Dataset Information

Air Pollution and Autism Spectrum Disorder in Israel: A Negative Control Analysis.

ABSTRACT:

Background

Residual confounding is a major concern for causal inference in observational studies on air pollution-autism spectrum disorder (ASD) associations. This study is aimed at assessing confounding in these associations using negative control exposures.

Methods

This nested case-control study included all children diagnosed with ASD (detected through 31 December 2016) born during 2007-2012 in Israel and residing in the study area (N = 3,843), and matched controls of the same age (N = 38,430). We assigned individual house-level exposure estimates for each child. We estimated associations using logistic regression models, mutually adjusted for all relevant exposure periods (prepregnancy, pregnancy, and postnatal). We assessed residual confounding using postoutcome negative control exposure at age 28-36 months.

Results

In mutually adjusted models, we observed positive associations with ASD for postnatal exposures to NOx (odds ratio per interquartile range, 95% confidence interval: 1.19, 1.02-1.38) and NO2 (1.20, 1.00-1.43), and gestational exposure to PM2.5-10 (1.08, 1.01-1.15). The result for the negative control period was 1.04, 0.99-1.10 for PM2.5, suggesting some residual confounding, but no associations for PM2.5-10 (0.98, 0.81-1.18), NOx (1.02, 0.84-1.25), or NO2 (0.98, 0.81-1.18), suggesting no residual confounding.

Conclusions

Our results further support a hypothesized causal link with ASD that is specific to postnatal exposures to traffic-related pollution.

SUBMITTER: Magen-Molho H

PROVIDER: S-EPMC8478838 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Air Pollution and Autism Spectrum Disorder in Israel: A Negative Control Analysis.

Magen-Molho Hadas H Weisskopf Marc G MG Nevo Daniel D Shtein Alexandra A Chen Shimon S Broday David D Kloog Itai I Levine Hagai H Pinto Ofir O Raz Raanan R

Epidemiology (Cambridge, Mass.) 20211101 6

<h4>Background</h4>Residual confounding is a major concern for causal inference in observational studies on air pollution-autism spectrum disorder (ASD) associations. This study is aimed at assessing confounding in these associations using negative control exposures.<h4>Methods</h4>This nested case-control study included all children diagnosed with ASD (detected through 31 December 2016) born during 2007-2012 in Israel and residing in the study area (N = 3,843), and matched controls of the same ...[more]

PMID: 34347685

Similar Datasets

Project description:BackgroundAutism Spectrum Disorder (ASD) risk is highly heritable, with potential additional non-genetic factors, such as prenatal exposure to ambient particulate matter with aerodynamic diameter < 2.5 µm (PM2.5) and maternal immune activation (MIA) conditions. Because these exposures may share common biological effect pathways, we hypothesized that synergistic associations of prenatal air pollution and MIA-related conditions would increase ASD risk in children.ObjectivesThis study examined interactions between MIA-related conditions and prenatal PM2.5 or major PM2.5 components on ASD risk.MethodsIn a population-based pregnancy cohort of children born between 2001 and 2014 in Southern California, 318,751 mother-child pairs were followed through electronic medical records (EMR); 4,559 children were diagnosed with ASD before age 5. Four broad categories of MIA-related conditions were classified, including infection, hypertension, maternal asthma, and autoimmune conditions. Average exposures to PM2.5 and four PM2.5 components, black carbon (BC), organic matter (OM), nitrate (NO3-), and sulfate (SO42-), were estimated at maternal residential addresses during pregnancy. We estimated the ASD risk associated with MIA-related conditions, air pollution, and their interactions, using Cox regression models to adjust for covariates.ResultsASD risk was associated with MIA-related conditions [infection (hazard ratio 1.11; 95% confidence interval 1.05-1.18), hypertension (1.30; 1.19-1.42), maternal asthma (1.22; 1.08-1.38), autoimmune disease (1.19; 1.09-1.30)], with higher pregnancy PM2.5 [1.07; 1.03-1.12 per interquartile (3.73 μg/m3) increase] and with all four PM2.5 components. However, there were no interactions of each category of MIA-related conditions with PM2.5 or its components on either multiplicative or additive scales.ConclusionsMIA-related conditions and pregnancy PM2.5 were independently associations with ASD risk. There were no statistically significant interactions of MIA conditions and prenatal PM2.5 exposure with ASD risk.

Project description:BACKGROUND:Ambient air pollution and maternal diabetes may affect common biological pathways underlying adverse neurodevelopmental effects. However, joint effects of maternal diabetes and air pollution on autism spectrum disorder (ASD) have not been studied. OBJECTIVE:We evaluated whether prenatal and early-life air pollution exposure interacts with maternal diabetes status to affect ASD risk. METHODS:This retrospective cohort study included 246,420 singleton children born in Kaiser Permanente Southern California hospitals in 1999-2009. Children were followed from birth until age 5, during which 2471 ASD cases were diagnosed. Ozone (O3), particulate matter?<?2.5??m (PM2.5) and <10??m in aerodynamic diameter, and nitrogen dioxide measured at regulatory air monitoring stations were interpolated to estimate exposures during preconception and each pregnancy trimester, and first year of life at each child's birth address. Hazard ratios (HRs) for ASD were estimated adjusting for birth year, KPSC service areas, and relevant maternal and child characteristics. For each exposure window, interactions were tested between pollutants and a 4-category maternal diabetes variable (none, GDM???24 and <24?weeks' gestation, and pre-existing type 2 diabetes). For an exposure window with statistically significant global interaction between pollutant and diabetes (p?<?0.05), pollutant-associated HRs were estimated separately for each category of maternal diabetes. RESULTS:There were associations of ASD with preconception, first and third trimesters, and first year of life PM2.5, but not with other pollutants. There were, however, interactions of maternal diabetes with first trimester and first year of life O3. Increased ASD risk was associated with first trimester O3 among mothers with GDM?<?24?weeks' gestation [adjusted HR 1.50 per 15.7?ppb O3 (95% CI: 1.08-2.09)]. No O3 associations with ASD were observed in other categories of maternal diabetes. CONCLUSIONS:GDM onset early in pregnancy may increase children's susceptibility to prenatal O3-associated ASD risk. These novel findings merit further investigation.

Project description:ImportanceThe etiology of autism spectrum disorder (ASD) is poorly understood, but prior studies suggest associations with airborne pollutants.ObjectiveTo evaluate the association between prenatal exposures to airborne pollutants and ASD in a large population-based cohort.Design, setting, and participantsThis population-based cohort encompassed nearly all births in Metro Vancouver, British Columbia, Canada, from 2004 through 2009, with follow-up through 2014. Children were diagnosed with ASD using a standardized assessment with the Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule. Monthly mean exposures to particulate matter with a diameter less than 2.5 µm (PM2.5), nitric oxide (NO), and nitrogen dioxide (NO2) at the maternal residence during pregnancy were estimated with temporally adjusted, high-resolution land use regression models. The association between prenatal air pollution exposures and the odds of developing ASD was evaluated using logistic regression adjusted for child sex, birth month, birth year, maternal age, maternal birthplace, and neighborhood-level urbanicity and income band. Data analysis occurred from June 2016 to May 2018.ExposuresMean monthly concentrations of ambient PM2.5, NO, and NO2 at the maternal residence during pregnancy, calculated retrospectively using temporally adjusted, high-resolution land use regression models.Main outcomes and measuresAutism spectrum disorder diagnoses based on standardized assessment of the Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule. The hypothesis being tested was formulated during data collection.ResultsIn a cohort of 132 256 births, 1307 children (1.0%) were diagnosed with ASD by the age of 5 years. The final sample size for the PM2.5-adjusted model was 129 439 children, and for NO and NO2, it was 129 436 children; of these, 1276 (1.0%) were diagnosed with ASD. Adjusted odds ratios for ASD per interquartile range (IQR) were not significant for exposure to PM2.5 during pregnancy (1.04 [95% CI, 0.98-1.10] per 1.5 μg/m3 increase [IQR] in PM2.5) or NO2 (1.06 [95% CI, 0.99-1.12] per 4.8 ppb [IQR] increase in NO2) but the odds ratio was significant for NO (1.07 [95% CI, 1.01-1.13] per 10.7 ppb [IQR] increase in NO). Odds ratios for male children were 1.04 (95% CI, 0.98-1.10) for PM2.5; 1.09 (95% CI, 1.02-1.15) for NO; and 1.07 (95% CI, 1.00-1.13) for NO2. For female children, they were for 1.03 (95% CI, 0.90-1.18) for PM2.5; 0.98 (95% CI, 0.83-1.13) for NO; and 1.00 (95% CI, 0.86-1.16) for NO2.Conclusions and relevanceIn a population-based birth cohort, we detected an association between exposure to NO and ASD but no significant association with PM2.5 and NO2.

Project description:BackgroundStudies have shown that air pollution exposures during pregnancy are associated with an increased risk of autism spectrum disorder (ASD) in children, and the risk appears to be greater for boys. However, studies assessing gestational windows of susceptibility have been mostly limited by trimesters.ObjectiveWe identified sensitive windows of exposure to regional air pollution and risk of ASD and examined sex differences in a large birth cohort.MethodsThis population-based retrospective cohort study included 294,937 mother-child pairs with singleton deliveries in Kaiser Permanente Southern California (KPSC) hospitals from 2001 to 2014. Children were followed using electronic medical records until clinical ASD diagnosis, non-KPSC membership, death, or 31 December 2019, whichever came first. Weekly mean fine particulate matter [PM with an aerodynamic diameter of ≤2.5μm (PM2.5)], nitrogen dioxide (NO2), and ozone (O3) pregnancy exposures were estimated using spatiotemporal prediction models. Cox proportional hazard models with distributed lags were used to estimate weekly pollutant exposure associations with ASD risk for the entire cohort, and separately for boys and for girls. Models were adjusted for child sex (for full cohort), maternal race/ethnicity, maternal age at delivery, parity, maternal education, maternal comorbidities, medical center, census tract median household income, birth year, and season.ResultsThere were 5,694 ASD diagnoses (4,636 boys, 1,058 girls). Sensitive PM2.5 exposure windows associated with ASD were found early in pregnancy, statistically significant throughout the first two trimesters [1-27 wk of gestation, cumulative hazard ratio (HR)=1.14 [95% confidence interval (CI): 1.06, 1.23] per interquartile range (IQR) (7.4-μg/m3) increase]. O3 exposure during 34-37 wk of gestation was associated with increased risk [HR=1.06 (95% CI: 1.01, 1.11) per IQR (17.4 ppb) increase] but with reduced risk during 20-28 wk of gestation [HR=0.93 (95% CI: 0.89, 0.98)]. No associations were observed with NO2. Sex-stratified early gestational PM2.5 associations were stronger among boys [boys HR=1.16 (95% CI: 1.08, 1.26); girls HR=1.06 (95% CI: 0.89, 1.26)]. O3 associations in later gestation were observed only in boys [boys HR=1.10 (95% CI: 1.04, 1.16); girls HR=0.94 (95% CI: 0.84, 1.05)].ConclusionsExposures to PM2.5 in the first two gestational trimesters were associated with increased ASD risk in children, with stronger associations observed for boys. The role of O3 exposure on ASD risk merits further investigation. https://doi.org/10.1289/EHP9509.

Project description:BackgroundPreviously, numerous epidemiologic studies reported an association between autism spectrum disorder (ASD) and exposure to air pollution during pregnancy. However, there have been no metabolomics studies investigating the impact of pregnancy pollution exposure to ASD risk in offspring.ObjectivesTo identify differences in maternal metabolism that may reflect a biological response to exposure to high air pollution in pregnancies of offspring who later did or did not develop ASD.MethodsWe obtained stored mid-pregnancy serum from 214 mothers who lived in California's Central Valley and experienced the highest levels of air pollution during early pregnancy. We estimated each woman's average traffic-related air pollution exposure (carbon monoxide, nitric oxides, and particulate matter <2.5 μm) during the first trimester using the California Line Source Dispersion Model, version 4 (CALINE4). By utilizing liquid chromatography-high resolution mass spectrometry, we identified the metabolic profiles of maternal serum for 116 mothers with offspring who later developed ASD and 98 control mothers. Partial least squares discriminant analysis (PLS-DA) was employed to select metabolic features associated with air pollution exposure or autism risk in offspring. We also conducted extensive pathway enrichment analysis to elucidate potential ASD-related changes in the metabolome of pregnant women.ResultsWe extracted 4022 and 4945 metabolic features from maternal serum samples in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 (negative ion mode) columns, respectively. After controlling for potential confounders, we identified 167 and 222 discriminative features (HILIC and C18, respectively). Pathway enrichment analysis to discriminate metabolic features associated with ASD risk indicated various metabolic pathway perturbations linked to the tricarboxylic acid (TCA) cycle and mitochondrial function, including carnitine shuttle, amino acid metabolism, bile acid metabolism, and vitamin A metabolism.ConclusionUsing high resolution metabolomics, we identified several metabolic pathways disturbed in mothers with ASD offspring among women experiencing high exposure to traffic-related air pollution during pregnancy that were associated with mitochondrial dysfunction. These findings provide us with a better understanding of metabolic disturbances involved in the development of ASD under adverse environmental conditions.

Dataset Information

Air Pollution and Autism Spectrum Disorder in Israel: A Negative Control Analysis.

Background

Methods

Results

Conclusions

Publications

Air Pollution and Autism Spectrum Disorder in Israel: A Negative Control Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets