Exposure information in environmental health research: current opportunities and future directions for particulate matter, ozone, and toxic air pollutants

Environmental exposures and lymphoma risk: a nested case-control study using the Golden Retriever Lifetime Study cohort

Lymphoma is the second most common cancer affecting Golden Retrievers and is hypothesized to arise through a complex interaction of genetic and environmental factors. The aim of this nested case–control study was to investigate the association between potential environmental pollutant sources and lymphoma risk among Golden Retrievers participating in the Golden Retriever Lifetime Study. Forty-nine Golden Retrievers with non-cutaneous lymphoma and 98 Golden Retrievers without a history of cancer matched by age, sex and neuter status were selected from the Golden Retriever Lifetime Study cohort. Geographic proximity between each dog’s primary residence and nine potential sources of environmental pollution was determined. In addition, the average annual ozone and airborne fine particulate matter levels for each dog’s county of residence and owner-reported secondhand smoke exposure were evaluated. Environmental pollution sources of interest included chemical plants, municipal dumps, manufacturing plants, incineration plants, railroad embankment tracks, landfills, coal plants, high-voltage transmission lines, and nuclear power plants. Conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for each exposure of interest. Subgroup analyses were conducted to evaluate whether associations differed among 1) dogs with multicentric lymphoma, 2) dogs with B-cell lymphoma, and 3) dogs with T-cell lymphoma. No variables reached statistical significance when evaluating all cases together. However, cumulative exposure burden (household proximity to 3 or more pollution sources) approached significance within the multicentric lymphoma subgroup (OR = 2.60, 95%CI 0.99–6.86, p-value = 0.053). Patterns emerged among B- and T-cell subgroups, but none reached statistical significance. Ongoing research is warranted to discern if different environmental mechanisms may be driving B- and T-cell lymphoma immunophenotypes, consistent with previously reported regional differences in subtype prevalence.

Lymphoma is a common cancer affecting dogs, particularly Golden Retrievers. By identifying risk factors for lymphoma, work can be done to reduce harmful exposures or increase monitoring among dogs at a higher risk of disease. Using a subset of dogs from the Golden Retriever Lifetime Study, we sought to investigate whether dogs with lymphoma were more likely to live near certain environmental pollutant sources than dogs without lymphoma.

Forty-nine Golden Retrievers with non-cutaneous lymphoma and 98 Golden Retrievers without a history of cancer were selected from the Golden Retriever Lifetime Study Cohort. We evaluated how close each dog lived to nine environmental pollutant sources: chemical plants, municipal dumps, manufacturing plants, incineration plants, railroad embankment tracks, landfills, coal plants, high-voltage transmission lines, and nuclear power plants. Additionally, we evaluated individual exposure to secondhand smoke, and average annual ozone and particulate matter exposure (as surrogate measures for air pollution) for each dog’s county of residence.

None of the exposures examined were associated with an increased lymphoma risk in this population. More research is needed, including direct biomonitoring, to determine whether specific environmental exposures are associated with lymphoma in the Golden Retriever breed.

Does ozone inhalation cause adverse metabolic effects in humans? A systematic review

We utilized a practical, transparent approach for systematically reviewing a chemical-specific evidence base. This approach was used for a case study of ozone inhalation exposure and adverse metabolic effects (overweight/obesity, Type 1 diabetes [T1D], Type 2 diabetes [T2D], and metabolic syndrome). We followed the basic principles of systematic review. Studies were defined as "Suitable" or "Supplemental." The evidence for Suitable studies was characterized as strong or weak. An overall causality judgment for each outcome was then determined as either causal, suggestive, insufficient, or not likely. Fifteen epidemiologic and 33 toxicologic studies were Suitable for evidence synthesis. The strength of the human evidence was weak for all outcomes. The toxicologic evidence was weak for all outcomes except two: body weight, and impaired glucose tolerance/homeostasis and fasting/baseline hyperglycemia. The combined epidemiologic and toxicologic evidence was categorized as weak for overweight/obesity, T1D, and metabolic syndrome,. The association between ozone exposure and T2D was determined to be insufficient or suggestive. The streamlined approach described in this paper is transparent and focuses on key elements. As systematic review guidelines are becoming increasingly complex, it is worth exploring the extent to which related health outcomes should be combined or kept distinct, and the merits of focusing on critical elements to select studies suitable for causal inference. We recommend that systematic review results be used to target discussions around specific research needs for advancing causal determinations.

Emergency hospital admissions for cardiovascular diseases attributed to air pollution in Tehran during 2016-2019

The burden of five main air pollutants, including CO, O3, NO2, SO2, and PM2.5, on the emergency department visits (EDVs) during January 2016-December 2019 due to all cardiovascular diseases was assessed in Tehran by using a time-series model. The pollutants data were collected from Iran Department of Environment including 10 air pollution monitoring stations for the period of our study. Cumulative relative risk and attributable number/fraction were calculated for each pollutants by a Quasi-Poisson time-series regression and distributed lag non-linear model (DLNM). The maximum lag was set to 14 days because harvesting effect is more likely happened during few days. We used percentile 25 as reference value in order to calculate cumulative relative risk and attributable fraction. About 69,000 patients with cardiovascular symptoms have been admitted into the hospital during 4 years. The cumulative relative risk during the 14 days was 1.13 (1.01, 1.26), 1.15 (1.02, 1.29), and 1.08 (1.01, 1.18) for CO, NO2, and PM2.5, respectively. The numbers attributed to all values of CO were more than others; about 3800 EDVs were significantly attributed to CO, of which over 3000 were significantly attributed to high values of the pollutant. Low values of all pollutants were, not surprisingly, responsible for low number of EDVs. PM2.5, CO, and NO2 were responsible to considerable attributable number of EDVs. Our study emphasizes the need for local authorities to establish a program to reduce the air pollution in Tehran.

The evaluation and optimization of calibration methods for low-cost particulate matter sensors: Inter-comparison between fixed and mobile methods

With the development of the air pollution control, the low-cost sensors are widely used in air quality monitoring, while the data quality of these sensors is always the most concern for users. In this study, data from nine air monitoring stations with standard PM instruments were used as reference and compared with the data of mobile and fixed PM sensors in Jinan, the capital city of Shandong Province, China. Data quality of PM sensors was checked by the cross-comparison among standard method, fixed and mobile sensors. And the impacts of relative humidity and size distribution (PM_2.5/PM₁₀) on the performance of PM sensors were evaluated as well. To optimize the calibration method for both fixed and mobile PM sensors, a two-step model was designed, in which the RH and PM_2.5/PM₁₀ ratio were both used as input parameters. We firstly calibrated the sensors with five independent models, and then all the calibrated data were linearly fitted by the LR-final model. In comparison with standard instruments, the LR-final model increased the R² values of the PM_2.5 and PM₁₀ measured by fixed sensors from 0.89 and 0.79 to 0.98 and 0.97, respectively. The R² values of PM_2.5 and PM₁₀ measured by the mobile sensors both increased to 0.99 from 0.79 and 0.62. Overall, the two-step calibration model appeared to be a promising approach to solve the poor performance of low-cost sensors.

Modification Effects of Temperature on the Ozone-Mortality Relationship: A Nationwide Multicounty Study in China

Both ozone exposure and extreme temperatures are found to be significantly associated with mortality; however, inconsistent results have been obtained on the modification effects of temperature on the ozone-mortality association. In the present study, we conducted a nationwide time-series analysis in 128 counties from 2013-2018 to examine whether temperature modifies the association between short-term ozone exposure with nonaccidental and cause-specific mortality in China. First, we analyzed the effects of ozone exposure on mortality at different temperature levels. Then, we calculated the pooled effects through a meta-analysis across China. We found that high-temperature conditions (>75th percentile in each county) significantly enhanced the effects of ozone on nonaccidental, cardiovascular, and respiratory mortality, with increases of 0.44% (95% confidence interval (CI): 0.36 and 0.51%), 0.42% (95% CI: 0.32 and 0.51%) and 0.50% (95% CI: 0.31 and 0.68%), respectively, for a 10 μg/m³ increase in ozone at high temperatures. Stronger effects on nonaccidental and cardiovascular mortality were observed at high temperatures among elderly individuals aged 65 years and older compared with the younger people. Our findings provide evidence that health damage because of ozone may be influenced by the impacts of increasing temperatures, which point to the importance of mitigating ozone exposure in China under the context of climate change to further reduce the public health burden.

Spatial and Temporal Dynamics in Air Pollution Exposure Assessment

Analyzing individual exposure in urban areas offers several challenges where both the individual's activities and air pollution levels demonstrate a large degree of spatial and temporal dynamics. This review article discusses the concepts, key elements, current developments in assessing personal exposure to urban air pollution (seventy-two studies reviewed) and respective advantages and disadvantages. A new conceptual structure to organize personal exposure assessment methods is proposed according to two classification criteria: (i) spatial-temporal variations of individuals' activities (point-fixed or trajectory based) and (ii) characterization of air quality (variable or uniform). This review suggests that the spatial and temporal variability of urban air pollution levels in combination with indoor exposures and individual's time-activity patterns are key elements of personal exposure assessment. In the literature review, the majority of revised studies (44 studies) indicate that the trajectory based with variable air quality approach provides a promising framework for tackling the important question of inter- and intra-variability of individual exposure. However, future quantitative comparison between the different approaches should be performed, and the selection of the most appropriate approach for exposure quantification should take into account the purpose of the health study. This review provides a structured basis for the intercomparing of different methodologies and to make their advantages and limitations more transparent in addressing specific research objectives.

A decade of environmental public health tracking (2002-2012): progress and challenges

BACKGROUND

The creation of the Centers for Disease Control and Prevention Environmental Public Health Tracking Program spawned an invigorating and challenging approach toward implementing the nation's first population-based, environmental disease tracking surveillance system. More than 10 years have passed since its creation and an abundance of peer-reviewed articles have been published spanning a broad variety of public health topics related primarily to the goal of reducing diseases of environmental origin.

OBJECTIVE

To evaluate peer-reviewed literature related to Environmental Public Health Tracking during 2002-2012, recognize major milestones and challenges, and offer recommendations.

DESIGN

A narrative overview was conducted using titles and abstracts of peer-reviewed articles, key word searches, and science-based search engine databases.

MAIN OUTCOMES

Eighty published articles related to "health tracking" were identified and categorized according to 4 crossed-central themes. The Science and Research theme accounted for the majority of published articles, followed by Policy and Practice, Collaborations Among Health and Environmental Programs, and Network Development.

CONCLUSIONS

Overall, progress was reported in the areas of data linkage, data sharing, surveillance methods, and network development. Ongoing challenges included formulating better ways to establish the connections between health and the environment, such as using biomonitoring, public water systems, and private well water data. Recommendations for future efforts include use of data to inform policy and practice and use of electronic health records data for environmental health surveillance.

A quantitative approach for integrating multiple lines of evidence for the evaluation of environmental health risks

Decision analysis often considers multiple lines of evidence during the decision making process. Researchers and government agencies have advocated for quantitative weight-of-evidence approaches in which multiple lines of evidence can be considered when estimating risk. Therefore, we utilized Bayesian Markov Chain Monte Carlo to integrate several human-health risk assessment, biomonitoring, and epidemiology studies that have been conducted for two common insecticides (malathion and permethrin) used for adult mosquito management to generate an overall estimate of risk quotient (RQ). The utility of the Bayesian inference for risk management is that the estimated risk represents a probability distribution from which the probability of exceeding a threshold can be estimated. The mean RQs after all studies were incorporated were 0.4386, with a variance of 0.0163 for malathion and 0.3281 with a variance of 0.0083 for permethrin. After taking into account all of the evidence available on the risks of ULV insecticides, the probability that malathion or permethrin would exceed a level of concern was less than 0.0001. Bayesian estimates can substantially improve decisions by allowing decision makers to estimate the probability that a risk will exceed a level of concern by considering seemingly disparate lines of evidence.

Evaluating children's location using a personal GPS logging instrument: limitations and lessons learned

Global positioning system (GPS) technology is increasingly used to assess geographically varying exposure in population studies. However, there has been limited evaluation of accuracy and completeness of personal GPS data. The ability of a GPS data logger to assess location of children during usual activity was evaluated. Data collected for 4 days from 17 children wearing GPS loggers, recorded every 15 s, were evaluated for completeness by time of day during weekend and weekdays, and for accuracy during nighttime at home. Percentage of possible GPS-recorded points and of 5-min intervals with at least one recorded location were examined. Mean percentage of total possible 15-s interval locations recorded daily was less than 30%. Across participants, the GPS loggers recorded 1-47% of total possible location points on weekends and 1-55% on weekdays. More complete data were measured during travel to school (average 91%). The percentage of daily 5-min intervals with recorded data was as high as 53%. At least one location was recorded during 69% of 5-min intervals before school (0630-0800 h), 62% during school (0800-1400 h) and 56% after school (1400-1700 h). During night time (0000-0600 h), on average, location was recorded for less than 25% of 5-min intervals and accuracy was poor. The large proportion of missing data limits the usefulness of GPS logging instruments for population studies. They have potential utility for assessing on-road travel time and route. GPS technology has limitations, and lessons learned from this evaluation can be generalized to the use of GPS in other research settings.

Modeling of human exposure to benzene in urban environments

Urban areas characterized by high spatial and temporal variability in air pollution levels require implementation of comprehensive approaches to address exposure of individuals. The main objective of this study was to implement a quantitative assessment of individual exposure to benzene in urban environments. For this purpose, ExPOSITION model based on a global positioning system (GPS) tracking approach was applied to estimate individual exposure in different microenvironments. The current investigation provides an application example and validation of the modeling approach against personal and biological exposure measurements collected during the measurements campaign. The probabilistic approach using the Johnson system of distributions was implemented to characterize variability of indoor concentrations. The results obtained for daily average individual exposure to benzene corresponded to mean levels of 1.6 and 0.8-2.7 μg/m(3) in terms of 5th-95th percentiles. Validation of the model results against several personal exposure samples collected for the selected individuals revealed a Pearson's correlation coefficient of .66. This modeling approach explicitly addressed the temporal and spatial variability in the exposure and established a source-receptor relationship.

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 with 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 NO(x)). In addition, the optimal exposure estimation approach also depends upon the epidemiological study design. We recommend that future research develops pollutant-specific infiltration data (including for PM species) and improves 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.

Development and evaluation of alternative approaches for exposure assessment of multiple air pollutants in Atlanta, Georgia

Measurements from central site (CS) monitors are often used as estimates of exposure in air pollution epidemiological studies. As these measurements are typically limited in their spatiotemporal resolution, true exposure variability within a population is often obscured, leading to potential measurement errors. To fully examine this limitation, we developed a set of alternative daily exposure metrics for each of the 169 ZIP codes in the Atlanta, GA, metropolitan area, from 1999 to 2002, for PM(2.5) and its components (elemental carbon (EC), SO(4)), O(3), carbon monoxide (CO), and nitrogen oxides (NOx). Metrics were applied in a study investigating the respiratory health effects of these pollutants. The metrics included: (i) CS measurements (one CS per pollutant); (ii) air quality model results for regional background pollution; (iii) local-scale AERMOD air quality model results; (iv) hybrid air quality model estimates (a combination of (ii) and (iii)); and (iv) population exposure model predictions (SHEDS and APEX). Differences in estimated spatial and temporal variability were compared by exposure metric and pollutant. Comparisons showed that: (i) both hybrid and exposure model estimates exhibited high spatial variability for traffic-related pollutants (CO, NO(x), and EC), but little spatial variability among ZIP code centroids for regional pollutants (PM(2.5), SO(4), and O(3)); (ii) for all pollutants except NO(x), temporal variability was consistent across metrics; (iii) daily hybrid-to-exposure model correlations were strong (r>0.82) for all pollutants, suggesting that when temporal variability of pollutant concentrations is of main interest in an epidemiological application, the use of estimates from either model may yield similar results; (iv) exposure models incorporating infiltration parameters, time-location-activity budgets, and other exposure factors affect the magnitude and spatiotemporal distribution of exposure, especially for local pollutants. The results of this analysis can inform the development of more appropriate exposure metrics for future epidemiological studies of the short-term effects of particulate and gaseous ambient pollutant exposure in a community.

Air pollution exposure prediction approaches used in air pollution epidemiology studies

Epidemiological studies of the health effects of outdoor air pollution have traditionally relied upon surrogates of personal exposures, most commonly ambient concentration measurements from central-site monitors. However, this approach may introduce exposure prediction errors and misclassification of exposures for pollutants that are spatially heterogeneous, such as those associated with traffic emissions (e.g., carbon monoxide, elemental carbon, nitrogen oxides, and particulate matter). We review alternative air quality and human exposure metrics applied in recent air pollution health effect studies discussed during the International Society of Exposure Science 2011 conference in Baltimore, MD. Symposium presenters considered various alternative exposure metrics, including: central site or interpolated monitoring data, regional pollution levels predicted using the national scale Community Multiscale Air Quality model or from measurements combined with local-scale (AERMOD) air quality models, hybrid models that include satellite data, statistically blended modeling and measurement data, concentrations adjusted by home infiltration rates, and population-based human exposure model (Stochastic Human Exposure and Dose Simulation, and Air Pollutants Exposure models) predictions. These alternative exposure metrics were applied in epidemiological applications to health outcomes, including daily mortality and respiratory hospital admissions, daily hospital emergency department visits, daily myocardial infarctions, and daily adverse birth outcomes. This paper summarizes the research projects presented during the symposium, with full details of the work presented in individual papers in this journal issue.

Study of environmental health problems in Korea using integrated environmental health indicators

We have investigated the usefulness of environmental health indicators for the evaluation of environmental health in Korea. We also assessed the association between environmental contamination and health outcomes by integrating indicators into a composite measure. We selected health-related environmental indicators and environment-related health status indicators. The data were obtained from published statistical data from the period 2008–2009. Both synthesized measures of environmental indicators and health status indicators were calculated using Strahll’s taxonometric methods. The range of values determined by this method is 0–1, with higher values representing a better situation in the given area. The study area consisted of 16 large administrative areas within Korea. The arithmetic mean of the synthesized measure of environmental indicators was 0.348 (SD = 0.151), and that of the synthesized measure of health status indicators was 0.708 (SD = 0.107). The correlation coefficient between the synthesized measures of environmental indicators and health status indicators was 0.69 (95% CI: 0.28–0.88). Comparisons between local communities based on integrated indicators may provide useful information for decision-makers, allowing them to identify priorities in pollutant mitigation policies or in improvement actions for public health. Integrated indicators are also useful to describe the relationships between environmental contamination and health effects.

Quantifying human exposure to air pollution--moving from static monitoring to spatio-temporally resolved personal exposure assessment

Quantifying human exposure to air pollutants is a challenging task. Ambient concentrations of air pollutants at potentially harmful levels are ubiquitous in urban areas and subject to high spatial and temporal variability. At the same time, every individual has unique activity-patterns. Exposure results from multifaceted relationships and interactions between environmental and human systems, adding complexity to the assessment process. Traditionally, approaches to quantify human exposure have relied on pollutant concentrations from fixed air quality network sites and static population distributions. New developments in sensor technology now enable us to monitor personal exposure to air pollutants directly while people are moving through their activity spaces and varying concentration fields. The literature review on which this paper is based on reflects recent developments in the assessment of human exposure to air pollution. This includes the discussion of methodologies and concepts, and the elaboration of approaches and study designs applied in the field. We identify shortcomings of current approaches and discuss future research needs. We close by proposing a novel conceptual model for the integrated assessment of human exposure to air pollutants taking into account latest technological capabilities and contextual information.

Have guidelines addressing physical activity been established in nonalcoholic fatty liver disease?

The purpose of this review was to highlight, in relation to the currently accepted pathophysiology of non-alcoholic fatty liver disease (NAFLD), the known exercise habits of patients with NAFLD and to detail the benefits of lifestyle modification with exercise (and/or physical activity) on parameters of metabolic syndrome. More rigorous, controlled studies of longer duration and defined histopathological end-points comparing exercise alone and other treatment are needed before better, evidence-based physical activity modification guidelines can be established, since several questions remain unanswered.

Adult asthma and traffic exposure at residential address, workplace address, and self-reported daily time outdoor in traffic: A two-stage case-control study

Background

Most epidemiologic studies use traffic at residential address as a surrogate for total traffic exposure when investigating effects of traffic on respiratory health. This study used GIS (Geographical Information Systems) to estimate traffic exposure, not only on residential, but also on workplace address, in addition to survey questions on time spent in traffic during commuting or other daily activities.

The aim was to investigate 1) if there is an association between traffic exposure and prevalence of adult asthma and asthma symptoms, and 2) if so, does this association become stronger using more complete traffic exposure information.

Methods

This study was conducted in two stages: A first cross-sectional survey in Southern Sweden 2004 (n = 24819, 18-80 years, response rate 59%) was followed by a case-control study in 2005 to obtain more detailed exposure and confounder information (n = 2856, asthmatics and controls (1:3), 86% response rate). In the first survey, only residential address was known. In the second survey, questions about workplace addresses and daily time spent in traffic were also included. Residential and workplace addresses were geocoded and linked with GIS to road data and dispersion modelled outdoor concentrations of NO_x (annual mean, 250 × 250 m resolution).

Results

Living within 50 m of a road (measured by GIS) with traffic intensity of >10 cars/minute (compared with no road within this distance) was associated with an increased prevalence of asthma, (OR = 1.8, 95% CI = (1.1-2.8), and with asthma symptoms last 12 months. No statistically significant effects were seen for traffic exposure at workplace address, daily time spent in traffic, or commuting time to work, after adjustment for confounders. A combined total exposure estimate did not give a stronger association with asthma prevalence or asthma symptoms.

Conclusions

Traffic exposure at close proximity to residential address showed association with asthma prevalence and asthma symptoms last 12 months, among adults in southern Sweden. The associations were not stronger when accounting for total traffic exposure. This could reflect exposure misclassfication at workplace address and for other daily time in traffic, but also that residential address remains the main determinant for traffic exposure among adults.

A study protocol to evaluate the relationship between outdoor air pollution and pregnancy outcomes

Background

The present study protocol is designed to assess the relationship between outdoor air pollution and low birth weight and preterm births outcomes performing a semi-ecological analysis. Semi-ecological design studies are widely used to assess effects of air pollution in humans. In this type of analysis, health outcomes and covariates are measured in individuals and exposure assignments are usually based on air quality monitor stations. Therefore, estimating individual exposures are one of the major challenges when investigating these relationships with a semi-ecologic design.

Methods/Design

Semi-ecologic study consisting of a retrospective cohort study with ecologic assignment of exposure is applied. Health outcomes and covariates are collected at Primary Health Care Center. Data from pregnant registry, clinical record and specific questionnaire administered orally to the mothers of children born in period 2007-2010 in Portuguese Alentejo Litoral region, are collected by the research team. Outdoor air pollution data are collected with a lichen diversity biomonitoring program, and individual pregnancy exposures are assessed with spatial geostatistical simulation, which provides the basis for uncertainty analysis of individual exposures. Awareness of outdoor air pollution uncertainty will improve validity of individual exposures assignments for further statistical analysis with multivariate regression models.

Discussion

Exposure misclassification is an issue of concern in semi-ecological design. In this study, personal exposures are assigned to each pregnant using geocoded addresses data. A stochastic simulation method is applied to lichen diversity values index measured at biomonitoring survey locations, in order to assess spatial uncertainty of lichen diversity value index at each geocoded address. These methods assume a model for spatial autocorrelation of exposure and provide a distribution of exposures in each study location. We believe that variability of simulated exposure values at geocoded addresses will improve knowledge on variability of exposures, improving therefore validity of individual exposures to input in posterior statistical analysis.

Availability and comparability of human biomonitoring data across Europe: a case-study on blood-lead levels

Recently, it has become clear that the complexity of environmental health issues requires an approach that takes into account the complexities, interdependencies and uncertainties of the real world. An urgent issue that has surfaced is the need for accurate tools to better describe exposure characterization to environmental chemicals. By including human biomonitoring (HBM) data, a greater precision in exposure and associated risk estimates and more accurate dose-response relationships may be achieved. A restricting issue still is the availability of reliable and comparable HBM data. The aim of the current study was twofold: (1) to find out whether it is practically feasible to collect raw, individual HBM data across Europe; and (2) to evaluate the comparability and use of these HBM data for environmental health impact assessment at a European scale. Blood-lead (B-Pb) was selected as the chemical of choice because of its long history as an environmental pollutant in HBM programs and its known public health relevance. Through literature search and identification of HBM experts across Europe, HBM programs that measured B-Pb were identified and asked to share individual data on age, gender and B-Pb levels. Following this request, more than 20,000 individual data points from 8 European countries were collected. Analysing these data made clear that it is difficult to use disparate data collections because of the inherent variability with respect to the gender and age of participants and calendar-years sampled. When these confounders were taken however, there was no additional variability in B-Pb distributions among different countries. It was concluded that while it is possible to collect HBM data from different sources across Europe, the need to get data from comparable (sub-)populations is essential for appropriate use and interpretation of HBM data for environmental health impact assessment.

Human Exposure: Indoor and Outdoor

Human exposure to air pollution is highly variable, reflecting the strong spatial and temporal variability of air pollutant concentrations in urban environments. A wide variety of outdoor and indoor sources contribute to acute and chronic exposures to respirable particles, carbon monoxide, nitrogen oxides, sulfur dioxide, ozone, volatile organic compounds and polycyclic aromatic hydrocarbons. Ambient air quality measurements and dispersion model simulations are commonly used to estimate population exposure to air pollutants in cities. In addition, time-activity micro-environmental and other dynamic time-space models can be used to characterise the personal exposure of individuals or population subgroups. People in developed countries typically spend 90% of their time indoors, and impact of indoor sources, such as tobacco smoking, gas cooking, construction and furnishing materials, and household chemicals (e.g. paints, adhesives, cleaning products, etc.), on personal exposure can become dominant. Recent exposure surveys have shown that personal exposure is typically higher than both indoor and outdoor concentrations of traffic-related pollutants such as benzene. In most cases, this is due to peak personal exposures occurring within transient (e.g. commuting) and other highly polluted micro-environments (e.g. petrol stations, garages, etc.). In developing countries, domestic fuel combustion (e.g. biomass burning for cooking and heating) has been identified as a major factor contributing to elevated exposure of the population to respirable particles, carbon monoxide, polycyclic aromatic hydrocarbons, nitrogen oxides and sulfur dioxide.

Use of health information in air pollution health research: past successes and emerging needs

In September 2006, the US Environmental Protection Agency and the US Centers for Disease Control (CDC) co-organized a symposium on "Air Pollution Exposure and Health." The main objective of this symposium was to identify opportunities for improving the use of exposure and health information in future studies of air pollution health effects. This paper deals with the health information needs of such studies. We begin with a selected review of different types of health data and how they were used in previous epidemiologic studies of health effects of ambient particulate matter (PM). We then examine the current and emerging information needs of the environmental health community, dealing with PM and other air pollutants of health concern. We conclude that the past use of routinely collected health data proved to be essential for activities to protect public health, including the identification and evaluation of health hazards by air pollution research, setting standards for criteria pollutants, surveillance of health outcomes to identify incidence trends, and the more recent CDC environmental public health tracking program. Unfortunately, access to vital statistics records that have informed such pivotal research has recently been curtailed sharply, threatening the continuation of the type of research necessary to support future standard setting and research on emerging exposure and health problems (e.g. asthma, multiple sclerosis, diabetes, and others), as well as our ability to evaluate the efficacy of regulatory and other prevention activities. A comprehensive devoted effort, perhaps new legislation, will be needed to address the standardization, centralization, and sharing of data sets, as well as to harmonize the interpretation of confidentiality and privacy protections across jurisdictions. These actions, combined with assuring researchers and public health practitioners appropriate access to data for evaluation of environmental risks, will be essential for the achievement of our environmental health protection goals.

Summary and findings of the EPA and CDC symposium on air pollution exposure and health

The U.S. Environmental Protection Agency (EPA) and the U.S. Centers for Disease Control (CDC) co-organized a symposium on "Air Pollution Exposure and Health" at Research Triangle Park, North Carolina on September 19-20, 2006. The symposium brought together health and environmental scientists to discuss the state of the science and the cross-jurisdictional and methodological challenges in conducting air pollution epidemiology, environmental public health tracking and accountability research. The symposium was held over 2 days and consisted of technical presentations and breakout group discussions on each of the three principal themes of this meeting: (1) monitoring and exposure modeling information, (2) health effects data and (3) linkage of air quality and health data for research, tracking and accountability. This paper summarizes the symposium presentations and the conclusions and recommendations developed during the meeting. The accompanying two papers, which appear in this issue of the Journal, provide more in-depth discussion of issues pertinent to obtaining and analyzing air pollution exposure and health information. The symposium succeeded in identifying areas where there are critical gaps of knowledge in existing air pollution exposure and health information and in discovering institutional or programmatic barriers, which impede accessing and linking disparate data sets. Several suggestions and recommendations emerged from this meeting, directed toward (1) improving the utility of air monitoring data for exposure quantification, (2) improving access to and the quality of health data, (3) studying emerging air quality and health issues, (4) exploring improved or novel methods for linking data and (5) developing partnerships, building capacity and facilitating interdisciplinary communication. The meeting was successful in promoting an interdisciplinary dialogue around these issues and in formulating strategies to support these recommended activities. Finally, this symposium subsequently led to strengthening and initiating new partnerships or interactions between the EPA, CDC, States, academia and the research community at large.