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Preconception and early pregnancy air pollution exposures and risk of gestational diabetes mellitus.

ABSTRACT: BACKGROUND:Air pollution has been linked to gestational diabetes mellitus (GDM) but no studies have evaluated impact of preconception and early pregnancy air pollution exposures on GDM risk. METHODS:Electronic medical records provided data on 219,952 singleton deliveries to mothers with (n=11,334) and without GDM (n=208,618). Average maternal exposures to particulate matter (PM) ? 2.5?m (PM2.5) and PM2.5 constituents, PM ? 10?m (PM10), nitrogen oxides (NOx), carbon monoxide, sulfur dioxide (SO2) and ozone (O3) were estimated for the 3-month preconception window, first trimester, and gestational weeks 1-24 based on modified Community Multiscale Air Quality models for delivery hospital referral regions. Binary regression models with robust standard errors estimated relative risks (RR) for GDM per interquartile range (IQR) increase in pollutant concentrations adjusted for study site, maternal age and race/ethnicity. RESULTS:Preconception maternal exposure to NOX (RR=1.09, 95% CI: 1.04, 1.13) and SO2 (RR=1.05, 1.01, 1.09) were associated with increased risk of subsequent GDM and risk estimates remained elevated for first trimester exposure. Preconception O3 was associated with lower risk of subsequent GDM (RR=0.93, 0.90, 0.96) but risks increased later in pregnancy. CONCLUSION:Maternal exposures to NOx and SO2 preconception and during the first few weeks of pregnancy were associated with increased GDM risk. O3 appeared to increase GDM risk in association with mid-pregnancy exposure but not in earlier time windows. These common exposures merit further investigation.

SUBMITTER: Robledo CA

PROVIDER: S-EPMC6204222 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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Preconception and early pregnancy air pollution exposures and risk of gestational diabetes mellitus.

Robledo Candace A CA Mendola Pauline P Yeung Edwina E Männistö Tuija T Sundaram Rajeshwari R Liu Danping D Ying Qi Q Sherman Seth S Grantz Katherine L KL

Environmental research 20150117

<h4>Background</h4>Air pollution has been linked to gestational diabetes mellitus (GDM) but no studies have evaluated impact of preconception and early pregnancy air pollution exposures on GDM risk.<h4>Methods</h4>Electronic medical records provided data on 219,952 singleton deliveries to mothers with (n=11,334) and without GDM (n=208,618). Average maternal exposures to particulate matter (PM) ≤ 2.5μm (PM2.5) and PM2.5 constituents, PM ≤ 10μm (PM10), nitrogen oxides (NOx), carbon monoxide, sulfu ...[more]

PMID: 25601734

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Project description:BackgroundEmerging evidence suggests a potential association between ambient air pollution and risk of gestational diabetes mellitus (GDM), but results have been inconsistent. Accordingly, we assessed the associations between ambient fine particulate matter (PM2.5) and nitrogen dioxide (NO2) levels with risk of GDM.MethodsUsing linked data from birth certificates, hospital discharge diagnoses, and air pollution estimates informed by the New York City Community Air Survey, we fit conditional logistic regression models to evaluate the association between residential levels of PM2.5 and NO2 with risk of GDM among 256,372 singleton live births of non-smoking mothers in New York City born 2008-2010, adjusting for sociodemographic factors and stratified on zip code of maternal address.ResultsGDM was identified in 17,065 women, yielding a risk of GDM in the study sample of 67 per 1000 deliveries. In single pollutant models, 1st and 2nd trimester PM2.5 was associated with a lower and higher risk of GDM, respectively. In models mutually adjusting for PM2.5 levels in both trimesters, GDM was associated with PM2.5 levels in the 2nd trimester (OR: 1.06, 95% CI: 1.02, 1.10 per interquartile range increase in PM2.5), but not the 1st trimester (OR: 0.99, 95% CI: 0.96, 1.02). Conversely, GDM was associated with NO2 during the 1st trimester (OR: 1.05, 95% CI: 1.01, 1.09), but not the 2nd trimester (OR: 1.02, 95% CI: 0.98, 1.06). The positive associations between pollutants and GDM were robust to different model specifications. PM2.5 in the 2nd trimester was more strongly associated with GDM among mothers who were aged <35 years and not Medicaid recipients. NO2 in the 1st trimester was more strongly associated with GDM among overweight and parous women.ConclusionsIn this large cohort of singleton births in New York City, NO2 in the 1st trimester and PM2.5 in the 2nd trimester were associated with higher odds of GDM, while 1st trimester PM2.5 was weakly and inconsistently associated with lower odds of GDM.

Project description:Implementation of dietary and lifestyle interventions prior to and early in pregnancy in high risk women has been shown to reduce the risk of gestational diabetes mellitus (GDM) development later in pregnancy. Although numerous risk factors for GDM have been identified, the ability to accurately identify women before or early in pregnancy who could benefit most from these interventions remains limited. As nulliparous women are an under-screened population with risk profiles that differ from their multiparous counterparts, development of a prediction model tailored to nulliparous women may facilitate timely preventive intervention and improve maternal and infant outcomes. We aimed to develop and validate a model for preconception and early pregnancy prediction of gestational diabetes mellitus based on clinical risk factors for nulliparous women. A risk prediction model was built within a large California birth cohort including singleton live birth records from 2007-2012. Model accuracy was assessed both internally and externally, within a cohort of women who delivered at University of Iowa Hospitals and Clinics between 2009-2017, using discrimination and calibration. Differences in predictive accuracy of the model were assessed within specific racial/ethnic groups. The prediction model included five risk factors: race/ethnicity, age at delivery, pre-pregnancy body mass index, family history of diabetes, and pre-existing hypertension. The area under the curve (AUC) for the California internal validation cohort was 0.732 (95% confidence interval (CI) 0.728, 0.735), and 0.710 (95% CI 0.672, 0.749) for the Iowa external validation cohort. The model performed particularly well in Hispanic (AUC 0.739) and Black women (AUC 0.719). Our findings suggest that estimation of a woman's risk for GDM through model-based incorporation of risk factors accurately identifies those at high risk (i.e., predicted risk >6%) who could benefit from preventive intervention encouraging prompt incorporation of this tool into preconception and prenatal care.

Project description:BackgroundStudies of effects of air pollution on gestational diabetes mellitus (GDM) have not been consistent, and there has been little investigation of effects of exposure preceding pregnancy. In previous studies, the temporal relationship between exposure and GDM onset has been difficult to establish.MethodsData were obtained for 239,574 pregnancies between 1999 and 2009 in a population-based health care system with comprehensive electronic medical records. Concentrations of ambient nitrogen dioxide (NO2), particulate matter (PM) ≤2.5 μm in aerodynamic diameter (PM2.5) and ≤10 μm (PM10), and ozone (O3) during preconception and the first trimester of pregnancy at the residential birth address were estimated from regulatory air monitoring stations. Odds ratios (ORs) of GDM diagnosed in the second and third trimesters in association with pollutant exposure were estimated using generalized estimating equation models adjusted for birth year, medical center service areas, maternal age, race/ethnicity, education, census-tract household income, and parity.ResultsIn single-pollutant models, preconception NO2 was associated with increased risk of GDM (OR = 1.10 per 10.4 ppb, 95% confidence interval [CI]: 1.07, 1.13). First trimester NO2 was weakly associated with GDM, and this was not statistically significant (OR = 1.02 per 10.4 ppb, 95% CI: 0.99, 1.05). Preconception NO2 associations were robust in multi-pollutant models adjusted for first trimester NO2 with another co-pollutant from both exposure windows. In single-pollutant models, preconception PM2.5 and PM10 associations were associated with increased risk of GDM (OR = 1.04 per 6.5 μg/m3, 95% CI: 1.01, 1.06; OR = 1.03 per 16.1 μg/m3, 95% CI: 1.00, 1.06, respectively), but these effect estimates were not robust to adjustment for other pollutants. In single-pollutant models, preconception and first trimester O3 were associated with reduced risk of GDM (OR = 0.94 per 15.7 ppb, 95% CI: 0.92, 0.95; OR = 0.95 per 15.7 ppb, 95% CI: 0.94, 0.97), associations that were robust to adjustment for co-pollutants.ConclusionsMaternal exposure to NO2 during the preconception trimester may increase risk of GDM.

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:Few epidemiologic studies have evaluated the effects of air pollution on the risk of Parkinson disease (PD).We investigated the associations of long-term residential concentrations of ambient particulate matter (PM) < 10 ?m in diameter (PM10) and < 2.5 ?m in diameter (PM2.5) and nitrogen dioxide (NO2) in relation to PD risk.Our nested case-control analysis included 1,556 self-reported physician-diagnosed PD cases identified between 1995 and 2006 and 3,313 controls frequency-matched on age, sex, and race. We geocoded home addresses reported in 1995-1996 and estimated the average ambient concentrations of PM10, PM2.5, and NO2 using a national fine-scale geostatistical model incorporating roadway information and other geographic covariates. Air pollutant exposures were analyzed as both quintiles and continuous variables, adjusting for matching variables and potential confounders.We observed no statistically significant overall association between PM or NO2 exposures and PD risk. However, in preplanned subgroup analyses, a higher risk of PD was associated with higher exposure to PM10 (ORQ5 vs. Q1 = 1.65; 95% CI: 1.11, 2.45; p-trend = 0.02) among women, and with higher exposure to PM2.5 (ORQ5 vs. Q1 = 1.29; 95% CI: 0.94, 1.76; p-trend = 0.04) among never smokers. In post hoc analyses among female never smokers, both PM2.5 (ORQ5 vs. Q1 = 1.79; 95% CI: 1.01, 3.17; p-trend = 0.05) and PM10 (ORQ5 vs. Q1 = 2.34; 95% CI: 1.29, 4.26; p-trend = 0.01) showed positive associations with PD risk. Analyses based on continuous exposure variables generally showed similar but nonsignificant associations.Overall, we found limited evidence for an association between exposures to ambient PM10, PM2.5, or NO2 and PD risk. The suggestive evidence that exposures to PM2.5 and PM10 may increase PD risk among female never smokers warrants further investigation. Citation: Liu R, Young MT, Chen JC, Kaufman JD, Chen H. 2016. Ambient air pollution exposures and risk of Parkinson disease. Environ Health Perspect 124:1759-1765;?http://dx.doi.org/10.1289/EHP135.

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Preconception and early pregnancy air pollution exposures and risk of gestational diabetes mellitus.

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Preconception and early pregnancy air pollution exposures and risk of gestational diabetes mellitus.

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