Itai Kloog

Using new satellite based exposure methods to study the association between pregnancy pm2.5 exposure, premature birth and birth weight in Massachusetts

BackgroundAdverse birth outcomes such as low birth weight and premature birth have been previously linked with exposure to ambient air pollution. Most studies relied on a limited number of monitors in the region of interest, which can introduce exposure error or restrict the analysis to persons living near a monitor, which reduces sample size and generalizability and may create selection bias.MethodsWe evaluated the relationship between premature birth and birth weight with exposure to ambient particulate matter (PM2.5) levels during pregnancy in Massachusetts for a 9-year period (2000–2008). Building on a novel method we developed for predicting daily PM2.5 at the spatial resolution of a 10x10km grid across New-England, we estimated the average exposure during 30 and 90u2009days prior to birth as well as the full pregnancy period for each mother. We used linear and logistic mixed models to estimate the association between PM2.5 exposure and birth weight (among full term births) and PM2.5 exposure and preterm birth adjusting for infant sex, maternal age, maternal race, mean income, maternal education level, prenatal care, gestational age, maternal smoking, percent of open space near mothers residence, average traffic density and mothers health.ResultsBirth weight was negatively associated with PM2.5 across all tested periods. For example, a 10u2009μg/m3 increase of PM2.5 exposure during the entire pregnancy was significantly associated with a decrease of 13.80u2009g [95% confidence interval (CI)u2009=u2009−21.10, -6.05] in birth weight after controlling for other factors, including traffic exposure. The odds ratio for a premature birth was 1.06 (95% confidence interval (CI)u2009=u20091.01–1.13) for each 10u2009μg/m3 increase of PM2.5 exposure during the entire pregnancy period.ConclusionsThe presented study suggests that exposure to PM2.5 during the last month of pregnancy contributes to risks for lower birth weight and preterm birth in infants.

Acute and Chronic Effects of Particles on Hospital Admissions in New-England

Background Many studies have reported significant associations between exposure to PM2.5 and hospital admissions, but all have focused on the effects of short-term exposure. In addition all these studies have relied on a limited number of PM2.5 monitors in their study regions, which introduces exposure error, and excludes rural and suburban populations from locations in which monitors are not available, reducing generalizability and potentially creating selection bias. Methods Using our novel prediction models for exposure combining land use regression with physical measurements (satellite aerosol optical depth) we investigated both the long and short term effects of PM2.5 exposures on hospital admissions across New-England for all residents aged 65 and older. We performed separate Poisson regression analysis for each admission type: all respiratory, cardiovascular disease (CVD), stroke and diabetes. Daily admission counts in each zip code were regressed against long and short-term PM2.5 exposure, temperature, socio-economic data and a spline of time to control for seasonal trends in baseline risk. Results We observed associations between both short-term and long-term exposure to PM2.5 and hospitalization for all of the outcomes examined. In example, for respiratory diseases, for every10-µg/m3 increase in short-term PM2.5 exposure there is a 0.70 percent increase in admissions (CIu200a=u200a0.35 to 0.52) while concurrently for every10-µg/m3 increase in long-term PM2.5 exposure there is a 4.22 percent increase in admissions (CIu200a=u200a1.06 to 4.75). Conclusions As with mortality studies, chronic exposure to particles is associated with substantially larger increases in hospital admissions than acute exposure and both can be detected simultaneously using our exposure models.

Temporal and spatial assessments of minimum air temperature using satellite surface temperature measurements in Massachusetts, USA

Although meteorological stations provide accurate air temperature observations, their spatial coverage is limited and thus often insufficient for epidemiological studies. Satellite data expand spatial coverage, enhancing our ability to estimate near surface air temperature (Ta). However, the derivation of Ta from surface temperature (Ts) measured by satellites is far from being straightforward. In this study, we present a novel approach that incorporates land use regression, meteorological variables and spatial smoothing to first calibrate between Ts and Ta on a daily basis and then predict Ta for days when satellite Ts data were not available. We applied mixed regression models with daily random slopes to calibrate Moderate Resolution Imaging Spectroradiometer (MODIS) Ts data with monitored Ta measurements for 2003. Then, we used a generalized additive mixed model with spatial smoothing to estimate Ta in days with missing Ts. Out-of-sample tenfold cross-validation was used to quantify the accuracy of our predictions. Our model performance was excellent for both days with available Ts and days without Ts observations (mean out-of-sample R(2)=0.946 and R(2)=0.941 respectively). Furthermore, based on the high quality predictions we investigated the spatial patterns of Ta within the study domain as they relate to urban vs. non-urban land uses.

Effects of prenatal community violence and ambient air pollution on childhood wheeze in an urban population

BACKGROUNDnPrenatal exposures to stress and physical toxins influence childrens respiratory health, although few studies consider these factors together.nnnOBJECTIVESnWe sought to concurrently examine the effects of prenatal community-level psychosocial (exposure to community violence [ECV]) and physical (air pollution) stressors on repeated wheeze in 708 urban children followed to age 2 years.nnnMETHODSnMulti-item ECV reported by mothers in pregnancy was summarized into a continuous score by using Rasch modeling. Prenatal black carbon exposure was estimated by using land-use regression (LUR) modeling; particulate matter with a diameter of less than 2.5 μm (PM2.5) was estimated by using LUR modeling incorporating satellite data. Mothers reported childs wheeze every 3 months. The effects of ECV and air pollutants on repeated wheeze (≥ 2 episodes) were examined by using logistic regression. Interactions between ECV and pollutants were examined.nnnRESULTSnMothers were primarily black (29%) and Hispanic (55%), with lower education (62% with ≤ 12 years); 87 (12%) children wheezed repeatedly. In models examining concurrent exposures, ECV (odds ratio [OR], 1.95; 95% CI, 1.13-3.36; highest vs lowest tertile) and black carbon (OR, 1.84; 95% CI, 1.08-3.12; median or greater vs less than median) were independently associated with wheeze adjusting for sex, birth season, maternal atopy, education, race, and cockroach antigen. Associations were similar for PM2.5 (adjusted OR, 2.02; 95% CI, 1.20-3.40). An interaction between ECV with air pollution levels was suggested.nnnCONCLUSIONSnThese findings suggest that both prenatal community violence and air pollution can contribute to respiratory health in these urban children. Moreover, place-based psychosocial stressors might affect host resistance such that physical pollutants can have adverse effects, even at relatively lower levels.

Short Term Effects of Particle Exposure on Hospital Admissions in the Mid-Atlantic States: A Population Estimate

Background Many studies report significant associations between PM2.5 (particulate matter <2.5 micrometers) and hospital admissions. These studies mostly rely on a limited number of monitors which introduces exposure error, and excludes rural and suburban populations from locations where monitors are not available, reducing generalizability and potentially creating selection bias. Methods Using prediction models developed by our group, daily PM2.5 exposure was estimated across the Mid-Atlantic (Washington D.C., and the states of Delaware, Maryland, New Jersey, Pennsylvania, Virginia, New York and West Virginia). We then investigated the short-term effects of PM2.5 exposures on emergency hospital admissions of the elderly in the Mid-Atlantic region.We performed case-crossover analysis for each admission type, matching on day of the week, month and year and defined the hazard period as lag01 (a moving average of day of admission exposure and previous day exposure). Results We observed associations between short-term exposure to PM2.5 and hospitalization for all outcomes examined. For example, for every 10-µg/m3 increase in short-term PM 2.5 there was a 2.2% increase in respiratory diseases admissions (95% CIu200a=u200a1.9 to 2.6), and a 0.78% increase in cardiovascular disease (CVD) admission rate (95% CIu200a=u200a0.5 to 1.0). We found differences in risk for CVD admissions between people living in rural and urban areas. For every10-µg/m3 increase in PM 2.5 exposure in the ‘rural’ group there was a 1.0% increase (95% CIu200a=u200a0.6 to 1.5), while for the ‘urban’ group the increase was 0.7% (95% CIu200a=u200a0.4 to 1.0). Conclusions Our findings showed that PM2.5 exposure was associated with hospital admissions for all respiratory, cardio vascular disease, stroke, ischemic heart disease and chronic obstructive pulmonary disease admissions. In addition, we demonstrate that our AOD (Aerosol Optical Depth) based exposure models can be successfully applied to epidemiological studies investigating the health effects of short-term exposures to PM2.5.

Evaluation of Chronic Obstructive Pulmonary Disease (COPD) attributed to atmospheric O3, NO2, and SO2 using Air Q Model (2011–2012 year)

Chronic obstructive pulmonary disease (COPD) is an important disease worldwide characterized by chronically poor airflow. The economic burden of COPD on any society can be enormous if not managed. We applied the approach proposed by the World Health Organization (WHO) using the AirQ2.2.3 software developed by the WHO European Center for Environment and Health on air pollutants in Tabriz (Iran) (2011-2012 year). A 1h average of concentrations of ozone (O3), daily average concentrations of nitrogen dioxide (NO2) and sulfur dioxide (SO2) were used to assess human exposure and health effect in terms of attributable proportion of the health outcome and annual number of excess cases of Hospital Admissions for COPD (HA COPD). The results of this study showed that 2% (95% CI: 0.8-3.1%) of HA COPD were attributed to O3 concentrations over 10 μg/m(3). In addition, 0.7 % (95% CI: 0.1-1.8%) and 0.5% (95% CI: 0-1%) of HA COPD were attributed to NO2 and SO2 concentrations over 10 μg/m(3) respectively. In this study, we have shown that O3, NO2 and SO2 have a significant impact on COPD hospitalization. Given these results the policy decisions are needed in order to reduce the chronic pulmonary diseases caused by air pollution and furthermore better quantification studies are recommended.

Associations between arrhythmia episodes and temporally and spatially resolved black carbon and particulate matter in elderly patients

Objectives Ambient air pollution has been associated with sudden deaths, some of which are likely due to ventricular arrhythmias. Defibrillator discharge studies have examined the association of air pollution with arrhythmias in sensitive populations. No studies have assessed this association using residence-specific estimates of air pollution exposure. Methods In the Normative Aging Study, we investigated the association between temporally resolved and spatially resolved black carbon (BC) and PM2.5 and arrhythmia episodes (bigeminy, trigeminy or couplets episodes) measured as ventricular ectopy (VE) by 4 min ECG monitoring in repeated measures of 701 subjects, during the years 2000–2010. We used a binomial distribution (having or not a VE episode) in a mixed effect model with a random intercept for subject, controlling for seasonality, temperature, day of the week, medication use, smoking, having diabetes, body mass index and age. We also examined whether these associations were modified by genotype or phenotype. Results We found significant increases in VE with both pollutants and lags; for the estimated concentration averaged over the 3u2005days prior to the health assessment, we found increases in the odds of having VE with an OR of 1.52 (95% CI 1.19 to 1.94) for an IQR (0.30u2005μg/m3) increase in BC and an OR of 1.39 (95% CI 1.12 to 1.71) for an IQR (5.63u2005μg/m3) increase in PM2.5. We also found higher effects in subjects with the glutathione S-transferase theta-1 and glutathione S-transferase mu-1 variants and in obese (p<0.05). Conclusions Increased levels of short-term traffic-related pollutants may increase the risk of ventricular arrhythmia in elderly subjects.

A review of AirQ Models and their applications for forecasting the air pollution health outcomes

Even though clean air is considered as a basic requirement for the maintenance of human health, air pollution continues to pose a significant health threat in developed and developing countries alike. Monitoring and modeling of classic and emerging pollutants is vital to our knowledge of health outcomes in exposed subjects and to our ability to predict them. The ability to anticipate and manage changes in atmospheric pollutant concentrations relies on an accurate representation of the chemical state of the atmosphere. The task of providing the best possible analysis of air pollution thus requires efficient computational tools enabling efficient integration of observational data into models. A number of air quality models have been developed and play an important role in air quality management. Even though a large number of air quality models have been discussed or applied, their heterogeneity makes it difficult to select one approach above the others. This paper provides a brief review on air quality models with respect to several aspects such as prediction of health effects.

Exposure to sub-chronic and long-term particulate air pollution and heart rate variability in an elderly cohort: the Normative Aging Study

BackgroundShort-term particulate air pollution exposure is associated with reduced heart rate variability (HRV), a risk factor for cardiovascular morbidity and mortality, in many studies. Associations with sub-chronic or long-term exposures, however, have been sparsely investigated. We evaluated the effect of fine particulate matter (PM2.5) and black carbon (BC) exposures on HRV in an elderly cohort: the Normative Aging Study.MethodsWe measured power in high frequency (HF) and low frequency (LF), standard deviation of normal-to-normal intervals (SDNN), and the LF:HF ratio among participants from the Greater Boston area. Residential BC exposures for 540 men (1161 study visits, 2000–2011) were estimated using a spatio-temporal land use regression model, and residential PM2.5 exposures for 475 men (992 visits, 2003–2011) were modeled using a hybrid satellite based and land-use model. We evaluated associations between moving averages of sub-chronic (3–84 day) and long-term (1xa0year) pollutant exposure estimates and HRV parameters using linear mixed models.ResultsOne-standard deviation increases in sub-chronic, but not long-term, BC were associated with reduced HF, LF, and SDNN and an increased LF:HF ratio (e.g., 28xa0day BC: −2.3xa0% HF [95xa0% CI:−4.6, −0.02]). Sub-chronic and long-term PM2.5 showed evidence of relations to an increased LF and LF:HF ratio (e.g., 1xa0yearxa0PM: 21.0xa0% LF:HF [8.6, 34.8]), but not to HF or SDNN, though the effect estimates were very imprecise and mostly spanned the null.ConclusionsWe observed some evidence of a relation between longer-term BC and PM2.5 exposures and changes in HRV in an elderly cohort. While previous studies focused on short-term air pollution exposures, our results suggest that longer-term exposures may influence cardiac autonomic function.

Prenatal and childhood traffic-related air pollution exposure and childhood executive function and behavior

BACKGROUNDnTraffic-related air pollution exposure may influence brain development and function and thus be related to neurobehavioral problems in children, but little is known about windows of susceptibility.nnnAIMSnExamine associations of gestational and childhood exposure to traffic-related pollution with executive function and behavior problems in children.nnnMETHODSnWe studied associations of pre- and postnatal pollution exposures with neurobehavioral outcomes in 1212 children in the Project Viva pre-birth cohort followed to mid-childhood (median age 7.7years). Parents and classroom teachers completed the Behavior Rating Inventory of Executive Function (BRIEF) and the Strengths and Difficulties Questionnaire (SDQ). Using validated spatiotemporal models, we estimated exposure to black carbon (BC) and fine particulate matter (PM2.5) in the third trimester of pregnancy, from birth to 3years, from birth to 6years, and in the year before behavioral ratings. We also measured residential distance to major roadways and near-residence traffic density at birth and in mid-childhood. We estimated associations of BC, PM2.5, and other traffic exposure measures with BRIEF and SDQ scores, adjusted for potential confounders.nnnRESULTSnHigher childhood BC exposure was associated with higher teacher-rated BRIEF Behavioral Regulation Index (BRI) scores, indicating greater problems: 1.0 points (95% confidence interval (CI): 0.0, 2.1) per interquartile range (IQR) increase in birth-age 6BC, and 1.7 points (95% CI: 0.6, 2.8) for BC in the year prior to behavioral ratings. Mid-childhood residential traffic density was also associated with BRI score (0.6, 95% CI: 0.1, 1.1). Birth-age 3BC was not associated with BRIEF or SDQ scores. Third trimester BC exposure was not associated with teacher-rated BRI scores (-0.2, 95% CI: -1.1, 0.8), and predicted lower scores (fewer problems) on the BRIEF Metacognition Index (-1.2, 95% CI: -2.2, -0.2) and SDQ total difficulties (-0.9, 95% CI: -1.4, -0.4). PM2.5 exposure was associated with teacher-rated BRIEF and SDQ scores in minimally adjusted models but associations attenuated with covariate adjustment. None of the parent-rated outcomes suggested adverse effects of greater pollution exposure at any time point.nnnCONCLUSIONSnChildren with higher mid-childhood exposure to BC and greater near-residence traffic density in mid-childhood had greater problems with behavioral regulation as assessed by classroom teachers, but not as assessed by parents. Prenatal and early childhood exposure to traffic-related pollution did not predict greater executive function or behavior problems; third trimester BC was associated with lower scores (representing fewer problems) on measures of metacognition and behavioral problems.