Measurement error in mobile source air pollution exposure estimates due to residential mobility during pregnancy.
ABSTRACT: Prenatal air pollution exposure is frequently estimated using maternal residential location at the time of delivery as a proxy for residence during pregnancy. We describe residential mobility during pregnancy among 19,951 children from the Kaiser Air Pollution and Pediatric Asthma Study, quantify measurement error in spatially resolved estimates of prenatal exposure to mobile source fine particulate matter (PM2.5) due to ignoring this mobility, and simulate the impact of this error on estimates of epidemiologic associations. Two exposure estimates were compared, one calculated using complete residential histories during pregnancy (weighted average based on time spent at each address) and the second calculated using only residence at birth. Estimates were computed using annual averages of primary PM2.5 from traffic emissions modeled using a Research LINE-source dispersion model for near-surface releases (RLINE) at 250?m resolution. In this cohort, 18.6% of children were born to mothers who moved at least once during pregnancy. Mobile source PM2.5 exposure estimates calculated using complete residential histories during pregnancy and only residence at birth were highly correlated (rS>0.9). Simulations indicated that ignoring residential mobility resulted in modest bias of epidemiologic associations toward the null, but varied by maternal characteristics and prenatal exposure windows of interest (ranging from -2% to -10% bias).
Project description:Identifying periods of increased vulnerability to air pollution during pregnancy with respect to the development of adverse birth outcomes can improve understanding of possible mechanisms of disease development and provide guidelines for protection of the child. Exposure to air pollution during pregnancy is typically based on the mother's residence at delivery, potentially resulting in exposure misclassification and biasing the estimation of critical windows of pregnancy. In this study, we determined the impact of maternal residential mobility during pregnancy on defining weekly exposure to particulate matter less than or equal to 10 μm in aerodynamic diameter (PM10) and estimating windows of susceptibility to term low birth weight. We utilized data sets from 4 Connecticut birth cohorts (1988-2008) that included information on all residential addresses between conception and delivery for each woman. We designed a simulation study to investigate the impact of increasing levels of mobility on identification of critical windows. Increased PM10 exposure during pregnancy weeks 16-18 was associated with an increased probability of term low birth weight. Ignoring residential mobility when defining weekly exposure had only a minor impact on the identification of critical windows for PM10 and term low birth weight in the data application and simulation study. Identification of critical pregnancy windows was robust to exposure misclassification caused by ignoring residential mobility in these Connecticut birth cohorts.
Project description:<h4>Background</h4>Few epidemiological studies of air pollution have used residential histories to develop long-term retrospective exposure estimates for multiple ambient air pollutants and vehicle and industrial emissions. We present such an exposure assessment for a Canadian population-based lung cancer case-control study of 8353 individuals using self-reported residential histories from 1975 to 1994. We also examine the implications of disregarding and/or improperly accounting for residential mobility in long-term exposure assessments.<h4>Methods</h4>National spatial surfaces of ambient air pollution were compiled from recent satellite-based estimates (for PM2.5 and NO2) and a chemical transport model (for O3). The surfaces were adjusted with historical annual air pollution monitoring data, using either spatiotemporal interpolation or linear regression. Model evaluation was conducted using an independent ten percent subset of monitoring data per year. Proximity to major roads, incorporating a temporal weighting factor based on Canadian mobile-source emission estimates, was used to estimate exposure to vehicle emissions. A comprehensive inventory of geocoded industries was used to estimate proximity to major and minor industrial emissions.<h4>Results</h4>Calibration of the national PM2.5 surface using annual spatiotemporal interpolation predicted historical PM2.5 measurement data best (R2 = 0.51), while linear regression incorporating the national surfaces, a time-trend and population density best predicted historical concentrations of NO2 (R2 = 0.38) and O3 (R2 = 0.56). Applying the models to study participants residential histories between 1975 and 1994 resulted in mean PM2.5, NO2 and O3 exposures of 11.3 ?g/m3 (SD = 2.6), 17.7 ppb (4.1), and 26.4 ppb (3.4) respectively. On average, individuals lived within 300 m of a highway for 2.9 years (15% of exposure-years) and within 3 km of a major industrial emitter for 6.4 years (32% of exposure-years). Approximately 50% of individuals were classified into a different PM2.5, NO2 and O3 exposure quintile when using study entry postal codes and spatial pollution surfaces, in comparison to exposures derived from residential histories and spatiotemporal air pollution models. Recall bias was also present for self-reported residential histories prior to 1975, with cases recalling older residences more often than controls.<h4>Conclusions</h4>We demonstrate a flexible exposure assessment approach for estimating historical air pollution concentrations over large geographical areas and time-periods. In addition, we highlight the importance of including residential histories in long-term exposure assessments. For submission to: Environmental Health.
Project description:BACKGROUND:We have developed an open-source ALgorithm for Generating Address Exposures (ALGAE) that cleans residential address records to construct address histories and assign spatially-determined exposures to cohort participants. The first application of this algorithm was to construct prenatal and early life air pollution exposure for individuals of the Avon Longitudinal Study of Parents and Children (ALSPAC) in the South West of England, using previously estimated particulate matter ?10? µm (PM10) concentrations. METHODS:ALSPAC recruited 14 541 pregnant women between 1991 and 1992. We assigned trimester-specific estimated PM10 exposures for 12 752 pregnancies, and first year of life exposures for 12 525 births, based on maternal residence and residential mobility. RESULTS:Average PM10 exposure was 32.6 ?µg/m3 [standard deviation (S.D.) 3.0 ?µg/m3] during pregnancy and 31.4 µg/m3 (S.D. 2.6 ?µg/m3) during the first year of life; 6.7% of women changed address during pregnancy, and 18.0% moved during first year of life of their infant. Exposure differences ranged from -5.3 ?µg/m3 to 12.4 ?µg/m3 (up to 26% difference) during pregnancy and -7.22 ?µg/m3 to 7.64 ?µg/m3 (up to 27% difference) in the first year of life, when comparing estimated exposure using the address at birth and that assessed using the complete cleaned address history. For the majority of individuals exposure changed by <5%, but some relatively large changes were seen both in pregnancy and in infancy. CONCLUSIONS:ALGAE provides a generic and adaptable, open-source solution to clean addresses stored in a cohort contact database and assign life stage-specific exposure estimates with the potential to reduce exposure misclassification.
Project description:<b>Methods: </b>We studied associations between prenatal exposure to particulate matter with diameter ? 2.5 ?m (PM2.5) and postpartum psychological functioning in a lower income, ethnically mixed sample of urban US women enrolled in a pregnancy cohort study. Analyses included 557 mothers who delivered at ?37 weeks gestation. Daily estimates of residential PM2.5 over gestation were derived using a satellite-based spatio-temporally resolved model. Outcomes included the Edinburgh Postnatal Depression Scale (EPDS) score from 6 or 12 months postpartum and subscale scores for anhedonia, depressive and anxiety symptoms. Associations were also examined within racial/ethnic groups. Distributed lag models (DLMs) were implemented to identify windows of vulnerability during pregnancy.<br><br><b>Results: </b>Most mothers had less than a high school education (64%) and were primarily Hispanic (55%) and Black (29%). In the overall sample, a DLM adjusted for age, race, education, prenatal smoking, and season of delivery, we found significant associations between higher PM2.5 exposure in the second trimester and increased anhedonia subscale scores postpartum. In race stratified analyses, mid-pregnancy PM2.5 exposure was significantly associated with increased total EPDS scores as well as higher anhedonia and depressive symptom subscale scores among Black women.<br><br><b>Conclusions: </b>Increased PM2.5 exposure in mid-pregnancy was associated with increased depressive and anhedonia symptoms, particularly in Black women.
Project description:BACKGROUND:Environmental factors may contribute to the development of Kawasaki disease in children, but prenatal environmental exposures are understudied. OBJECTIVE:We used a population-based cohort to investigate whether prenatal exposure to outdoor air pollution is associated with the incidence of Kawasaki disease in childhood. METHODS:We performed a longitudinal cohort study of all children born in Quebec, Canada, between 2006 and 2012. Children were followed for Kawasaki disease from birth until 31 March 2018. We assigned prenatal air pollutant exposure according to the residential postal code at birth. The main exposure was annual average concentration of ambient fine particulate matter [PM ?2.5?m in aerodynamic diameter (PM2.5) and nitrogen dioxide (NO2) from satellite-based estimates and land-use regression models. As secondary exposures, we considered industrial PM2.5, NO2, and sulfur dioxide (SO2) emissions estimated from dispersion models. We estimated hazard ratios (HRs) using Cox proportional hazards models, adjusted for maternal age, parity, sex, multiple birth, maternal smoking during pregnancy, socioeconomic status, birth year, and rural residence. We considered single and multipollutant models. We performed several sensitivity analyses, including assessing modifying effects of maternal comorbidities (e.g., diabetes, preeclampsia). RESULTS:The cohort comprised 505,336 children, including 539 with Kawasaki disease. HRs for each interquartile range increase in ambient air pollution were 1.16 (95% CI: 0.96, 1.39) for PM2.5 and 1.12 (95% CI: 0.96, 1.31) for NO2. For industrial air pollution, HRs were 1.07 (95% CI: 1.01, 1.13) for SO2, 1.09 (95% CI: 0.99, 1.20) for NO2, and 1.01 (95% CI: 0.97, 1.05) for PM2.5. In multipollutant models, associations for ambient PM2.5 and NO2 (i.e., from all sources) were robust to adjustment for industrial pollution, and vice versa. DISCUSSION:In this population-based cohort study, both prenatal exposure to ambient and industrial air pollution were associated with the incidence of Kawasaki disease in childhood. Further studies are needed to consolidate the observed associations. https://doi.org/10.1289/EHP6920.
Project description:BACKGROUND:Prenatal 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). METHODS:A 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. RESULTS:During 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 ?g/m3) which was not related to the socioeconomic profile of the women. The commuting mode made a greater difference (+?1.46 ?g/m3 on average), in particular among women living in the most deprived census blocks. CONCLUSIONS:Our 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:It remains unclear as to whether neglecting residential mobility during pregnancy introduces bias in studies investigating air pollution and adverse perinatal outcomes, as most studies assess exposure based on residence at birth. The aim of this study was to ascertain whether such bias can be observed in a study on the effects of PM10 on risk of preterm birth and fetal growth restriction. METHODS:This was a retrospective study using four pregnancy cohorts of women recruited in Connecticut, USA (N=10,025). We ascertained associations with PM10 exposure calculated using first recorded maternal address, last recorded address, and full address histories. We used a discrete time-to-event model for preterm birth, and logistic regression to investigate associations with small for gestational age (SGA) and term low birth weight (LBW). RESULTS:Pregnant women tended to move to areas with lower levels of PM10. For all outcomes, there was negligible difference between effect sizes corresponding to exposures calculated with first, last and full address histories. For LBW, associations were observed for exposure in second trimester (OR 1.09; 95% CI: 1.04-1.14 per 1?g/m(3) PM10) and whole pregnancy (OR 1.08; 95% CI: 1.02-1.14). For SGA, associations were observed for elevated exposure in second trimester (OR 1.02; 95% CI: 1.00-1.04) and whole pregnancy (OR 1.03; 95% CI: 1.01-1.05). There was insufficient evidence for association with preterm birth. CONCLUSION:PM10 was associated with both SGA and term LBW. However, there was negligible benefit in accounting for residential mobility in pregnancy in this study.
Project description:INTRODUCTION:Changes in mitochondrial DNA (mtDNA) can serve as a marker of cumulative oxidative stress (OS) due to the mitochondria's unique genome and relative lack of repair systems. In utero particulate matter ?2.5?m (PM2.5) exposure can enhance oxidative stress. Our objective was to identify sensitive windows to predict mtDNA damage experienced in the prenatal period due to PM2.5 exposure using mtDNA content measured in cord blood. MATERIAL AND METHODS:Women affiliated with the Mexican social security system were recruited during pregnancy in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) study. Mothers with cord blood collected at delivery and complete covariate data were included (n=456). Mothers' prenatal daily exposure to PM2.5 was estimated using a satellite-based spatio-temporally resolved prediction model and place of residence during pregnancy. DNA was extracted from umbilical cord leukocytes. Quantitative real-time polymerase chain reaction (qPCR) was used to determine mtDNA content. A distributive lag regression model (DLM) incorporating weekly averages of daily PM2.5 predictions was constructed to plot the association between exposure and OS over the length of pregnancy. RESULTS:In models that included child's sex, mother's age at delivery, prenatal environmental tobacco smoke exposure, birth year, maternal education, and assay batch, we found significant associations between higher PM2.5 exposure during late pregnancy (35-40weeks) and lower mtDNA content in cord blood. CONCLUSIONS:Increased PM2.5 during a specific prenatal window in the third trimester was associated with decreased mtDNA content suggesting heightened sensitivity to PM-induced OS during this life stage.
Project description:INTRODUCTION:In utero particulate matter exposure produces oxidative stress that impacts cellular processes that include telomere biology. Newborn telomere length is likely critical to an individual's telomere biology; reduction in this initial telomere setting may signal increased susceptibility to adverse outcomes later in life. We examined associations between prenatal particulate matter with diameter ?2.5?µm (PM2.5) and relative leukocyte telomere length (LTL) measured in cord blood using a data-driven approach to characterize sensitive windows of prenatal PM2.5 effects and explore sex differences. METHODS:Women who were residents of Mexico City and affiliated with the Mexican Social Security System were recruited during pregnancy (n?=?423 for analyses). Mothers' prenatal exposure to PM2.5 was estimated based on residence during pregnancy using a validated satellite-based spatio-temporally resolved prediction model. Leukocyte DNA was extracted from cord blood obtained at delivery. Duplex quantitative polymerase chain reaction was used to compare the relative amplification of the telomere repeat copy number to single gene (albumin) copy number. A distributed lag model incorporating weekly averages for PM2.5 over gestation was used in order to explore sensitive windows. Sex-specific associations were examined using Bayesian distributed lag interaction models. RESULTS:In models that included child's sex, mother's age at delivery, prenatal environmental tobacco smoke exposure, pre-pregnancy BMI, gestational age, birth season and assay batch, we found significant associations between higher PM2.5 exposure during early pregnancy (4-9 weeks) and shorter LTL in cord blood. We also identified two more windows at 14-19 and 34-36 weeks in which increased PM2.5 exposure was associated with longer LTL. In stratified analyses, the mean and cumulative associations between PM2.5 and shortened LTL were stronger in girls when compared to boys. CONCLUSIONS:Increased PM2.5 during specific prenatal windows was associated with shorter LTL and longer LTL. PM2.5 was more strongly associated with shortened LTL in girls when compared to boys. Understanding sex and temporal differences in response to air pollution may provide unique insight into mechanisms.
Project description:Importance:Telomere length is a marker of biological aging that may provide a cellular memory of exposures to oxidative stress and inflammation. Telomere length at birth has been related to life expectancy. An association between prenatal air pollution exposure and telomere length at birth could provide new insights in the environmental influence on molecular longevity. Objective:To assess the association of prenatal exposure to particulate matter (PM) with newborn telomere length as reflected by cord blood and placental telomere length. Design, Setting, and Participants:In a prospective birth cohort (ENVIRONAGE [Environmental Influence on Ageing in Early Life]), a total of 730 mother-newborn pairs were recruited in Flanders, Belgium between February 2010 and December 2014, all with a singleton full-term birth (?37 weeks of gestation). For statistical analysis, participants with full data on both cord blood and placental telomere lengths were included, resulting in a final study sample size of 641. Exposures:Maternal residential PM2.5 (particles with an aerodynamic diameter ?2.5 ?m) exposure during pregnancy. Main Outcomes and Measures:In the newborns, cord blood and placental tissue relative telomere length were measured. Maternal residential PM2.5 exposure during pregnancy was estimated using a high-resolution spatial-temporal interpolation method. In distributed lag models, both cord blood and placental telomere length were associated with average weekly exposures to PM2.5 during pregnancy, allowing the identification of critical sensitive exposure windows. Results:In 641 newborns, cord blood and placental telomere length were significantly and inversely associated with PM2.5 exposure during midgestation (weeks 12-25 for cord blood and weeks 15-27 for placenta). A 5-µg/m3 increment in PM2.5 exposure during the entire pregnancy was associated with 8.8% (95% CI, -14.1% to -3.1%) shorter cord blood leukocyte telomeres and 13.2% (95% CI, -19.3% to -6.7%) shorter placental telomere length. These associations were controlled for date of delivery, gestational age, maternal body mass index, maternal age, paternal age, newborn sex, newborn ethnicity, season of delivery, parity, maternal smoking status, maternal educational level, pregnancy complications, and ambient temperature. Conclusions and Relevance:Mothers who were exposed to higher levels of PM2.5 gave birth to newborns with shorter telomere length. The observed telomere loss in newborns by prenatal air pollution exposure indicates less buffer for postnatal influences of factors decreasing telomere length during life. Therefore, improvements in air quality may promote molecular longevity from birth onward.