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1.  Refined ambient PM2.5 exposure surrogates and the risk of myocardial infarction 
Using a case-crossover study design and conditional logistic regression, we compared the relative odds of transmural (full-wall) myocardial infarction (MI) calculated using exposure surrogates that account for human activity patterns and the indoor transport of ambient PM2.5 with those calculated using central-site PM2.5 concentrations to estimate exposure to PM2.5 of outdoor origin (exposure to ambient PM2.5). Because variability in human activity and indoor PM2.5 transport contributes exposure error in epidemiologic analyses when central-site concentrations are used as exposure surrogates, we refer to surrogates that account for this variability as “refined” surrogates. As an alternative analysis, we evaluated whether the relative odds of transmural MI associated with increases in ambient PM2.5 is modified by residential air exchange rate (AER), a variable that influences the fraction of ambient PM2.5 that penetrates and persists indoors. Use of refined exposure surrogates did not result in larger health effect estimates (ORs = 1.10 – 1.11 with each interquartile range increase.), narrower confidence intervals, or better model fits compared to the analysis that used central-site PM2.5. We did observe evidence for heterogeneity in the relative odds of transmural MI with residential AER (effect-modification), with residents of homes with higher AERs having larger ORs than homes in lower AER tertiles. For the level of exposure-estimate refinement considered here, our findings add support to the use of central-site PM2.5 concentrations for epidemiological studies that employ similar case-crossover study designs. In such designs, each subject serves as his or her own matched control. Thus, exposure error related to factors that vary spatially or across subjects should only minimally impact effect estimates. These findings also illustrate that variability in factors that influence the fraction of ambient PM2.5 in indoor air (e.g., AER) could possibly bias health effects estimates in study designs for which a spatio-temporal comparison of exposure effects across subjects is conducted.
PMCID: PMC4084717  PMID: 23715082
2.  Exposure prediction approaches used in air pollution epidemiology studies: Key findings and future recommendations 
Many epidemiologic studies of the health effects of exposure to ambient air pollution use measurements from central-site monitors as their exposure estimate. However, measurements from central-site monitors may lack the spatial and temporal resolution required to capture exposure variability in a study population, thus resulting in exposure error and biased estimates. Articles in this dedicated issue examine various approaches to predict or assign exposures to ambient pollutants. These methods include: combining existing central-site pollution measurements with local- and/or regional-scale air quality models to create new or “hybrid” models for pollutant exposure estimates, and using exposure models to account for factors such as infiltration of pollutants indoors and human activity patterns. Key findings from these articles are summarized to provide lessons learned and recommendations for additional research on improving exposure estimation approaches for future epidemiological studies. In summary, when compared to use of central-site monitoring data, the enhanced spatial resolution of air quality or exposure models can have an impact on resultant health effect estimates, especially for pollutants derived from local sources such as traffic (e.g. EC, CO, and NOx). In addition, the optimal exposure estimation approach also depends upon the epidemiological study design. We recommend that future research develop pollutant-specific infiltration data (including for PM species), and improve existing data on human time-activity patterns, and exposure to local source (e.g. traffic), in order to enhance human exposure modeling estimates. We also recommend comparing how various approaches to exposure estimation characterize relationships between multiple pollutants in time and space, and investigating the impact of improved exposure estimates in chronic health studies.
PMCID: PMC4088339  PMID: 24084756
exposure metrics; exposure models; air exchange rate; epidemiology; PM2.5; ambient pollution
3.  The triggering of myocardial infarction by fine particles is enhanced when particles are enriched in secondary species 
Environmental science & technology  2013;47(16):10.1021/es4027248.
Previous studies have reported an increased risk of myocardial infarction (MI) associated with acute increases in PM concentration. Recently, we reported that MI/fine particle (PM2.5) associations may be limited to transmural infarctions. In this study, we retained data on hospital discharges with a primary diagnosis of acute myocardial infarction (using International Classification of Diseases 9th Revision [ICD-9] codes), for those admitted January 1, 2004 to December 31, 2006, who were ≥18 years of age, and were residents of New Jersey at the time of their MI. We excluded MI with a diagnosis of a previous MI and MI coded as a subendocardial infarction, leaving n=1563 transmural infarctions available for analysis. We coupled these health data with PM2.5 species concentrations predicted by the Community Multiscale Air Quality chemical transport model, ambient PM2.5 concentrations, and used the same case-crossover methods to evaluate whether the relative odds of transmural MI associated with increased PM2.5 concentration is modified by the PM2.5 composition/mixture (i.e. mass fractions of sulfate, nitrate, elemental carbon, organic carbon, and ammonium). We found the largest relative odds estimates on the days with the highest tertile of sulfate mass fraction (OR=1.13; 95% CI = 1.00, 1.27), nitrate mass fraction (OR=1.18; 95% CI = 0.98, 1.35), and ammonium mass fraction (OR=1.13; 95% CI = 1.00 1.28), and the lowest tertile of EC mass fraction (OR=1.17; 95% CI = 1.03, 1.34). Air pollution mixtures on these days were enhanced in pollutants formed through atmospheric chemistry (i.e., secondary PM2.5) and depleted in primary pollutants (e.g., EC). When mixtures were laden with secondary PM species (sulfate, nitrate, and/or organics) we observed larger relative odds of myocardial infarction associated with increased PM2.5 concentrations. Further work is needed to confirm these findings and examine which secondary PM2.5 component(s) is/are responsible for an acute MI response.
PMCID: PMC3856764  PMID: 23819750
4.  Exposure Assessment in Cohort Studies of Childhood Asthma 
Environmental Health Perspectives  2010;119(5):591-597.
The environment is suspected to play an important role in the development of childhood asthma. Cohort studies are a powerful observational design for studying exposure–response relationships, but their power depends in part upon the accuracy of the exposure assessment.
The purpose of this paper is to summarize and discuss issues that make accurate exposure assessment a challenge and to suggest strategies for improving exposure assessment in longitudinal cohort studies of childhood asthma and allergies.
Data synthesis
Exposures of interest need to be prioritized, because a single study cannot measure all potentially relevant exposures. Hypotheses need to be based on proposed mechanisms, critical time windows for effects, prior knowledge of physical, physiologic, and immunologic development, as well as genetic pathways potentially influenced by the exposures. Modifiable exposures are most important from the public health perspective. Given the interest in evaluating gene–environment interactions, large cohort sizes are required, and planning for data pooling across independent studies is critical. Collection of additional samples, possibly through subject participation, will permit secondary analyses. Models combining air quality, environmental, and dose data provide exposure estimates across large cohorts but can still be improved.
Exposure is best characterized through a combination of information sources. Improving exposure assessment is critical for reducing measurement error and increasing power, which increase confidence in characterization of children at risk, leading to improved health outcomes.
PMCID: PMC3094407  PMID: 21081299
childhood asthma; cohort studies; exposure assessment
5.  Feasibility of Assessing Public Health Impacts of Air Pollution Reduction Programs on a Local Scale: New Haven Case Study 
Environmental Health Perspectives  2011;119(4):487-493.
New approaches to link health surveillance data with environmental and population exposure information are needed to examine the health benefits of risk management decisions.
We examined the feasibility of conducting a local assessment of the public health impacts of cumulative air pollution reduction activities from federal, state, local, and voluntary actions in the City of New Haven, Connecticut (USA).
Using a hybrid modeling approach that combines regional and local-scale air quality data, we estimated ambient concentrations for multiple air pollutants [e.g., PM2.5 (particulate matter ≤ 2.5 μm in aerodynamic diameter), NOx (nitrogen oxides)] for baseline year 2001 and projected emissions for 2010, 2020, and 2030. We assessed the feasibility of detecting health improvements in relation to reductions in air pollution for 26 different pollutant–health outcome linkages using both sample size and exploratory epidemiological simulations to further inform decision-making needs.
Model projections suggested decreases (~ 10–60%) in pollutant concentrations, mainly attributable to decreases in pollutants from local sources between 2001 and 2010. Models indicated considerable spatial variability in the concentrations of most pollutants. Sample size analyses supported the feasibility of identifying linkages between reductions in NOx and improvements in all-cause mortality, prevalence of asthma in children and adults, and cardiovascular and respiratory hospitalizations.
Substantial reductions in air pollution (e.g., ~ 60% for NOx) are needed to detect health impacts of environmental actions using traditional epidemiological study designs in small communities like New Haven. In contrast, exploratory epidemiological simulations suggest that it may be possible to demonstrate the health impacts of PM reductions by predicting intraurban pollution gradients within New Haven using coupled models.
PMCID: PMC3080930  PMID: 21335318
air pollution; feasibility analysis; health effects; nitrogen oxides; particulate matter
6.  Biologically based modeling of multimedia, multipathway, multiroute population exposures to arsenic 
This article presents an integrated, biologically based, source-to-dose assessment framework for modeling multimedia/multipathway/multiroute exposures to arsenic. Case studies demonstrating this framework are presented for three US counties (Hunderton County, NJ; Pima County, AZ; and Franklin County, OH), representing substantially different conditions of exposure. The approach taken utilizes the Modeling ENvironment for TOtal Risk studies (MENTOR) in an implementation that incorporates and extends the approach pioneered by Stochastic Human Exposure and Dose Simulation (SHEDS), in conjunction with a number of available databases, including NATA, NHEXAS, CSFII, and CHAD, and extends modeling techniques that have been developed in recent years. Model results indicate that, in most cases, the food intake pathway is the dominant contributor to total exposure and dose to arsenic. Model predictions are evaluated qualitatively by comparing distributions of predicted total arsenic amounts in urine with those derived using biomarker measurements from the NHEXAS — Region V study: the population distributions of urinary total arsenic levels calculated through MENTOR and from the NHEXAS measurements are in general qualitative agreement. Observed differences are due to various factors, such as interindividual variation in arsenic metabolism in humans, that are not fully accounted for in the current model implementation but can be incorporated in the future, in the open framework of MENTOR. The present study demonstrates that integrated source-to-dose modeling for arsenic can not only provide estimates of the relative contributions of multipathway exposure routes to the total exposure estimates, but can also estimate internal target tissue doses for speciated organic and inorganic arsenic, which can eventually be used to improve evaluation of health risks associated with exposures to arsenic from multiple sources, routes, and pathways.
PMCID: PMC3068596  PMID: 18073786
arsenic; modeling; exposure; exposure biology; dose; multimedia; PBPK
8.  Analysis of coupled model uncertainties in source-to-dose modeling of human exposures to ambient air pollution: A PM2.5 case study 
Quantitative assessment of human exposures and health effects due to air pollution involve detailed characterization of impacts of air quality on exposure and dose. A key challenge is to integrate these three components on a consistent spatial and temporal basis taking into account linkages and feedbacks. The current state-of-practice for such assessments is to exercise emission, meteorology, air quality, exposure, and dose models separately, and to link them together by using the output of one model as input to the subsequent downstream model. Quantification of variability and uncertainty has been an important topic in the exposure assessment community for a number of years. Variability refers to differences in the value of a quantity (e.g., exposure) over time, space, or among individuals. Uncertainty refers to lack of knowledge regarding the true value of a quantity. An emerging challenge is how to quantify variability and uncertainty in integrated assessments over the source-to-dose continuum by considering contributions from individual as well as linked components. For a case study of fine particulate matter (PM2.5) in North Carolina during July 2002, we characterize variability and uncertainty associated with each of the individual concentration, exposure and dose models that are linked, and use a conceptual framework to quantify and evaluate the implications of coupled model uncertainties. We find that the resulting overall uncertainties due to combined effects of both variability and uncertainty are smaller (usually by a factor of 3–4) than the crudely multiplied model-specific overall uncertainty ratios. Future research will need to examine the impact of potential dependencies among the model components by conducting a truly coupled modeling analysis.
PMCID: PMC2798576  PMID: 20041038
Air quality model; Exposure model; Particulate matter; Variability; Uncertainty
9.  Exposure Assessment in the National Children’s Study: Introduction 
Environmental Health Perspectives  2005;113(8):1076-1082.
The science of exposure assessment is relatively new and evolving rapidly with the advancement of sophisticated methods for specific measurements at the picogram per gram level or lower in a variety of environmental and biologic matrices. Without this measurement capability, environmental health studies rely on questionnaires or other indirect means as the primary method to assess individual exposures. Although we use indirect methods, they are seldom used as stand-alone tools. Analyses of environmental and biologic samples have allowed us to get more precise data on exposure pathways, from sources to concentrations, to routes, to exposure, to doses. They also often allow a better estimation of the absorbed dose and its relation to potential adverse health outcomes in individuals and in populations. Here, we make note of various environmental agents and how best to assess exposure to them in the National Children’s Study—a longitudinal epidemiologic study of children’s health. Criteria for the analytical method of choice are discussed with particular emphasis on the need for long-term quality control and quality assurance measures.
PMCID: PMC1280352  PMID: 16079082
biomonitoring; environmental monitoring questionnaire; exposure assessment; limit of detection; National Children’s Study
10.  Exposure Assessment Implications for the Design and Implementation of the National Children’s Study 
Environmental Health Perspectives  2005;113(8):1108-1115.
Examining the influence of environmental exposures on various health indices is a critical component of the planned National Children’s Study (NCS). An ideal strategy for the exposure monitoring component of the NCS is to measure indoor and outdoor concentrations and personal exposures of children to a variety of pollutants, including ambient particulate and gaseous pollutants, biologic agents, persistent organics, nonpersistent organics (e.g., pesticides), inorganic chemicals (e.g., metals), and others. However, because of the large sample size of the study (~ 100,000 children), it is not feasible to assess every possible exposure of each child. We envision that cost-effective strategies for gathering the necessary exposure-related information with minimum burden to participants, such as broad administration of product-use questionnaires and diaries, would likely be considered in designing the exposure component of the NCS. In general a biologic (e.g., blood, urine, hair, saliva) measure could be the dosimeter of choice for many of the persistent and for some of the nonpersistent organic pollutants. Biologic specimens, such as blood, can also indicate long-term internal dose to various metals, including lead and mercury. Environmental measures, on the other hand, provide pathway/source-specific exposure estimates to many of the environmental agents, including those where biologic measurements are not currently feasible (e.g., for particulate matter and for some gaseous criteria pollutants). However, these may be burdensome and costly to either collect or analyze and may not actually indicate the absorbed dose. Thus, an important technical and logistical challenge for the NCS is to develop an appropriate study design with adequate statistical power that will permit detection of exposure-related health effects, based on an optimum set of exposure measurement methods. We anticipate that low-cost, low-burden methods such as questionnaires and screening type assessments of environmental and biologic samples could be employed, when exposures at different critical life stages of vulnerability can be reliably estimated by these simpler methods. However, when reliability and statistical power considerations dictate the need for collecting more specific exposure information, more extensive environmental, biologic, and personal exposure measurements should be obtained from various “validation” subsets of the NCS population that include children who are in different life stages. This strategy of differential exposure measurement design may allow the exposure–response relationships to be tested on the whole cohort by incorporating the information on the relationship between different types of exposure measures (i.e., ranging from simple to more complex) derived from the detailed validation subsamples.
PMCID: PMC1280356  PMID: 16079086
biomonitoring; environmental; epidemiologic study design; exposure assessment; measurement; National Children’s Study; questionnaires
11.  Chlorpyrifos Accumulation Patterns for Child-Accessible Surfaces and Objects and Urinary Metabolite Excretion by Children for 2 Weeks after Crack-and-Crevice Application 
Environmental Health Perspectives  2004;113(2):211-219.
The Children’s Post-Pesticide Application Exposure Study (CPPAES) was conducted to look at the distribution of chlorpyrifos within a home environment for 2 weeks after a routine professional crack-and-crevice application and to determine the amount of the chlorpyrifos that is absorbed by a child living within the home. Ten residential homes with a 2- to 5-year-old child in each were selected for study, and the homes were treated with chlorpyrifos. Pesticide measurements were made from the indoor air, indoor surfaces, and plush toys. In addition, periodic morning urine samples were collected from each of the children throughout the 2-week period. We analyzed the urine samples for 3,5,6-trichloropyridinol, the primary urinary metabolite of chlorpyrifos, and used the results to estimate the children’s absorbed dose. Average chlorpyrifos levels in the indoor air and surfaces were 26 (pretreatment)/120 (posttreatment) ng/m3 and 0.48 (pretreatment)/2.8 (posttreatment) ng/cm2, respectively, reaching peak levels between days 0 and 2; subsequently, concentrations decreased throughout the 2-week period. Chlorpyrifos in/on the plush toys ranged from 7.3 to 1,949 ng/toy postapplication, with concentrations increasing throughout the 2-week period, demonstrating a cumulative adsorption/absorption process indoors. The daily amount of chlorpyrifos estimated to be absorbed by the CPPAES children postapplication ranged from 0.04 to 4.8 μg/kg/day. During the 2 weeks after the crack-and-crevice application, there was no significant increase in the amount of chlorpyrifos absorbed by the CPPAES children.
PMCID: PMC1277867  PMID: 15687060
biomarker; child; children; chlorpyrifos; crack-and-crevice; indoor chemical use; pesticide

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