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Associations of gestational diabetes mellitus with residential air pollution exposure in a large Southern California pregnancy cohort.

ABSTRACT: BACKGROUND:Studies 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. METHODS:Data 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??m in aerodynamic diameter (PM2.5) and ?10??m (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. RESULTS:In 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??g/m3, 95% CI: 1.01, 1.06; OR?=?1.03 per 16.1??g/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. CONCLUSIONS:Maternal exposure to NO2 during the preconception trimester may increase risk of GDM.

SUBMITTER: Jo H

PROVIDER: S-EPMC6684238 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Associations of gestational diabetes mellitus with residential air pollution exposure in a large Southern California pregnancy cohort.

Jo Heejoo H Eckel Sandrah P SP Chen Jiu-Chiuan JC Cockburn Myles M Martinez Mayra P MP Chow Ting T Lurmann Fred F Funk William E WE McConnell Rob R Xiang Anny H AH

Environment international 20190621

<h4>Background</h4>Studies 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.<h4>Methods</h4>Data were obtained for 239,574 pregnancies between 1999 and 2009 in a population-based health care system with comprehensive electronic medical records. Concentrations of ...[more]

PMID: 31234004

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Project description:BackgroundEpidemiological findings are inconsistent regarding the associations between air pollution exposure during pregnancy and gestational diabetes mellitus (GDM). Several limitations exist in previous studies, including potential outcome and exposure misclassification, unassessed confounding, and lack of simultaneous consideration of air pollution mixtures and particulate matter (PM) constituents.ObjectivesTo assess the association between GDM and maternal residential exposure to air pollution, and the joint effect of the mixture of air pollutants and PM constituents.MethodsDetailed clinical data were obtained for 395,927 pregnancies in southern California (2008-2018) from Kaiser Permanente Southern California (KPSC) electronic health records. GDM diagnosis was based on KPSC laboratory tests. Monthly average concentrations of fine particulate matter < 2.5 μm (PM2.5), <10 μm (PM10), nitrogen dioxide (NO2), and ozone (O3) were estimated using kriging interpolation of Environmental Protection Agency's routine monitoring station data, while PM2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon) were estimated using a fine-resolution geoscience-derived model. A multilevel logistic regression was used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of air pollution and PM component mixtures. Main analyses adjusted for maternal age, race/ethnicity, education, median family household income, pre-pregnancy BMI, smoking during pregnancy, insurance type, season of conception and year of delivery.ResultsThe incidence of GDM was 10.9% in the study population. In single-pollutant models, we observed an increased odds for GDM associated with exposures to PM2.5, PM10, NO2 and PM2.5 constituents. The association was strongest for NO2 [adjusted odds ratio (OR) per interquartile range: 1.176, 95% confidence interval (CI): 1.147-1.205)]. In multi-pollutant models, increased ORs for GDM in association with one quartile increase in air pollution mixtures were found for both kriging-based regional air pollutants (NO2, PM2.5, and PM10, OR = 1.095, 95% CI: 1.082-1.108) and PM2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon, OR = 1.258, 95% CI: 1.206-1.314); NO2 (78%) and black carbon (48%) contributed the most to the overall mixture effects among all krigged air pollutants and all PM2.5 constituents, respectively. The risk of GDM associated with air pollution exposure were significantly higher among Hispanic mothers, and overweight/obese mothers.ConclusionThis study found that exposure to a mixture of ambient PM2.5, PM10, NO2, and PM2.5 chemical constituents was associated with an increased risk of GDM. NO2 and black carbon PM2.5 contributed most to GDM risk.

Project description:BackgroundPrenatal exposure to outdoor air pollution has been shown to have health effects in many studies; low birth weight, preterm delivery, small for gestational age, and stillbirth are the most often cited. However, exposure of pregnant women is difficult to quantify, especially with regard to their mobility, which is rarely taken into account in epidemiological studies. This study aimed to assess the impact of mobility of pregnant women living in Paris, France, on their exposure estimates to nitrogen dioxide (NO2).MethodsA total of 486 pregnant women were recruited in 5 maternity hospitals in Paris between January and April 2016. A questionnaire was used to collect mothers' characteristics (demography, education, etc.) and to assess their daily mobility during pregnancy (time spent at work, commuting time and mode used to move from residential to occupational places). Daily NO2 concentrations were estimated based on the combination of annual average concentrations modeled at the census block scale and daily concentrations measured from fixed monitoring stations. Different models were used to compare the exposure of pregnant women in residential and occupational places, also taking into account travel time and travel mode. The socioeconomic profile of the census blocks was characterized using a multi-component index.ResultsDuring the first trimester of pregnancy, women living in the least deprived census blocks were exposed to higher concentrations of NO2 than those living in the most deprived ones. Occupational mobility had a small impact on exposure levels (average increase after taking account of mobility: + 0.52 μg/m3) which was not related to the socioeconomic profile of the women. The commuting mode made a greater difference (+ 1.46 μg/m3 on average), in particular among women living in the most deprived census blocks.ConclusionsOur study illustrates that air pollution exposure can be underestimated when ignoring occupational mobility and commuting mode of pregnant women. This effect might be differential according to the neighborhood deprivation profile.

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:An Environmental Justice (EJ) analysis was carried out using full Chemical Transport Models (CTMs) over Los Angeles, California, to determine how the combination of domain size and spatial resolution affects predicted air pollution disparities in present day and future simulations when data support from measurements is not available. One set of simulations used the Weather Research and Forecasting (WRF) model coupled with Chemistry (WRF/Chem) with spatial resolution ranging from 250 m to 36 km, comparable to census tract sizes, over domains ranging in size from 320 km2 to 10,000 km2. A second set of simulations used the UCD/CIT CTM with spatial resolution ranging from 4 km to 24 km over domains ranging in size from 98,000 km2 to 1,000,000 km2. Overall WRF/Chem model accuracy improved approximately 9% as spatial resolution increased from 4 km to 250 m in present-day simulations, with similar results expected for future simulations. Exposure disparity results are consistent with previous findings: the average Non-Hispanic White person in the study domain experiences PM2.5 mass concentrations 6–14% lower than the average resident, while the average Black and African American person experiences PM2.5 mass concentrations that are 3–22% higher than the average resident. Predicted exposure disparities were a function of the model configuration. Increasing the spatial resolution finer than approximately 1 km produced diminishing returns because the increased spatial resolution came at the expense of reduced domain size in order to maintain reasonable computational burden. Increasing domain size to capture regional trends, such as wealthier populations living in coastal areas, identified larger exposure disparities but the benefits were limited. CTM configurations that use spatial resolution/domain size of 1 km/103 km2 and 4 km/104 km2 over Los Angeles can detect a 0.5 μg m−3 exposure difference with statistical power greater than 90%. These configurations represent a balanced approach between statistical power, sensitivity across socio-economic groups, and computational burden when predicting current and future air pollution exposure disparities in Los Angeles. Air quality; Environmental disparity; PM2.5; Chemical transport model.

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Associations of gestational diabetes mellitus with residential air pollution exposure in a large Southern California pregnancy cohort.

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Associations of gestational diabetes mellitus with residential air pollution exposure in a large Southern California pregnancy cohort.

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