The Camp fire and perinatal health: An example of the generalized synthetic control method to identify susceptible windows of exposure.

BACKGROUND: The November 2018 Camp fire was the most destructive wildfire in California history, but its effects on reproductive health are not known. METHODS: We linked California birth records from 2017-2019 to daily smoke levels using U.S. EPA Air Quality System (AQS) PM2.5 data and NOAA Hazard Mapping System smoke plume polygons during the Camp fire. In the main analysis, pregnancies were considered exposed if they had median AQS PM2.5 levels above 50 µg/m3 for at least 7 days during November 8-22, 2018. We calculated rates of preterm birth and the infant sex ratio based on week of conception and used the generalized synthetic control method to estimate the average treatment effect on the treated and to propose a novel approach to identify potential critical weeks of exposure during pregnancy. RESULTS: We found associations between Camp fire-related smoke exposure and rates of preterm birth, with a risk difference (RD) = 0.005, 95% CI 0.001, 0.010. Exposure during week 10 of pregnancy was consistently associated with increased preterm birth (RD = 0.030, 95% CI 0.004, 0.056). We did not observe differences in the infant sex ratio. CONCLUSIONS: Camp fire smoke exposure was associated with increased rates of preterm birth, with sensitive windows in the first trimester.

Prenatal and Early Life Exposure to Ambient Air Pollutants Is Associated with the Fecal Metabolome in the First Two Years of Life.

Prenatal and early life air pollution exposure has been linked with several adverse health outcomes. However, the mechanisms underlying these relationships are not yet fully understood. Therefore, this study utilizes fecal metabolomics to determine if pre- and postnatal exposure to ambient air pollutants (i.e., PM10, PM2.5, and NO2) is associated with the fecal metabolome in the first 2 years of life in a Latino cohort from Southern California. The aims of this analysis were to estimate associations between (1) prenatal air pollution exposure with fecal metabolic features at 1-month of age, (2) prior month postnatal air pollution exposure with fecal metabolites from 1-month to 2 years of age, and (3) how postnatal air pollution exposure impacts the change over time of fecal metabolites in the first 2 years of life. Prenatal exposure to air pollutants was associated with several Level-1 metabolites, including those involved in vitamin B6 and tyrosine metabolism. Prior month air pollution exposure in the postnatal period was associated with Level-1 metabolites involved in histidine metabolism. Lastly, we found that pre- and postnatal ambient air pollution exposure was associated with changes in metabolic features involved in metabolic pathways including amino acid metabolism, histidine metabolism, and fatty acid metabolism.

Prenatal air pollution exposure is associated with inflammatory, cardiovascular, and metabolic biomarkers in mothers and newborns.

BACKGROUND: Prenatal air pollution exposure has been associated with individual inflammatory, cardiovascular, and metabolic biomarkers in mothers and neonates. However, studies of air pollution and a comprehensive panel of biomarkers across maternal and cord blood samples remain limited. Few studies used data-driven methods to identify biomarker groupings that converge biomarkers from multiple biological pathways. This study aims to investigate the impacts of prenatal air pollution on groups of biomarkers in maternal and cord blood samples. METHODS: In the Maternal And Developmental Risks from Environmental and Social Stressors (MADRES) cohort, 87 biomarkers were quantified from 45 trimester 1 maternal blood and 55 cord blood samples. Pregnancy and trimester 1-averaged concentrations of particulate matter ≤2.5 µm and ≤10 µm in diameter (PM2.5 and PM10), nitrogen dioxide (NO2), and ozone (O3) were estimated, using inverse distance squared weighted spatial interpolation from regulatory air monitoring stations. Traffic-related NOx was assessed using California Line Source Dispersion Model: freeway/highway roads, non-freeway major roads, non-freeway minor roads, and their sum as total NOx. Elastic Net (EN) regression within the rexposome R package was used to group biomarkers and assess their associations with air pollution. RESULTS: In maternal samples, trimester 1-averaged PM10 was associated with elevated inflammation biomarkers and lowered cardiovascular biomarkers. NO2 exhibited positive associations with cardiovascular and inflammation markers. O3 was inversely associated with inflammation, metabolic, and cardiovascular biomarkers. In cord blood, pregnancy-averaged PM2.5 was associated with higher cardiovascular biomarkers and lower metabolic biomarkers. PM10 was associated with lower inflammation and higher cardiovascular biomarkers. Total and major road NOx was associated with lower cardiovascular biomarkers. CONCLUSION: Prenatal air pollution exposure was associated with changes in biomarkers related to inflammation, cardiovascular, metabolic, cancer, and neurological function in both mothers and neonates. This study shed light on mechanisms by which air pollution can influence biological function during pregnancy.

Prenatal ambient air pollution exposure and child weight trajectories from the 3rd trimester of pregnancy to 2 years of age: a cohort study.

BACKGROUND: Prenatal air pollution exposure may increase risk for childhood obesity. However, few studies have evaluated in utero growth measures and infant weight trajectories. This study will evaluate the associations of prenatal exposure to ambient air pollutants with weight trajectories from the 3rd trimester through age 2 years. METHODS: We studied 490 pregnant women who were recruited from the Maternal and Development Risks from Environmental and Social Stressors (MADRES) cohort, which comprises a low-income, primarily Hispanic population in Los Angeles, California. Nitrogen dioxide (NO2), particulate matter < 10 µm (PM10), particulate matter < 2.5 µm (PM2.5), and ozone (O3) concentrations during pregnancy were estimated from regulatory air monitoring stations. Fetal weight was estimated from maternal ultrasound records. Infant/child weight measurements were extracted from medical records or measured during follow-up visits. Piecewise spline models were used to assess the effect of air pollutants on weight, overall growth, and growth during each period. RESULTS: The mean (SD) prenatal exposure concentrations for NO2, PM2.5, PM10, and O3 were 16.4 (2.9) ppb, 12.0 (1.1) µg/m3, 28.5 (4.7) µg/m3, and 26.2 (2.9) ppb, respectively. Comparing an increase in prenatal average air pollutants from the 10th to the 90th percentile, the growth rate from the 3rd trimester to age 3 months was significantly increased (1.55% [95%CI 1.20%, 1.99%] for PM2.5 and 1.64% [95%CI 1.27%, 2.13%] for NO2), the growth rate from age 6 months to age 2 years was significantly decreased (0.90% [95%CI 0.82%, 1.00%] for NO2), and the attained weight at age 2 years was significantly lower (- 7.50% [95% CI - 13.57%, - 1.02%] for PM10 and - 7.00% [95% CI - 11.86%, - 1.88%] for NO2). CONCLUSIONS: Prenatal ambient air pollution was associated with variable changes in growth rate and attained weight from the 3rd trimester to age 2 years. These results suggest continued public health benefits of reducing ambient air pollution levels, particularly in marginalized populations.

Associations of Autism Spectrum Disorder with PM2.5 Components: A Comparative Study Using Two Different Exposure Models.

This retrospective cohort study examined associations of autism spectrum disorder (ASD) with prenatal exposure to major fine particulate matter (PM2.5) components estimated using two independent exposure models. The cohort included 318 750 mother-child pairs with singleton deliveries in Kaiser Permanente Southern California hospitals from 2001 to 2014 and followed until age five. ASD cases during follow-up (N = 4559) were identified by ICD codes. Prenatal exposures to PM2.5, elemental (EC) and black carbon (BC), organic matter (OM), nitrate (NO3-), and sulfate (SO42-) were constructed using (i) a source-oriented chemical transport model and (ii) a hybrid model. Exposures were assigned to each maternal address during the entire pregnancy, first, second, and third trimester. In single-pollutant models, ASD was associated with pregnancy-average PM2.5, EC/BC, OM, and SO42- exposures from both exposure models, after adjustment for covariates. The direction of effect estimates was consistent for EC/BC and OM and least consistent for NO3-. EC/BC, OM, and SO42- were generally robust to adjustment for other components and for PM2.5. EC/BC and OM effect estimates were generally larger and more consistent in the first and second trimester and SO42- in the third trimester. Future PM2.5 composition health effect studies might consider using multiple exposure models and a weight of evidence approach when interpreting effect estimates.

Associations between prenatal and early-life air pollution exposure and lung function in young children: Exploring influential windows of exposure on lung development.

BACKGROUND: Evidence in the literature suggests that air pollution exposures experienced prenatally and early in life can be detrimental to normal lung development, however the specific timing of critical windows during development is not fully understood. OBJECTIVES: We evaluated air pollution exposures during the prenatal and early-life period in association with lung function at ages 6-9, in an effort to identify potentially influential windows of exposure for lung development. METHODS: Our study population consisted of 222 children aged 6-9 from the Fresno-Clovis metro area in California with spirometry data collected between May 2015 and May 2017. We used distributed-lag non-linear models to flexibly model the exposure-lag-response for monthly average exposure to fine particulate matter (PM2.5) and ozone (O3) during the prenatal months and first three years of life in association with forced vital capacity (FVC), and forced expiratory volume in the first second (FEV1), adjusted for covariates. RESULTS: PM2.5 exposure during the prenatal period and the first 3-years of life was associated with lower FVC and FEV1 assessed at ages 6-9. Specifically, an increase from the 5th percentile of the observed monthly average exposure (7.55 µg/m3) to the median observed exposure (12.69 µg/m3) for the duration of the window was associated with 0.42 L lower FVC (95% confidence interval (CI): -0.82, -0.03) and 0.38 L lower FEV1 (95% CI: -0.75, -0.02). The shape of the lag-response indicated that the second half of pregnancy may be a particularly influential window of exposure. Associations for ozone were not as strong and typically CIs included the null. CONCLUSIONS: Our findings indicate that prenatal and early-life exposures to PM2.5 are associated with decreased lung function later in childhood. Exposures during the latter months of pregnancy may be especially influential.

Ambient Air Pollutant Exposures and COVID-19 Severity and Mortality in a Cohort of Patients with COVID-19 in Southern California.

Rationale: Ecological studies have shown air pollution associations with coronavirus disease (COVID-19) outcomes. However, few cohort studies have been conducted. Objectives: To conduct a cohort study investigating the association between air pollution and COVID-19 severity using individual-level data from the electronic medical record. Methods: This cohort included all individuals who received diagnoses of COVID-19 from Kaiser Permanente Southern California between March 1 and August 31, 2020. One-year and 1-month averaged ambient air pollutant (particulate matter ⩽2.5 µm in aerodynamic diameter [PM2.5], NO2, and O3) exposures before COVID-19 diagnosis were estimated on the basis of residential address history. Outcomes included COVID-19-related hospitalizations, intensive respiratory support (IRS), and ICU admissions within 30 days and mortality within 60 days after COVID-19 diagnosis. Covariates included socioeconomic characteristics and comorbidities. Measurements and Main Results: Among 74,915 individuals (mean age, 42.5 years; 54% women; 66% Hispanic), rates of hospitalization, IRS, ICU admission, and mortality were 6.3%, 2.4%, 1.5%, and 1.5%, respectively. Using multipollutant models adjusted for covariates, 1-year PM2.5 and 1-month NO2 average exposures were associated with COVID-19 severity. The odds ratios associated with a 1-SD increase in 1-year PM2.5 (SD, 1.5 µg/m3) were 1.24 (95% confidence interval [CI], 1.16-1.32) for COVID-19-related hospitalization, 1.33 (95% CI, 1.20-1.47) for IRS, and 1.32 (95% CI, 1.16-1.51) for ICU admission; the corresponding odds ratios associated with 1-month NO2 (SD, 3.3 ppb) were 1.12 (95% CI, 1.06-1.17) for hospitalization, 1.18 (95% CI, 1.10-1.27) for IRS, and 1.21 (95% CI, 1.11-1.33) for ICU admission. The hazard ratios for mortality were 1.14 (95% CI, 1.02-1.27) for 1-year PM2.5 and 1.07 (95% CI, 0.98-1.16) for 1-month NO2. No significant interactions with age, sex or ethnicity were observed. Conclusions: Ambient PM2.5 and NO2 exposures may affect COVID-19 severity and mortality.

Ambient air pollution and COVID-19 incidence during four 2020-2021 case surges.

BACKGROUND: Air pollution exposure may make people more vulnerable to COVID-19 infection. However, previous studies in this area mostly focused on infection before May 2020 and long-term exposure. OBJECTIVE: To assess both long-term and short-term exposure to air pollution and COVID-19 incidence across four case surges from 03/1/2020 to 02/28/2021. METHODS: The cohort included 4.6 million members from a large integrated health care system in southern California with comprehensive electronic medical records (EMR). COVID-19 cases were identified from EMR. Incidence of COVID-19 was computed at the census tract-level among members. Prior 1-month and 1-year averaged air pollutant levels (PM2.5, NO2, and O3) at the census tract-level were estimated based on hourly and daily air quality data. Data analyses were conducted by each wave: 3/1/2020-5/31/2020, 6/1/202-9/30/2020, 10/1/2020-12/31/2020, and 1/1/2021-2/28/2021 and pooled across waves using meta-analysis. Generalized linear mixed effects models with Poisson distribution and spatial autocorrelation were used with adjustment for meteorological factors and census tract-level social and health characteristics. Results were expressed as relative risk (RR) per 1 standard deviation. RESULTS: The cohort included 446,440 COVID-19 cases covering 4609 census tracts. The pooled RRs (95% CI) of COVID-19 incidence associated with 1-year exposures to PM2.5, NO2, and O3 were 1.11 (1.04, 1.18) per 2.3 µg/m3,1.09 (1.02, 1.17) per 3.2 ppb, and 1.06 (1.00, 1.12) per 5.5 ppb respectively. The corresponding RRs (95% CI) associated with prior 1-month exposures were 1.11 (1.03, 1.20) per 5.2 µg/m3 for PM2.5, 1.09 (1.01, 1.17) per 6.0 ppb for NO2 and 0.96 (0.85, 1.08) per 12.0 ppb for O3. CONCLUSION: Long-term PM2.5 and NO2 exposures were associated with increased risk of COVID-19 incidence across all case surges before February 2021. Short-term PM2.5 and NO2 exposures were also associated. Our findings suggest that air pollution may play a role in increasing the risk of COVID-19 infection.

Identifying pre-conception and pre-natal periods in which ambient air pollution exposure affects fetal growth in the predominately Hispanic MADRES cohort.

BACKGROUND: It is well documented that persons of color experience disproportionate exposure to environmental contaminants, including air pollution, and have poorer pregnancy outcomes. This study assessed the critical windows of exposure to ambient air pollution on in utero fetal growth among structurally marginalized populations in urban Los Angeles. METHODS: Participants (N = 281) from the larger ongoing MADRES pregnancy cohort study were included in this analysis. Fetal growth outcomes were measured on average at 32 [Formula: see text] 2 weeks of gestation by a certified sonographer and included estimated fetal weight, abdominal circumference, head circumference, biparietal diameter and femur length. Daily ambient air pollutant concentrations were estimated for four pollutants (particulate matter less than 2.5 µm (PM2.5) and less than 10 µm (PM10) in aerodynamic diameter, nitrogen dioxide (NO2), and 8-h maximum ozone (O3)) at participant residences using inverse-distance squared spatial interpolation from ambient monitoring data. Weekly gestational averages were calculated from 12 weeks prior to conception to 32 weeks of gestation (44 total weeks), and their associations with growth outcomes were modeled using adjusted distributed lag models (DLMs). RESULTS: Participants were on average 29 years [Formula: see text] 6 old and predominately Hispanic (82%). We identified a significant sensitive window of PM2.5 exposure (per IQR increase of 6 [Formula: see text]3) between gestational weeks 4-16 for lower estimated fetal weight [Formula: see text] averaged4-16 = -8.7 g; 95% CI -16.7, -0.8). Exposure to PM2.5 during gestational weeks 1-23 was also significantly associated with smaller fetal abdominal circumference ([Formula: see text] averaged1-23 = -0.6 mm; 95% CI -1.1, -0.2). Additionally, prenatal exposure to PM10 (per IQR increase of 13 [Formula: see text]3) between weeks 6-15 of pregnancy was significantly associated with smaller fetal abdominal circumference ([Formula: see text] averaged6-15 = -0.4 mm; 95% CI -0.8, -0.1). DISCUSSION: These results suggest that exposure to particulate matter in early to mid-pregnancy, but not preconception or late pregnancy, may have critical implications on fetal growth.

Traffic-related air pollution is associated with glucose dysregulation, blood pressure, and oxidative stress in children.

BACKGROUND: Metabolic syndrome increases the risk of cardiovascular disease in adults. Antecedents likely begin in childhood and whether childhood exposure to air pollution plays a contributory role is not well understood. OBJECTIVES: To assess whether children's exposure to air pollution is associated with markers of risk for metabolic syndrome and oxidative stress, a hypothesized mediator of air pollution-related health effects. METHODS: We studied 299 children (ages 6-8) living in the Fresno, CA area. At a study center visit, questionnaire and biomarker data were collected. Outcomes included hemoglobin A1c (HbA1c), urinary 8-isoprostane, systolic blood pressure (SBP), and BMI. Individual-level exposure estimates for a set of four pollutants that are constituents of traffic-related air pollution (TRAP) - the sum of 4-, 5-, and 6-ring polycyclic aromatic hydrocarbon compounds (PAH456), NO2, elemental carbon, and fine particulate matter (PM2.5) - were modeled at the primary residential location for 1-day lag, and 1-week, 1-month, 3-month, 6-month, and 1-year averages prior to each participant's visit date. Generalized additive models were used to estimate associations between each air pollutant exposure and outcome. RESULTS: The study population was 53% male, 80% Latinx, 11% Black and largely low-income (6% were White and 3% were Asian/Pacific Islander). HbA1c percentage was associated with longer-term increases in TRAP; for example a 4.42 ng/m3 increase in 6-month average PAH456 was associated with a 0.07% increase (95% CI: 0.01, 0.14) and a 3.62 µg/m3 increase in 6-month average PM2.5 was associated with a 0.06% increase (95% CI: 0.01, 0.10). The influence of air pollutants on blood pressure was strongest at 3 months; for example, a 6.2 ppb increase in 3-month average NO2 was associated with a 9.4 mmHg increase in SBP (95% CI: 2.8, 15.9). TRAP concentrations were not significantly associated with anthropometric or adipokine measures. Short-term TRAP exposure averages were significantly associated with creatinine-adjusted urinary 8-isoprostane. DISCUSSION: Our results suggest that both short- and longer-term estimated individual-level outdoor residential exposures to several traffic-related air pollutants, including ambient PAHs, are associated with biomarkers of risk for metabolic syndrome and oxidative stress in children.

Prenatal ambient air pollution and maternal depression at 12 months postpartum in the MADRES pregnancy cohort.

BACKGROUND: Depression is the leading cause of mental health-related morbidity and affects twice as many women as men. Hispanic/Latina women in the US have unique risk factors for depression and they have lower utilization of mental health care services. Identifying modifiable risk factors for maternal depression, such as ambient air pollution, is an urgent public health priority. We aimed to determine whether prenatal exposure to ambient air pollutants was associated with maternal depression at 12 months after childbirth. METHODS: One hundred eighty predominantly low-income Hispanic/Latina women participating in the ongoing MADRES cohort study in Los Angeles, CA were followed from early pregnancy through 12 months postpartum through a series of phone questionnaires and in-person study visits. Daily prenatal ambient pollutant estimates of nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM10 and PM2.5) were assigned to participant residences using inverse-distance squared spatial interpolation from ambient monitoring data. Exposures were averaged for each trimester and across pregnancy. The primary outcome measure was maternal depression at 12 months postpartum, as reported on the 20-item Center for Epidemiologic Studies-Depression (CES-D) scale. We classified each participant as depressed (n = 29) or not depressed (n = 151) based on the suggested cutoff of 16 or above (possible scores range from 0 to 60) and fitted logistic regression models, adjusting for potential confounders. RESULTS: We found over a two-fold increased odds of depression at 12 months postpartum associated with second trimester NO2 exposure (OR = 2.63, 95% CI: 1.41-4.89) and pregnancy average NO2 (OR = 2.04, 95% CI: 1.13-3.69). Higher second trimester PM2.5 exposure also was associated with increased depression at 12 months postpartum (OR = 1.56, 95% CI: 1.01-2.42). The effect for second trimester PM10 was similar and was borderline significant (OR = 1.58, 95% CI: 0.97-2.56). CONCLUSIONS: In a low-income cohort consisting of primarily Hispanic/Latina women in urban Los Angeles, we found that prenatal ambient air pollution, especially mid-pregnancy NO2 and PM2.5, increased the risk of depression at 12 months after childbirth. These results underscore the need to better understand the contribution of modifiable environmental risk factors during potentially critical exposure periods.

Decrease in Ambient Polycyclic Aromatic Hydrocarbon Concentrations in California's San Joaquin Valley 2000-2019.

As part of our ongoing research to understand the impact of polycyclic aromatic hydrocarbon (PAH) exposures on health in the San Joaquin Valley, we evaluated airborne PAH concentration data collected over 19 years (2000-2019) at the central air monitoring site in Fresno, California. We found a dramatic decline in outdoor airborne PAH concentrations between 2000 and 2004 that has been maintained through 2019. This decline was present in both the continuous particle-bound PAHs and the filter-based individual PAHs. The decline was more extreme when restricted to winter concentrations. Annual mean PAHs concentrations in 2017- 2018 of particle-bound PAHs were 6.8 ng/m3 or 62% lower than 2000 - 2001. The decline for winter concentrations of continuous particle-bound PAHs between winter 2019 and winter 2001 was 17.2 ng/m3, a drop of 70%. The 2001 to 2018 decline in average wintertime concentrations for filter-based individual PAHs was 82%. We examined industrial emissions, on-road vehicle emissions, residential wood burning, and agricultural and biomass waste burning as possible explanations. The major decline in PAHs from 2000-2004 was coincident with and most likely due to a similar decline in the amount of agricultural and biomass waste burned in Fresno and Madera Counties. On-road vehicle emissions and residential wood burning did not decline until after 2005. Industrial emissions were too low (2% of total) to explain such large decreases in PAH concentrations.

Ambient air pollution, asthma drug response, and telomere length in African American youth.

BACKGROUND: Telomere length (TL) can serve as a potential biomarker for conditions associated with chronic oxidative stress and inflammation, such as asthma. Air pollution can induce oxidative stress. Understanding the relationship between TL, asthma, and air pollution is important for identifying risk factors contributing to unhealthy aging in children. OBJECTIVES: We sought to investigate associations between exposures to ambient air pollutants and TL in African American children and adolescents and to examine whether African ancestry, asthma status, and steroid medication use alter the association. METHODS: Linear regression was used to examine associations between absolute telomere length (aTL) and estimated annual average residential ozone (O3) and fine particulate matter with a diameter of 2.5 µm or less (PM2.5) exposures in a cross-sectional analysis of 1072 children in an existing asthma case-control study. African ancestry, asthma status, and use of steroid medications were examined as effect modifiers. RESULTS: Participants' aTLs were measured by using quantitative PCR. A 1-ppb and 1 µg/m3 increase in annual average exposure to O3 and PM2.5 were associated with a decrease in aTL of 37.1 kilo-base pair (kb; 95% CI, -66.7 to -7.4 kb) and 57.1 kb (95% CI, -118.1 to 3.9 kb), respectively. African ancestry and asthma were not effect modifiers; however, exposure to steroid medications modified the relationships between TL and pollutants. Past-year exposure to O3 and PM2.5 was associated with shorter TLs in patients without steroid use. CONCLUSION: Exposure to air pollution was associated with shorter TLs in nonasthmatic children and adolescents. This was not the case for asthmatic children as a group, but those receiving steroid medication had less shortening than those not using steroids. Reduced exposure to air pollution in childhood might help to preserve TL.

Study Design, Protocol and Profile of the Maternal And Developmental Risks from Environmental and Social Stressors (MADRES) Pregnancy Cohort: a Prospective Cohort Study in Predominantly Low-Income Hispanic Women in Urban Los Angeles.

BACKGROUND: The burden of childhood and adult obesity disproportionally affects Hispanic and African-American populations in the US, and these groups as well as populations with lower income and education levels are disproportionately affected by environmental pollution. Pregnancy is a critical developmental period where maternal exposures may have significant impacts on infant and childhood growth as well as the future health of the mother. We initiated the "Maternal And Developmental Risks from Environmental and Social Stressors (MADRES)" cohort study to address critical gaps in understanding the increased risk for childhood obesity and maternal obesity outcomes among minority and low-income women in urban Los Angeles. METHODS: The MADRES cohort is specifically examining whether pre- and postpartum environmental exposures, in addition to exposures to psychosocial and built environment stressors, lead to excessive gestational weight gain and postpartum weight retention in women and to perturbed infant growth trajectories and increased childhood obesity risk through altered psychological, behavioral and/or metabolic responses. The ongoing MADRES study is a prospective pregnancy cohort of 1000 predominantly lower-income, Hispanic women in Los Angeles, CA. Enrollment in the MADRES cohort is initiated prior to 30 weeks gestation from partner community health clinics in Los Angeles. Cohort participants are followed through their pregnancies, at birth, and during the infant's first year of life through a series of in-person visits with interviewer-administered questionnaires, anthropometric measurements and biospecimen collection as well as telephone interviews conducted with the mother. DISCUSSION: In this paper, we outline the study rationale and data collection protocol for the MADRES cohort, and we present a profile of demographic, health and exposure characteristics for 291 participants who have delivered their infants, out of 523 participants enrolled in the study from November 2015 to October 2018 from four community health clinics in Los Angeles. Results from the MADRES cohort could provide a powerful rationale for regulation of targeted chemical environmental components, better transportation and urban design policies, and clinical recommendations for stress-coping strategies and behavior to reduce lifelong obesity risk.

Long-Term Ambient Temperature and Externalizing Behaviors in Adolescents.

The climate-violence relationship has been debated for decades, and yet most of the supportive evidence has come from ecological or cross-sectional analyses with very limited long-term exposure data. We conducted an individual-level, longitudinal study to investigate the association between ambient temperature and externalizing behaviors of urban-dwelling adolescents. Participants (n = 1,287) in the Risk Factors for Antisocial Behavior Study, in California, were examined during 2000-2012 (aged 9-18 years) with repeated assessments of their externalizing behaviors (e.g., aggression, delinquency). Ambient temperature data were obtained from the local meteorological information system. In adjusted multilevel models, aggressive behaviors significantly increased with rising average temperatures (per 1°C increment) in the preceding 1, 2, or 3 years (respectively, ß = 0.23, 95% confidence interval (CI): 0.00, 0.46; ß = 0.35, 95% CI: 0.06, 0.63; or ß = 0.41, 95% CI: 0.08, 0.74), equivalent to 1.5-3.0 years of delay in age-related behavioral maturation. These associations were slightly stronger among girls and families of lower socioeconomic status but greatly diminished in neighborhoods with more green space. No significant associations were found with delinquency. Our study provides the first individual-level epidemiologic evidence supporting the adverse association of long-term ambient temperature and aggression. Similar approaches to studying meteorology and violent crime might further inform scientific debates on climate change and collective violence.

Association of improved air quality with lung development in children.

BACKGROUND: Air-pollution levels have been trending downward progressively over the past several decades in southern California, as a result of the implementation of air quality-control policies. We assessed whether long-term reductions in pollution were associated with improvements in respiratory health among children. METHODS: As part of the Children's Health Study, we measured lung function annually in 2120 children from three separate cohorts corresponding to three separate calendar periods: 1994-1998, 1997-2001, and 2007-2011. Mean ages of the children within each cohort were 11 years at the beginning of the period and 15 years at the end. Linear-regression models were used to examine the relationship between declining pollution levels over time and lung-function development from 11 to 15 years of age, measured as the increases in forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) during that period (referred to as 4-year growth in FEV1 and FVC). RESULTS: Over the 13 years spanned by the three cohorts, improvements in 4-year growth of both FEV1 and FVC were associated with declining levels of nitrogen dioxide (P<0.001 for FEV1 and FVC) and of particulate matter with an aerodynamic diameter of less than 2.5 µm (P= 0.008 for FEV1 and P<0.001 for FVC) and less than 10 µm (P<0.001 for FEV1 and FVC). These associations persisted after adjustment for several potential confounders. Significant improvements in lung-function development were observed in both boys and girls and in children with asthma and children without asthma. The proportions of children with clinically low FEV1 (defined as <80% of the predicted value) at 15 years of age declined significantly, from 7.9% to 6.3% to 3.6% across the three periods, as the air quality improved (P = 0.001). CONCLUSIONS: We found that long-term improvements in air quality were associated with statistically and clinically significant positive effects on lung-function growth in children. (Funded by the Health Effects Institute and others.).

Genetic variation in biotransformation enzymes, air pollution exposures, and risk of spina bifida.

Spina bifida is a birth defect characterized by incomplete closure of the embryonic neural tube. Genetic factors as well as environmental factors have been observed to influence risks for spina bifida. Few studies have investigated possible gene-environment interactions that could contribute to spina bifida risk. The aim of this study is to examine the interaction between gene variants in biotransformation enzyme pathways and ambient air pollution exposures and risk of spina bifida. We evaluated the role of air pollution exposure during pregnancy and gene variants of biotransformation enzymes from bloodspots and buccal cells in a California population-based case-control (86 cases of spina bifida and 208 non-malformed controls) study. We considered race/ethnicity and folic acid vitamin use as potential effect modifiers and adjusted for those factors and smoking. We observed gene-environment interactions between each of the five pollutants and several gene variants: NO (ABCC2), NO2 (ABCC2, SLC01B1), PM10 (ABCC2, CYP1A1, CYP2B6, CYP2C19, CYP2D6, NAT2, SLC01B1, SLC01B3), PM2.5 (CYP1A1 and CYP1A2). These analyses show positive interactions between air pollution exposure during early pregnancy and gene variants associated with metabolizing enzymes. These exploratory results suggest that some individuals based on their genetic background may be more susceptible to the adverse effects of pollution.

Longitudinal associations of in utero and early life near-roadway air pollution with trajectories of childhood body mass index.

BACKGROUND: Evidence suggests that childhood near-roadway air pollution (NRAP) exposures contribute to increased body mass index (BMI); however, effects of NRAP exposure during the vulnerable periods including in utero and first year of life have yet to be established. In this study, we examined whether exposure to elevated concentrations of NRAP during in utero and/or first year of life increase childhood BMI growth. METHODS: Participants in the Children's Health Study enrolled from 2002 to 2003 with annual visits over a four-year period and who changed residences before study entry were included (n = 2318). Annual height and weight were measured and lifetime residential NRAP exposures including in utero and first year of life periods were estimated by nitrogen oxides (NOx) using the California line-source dispersion model. Linear mixed effects models assessed in utero or first year near-road freeway and non-freeway NOx exposures and BMI growth after adjusting for age, sex, race/ethnicity, parental education, Spanish questionnaire, and later childhood near-road NOx exposure. RESULTS: A two-standard deviation difference in first year of life near-road freeway NOx exposure was associated with a 0.1 kg/m2 (95% confidence interval (CI): 0.03, 0.2) faster increase in BMI growth per year and a 0.5 kg/m2 (95% CI: 0.02, 0.9) higher attained BMI at age 10 years. CONCLUSIONS: Higher exposure to early life NRAP increased the rate of change of childhood BMI and resulted in a higher attained BMI at age 10 years that were independent of later childhood exposures. These findings suggest that elevated early life NRAP exposures contribute to increased obesity risk in children.

Constrained Mixed-Effect Models with Ensemble Learning for Prediction of Nitrogen Oxides Concentrations at High Spatiotemporal Resolution.

Spatiotemporal models to estimate ambient exposures at high spatiotemporal resolutions are crucial in large-scale air pollution epidemiological studies that follow participants over extended periods. Previous models typically rely on central-site monitoring data and/or covered short periods, limiting their applications to long-term cohort studies. Here we developed a spatiotemporal model that can reliably predict nitrogen oxide concentrations with a high spatiotemporal resolution over a long time span (>20 years). Leveraging the spatially extensive highly clustered exposure data from short-term measurement campaigns across 1-2 years and long-term central site monitoring in 1992-2013, we developed an integrated mixed-effect model with uncertainty estimates. Our statistical model incorporated nonlinear and spatial effects to reduce bias. Identified important predictors included temporal basis predictors, traffic indicators, population density, and subcounty-level mean pollutant concentrations. Substantial spatial autocorrelation (11-13%) was observed between neighboring communities. Ensemble learning and constrained optimization were used to enhance reliability of estimation over a large metropolitan area and a long period. The ensemble predictions of biweekly concentrations resulted in an R2 of 0.85 (RMSE: 4.7 ppb) for NO2 and 0.86 (RMSE: 13.4 ppb) for NOx. Ensemble learning and constrained optimization generated stable time series, which notably improved the results compared with those from initial mixed-effects models.