Measurement error in mobile source air pollution exposure estimates due to residential mobility during pregnancy

Maternal residential exposure to solvents from industrial sources during pregnancy and childhood cancer risk in California

BACKGROUND

Maternal solvent exposure has been suspected to increase offspring cancer risk. The study aimed to evaluate the associations between maternal residential exposure to solvents from industrial pollution during pregnancy and childhood cancer.

METHODS

The present study included 15,744 cancer cases (aged 0-19 years at diagnosis) identified from California Cancer Registry and 283,141 controls randomly selected from California Birth Registry (20:1 frequency-matched by birth year: 1998-2016). We examined industrial releases of tetrachloroethylene and 1,1,1-trichloroethane within 3 km of the birth address, while we used a 5 km buffer for carbon disulfide. We calculated the total exposure from all linked Toxic Release Inventory sites during each index pregnancy and assigned "ever/never" and "high/low exposed/unexposed" exposure, using median values. We performed quadratic decay models to estimate cancer risks associated with maternal solvent exposure in pregnancy.

RESULTS

1,1,1-Trichloroethane was associated with rhabdomyosarcoma (adjusted Odds Ratio (aOR): 1.96; 95% Confidence Interval (CI): 1.16, 3.32) in the "ever exposed" group. Ever exposure to carbon disulfide was associated with increased risks of medulloblastoma (OR = 1.85, 95% CI 1.01, 3.40) and ependymoma (OR = 1.63, 95% CI 0.97, 2.74).

CONCLUSIONS

Overall, our findings suggested maternal residential exposure to solvents from industrial sources might be associated with elevated childhood cancer risks.

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.

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.

Wildfire smoke exposure and early childhood respiratory health: a study of prescription claims data

Wildfire smoke is associated with short-term respiratory outcomes including asthma exacerbation in children. As investigations into developmental wildfire smoke exposure on children's longer-term respiratory health are sparse, we investigated associations between developmental wildfire smoke exposure and first use of respiratory medications. Prescription claims from IBM MarketScan Commercial Claims and Encounters database were linked with wildfire smoke plume data from NASA satellites based on Metropolitan Statistical Area (MSA). A retrospective cohort of live infants (2010-2016) born into MSAs in six western states (U.S.A.), having prescription insurance, and whose birthdate was estimable from claims data was constructed (N = 184,703); of these, gestational age was estimated for 113,154 infants. The residential MSA, gestational age, and birthdate were used to estimate average weekly smoke exposure days (smoke-day) for each developmental period: three trimesters, and two sequential 12-week periods post-birth. Medications treating respiratory tract inflammation were classified using active ingredient and mode of administration into three categories:: 'upper respiratory', 'lower respiratory', 'systemic anti-inflammatory'. To evaluate associations between wildfire smoke exposure and medication usage, Cox models associating smoke-days with first observed prescription of each medication category were adjusted for infant sex, birth-season, and birthyear with a random intercept for MSA. Smoke exposure during postnatal periods was associated with earlier first use of upper respiratory medications (1-12 weeks: hazard ratio (HR) = 1.094 per 1-day increase in average weekly smoke-day, 95%CI: (1.005,1.191); 13-24 weeks: HR = 1.108, 95%CI: (1.016,1.209)). Protective associations were observed during gestational windows for both lower respiratory and systemic anti-inflammatory medications; it is possible that these associations may be a consequence of live-birth bias. These findings suggest wildfire smoke exposure during early postnatal developmental periods impact subsequent early life respiratory health.

A nationwide study of maternal exposure to ambient ozone and term birth weight in the United States

BACKGROUND

Maternal exposure to ozone (O₃) may cause systemic inflammation and oxidative stress and contribute to fetal growth restriction. We sought to estimate the association between maternal exposure to O₃ and term birth weight and term small for gestational age (SGA) in the United States (US).

METHODS

We conducted a nationwide study including 2,179,040 live term singleton births that occurred across 453 populous counties in the contiguous US in 2002. Daily county-level concentrations of O₃ data were estimated using a Bayesian fusion model. We used linear regression to estimate the association between O₃ exposure and term birth weight and logistic regression to estimate the association between O₃ exposure and term SGA during each trimester of the pregnancy and the entire pregnancy after adjusting for maternal characteristics, infant sex, season of conception, ambient temperature, county poverty rate, and census region. We additionally used distributed lag models to identify the critical exposure windows by estimating the monthly and weekly associations.

RESULTS

A 10 parts per billion (ppb) increase in O₃ over the entire pregnancy was associated with a lower term birth weight (-7.6 g; 95 % CI: -8.8 g, -6.4 g) and increased risk of SGA (odds ratio = 1.030; 95 % CI: 1.020, 1.040). The identified critical exposure windows were the 13th- 25th and 32nd -37th gestational weeks for term birth weight and 13th- 25th for term SGA. We found the association was more pronounced among mothers who were non-Hispanic Black, unmarried, or had lower education level.

CONCLUSIONS

Among US singleton term births, maternal exposure to O₃ was associated with lower rates of fetal growth, and the 13th- 25th gestational weeks were the identified critical exposure windows.

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.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Association of Physical Activity with Incidence of Dementia Is Attenuated by Air Pollution

INTRODUCTION

Physical activity (PA) is recognized as one of the key lifestyle behaviors that reduces risk of developing dementia late in life. However, PA also leads to increased respiration, and in areas with high levels of air pollution, PA may increase exposure to pollutants linked with higher risk of developing dementia. Here, we investigate whether air pollution attenuates the association between PA and dementia risk.

METHODS

This prospective cohort study included 35,562 adults 60 yrs and older from the UK Biobank. Average acceleration magnitude (ACCave) from wrist-worn accelerometers was used to assess PA levels. Air pollution levels (NO, NO2, PM10, PM2.5, PM2.5-10, and PM2.5 absorbance) were estimated with land use regression methods. Incident all-cause dementia was derived from inpatient hospital records and death registry data.

RESULTS

In adjusted models, ACCave was associated with reduced risk of developing dementia (HR = 0.71, 95% confidence interval [CI] = 0.60-0.83), whereas air pollution variables were not associated with dementia risk. There were significant interactions between ACCave and PM2.5 (HRinteraction = 1.33, 95% CI = 1.13-1.57) and PM2.5 absorbance (HRinteraction = 1.24, 95% CI = 1.07-1.45) on incident dementia. At the lowest tertiles of pollution, ACCave was associated with reduced risk of incident dementia (HRPM 2.5 = 0.66, 95% CI = 0.49-0.91; HRPM 2.5 absorbance = 0.60, 95% CI = 0.44-0.81). At the highest tertiles of these pollutants, there was no significant association of ACCave with incident dementia (HRPM 2.5 = 0.88, 95% CI = 0.68-1.14; HRPM 2.5 absorbance = 0.79, 95% CI = 0.60-1.04).

CONCLUSIONS

PA is associated with reduced risk of developing all-cause dementia. However, exposure to even moderate levels of air pollution attenuates the benefits of PA on risk of dementia.

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

INTRODUCTION

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

METHODS

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

RESULTS

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

CONCLUSION

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

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 PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 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 3rd 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.

Is maternal employment site a source of exposure misclassification in studies of environmental exposures and birth outcomes? A simulation-based bias analysis of haloacetic acids in tap water and hypospadias

In population research, exposure to environmental contaminants is often indirectly assessed by linking residence to geocoded databases of environmental exposures. We explored the potential for misclassification of residence-based environmental exposure as a result of not accounting for the workplace environments of employed pregnant women using data from a National Birth Defects Prevention Study (NBDPS) analysis of drinking water haloacetic acids and hypospadias.

Methods

The original analysis used NBDPS data from women with haloacetic acid exposure information in eight states who delivered an infant with second- or third-degree hypospadias (cases) or a male infant without a birth defect (controls) between 2000 and 2005. In this bias analysis, we used a uniform distribution to randomly select 11%-14% of employed women that were assumed to change municipal water systems between home and work and imputed new contaminant exposures for tap water beverages consumed at work among the selected women using resampled values from the control population. Multivariable logistic regression was used to estimate the association between hypospadias and haloacetic acid ingestion with the same covariates and exposure cut-points as the original study. We repeated this process across 10,000 iterations and then completed a sensitivity analysis of an additional 10,000 iterations where we expanded the uniform distribution (i.e., 0%, 28%).

Results

In both simulations, the average results of the 10,000 iterations were nearly identical to those of the initial study.

Conclusions

Our results suggest that household estimates may be sufficient proxies for worksite exposures to haloacetic acids in tap water.

Social Disparities in Benign Lung Diseases

The many socioeconomic disparities in the myriad of diagnoses that make up benign lung diseases are unfortunately a global issue that was most recently highlighted by the COVID-19 pandemic of 2020. In this chapter, we will be reviewing the socioeconomic disparities in benign lung disease from both a United States perspective as well as a global perspective. We will cover the spectrum of infectious, obstructive, and restrictive lung disease and review the evidence on how social disparities affect these populations and their access to medical care.

Association of Air Pollution and Physical Activity With Brain Volumes

BACKGROUND AND OBJECTIVES

In high-pollution areas, physical activity may have a paradoxical effect on brain health by increasing particulate deposition in the lungs. We examined whether physical activity modifies associations of air pollution (AP) with brain volumes in an epidemiologic framework.

METHODS

The UK Biobank enrolled >500,000 adult participants from 2006 to 2010. Wrist accelerometers, multimodal MRI with T1 images and T2 fluid-attenuated inversion recovery data, and land use regression were used to estimate vigorous physical activity (VigPA), structural brain volumes, and AP, respectively, in subsets of the full sample. We evaluated associations among AP interquartile ranges, VigPA, and brain structure volumes and assessed interactions between AP and VigPA.

RESULTS

Eight thousand six hundred participants were included, with an average age of 55.55 (SD 7.46) years. After correction for multiple testing, in overall models, VigPA was positively associated with gray matter volume (GMV) and negatively associated with white matter hyperintensity volume (WMHV), while NO2, PM2.5absorbance, and PM2.5 were negatively associated with GMV. NO2 and PM2.5absorbance interacted with VigPA on WMHV (false discovery rate-corrected interaction p = 0.037). Associations between these air pollutants and WMHVs were stronger among participants with high VigPA. Similarly, VigPA was negatively associated with WMHV for those in areas of low NO2 and PM2.5absorbance but was null among those living in areas of high NO2 and PM2.5absorbance. DISCUSSION: Physical activity is associated with beneficial brain outcomes, while AP is associated with detrimental brain outcomes. VigPA may exacerbate associations of AP with white matter hyperintensity lesions, and AP may attenuate the beneficial associations of physical activity with these lesions.

An algorithm to identify residential mobility from electronic health-record data

BACKGROUND

Environmental, social and economic exposures can be inferred from address information recorded in an electronic health record. However, these data often contain administrative errors and misspellings. These issues make it challenging to determine whether a patient has moved, which is integral for accurate exposure assessment. We aim to develop an algorithm to identify residential mobility events and avoid exposure misclassification.

METHODS

At Penn Medicine, we obtained a cohort of 12 147 pregnant patients who delivered between 2013 and 2017. From this cohort, we identified 9959 pregnant patients with address information at both time of delivery and one year prior. We developed an algorithm entitled REMAP (Relocation Event Moving Algorithm for Patients) to identify residential mobility during pregnancy and compared it to using ZIP code differences alone. We assigned an area-deprivation exposure score to each address and assessed how residential mobility changed the deprivation scores.

RESULTS

To assess the accuracy of our REMAP algorithm, we manually reviewed 3362 addresses and found that REMAP was 95.7% accurate. In this large urban cohort, 41% of patients moved during pregnancy. REMAP outperformed the comparison of ZIP codes alone (82.9%). If residential mobility had not been taken into account, absolute area deprivation would have misclassified 39% of the patients. When setting a threshold of one quartile for misclassification, 24.4% of patients would have been misclassified.

CONCLUSIONS

Our study tackles an important characterization problem for exposures that are assigned based upon residential addresses. We demonstrate that methods using ZIP code alone are not adequate. REMAP allows address information from electronic health records to be used for accurate exposure assessment and the determination of residential mobility, giving researchers and policy makers more reliable information.

Residential proximity to hydraulically fractured oil and gas wells and adverse birth outcomes in urban and rural communities in California (2006-2015)

Supplemental Digital Content is available in the text.

Background:

Prenatal exposure to hydraulic fracturing (HF), a chemically intensive oil and gas extraction method, may be associated with adverse birth outcomes, but no health studies have been conducted in California.

Methods:

We conducted a retrospective cohort study of 979,961 births to mothers in eight California counties with HF between 2006 and 2015. Exposed individuals had at least 1 well hydraulically fractured within 1 km of their residence during pregnancy; the reference population had no wells within 1 km, but at least one oil/gas well within 10 km. We examined associations between HF and low birth weight (LBW), preterm birth (PTB), small for gestational age birth (SGA), and term birth weight (tBW) using generalized estimating equations and assessing urban-rural effect modification in stratified models.

Results:

Fewer than 1% of mothers (N = 1,192) were exposed to HF during pregnancy. Among rural mothers, HF exposure was associated with increased odds of LBW (odds ratio [OR] = 1.74; 95% confidence interval [CI] = 1.10, 2.75), SGA (OR = 1.68; 95% CI = 1.42, 2.27) and PTB (OR = 1.17; 95% CI = 0.64, 2.12), and lower tBW (mean difference: –73 g; 95% CI = –131, –15). Among urban mothers, HF exposure was positively associated with SGA (OR = 1.23; 95% CI = 0.98, 1.55), inversely associated with LBW (OR = 0.83; 95% CI = 0.63, 1.07) and PTB (OR = 0.65; 95% CI = 0.48, 0.87), and not associated with tBW (mean difference: –2 g; 95% CI = –35, 31).

Conclusion:

HF proximity was associated with adverse birth outcomes, particularly among rural Californians.

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).

A review on the role of dispersion and receptor models in asthma research

There is substantial evidence that air pollution exposure is associated with asthma prevalence that affects millions of people worldwide. Air pollutant exposure can be determined using dispersion models and refined with receptor models. Dispersion models offer the advantage of giving spatially distributed outdoor pollutants concentration while the receptor models offer the source apportionment of specific chemical species. However, the use of dispersion and/or receptor models in asthma research requires a multidisciplinary approach, involving experts on air quality and respiratory diseases. Here, we provide a literature review on the role of dispersion and receptor models in air pollution and asthma research, their limitations, gaps and the way forward. We found that the methodologies used to incorporate atmospheric dispersion and receptor models in human health studies may vary considerably, and several of the studies overlook features such as indoor air pollution, model validation and subject pathway between indoor spaces. Studies also show contrasting results of relative risk or odds ratio for a health outcome, even using similar methodologies. Dispersion models are mostly used to estimate air pollution levels outside the subject's home, school or workplace; however, very few studies addressed the subject's routines or indoor/outdoor relationships. Conversely, receptor models are employed in regions where asthma incidence/prevalence is high or where a dispersion model has been previously used for this assessment. Road traffic (vehicle exhaust) and NOx are found to be the most targeted source and pollutant, respectively. Other key findings were the absence of a standard indicator, shortage of studies addressing VOC and UFP, and the shift toward chemical speciation of exposure.

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

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

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.

Ambient particle radioactivity and gestational diabetes: A cohort study of more than 1 million pregnant women in Massachusetts, USA

BACKGROUND

Exposure to ionizing radiation increases the risk of chronic metabolic disorders such as insulin resistance and type 2 diabetes. Internal ionizing radiation from inhaled radioactive aerosol may contribute to the associations between fine particulate matter (PM_2.5) and gestational diabetes mellitus (GDM).

METHODS

We used the Massachusetts Registry of Vital Records to study 1,061,937 pregnant women from 2001 to 2015 with a singleton pregnancy without pre-existing diabetes. Gross β activity measured by seven monitors of the U.S. Environmental Protection Agency's RadNet monitoring network was utilized to represent ambient particle radioactivity (PR). We obtained GDM status from birth certificates and used logistic regression analyses adjusted for socio-demographics, maternal comorbidities, PM_2.5, temperature and relative humidity. We also examined effect modification by smoking habits.

RESULTS

Ambient particle radioactivity exposure during first and second trimester of pregnancy was associated with higher odds of GDM (OR: 1.18 (95% CI 1.10 to 1.22). Controlling for PM_2.5 did not substantially change the effects of PR on GDM. In women that reported being former or current smokers, the association between PR and GDM was null. In the full cohort, the overall effect of PM_2.5 on GDM without adjusting for PR was not significant.

CONCLUSION

This is the first population-based study to examine the association between particle radioactivity and gestational diabetes mellitus - one of the most common pregnancy-related diseases with lifelong effects for the mother and the fetus. This finding has important public health policy implications because it enhances our understanding about the toxicity of PR, a modifiable risk factor, which to date, has been considered only as an indoor and occupational air quality risk.

Quantifying the impact of daily mobility on errors in air pollution exposure estimation using mobile phone location data

One major source of uncertainty in accurately estimating human exposure to air pollution is that human subjects move spatiotemporally, and such mobility is usually not considered in exposure estimation. How such mobility impacts exposure estimates at the population and individual level, particularly for subjects with different levels of mobility, remains under-investigated. In addition, a wide range of methods have been used in the past to develop air pollutant concentration fields for related health studies. How the choices of methods impact results of exposure estimation, especially when detailed mobility information is considered, is still largely unknown. In this study, by using a publicly available large cell phone location dataset containing over 35 million location records collected from 310,989 subjects, we investigated the impact of individual subjects' mobility on their estimated exposures for five chosen ambient pollutants (CO, NO₂, SO₂, O₃ and PM_2.5). We also estimated exposures separately for 10 groups of subjects with different levels of mobility to explore how increased mobility impacted their exposure estimates. Further, we applied and compared two methods to develop concentration fields for exposure estimation, including one based on Community Multiscale Air Quality (CMAQ) model outputs, and the other based on the interpolated observed pollutant concentrations using the inverse distance weighting (IDW) method. Our results suggest that detailed mobility information does not have a significant influence on mean population exposure estimate in our sample population, although impacts can be substantial at the individual level. Additionally, exposure classification error due to the use of home-location data increased for subjects that exhibited higher levels of mobility. Omitting mobility could result in underestimation of exposures to traffic-related pollutants particularly during afternoon rush-hour, and overestimate exposures to ozone especially during mid-afternoon. Between CMAQ and IDW, we found that the IDW method generates smooth concentration fields that were not suitable for exposure estimation with detailed mobility data. Therefore, the method for developing air pollution concentration fields when detailed mobility data were to be applied should be chosen carefully. Our findings have important implications for future air pollution health studies.

Tropical cyclones and risk of preterm birth: A retrospective analysis of 20 million births across 378 US counties

BACKGROUND

The public health impacts of tropical cyclones (TCs) are expected to increase due to the continued growth of coastal populations and the increasing severity of these events. However, the impact of TCs on pregnant women, a vulnerable population, remains largely unknown. We aimed to estimate the association between prenatal exposure to TCs and risk of preterm birth in the eastern United States (US) and to assess whether the association varies by individual- and area-level characteristics.

METHODS

We included data on 19,529,748 spontaneous singleton births from 1989 to 2002 across 378 US counties. In each county, we classified days as exposed to a TC when TC-associated peak sustained winds at the county's population-weighted center were >17.2 m/s (gale-force winds or greater). We defined preterm birth as births delivered prior to 37 completed weeks of gestation. We used distributed lag log-linear mixed-effects models to estimate the relative risk (RR) and absolute risk difference (ARD) for TC exposure by comparing preterm births occurring in TC-periods (from 2 days before to 30 days after the TC's closest approach to the county's population center) to matched non-TC periods. We conducted secondary analyses using other wind thresholds (12 m/s and 22 m/s) and other exposure metrics: county distance to storm track (30 km, 60 km, and 100 km) and cumulative rainfall within the county (75 mm, 100 mm, and 125 mm).

RESULTS

During the study period, there were 1,981,797 (10.1%) preterm births and 58 TCs that affected at least one US county on which we had birth data. The risk of preterm birth was positively associated with TC exposure defined as peak sustained wind speed >17.2 m/s (gale-force winds or greater) [RR: 1.01 (95% CI: 0.99, 1.03); ARD: 9 (95% CI: -7, 25) per 10,000 pregnancies], distance to storm track <60 km [RR: 1.02 (95% CI: 1.01, 1.04); ARD: 23 (95% CI: 9, 38) per 10,000 pregnancies], and cumulative rainfall >100 mm [RR: 1.04 (95% CI: 1.02, 1.06); ARD: 36 (95% CI: 16, 56) per 10,000 pregnancies]. Results were comparable when considering other wind, distance, or rain thresholds. The association was more pronounced among early preterm births and mothers living in more socially vulnerable counties but did not vary across strata of other hypothesized risk factors.

CONCLUSIONS

Maternal exposure to TC was associated with a higher risk of preterm birth. Our findings provide initial evidence that severe storms may trigger preterm birth.

Flaring from Unconventional Oil and Gas Development and Birth Outcomes in the Eagle Ford Shale in South Texas

BACKGROUND

Prior studies suggest exposure to oil and gas development (OGD) adversely affects birth outcomes, but no studies have examined flaring-the open combustion of natural gas-from OGD.

OBJECTIVES

We investigated whether residential proximity to flaring from OGD was associated with shorter gestation and reduced fetal growth in the Eagle Ford Shale of south Texas.

METHODS

We conducted a retrospective cohort study using administrative birth records from 2012 to 2015 (N = 23,487 ) and satellite observations of flaring activity during pregnancy within 5 km of maternal residence. Multivariate logistic and linear regression models were used to estimate associations between four outcomes (preterm birth, small-for-gestational age, continuous gestational age, and term birthweight) and exposure to a low (1-9) or high (≥ 10 ) number of nightly flare events, as compared with no exposure, while controlling for known maternal risk factors. We also examined associations with the number of oil and gas wells within 5 km using data from DrillingInfo (now Enverus).

RESULTS

Exposure to a high number of nightly flare events was associated with a 50% higher odds of preterm birth [odds ratio (OR) = 1.50 (95% CI: 1.23, 1.83)] and shorter gestation [mean difference = - 1.9 (95% CI: - 2.8 , - 0.9 ) d] compared with no exposure. Effect estimates were slightly reduced after adjustment for the number of wells within 5 km . In stratified models these associations were present only among Hispanic women. Flaring and fetal growth outcomes were not significantly associated. Women exposed to a high number of wells (fourth quartile, ≥ 27 ) vs. no wells within 5 km had a higher odds of preterm birth [OR = 1.31 (95% CI: 1.14, 1.49)], shorter gestation [- 1.3 (95% CI: - 1.9 , - 0.8 ) d], and lower average birthweight [- 19.4 (95% CI: - 36.7 , - 2.0 ) g].

DISCUSSION

Our study suggests exposure to flaring from OGD is associated with an increased risk of preterm birth. Our findings need to be confirmed in other populations. https://doi.org/10.1289/EHP6394.

Residential Proximity to Oil and Gas Development and Birth Outcomes in California: A Retrospective Cohort Study of 2006-2015 Births

BACKGROUND

Studies suggest associations between oil and gas development (OGD) and adverse birth outcomes, but few epidemiological studies of oil wells or inactive wells exist, and none in California.

OBJECTIVE

Our study aimed to investigate the relationship between residential proximity to OGD and birth outcomes in California.

METHODS

We conducted a retrospective cohort study of 2,918,089 births to mothers living within 10 km of at least one production well between January 1, 2006 and December 31, 2015. We estimated exposure during pregnancy to inactive wells count (no inactive wells, 1 well, 2-5 wells, 6+ wells) and production volume from active wells in barrels of oil equivalent (BOE) (no BOE, 1-100 BOE/day, >100 BOE/day). We used generalized estimating equations to examine associations between overall and trimester-specific OGD exposures and term birth weight (tBW), low birth weight (LBW), preterm birth (PTB), and small for gestational age birth (SGA). We assessed effect modification by urban/rural community type.

RESULTS

Adjusted models showed exposure to active OGD was associated with adverse birth outcomes in rural areas; effect estimates in urban areas were close to null. In rural areas, increasing production volume was associated with stronger adverse effect estimates. High (>100 BOE/day) vs. no production throughout pregnancy was associated with increased odds of LBW [odds ratio (OR)=1.40, 95% confidence interval (CI): 1.14, 1.71] and SGA (OR=1.22, 95% CI: 1.02, 1.45), and decreased tBW (mean difference = -36 grams, 95% CI: -54, -17), but not with PTB (OR=1.03, 95% CI: 0.91, 1.18).

CONCLUSION

Proximity to higher production OGD in California was associated with adverse birth outcomes among mothers residing in rural areas. Future studies are needed to confirm our findings in other populations and improve exposure assessment measures. https://doi.org/10.1289/EHP5842.

Prenatal pesticide exposure and childhood leukemia - A California statewide case-control study

BACKGROUND

A number of epidemiologic studies with a variety of exposure assessment approaches have implicated pesticides as risk factors for childhood cancers. Here we explore the association of pesticide exposure in pregnancy and early childhood with childhood acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) utilizing land use and pesticide use data in a sophisticated GIS tool.

METHODS

We identified cancer cases less than 6 years of age from the California Cancer Registry and cancer-free controls from birth certificates. Analyses were restricted to those living in rural areas and born 1998-2011, resulting in 162 cases of childhood leukemia and 9,805 controls. Possible carcinogens were selected from the Environmental Protection Agency's classifications and pesticide use was collected from the California Department of Pesticide Regulation's (CDPR) Pesticide Use Reporting (PUR) system and linked to land-use surveys. Exposures for subjects were assessed using a 4000m buffer around the geocoded residential addresses at birth. Unconditional logistic and hierarchical regression models were used to assess individual pesticide and pesticide class associations.

RESULTS

We observed elevated risks for ALL with exposure to any carcinogenic pesticide (adjusted Odds Ratio (aOR): 2.83, 95% CI: 1.67-4.82), diuron (Single-pesticide model, adjusted (OR): 2.38, 95% CI: 1.57-3.60), phosmet (OR: 2.10, 95% CI: 1.46-3.02), kresoxim-methyl (OR: 1.77, 95% CI: 1.14-2.75), and propanil (OR: 2.58, 95% CI: 1.44-4.63). Analyses based on chemical classes showed elevated risks for the group of 2,6-dinitroanilines (OR: 2.50, 95% CI: 1.56-3.99), anilides (OR: 2.16, 95% CI: 1.38-3.36), and ureas (OR: 2.18, 95% CI: 1.42-3.34).

CONCLUSION

Our findings suggest that in rural areas of California exposure to certain pesticides or pesticide classes during pregnancy due to residential proximity to agricultural applications may increase the risk of childhood ALL and AML. Future studies into the mechanisms of carcinogenicity of these pesticides may be beneficial.

Exposure to air pollution during the first 1000 days of life and subsequent health service and medication usage in children

BACKGROUND

Evidence of health effects following early life exposure to short-to-medium duration of high pollution levels is extremely limited.

OBJECTIVES

We aimed to evaluate the associations between: 1. intrauterine exposure to fine particulate matter (PM_2.5) from coal mine fire emissions and the frequencies of general practitioner attendances and dispensations of prescribed asthma inhalers, steroid skin creams, and antibiotics during the first year of life; 2. infant exposure and those outcomes during the year following the fire.

METHODS

All participants were recruited from the Latrobe Valley of Victoria, Australia. Participants' 24-h average and hourly peak mine fire-specific PM_2.5 exposures from 09/02/2014 to 31/03/2014 were estimated using chemical transport modelling. Outcome data were obtained from the Australian Medicare Benefits Schedule and Pharmaceutical Benefits Scheme from each child's birth to 31/12/2016. We used negative binomial and logistic regression models to independently assess risks of the outcomes associated with every 10 and 100 μg m^-3 increase in average or peak PM_2.5 exposure, respectively, while adjusting for potential confounders.

RESULTS

We included 286 of 311 children whose parents consented to be linked, comprising 77 with no exposure, 88 with intrauterine exposure and 121 with exposure in infancy. 10- and 100- μg m^-3 increases in average and peak PM_2.5 exposure during infancy were associated with greater incidence of antibiotics being dispensed during the year following the fire: the adjusted incidence rate ratios were 1.24 (95% CI 1.02, 1.50, p = 0.036) and 1.14 (1.00, 1.31, p = 0.048) respectively. No other significant associations were observed.

CONCLUSION

Exposure to coal mine fire emissions during infancy was associated with increased dispensing of antibiotics. This could reflect increased childhood infections or increased prescriptions of antibiotics in the year following the fire.

Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric models

Fine particulate matter (PM2.5) is a well-established risk factor for public health. To support both health risk assessment and epidemiological studies, data are needed on spatial and temporal patterns of PM2.5 exposures. This review article surveys publicly available exposure datasets for surface PM2.5 mass concentrations over the contiguous U.S., summarizes their applications and limitations, and provides suggestions on future research needs. The complex landscape of satellite instruments, model capabilities, monitor networks, and data synthesis methods offers opportunities for research development, but would benefit from guidance for new users. Guidance is provided to access publicly available PM2.5 datasets, to explain and compare different approaches for dataset generation, and to identify sources of uncertainties associated with various types of datasets. Three main sources used to create PM2.5 exposure data are ground-based measurements (especially regulatory monitoring), satellite retrievals (especially aerosol optical depth, AOD), and atmospheric chemistry models. We find inconsistencies among several publicly available PM2.5 estimates, highlighting uncertainties in the exposure datasets that are often overlooked in health effects analyses. Major differences among PM2.5 estimates emerge from the choice of data (ground-based, satellite, and/or model), the spatiotemporal resolutions, and the algorithms used to fuse data sources.Implications: Fine particulate matter (PM2.5) has large impacts on human morbidity and mortality. Even though the methods for generating the PM2.5 exposure estimates have been significantly improved in recent years, there is a lack of review articles that document PM2.5 exposure datasets that are publicly available and easily accessible by the health and air quality communities. In this article, we discuss the main methods that generate PM2.5 data, compare several publicly available datasets, and show the applications of various data fusion approaches. Guidance to access and critique these datasets are provided for stakeholders in public health sectors.

On the accuracy and potential of Google Maps location history data to characterize individual mobility for air pollution health studies

Appropriately characterizing spatiotemporal individual mobility is important in many research areas, including epidemiological studies focusing on air pollution. However, in many retrospective air pollution health studies, exposure to air pollution is typically estimated at the subjects' residential addresses. Individual mobility is often neglected due to lack of data, and exposure misclassification errors are expected. In this study, we demonstrate the potential of using location history data collected from smartphones by the Google Maps application for characterizing historical individual mobility and exposure. Here, one subject carried a smartphone installed with Google Maps, and a reference GPS data logger which was configured to record location every 10 s, for a period of one week. The retrieved Google Maps Location History (GMLH) data were then compared with the GPS data to evaluate their effectiveness and accuracy of the GMLH data to capture individual mobility. We also conducted an online survey (n = 284) to assess the availability of GMLH data among smartphone users in the US. We found the GMLH data reasonably captured the spatial movement of the subject during the one-week time period at up to 200 m resolution. We were able to accurately estimate the time the subject spent in different microenvironments, as well as the time the subject spent driving during the week. The estimated time-weighted daily exposures to ambient particulate matter using GMLH and the GPS data logger were also similar (error less than 1.2%). Survey results showed that GMLH data may be available for 61% of the survey sample. Considering the popularity of smartphones and the Google Maps application, detailed historical location data are expected to be available for large portion of the population, and results from this study highlight the potential of these location history data to improve exposure estimation for retrospective epidemiological studies.

Residence change during the first trimester of pregnancy and adverse birth outcomes

BACKGROUND

There are few published studies evaluating the impact of perinatal residence change on infant outcomes and whether these associations differ by socioeconomic status.

METHODS

We conducted a population-based cohort study using Washington State birth certificate data from 2007 to 2014 to assess whether women who moved during the first trimester of pregnancy (n=28 011) had a higher risk of low birth weight, preterm birth and small for gestational age than women who did not move during the first trimester (n=112 367). 'Non-first-trimester movers' were frequency matched 4:1 to movers by year. We used generalised linear models to calculate risk ratios and risk differences adjusted for maternal age, race, marital status, parity, education, smoking, income and insurance payer for the birth. We also stratified analyses by variables related to socioeconomic status to see whether associations differed across socioeconomic strata.

RESULTS

Moving in the first trimester was associated with an increased risk of low birth weight (6.4% vs 4.5%, adjusted risk ratio 1.37 (95% CI 1.29 to 1.45)) and preterm birth (9.1% vs 6.4%, adjusted risk ratio 1.42 (95% CI 1.36 to 1.49)) and a slight increased risk of small for gestational age (9.8% vs 8.7%, adjusted risk ratio 1.09 (95% CI 1.00 to 1.09)). Residence change was associated with low birth weight and preterm birth in all socioeconomic strata.

CONCLUSION

Moving during the first trimester of pregnancy may be a risk factor for adverse birth outcomes in US women. Healthcare providers may want to consider screening for plans to move and offering support.

Prodromal clinical, demographic, and socio-ecological correlates of asthma in adults: a 10-year statewide big data multi-domain analysis

Objectives: To identify prodromal correlates of asthma as compared to chronic obstructive pulmonary disease and allied-conditions (COPDAC) using a multi domain analysis of socio-ecological, clinical, and demographic domains.Methods: This is a retrospective case-risk-control study using data from Florida's statewide Healthcare Cost and Utilization Project (HCUP). Patients were grouped into three groups: asthma, COPDAC (without asthma), and neither asthma nor COPDAC. To identify socio-ecological, clinical, demographic, and clinical predictors of asthma and COPDAC, we used univariate analysis, feature ranking by bootstrapped information gain ratio, multivariable logistic regression with LogitBoost selection, decision trees, and random forests.Results: A total of 141,729 patients met inclusion criteria, of whom 56,052 were diagnosed with asthma, 85,677 with COPDAC, and 84,737 with neither asthma nor COPDAC. The multi-domain approach proved superior in distinguishing asthma versus COPDAC and non-asthma/non-COPDAC controls (area under the curve (AUROC) 84%). The best domain to distinguish asthma from COPDAC without controls was prior clinical diagnoses (AUROC 82%). Ranking variables from all the domains found the most important predictors for the asthma versus COPDAC and controls were primarily socio-ecological variables, while for asthma versus COPDAC without controls, demographic and clinical variables such as age, CCI, and prior clinical diagnoses, scored better.Conclusions: In this large statewide study using a machine learning approach, we found that a multi-domain approach with demographics, clinical, and socio-ecological variables best predicted an asthma diagnosis. Future work should focus on integrating machine learning-generated predictive models into clinical practice to improve early detection of those common respiratory diseases.

Ambient Temperature and Markers of Fetal Growth: A Retrospective Observational Study of 29 Million U.S. Singleton Births

BACKGROUND

Emerging studies suggest that ambient temperature during pregnancy may be associated with fetal growth, but the existing evidence is limited and inconsistent.

OBJECTIVES

We aimed to evaluate the association of trimester-specific temperature with risk of being born small for gestational age (SGA) and birth weight-markers of fetal growth-among term births in the contiguous United States.

METHODS

We included data on 29,597,735 live singleton births between 1989 and 2002 across 403 U.S. counties. We estimated daily county-level population-weighted mean temperature using a spatially refined gridded climate data set. We used logistic regression to estimate the association between trimester-specific temperature and risk of SGA and linear regression to evaluate the association between trimester-specific temperature and term birth weight z-score, adjusting for parity, maternal demographics, smoking or drinking during pregnancy, chronic hypertension, and year and month of conception. We then pooled results overall and by geographic regions and climate zones.

RESULTS

High ambient temperatures ([Formula: see text] percentile) during the entire pregnancy were associated with higher risk of term SGA {odds ratio [OR] [Formula: see text] 1.041 [95% confidence interval (CI): 1.029, 1.054]} and lower term birth weight [standardized to [Formula: see text] (95% CI: [Formula: see text], [Formula: see text]) reduction in birth weight for infants born at 40 weeks of gestation]. Low temperatures ([Formula: see text] percentile) during the entire pregnancy were not associated with SGA [OR [Formula: see text] 1.003 (95% CI: 0.991, 1.015)] but were associated with a small decrement in term birth weight [standardized to [Formula: see text] (95% CI: [Formula: see text], [Formula: see text])]. Risks of term SGA and birth weight were more strongly associated with temperature averaged across the second and third trimesters, in areas the Northeast, and in areas with cold or very cold climates.

CONCLUSIONS

Above-average temperatures during pregnancy were associated with lower fetal growth. Our findings provide evidence that temperature may be a novel risk factor for reduced fetal growth. https://doi.org/10.1289/EHP4648.

Residential mobility in early childhood and the impact on misclassification in pesticide exposures

Studies of environmental exposures and childhood cancers that rely on records often only use maternal address at birth or address at cancer diagnosis to assess exposures in early childhood, possibly leading to exposure misclassification and questionable validity due to residential mobility during early childhood. Our objective was to assess patterns and identify factors that may predict residential mobility in early childhood, and examine the impact of mobility on early childhood exposure assessment for agriculturally applied pesticides and childhood cancers in California. We obtained the addresses at diagnosis of all childhood cancer cases born in 1998-2011 and diagnosed at 0-5 years of age (n = 6478) from the California Cancer Registry (CCR), and their birth addresses from linked birth certificates. Controls were randomly selected from California birth records and frequency matched (20:1) to all cases by year of birth. We obtained residential histories from a public-record database LexisNexis for both case (n = 3877 with age at diagnosis 1-5 years) and control (n = 99,262) families. Logistic regression analyses were conducted to assess the socio-demographic factors in relation to residential mobility in early childhood. We employed a Geographic Information System (GIS)-based system to estimate children's first year of life exposures to agriculturally applied pesticides based on birth vs diagnosis address or residential histories based upon Lexis-Nexis Public Records and assessed agreement between exposure measures using Spearman correlations and kappa statistics. Over 20% of case and control children moved in their first year of life, and 55% of children with cancer moved between birth and diagnosis. Older age at diagnosis, younger maternal age, lower maternal education, not having a Hispanic ethnic background, use of public health insurance, and non-metropolitan residence at birth were predictors of higher residential mobility. There was moderate to strong correlation (Spearman correlation = 0.76-0.83) and good agreement (kappa = 0.75-0.81) between the first year of life exposure estimates for agricultural pesticides applied within 2 km of a residence relying on an address at birth or at diagnosis or LexisNexis addresses; this did not differ by outcome status, but agreement decreased with decreasing buffer size, and increasing distance moved or age at diagnosis. These findings suggest that residential addresses collected at one point in time may represent residential history in early childhood to a reasonable extent; nevertheless, they exposure misclassification in the first year of life remains an issue. Also, the highest proportion of women not captured by LexisNexis were Hispanic women born in Mexico and those living in the lowest SES neighborhoods, i.e. possibly those with the higher environmental exposures, as well as younger women and those with less than high school education. Though LexisNexis only captures a sub-population, its data may be useful for augmenting address information and assessing the extent of exposure misclassification when estimating environmental exposures in large record linkage studies. Future research should investigate how to correct for exposure misclassification introduced by residential mobility that is not being captured by records.

Predictors of residential mobility and its impact on air pollution exposure among children diagnosed with early childhood leukemia

Epidemiology studies relying on one address to assign exposures over time share common methodological limitations in failing to account for mobility that may introduce potential exposure misclassification. Using Texas birth certificate and cancer registry data, we identified predictors of residential mobility among mothers of children diagnosed with early childhood leukemia in Texas from 1995 to 2011. We used U.S. Environmental Protection Agency (EPA) National Air Toxics Assessment data to estimate residential levels of benzene and 1,3-butadiene based on addresses at birth and diagnosis and applied mixed-effects ordinal logistic regression models to evaluate differences in exposure classification between the two time periods. In total, 55% of children moved from time of birth to diagnosis, although they generally did not move far (median distance moved was 8 km). Predictors of mobility, at delivery, included younger age, being unmarried and living in neighborhoods with high benzene levels, and, at diagnosis, increasing child's age and living in neighborhoods with low poverty rates. We observed that the odds of being assigned to a higher exposure quartile at diagnosis relative to the time of birth decreased by 31% for 1,3-butadiene (OR = 0.69, 95% CI 0.59-0.82) and by 12% for benzene (OR = 0.88, 95% CI 0.75, 1.05).

Association between ambient gaseous and particulate air pollutants and attention deficit hyperactivity disorder (ADHD) in children; a systematic review

ADHD is a common neurodevelopmental disorder highly attributed to genetics, but the combination of other social and environmental determinants, as well as potential gene-environment interactions, can also be responsible. This paper aims to review relevant literature published up to April 2018 for determining whether air pollution caused by ambient gaseous (NO₂, SO₂, PCDD/Fs, Benzene) and particulate matters (PM₁₀, PM_2.5, PM₇, PAH, BC/EC) as an environmental risk factor is associated with increased risk of ADHD in children. Relevant literature was identified through electronic searches of PubMed, Embase, Web of Science, Scopus database and gray literature. A total of 872 articles were initially identified 28 of which meeting the defined inclusion criteria were included. The methodological quality of the included articles was evaluated using the modified Critical Appraisal Skills Programs (CASP) and confounding variables, exposure and outcome measurement were assessed. The results of this systematic review revealed that there is more evidence on the detrimental effects of EC, BC, and PM on ADHD compared to PAH. Among gaseous air pollutants, association was found between SO₂ and urinary level of t,t-MA (trans, trans-muconic acid) as a proxy-biomarker of NO₂ exposure, not merely benzene. However few studies related to NO₂ (0.46%) found detrimental effects. Overall, the number of studies reporting an association between air pollution and increased risk of ADHD is relatively higher compared to the number of studies reporting no association. However, the findings of the studies provided limited evidence to support the idea that exposure to air pollution may be linked to increased risk of ADHD. Well-designed and harmonized studies considering standard methods for individual exposure assessment, critical windows of susceptibility, and appropriate tools for outcome measurement, can improve the quality of epidemiological studies and strengthen the evidence. Since ADHD with its long-term consequences can impose large costs to communities and impact the children performance, determination of the risk factors in children and particularly the role of the environment as priorities for research should be considered.

Ambient Air Pollution Exposure and Fecundability in Women Undergoing In Vitro Fertilization

BACKGROUND

Limited research suggests ambient air pollution impairs fecundity but groups most susceptible have not been identified. We studied whether long-term ambient air pollution exposure prior to an in vitro fertilization (IVF) cycle was associated with successful livebirth, and whether associations were modified by underlying infertility diagnosis.

METHODS

Data on women initiating their 1st autologous IVF cycle in 2012-13 were obtained from four U.S. clinics. Outcomes included pregnancy, pregnancy loss, and livebirth. Annual average exposure to fine particulate matter (PM2.5), PM10, and nitrogen dioxide (NO2) prior to IVF start were estimated at residential address using a validated national spatial model incorporating land-use regression and universal kriging. We also assessed residential distance to major roadway. We calculated risk ratios (RR) using modified Poisson regression and evaluated effect modification (EM) by infertility diagnosis on additive and multiplicative scales.

RESULTS

Among 7,463 eligible participants, 36% had a livebirth. There was a non-significant indication of an association between PM2.5 or NO2 and decreased livebirth and increased pregnancy loss. Near roadway residence was associated with decreased livebirth (RR: 0.96, 95% CI: 0.82, 0.99. There was evidence for EM between high exposure to air pollutants and a diagnosis of diminished ovarian reserve (DOR) or male infertility and decreased livebirth.

CONCLUSIONS

Despite suggestive but uncertain findings for the overall effect of air pollution on fecundity, we found a suggestive indication that there may be synergistic effects of air pollution and DOR or male infertility diagnosis on livebirth. This suggests two possible targets for future research and intervention.

Mean and variance of greenness and pregnancy outcomes in Tel Aviv during 2000–14: longitudinal and cross-sectional approaches

Background

Natural environments may have beneficial impacts on pregnancy outcomes. However, longitudinal evidence is limited and the associations with variance in surrounding greenness is unknown. Our objective was to evaluate these associations among 73 221 live births in Tel Aviv, Israel.

Methods

Longitudinal exposure to mean of greenness during pregnancy and trimesters were calculated using satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) Normalised Difference Vegetation Index (NDVI) data. In addition, exposure to mean and variation of NDVI from high-resolution satellite and percentage of tree cover [Vegetation Continuous Fields (VCF)] at 300-m buffer were evaluated in a cross-sectional approach. Generalized linear models were used to estimate the crude and adjusted associations. We explore the possible mediating role of ambient exposures and distance to ‘outdoor gyms’ located in parks.

Results

Crude beneficial associations between exposure to higher mean NDVI during pregnancy and pregnancy outcomes were observed [for birthweight, 3rd/1st tertile exposure increased the mean by 25.5 g, 95% confidence intervals (CIs): 15.4, 35.5] and decreased the odds of low birthweight, small for gestational age, preterm deliveries (PTD) and very PTD. Adjustment for individual and neighbourhood-level markers of socio-economic status (SES) attenuated all the associations. Strongest associations were observed during the first and second trimesters. Cross-sectional associations for mean greenness were similar with narrower CIs, and associations with NDVI were stronger than with tree cover and stronger for mean compared with variance of greenness. Associations were consistent for term births, different buffer sizes and for further adjustment to maternal education. Stronger associations were observed for lowest SES. Distance to ‘outdoor gyms’ and variance of greenness had the largest estimates of mediation.

Conclusion

This study adds to the limited information on when exposure to greenness is most beneficial, on the association with variance of greenness and the possible pathways. These observations require confirmation in other populations.

Impacts of gestational age uncertainty in estimating associations between preterm birth and ambient air pollution

Supplemental Digital Content is available in the text.

Background:

Previous epidemiologic studies utilizing birth records have shown heterogeneous associations between air pollution exposure during pregnancy and the risk of preterm birth (PTB, gestational age <37 weeks). Uncertainty in gestational age at birth may contribute to this heterogeneity.

Methods:

We first examined disagreement between clinical and last menstrual period-based (LMP) determination of PTB from individual-level birth certificate data for the 20-county Atlanta metropolitan area during 2002 to 2006. We then estimated associations between five trimester-averaged pollutant exposures and PTB, defined using various methods based on the clinical or LMP gestational age. Finally, using a multiple imputation approach, we incorporated uncertainty in gestational age to quantify the impact of this variability on associations between pollutant exposures and PTB.

Results:

Odds ratios (OR) were most elevated when a more stringent definition of PTB was used. For example, defining PTB only when LMP and clinical diagnoses agree yielded an OR of 1.09 (95% confidence interval [CI] = 1.04, 1.14) per interquartile range increase in first trimester carbon monoxide exposure versus an OR of 1.04 (95% CI = 1.01, 1.08) when PTB was defined as either an LMP or clinical diagnosis. Accounting for outcome uncertainty resulted in wider CIs—between 7.4% and 43.8% wider than those assuming the PTB outcome is without error.

Conclusions:

Despite discrepancies in PTB derived using either the clinical or LMP gestational age estimates, our analyses demonstrated robust positive associations between PTB and ambient air pollution exposures even when gestational age uncertainty is present.

Associations between birth outcomes and maternal PM2.5 exposure in Shanghai: A comparison of three exposure assessment approaches

BACKGROUND

Few studies have estimated effects of maternal PM_2.5 exposure on birth outcomes in China due to the lack of historical air pollution data.

OBJECTIVES

We estimated the associations between maternal PM_2.5 exposure and birth outcomes using gap-filled satellite estimates in Shanghai, China.

METHODS

We obtained birth registration records of 132,783 singleton live births during 2011-2014 in Shanghai. PM_2.5 exposures were assessed from satellite-derived estimates or central-site measurements. Linear and logistic regressions were used to estimate associations with term birth weight and term low birth weight (LBW), respectively. Logistic and discrete-time survival models were used to estimate associations with preterm birth. Effect modification by maternal age and parental education levels was investigated.

RESULTS

A 10 μg/m³ increase in gap-filled satellite-based whole-pregnancy PM_2.5 exposure was associated with a -12.85 g (95% CI: -18.44, -7.27) change in term birth weight, increased risk of preterm birth (OR 1.27, 95% CI: 1.20, 1.36), and increased risk of term LBW (OR 1.22, 95% CI: 1.06, 1.41). Sensitivity analyses during 2013-2014, when ground PM_2.5 measurements were available, showed that the health associations using gap-filled satellite PM_2.5 concentrations were higher than those obtained using satellite PM_2.5 concentrations without accounting for missingness. The health associations using gap-filled satellite PM_2.5 had similar magnitudes to those using central-site measurements, but with narrower confidence intervals.

CONCLUSIONS

The magnitude of associations between maternal PM_2.5 exposure and adverse birth outcomes in Shanghai was higher than previous findings. One reason could be reduced exposure error of the gap-filled high-resolution satellite PM_2.5 estimates.

Early-Life Air Pollution Exposure, Neighborhood Poverty, and Childhood Asthma in the United States, 1990⁻2014

Ambient air pollution is a well-known risk factor of various asthma-related outcomes, however, past research has often focused on acute exacerbations rather than asthma development. This study draws on a population-based, multigenerational panel dataset from the United States to assess the association of childhood asthma risk with census block-level, annual-average air pollution exposure measured during the prenatal and early postnatal periods, as well as effect modification by neighborhood poverty. Findings suggest that early-life exposures to nitrogen dioxide (NO₂), a marker of traffic-related pollution, and fine particulate matter (PM2.5), a mixture of industrial and other pollutants, are positively associated with subsequent childhood asthma diagnosis (OR = 1.25, 95% CI = 1.10⁻1.41 and OR = 1.25, 95% CI = 1.06⁻1.46, respectively, per interquartile range (IQR) increase in each pollutant (NO₂ IQR = 8.51 ppb and PM2.5 IQR = 4.43 µ/m³)). These effects are modified by early-life neighborhood poverty exposure, with no or weaker effects in moderate- and low- (versus high-) poverty areas. This work underscores the importance of a holistic, developmental approach to elucidating the interplay of social and environmental contexts that may create conditions for racial-ethnic and socioeconomic disparities in childhood asthma risk.

Associations of mobile source air pollution during the first year of life with childhood pneumonia, bronchiolitis, and otitis media

Supplemental Digital Content is available in the text.

Background:

Exposure to air pollution from motor vehicles in early life may increase susceptibility to common pediatric infections.

Methods:

We estimated associations between residential exposure to primary fine particulate matter, nitrogen oxides, and carbon monoxide from traffic during the first year of life and incident pneumonia, bronchiolitis, and otitis media events by age 2 years in 22,441 children from the Kaiser Air Pollution and Pediatric Asthma Study, a retrospective birth cohort of children born during 2000–2010 and insured by Kaiser Permanente Georgia. Time to first clinical diagnosis of each outcome was defined using medical records. Exposure to traffic pollutants was based on observation-calibrated estimates from A Research LINE-source dispersion model for near surface releases and child residential histories. Associations were modeled using Cox proportional hazards models, with exposure as a continuous linear variable, a natural-log transformed continuous variable, and categorized by quintiles.

Results:

During follow-up, 2,181 children were diagnosed with pneumonia, 5,533 with bronchiolitis, and 14,374 with otitis media. We observed positive associations between early-life traffic exposures and all three outcomes; confidence intervals were widest for pneumonia as it was the least common outcome. For example, adjusted hazard ratios for a 1-unit increase in nitrogen oxides on the natural log scale (a 2.7-fold increase) were 1.19 (95% CI = 1.12, 1.27) for bronchiolitis, 1.17 (1.12, 1.22) for otitis media, and 1.08 (0.97, 1.20) for pneumonia.

Conclusions:

Our results provide evidence for modest, positive associations between exposure to traffic emissions and common pediatric infections during early childhood.

Exposure to Mobile Source Air Pollution in Early-life and Childhood Asthma Incidence: The Kaiser Air Pollution and Pediatric Asthma Study

BACKGROUND

Early-life exposure to traffic-related air pollution exacerbates childhood asthma, but it is unclear what role it plays in asthma development.

METHODS

The association between exposure to primary mobile source pollutants during pregnancy and during infancy and asthma incidence by ages 2 through 6 was examined in the Kaiser Air Pollution and Pediatric Asthma Study, a racially diverse birth cohort of 24,608 children born between 2000 and 2010 and insured by Kaiser Permanente Georgia. We estimated concentrations of mobile source fine particulate matter (PM2.5, µg/m), nitrogen oxides (NOX, ppb), and carbon monoxide (CO, ppm) at the maternal and child residence using a Research LINE source dispersion model for near-surface releases. Asthma was defined using diagnoses and medication dispensings from medical records. We used binomial generalized linear regression to model the impact of exposure continuously and by quintiles on asthma risk.

RESULTS

Controlling for covariates and modeling log-transformed exposure, a 2.7-fold increase in first year of life PM2.5 was associated with an absolute 4.1% (95% confidence interval, 1.6%, 6.6%) increase in risk of asthma by age 5. Quintile analysis showed an increase in risk from the first to second quintile, but similar risk across quintiles 2-5. Risk differences increased with follow-up age. Results were similar for NOX and CO and for exposure during pregnancy and the first year of life owing to high correlation.

CONCLUSIONS

Results provide limited evidence for an association of early-life mobile source air pollution with childhood asthma incidence with a steeper concentration-response relationship observed at lower levels of exposure.

Reproductive outcomes after non-occupational exposure to hexavalent chromium, Willits California, 1983-2014

BACKGROUND

From 1963-1995, a factory in Willits, Mendocino County, CA used toxic hexavalent chromium (Cr(VI)) without adequate measures to protect the population. We use longitudinal hospital data to compare reproductive outcomes for two generations in Willits and two generations in the Rest of County (ROC). This is the first study to quantify the reproductive impact of Cr(VI) in a non-occupational population.

METHODS

We searched California hospital discharge data (1983-2014) to find Mendocino County residents born 1950 or later. ZIP-code 95490 identifies Willits residents, with all others living in ROC. We used the Multi-Level Clinical Classification Software (CCS) to classify health outcomes. First, we calculated the crude birth rate using an external census denominator. The next two models used self-contained denominators to assess health of infants and two generations of pregnant women. Finally, we focused on non-pregnant females and, for comparison, males. Here we added admissions for people who moved, linked and summarized admissions to the person level, and calculated rates per census population.

RESULTS

We found 29311 newborn records in ROC and 5036 from Willits. At start of period, Willits birth rate was low and did not recover until 12 years after Plant closure. While the Plant was open, respiratory conditions, perinatal jaundice, and birth defect rates were higher for Willits infants compared to ROC, but improved post-closure. Risk for abnormal birthweight and term was high and remained high over the study period. During the period under study, we identified 31444 admissions of pregnant ROC women and 5558 from Willits. Willits women had significantly higher risk of pregnancy loss compared to ROC, whether stratified by generation, age group, or pre- and post-closure. Regardless of when exposed, Willits women continued to have significantly higher rates of in-hospital terminations, as animal studies of Cr(VI) exposure predict. In life course models, non-pregnant Willits women have significantly higher risk of reproductive organ conditions and neoplasms compared to ROC.

CONCLUSIONS

Adverse reproductive outcomes are elevated and consistent with animal studies. General health outcomes reflect the same broad effect reported for occupationally exposed workers. For the first time, the detrimental reproductive effects of non-occupational Cr(VI) exposure in human females and their infants is reported.