Contributions of a Child's Built, Natural, and Social Environments to Their General Cognitive Ability: A Systematic Scoping Review.

The etiology of a child's cognitive ability is complex, with research suggesting that it is not attributed to a single determinant or even a defined period of exposure. Rather, cognitive development is the product of cumulative interactions with the environment, both negative and positive, over the life course. The aim of this systematic scoping review was to collate evidence associated with children's cognitive health, including inherent factors as well as chemical and non-chemical stressors from the built, natural, and social environments. Three databases were used to identify recent epidemiological studies (2003-2013) that examined exposure factors associated with general cognitive ability in children. Over 100 factors were evaluated from 258 eligible studies. We found that recent literature mainly assessed the hypothesized negative effects of either inherent factors or chemical exposures present in the physical environment. Prenatal growth, sleep health, lead and water pollutants showed consistent negative effects. Of the few studies that examined social stressors, results consistently showed cognitive development to be influenced by both positive and negative social interactions at home, in school or the community. Among behavioral factors related to diet and lifestyle choices of the mother, breastfeeding was the most studied, showing consistent positive associations with cognitive ability. There were mostly inconsistent results for both chemical and non-chemical stressors. The majority of studies utilized traditional exposure assessments, evaluating chemical and non-chemical stressors separately. Collective evidence from a limited number of studies revealed that cumulative exposure assessment that incorporates multiple chemical and non-chemical stressors over the life course may unravel the variability in effect on cognitive development and help explain the inconsistencies across studies. Future research examining the interactions of multiple stressors within a child's total environment, depicting a more real-world exposure, will aid in understanding the cumulative effects associated with a child's ability to learn.

Integrating human health and environmental health into the DPSIR framework: a tool to identify research opportunities for sustainable and healthy communities.

The U.S. Environmental Protection Agency has recently realigned its research enterprise around the concept of sustainability. Scientists from across multiple disciplines have a role to play in contributing the information, methods, and tools needed to more fully understand the long-term impacts of decisions on the social and economic sustainability of communities. Success will depend on a shift in thinking to integrate, organize, and prioritize research within a systems context. We used the Driving forces-Pressures-State-Impact-Response (DPSIR) framework as a basis for integrating social, cultural, and economic aspects of environmental and human health into a single framework. To make the framework broadly applicable to sustainability research planning, we provide a hierarchical system of DPSIR keywords and guidelines for use as a communication tool. The applicability of the integrated framework was first tested on a public health issue (asthma disparities) for purposes of discussion. We then applied the framework at a science planning meeting to identify opportunities for sustainable and healthy communities research. We conclude that an integrated systems framework has many potential roles in science planning, including identifying key issues, visualizing interactions within the system, identifying research gaps, organizing information, developing computational models, and identifying indicators.

Feasibility of community food item collection for the National Children's Study.

BACKGROUND: The National Children's Study proposes to investigate biological, chemical, physical, and psychosocial environmental exposures and their role on health outcomes in pregnant women and children. One specific area of concern is contaminant exposure through the ingestion of solid foods. National food contaminant databases may miss dietary exposures unique to specific communities and sources of food. OBJECTIVE: The purpose of this study was to evaluate the feasibility of community food item collection for the assessment of pesticide exposure in pregnant women and young children. METHODS: A prospective observational design was used to test the food collection protocol in mothers (n=45) of children aged 15-24 months in Salt Lake City, Utah. Foods for collection were based on: 1) frequency of different foods consumed by the target population as determined by the National Health and Nutrition Examination Survey data; 2) child food frequency questionnaire; and 3) likelihood of pesticide contamination in the foods. Assessment measures included: demographics, environmental health survey, quality assurance checklist, and participant evaluation form. RESULTS: An average of three food items were obtained from 44 households, yielding a collection rate of 97.8%. Overall, 100% of the food samples were rated as acceptable. Moreover, a vast majority of mothers reported that the study was not burdensome (95.5%) and that preparing the food sample was easy (93.2%). CONCLUSIONS: This study suggests that the community food item collection methodology shows promise as a low-burden approach for capturing dietary exposures on a household level, and appears to be a feasible tool for large population studies to assess dietary exposures unique to specific communities.

Improving cost-effectiveness of epidemiological studies via designed missingness strategies.

Modern epidemiological studies face opportunities and challenges posed by an ever-expanding capacity to measure a wide range of environmental exposures, along with sophisticated biomarkers of exposure and response at the individual level. The challenge of deciding what to measure is further complicated for longitudinal studies, where logistical and cost constraints preclude the collection of all possible measurements on all participants at every follow-up time. This is true for the National Children's Study (NCS), a large-scale longitudinal study that will enroll women both prior to conception and during pregnancy and collect information on their environment, their pregnancies, and their children's development through early adulthood-with a goal of assessing key exposure/outcome relationships among a cohort of approximately 100 000 children. The success of the NCS will significantly depend on the accurate, yet cost-effective, characterization of environmental exposures thought to be related to the health outcomes of interest. The purpose of this paper is to explore the use of cost saving, yet valid and adequately powered statistical approaches for gathering exposure information within epidemiological cohort studies. The proposed approach involves the collection of detailed exposure assessment information on a specially selected subset of the study population, and collection of less-costly, and presumably less-detailed and less-burdensome, surrogate measures across the entire cohort. We show that large-scale efficiency in costs and burden may be achieved without making substantive sacrifices on the ability to draw reliable inferences concerning the relationship between exposure and health outcome. Several detailed scenarios are provided that document how the targeted sub-sampling design strategy can benefit large cohort studies like the NCS, as well as other more focused environmental epidemiologic studies.

Making sense of human biomonitoring data: findings and recommendations of a workshop.

The ability to measure chemicals in humans (often termed biomonitoring) is far outpacing the ability to interpret reliably these data for public health purposes, creating a major knowledge gap. Until this gap is filled, the great promise of routinely using biomonitoring data to support decisions to protect public health cannot be realized. Research is needed to link biomonitoring data quantitatively to the potential for adverse health risks, either through association with health outcomes or using information on the concentration and duration of exposure, which can then be linked to health guidelines. Developing such linkages in the risk assessment paradigm is one of the primary goals of the International Council of Chemical Associations' (ICCA) Long-Range Research Initiative (LRI) program in the area of biomonitoring. Therefore, ICCA sponsored a workshop to facilitate development of a coordinated agenda for research to enable an improved interpretation of human biomonitoring data. Discussions addressed three main topics: (1) exploration of the link between exposure, dose, and human biomonitoring data, (2) the use of computational tools to interpret biomonitoring data, and (3) the relevance of human biomonitoring data to the design of toxicological studies. Several overarching themes emerged from the workshop: (a) Interpretation and use of biomonitoring data should involve collaboration across all sectors (i.e., industry, government, and academia) and countries. (b) Biomonitoring is not a stand-alone tool, and it should be linked to exposure and toxicological dose information. (c) Effective communication is critical, because when uncertainty about the actual risks is high, the perceived risks grow in the absence of communication. (d) The scope of future biomonitoring activities encompasses a variety of research approaches - from advancing the science to fill data gaps to advancing the accessibility of the current knowledge to enable better information sharing.

Exposure assessment in the National Children's Study: introduction.

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.

Exposure assessment implications for the design and implementation of the National Children's Study.

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 (approximately 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.

Cost/variance optimization for human exposure assessment studies.

The National Human Exposure Assessment Survey (NHEXAS) field study in EPA Region V (one of three NHEXAS field studies) provides extensive exposure data on a representative sample of 249 residents of the Great Lakes states. Concentration data were obtained for both metals and volatile organic compounds (VOCs) from multiple environmental media and from human biomarkers. A variance model for the logarithms of concentration measurements is used to define intraclass correlations between observations within primary sampling units (PSUs) (nominally counties) and within secondary sampling units (SSUs) (nominally Census blocks). A model for the total cost of the study is developed in terms of fixed costs and variable costs per PSU, SSU, and participant. Intraclass correlations are estimated for media and analytes with sufficient sample sizes. We demonstrate how the intraclass correlations and variable cost components can be used to determine the sample allocation that minimizes cost while achieving pre-specified precision constraints for future studies that monitor environmental concentrations and human exposures for metals and VOCs.

Determinants of temporal variability in NHEXAS-Maryland environmental concentrations, exposures, and biomarkers.

The longitudinal NHEXAS-Maryland study measured metals, PAHs, and pesticides in several media to capture temporal variability. Questionnaires were concurrently administered to identify factors that influenced changes in contaminant levels over time. We constructed mixed-effects regression models for lead, phenanthrene, and chlorpyrifos (including metabolites) in indoor air, dust, dermal wipes, and biological fluids. Significant predictors represented time-varying activities as well as unchanging housing and demographic factors. There was little overlap among the models, with predictors generally reflecting the diverse characteristics of the target compounds. We estimated between- and within-person variance components to evaluate the reliability of the measurements. While only one measurement of lead in blood or chlopyrifos in dust was needed for a dependable estimate of an individual's average level, three to eight measurements were needed for most other compound/exposure medium combinations because of considerable temporal variability. Measurements in biological fluids and dust were generally more consistent than those in indoor air. The significant covariates in the full models preferentially reduced the between-person variance component. Since the regression models explained only 1-37% of the within-person variance, the questionnaires in this study provided only modest insight into the factors responsible for the temporal variability in the contaminant levels.

Assessment of data quality for the NHEXAS--Part II: Minnesota children's pesticide exposure study (MNCPES).

The Minnesota Children's Pesticide Exposure Study (MNCPES) of the National Human Exposure Assessment Survey (NHEXAS) was conducted in Minnesota to evaluate children's pesticide exposure. This study complements and extends the populations and chemicals included in the NHEXAS Region V study. One of the goals of the study was to test protocols for acquiring exposure measurements and developing databases for use in exposure models and assessments. Analysis of the data quality is one element in assessing the performance of the collection and analysis protocols used in this study. Data quality information must also be available to investigators to guide analysis of the study data. During the planning phase of MNCPES, quality assurance (QA) goals were established for precision, accuracy, and quantification limits. The data quality was assessed against these goals. The assessment is complex. First, data are not available for all analytes and media sampled. In addition, several laboratories were responsible for the analysis of the collected samples. Each laboratory provided data according to their standard operating procedures (SOPs) and protocols. Detection limits were authenticated for each analyte in each sample type. The approach used to calculate detection limits varied across the different analytical methods. The analytical methods for pesticides in air, food, hand rinses, dust wipe and urine were sufficiently sensitive and met the QA goals, with very few exceptions. This was also true for polynuclear aromatic hydrocarbons (PAHs) in air and food. The analytical methods for drinking water and beverages had very low detection limits; however, there were very little measurable data for these samples. The collection and analysis methods for pesticides in surface press samples and soil, and for PAHs in dust wipes were not sufficiently sensitive. Accuracy was assessed primarily as recovery from field controls. The results were good for pesticides and PAHs in air (75-125% recovery). Recovery was lower (<75%) for pesticides in drinking water and beverages. The recovery of pesticides from hand rinses met QA goals (75-100%), but surface press samples showed lower recovery (50-70%). Analysis by gas chromatography-mass spectrometry (GC-MS) did not confirm the presence of atrazine and other pesticides in hand rinse and surface press samples that had been detected by GC-ECD, but instead GC-MS confirmed background interferences. Assessment of the precision of sample collection and analysis is based on the percent relative standard deviation (%RSD) between the results for duplicate samples. Data are available only for pesticides and PAHs in air. Precision was good (<20% RSD) for analytes with measurable data. There were a few analytes with %RSD >20%, but the number of data pairs was very small in these cases. Precision for instrumental analysis of food sample extracts was excellent, with the median %RSD < 20 for all measurable pesticides. The median %RSD for the analysis of replicate aliquots of food from the same sample composite was considerably higher, indicating the potential for inhomogeneity of food homogenates.

Distributions, associations, and partial aggregate exposure of pesticides and polynuclear aromatic hydrocarbons in the Minnesota Children's Pesticide Exposure Study (MNCPES).

The Minnesota Children's Pesticide Exposure Study (MNCPES) provides exposure, environmental, and biologic data relating to multipathway exposures of children for four primary pesticides (chlorpyrifos, malathion, diazinon, and atrazine), 14 secondary pesticides, and 13 polynuclear aromatic hydrocarbons (PAHs). Monitoring was performed on a probability-based sample of 102 children aged 3-12 in Minneapolis/St. Paul and in a nearby rural area (Goodhue and Rice counties). This paper provides estimated distributions of this population's exposures and exposure-related measurements and examines associations among the various measures via rank (Spearman) correlations. In addition, it provides some aggregate and cumulative exposure estimates for pesticides, and compares the relative intakes from inhalation and dietary ingestion. Intakes for the four primary pesticides appeared to come principally from the ingestion rather than the inhalation route; this was clearly true for chlorpyrifos but was less certain for the other three primary pesticides because of their higher degree of nondetects. Solid food rather than beverages was clearly the main contributor to the ingestion intake. Despite the dominance of the ingestion route, the urinary metabolite of chlorpyrifos exhibited a stronger association with the air measurements than with the dietary measures. Personal-air samples exhibited strong rank correlations with indoor air samples for chlorpyrifos, malathion, and diazinon (0.81, 0.51, and 0.62, respectively), while personal-air atrazine levels correlated well with outdoor levels (0.69); personal-air diazinon levels also correlated well with outdoor levels (0.67). For the PAHs, many significant associations were evident among the various air samples and for the air samples with the dust samples, especially for those compounds with consistently high percent measurable values (particularly fluoranthene, phenanthrene, and pyrene).

Predicting children's short-term exposure to pesticides: results of a questionnaire screening approach.

The ability of questionnaires to predict children's exposure to pesticides was examined as part of the Minnesota Children's Pesticide Exposure Study (MNCPES). The MNCPES focused on a probability sample of 102 children between the ages of 3 and 13 years living in either urban (Minneapolis and St. Paul, MN) or nonurban (Rice and Goodhue Counties in Minnesota) households. Samples were collected in a variety of relevant media (air, food, beverages, tap water, house dust, soil, urine), and chemical analyses emphasized three organophosphate insecticides (chlorpyrifos, diazinon, malathion) and a herbicide (atrazine). Results indicate that the residential pesticide-use questions and overall screening approach used in the MNCPES were ineffective for identifying and oversampling children/households with higher levels of individual target pesticides.

Limitations on the uses of multimedia exposure measurements for multipathway exposure assessment--Part I: Handling observations below detection limits.

Multimedia data from two probability-based exposure studies were investigated in terms of how censoring of nondetects affected estimation of population parameters and associations. Appropriate methods for handling censored below-detection-limit(BDL)values in this context were unclear since sampling weights were involved and since bivariate associations/measures were of interest. Both simple substitution(e.g., using 1/2 or 2/3 of the detection limit(DL)for BDL values)and truncation-based strategies were investigated by creating some artificial DLs and comparing resultant estimates with the original studies'uncensored results. The substitution methods generally outperformed the truncation methods, with the(2/3)DL substitution generally performing best.

Limitations on the uses of multimedia exposure measurements for multipathway exposure assessment--Part II: Effects of missing data and imprecision.

Multimedia data from two probability-based exposure studies were investigated in terms of how missing data and measurement-error imprecision affected estimation of population parameters and associations. Missing data resulted mainly from individuals'refusing to participate in certain measurement activities, rather than from field or laboratory problems; it suggests that future studies should focus on methods for maximizing participation rates. Measurement error variances computed from duplicate-sample data were small relative to the inherent variation in the populations; consequently, adjustments in nonparametric percentile estimates to account for measurement imprecision were small. Methods of adjustment based on lognormality assumptions, however, appeared to perform poorly.