-related stressors and pollution while increasing exposure to socioeconomic stressors like job loss. Because of preexisting inequalities in health and other resources, we expected that less-educated mothers and black mothers would be more exposed to macroeconomic variation. Using fixed-effect regression models, we found that a 1-percentage-point increase in state unemployment during the first trimester of pregnancy increased the probability of preterm birth by 0.1 percentage points, while increases in the state unemployment rate during the second/third trimester reduced the probability of preterm birth by 0.06 percentage points. During the period encompassing the Great Recession, the magnitude of these associations doubled in size. We found substantial variation in the impact of economic conditions across different groups, with highly educated white women least affected and less-educated black women most affected. The results highlight the increased relevance of economic conditions for birth outcomes and population health as well as continuing, large inequities in the exposure and impact of macroeconomic fluctuations on birth outcomes.

Critical window variable selection: estimating the impact of air pollution on very preterm birth

Understanding the impact that environmental exposure during different stages of pregnancy has on the risk of adverse birth outcomes is vital for protection of the fetus and for the development of mechanistic explanations of exposure-disease relationships. As a result, statistical models to estimate critical windows of susceptibility have been developed for several different reproductive outcomes and pollutants. However, these current methods fail to adequately address the primary objective of this line of research; how to statistically identify a critical window of susceptibility. In this article, we introduce critical window variable selection (CWVS), a hierarchical Bayesian framework that directly addresses this question while simultaneously providing improved estimation of the risk parameters. Through simulation, we show that CWVS outperforms existing competing techniques in the setting of highly temporally correlated exposures in terms of (i) correctly identifying critical windows and (ii) accurately estimating risk parameters. We apply all competing methods to a case/control analysis of pregnant women in North Carolina, 2005-2008, with respect to the development of very preterm birth and exposure to ambient ozone and particulate matter $<$ 2.5 $\mu$m in aerodynamic diameter, and identify/estimate the critical windows of susceptibility. The newly developed method is implemented in the R package CWVS.