Understanding variability in time spent in selected locations for 7-12-year old children

Household mold exposure interacts with inflammation-related genetic variants on childhood asthma: a case-control study

BACKGROUND

A number of studies have examined the association between mold exposure and childhood asthma. However, the conclusions were inconsistent, which might be partly attributable to the lack of consideration of gene function, especially the key genes affecting the pathogenesis of childhood asthma. Research on the interactions between genes and mold exposure on childhood asthma is still very limited. We therefore examined whether there is an interaction between inflammation-related genes and mold exposure on childhood asthma.

METHODS

A case-control study with 645 asthmatic children and 910 non-asthmatic children aged 3-12 years old was conducted. Eight single nucleotide polymorphisms (SNPs) in inflammation-related genes were genotyped using MassARRAY assay. Mold exposure was defined as self-reported visible mold on the walls. Associations between visible mold exposure, SNPs and childhood asthma were evaluated using logistic regression models. In addition, crossover analyses were used to estimate the gene-environment interactions on childhood asthma on an additive scale.

RESULTS

After excluding children without information on visible mold exposure or SNPs, 608 asthmatic and 839 non-asthmatic children were included in the analyses. Visible mold exposure was reported in 151 asthmatic (24.8%) and 119 non-asthmatic children (14.2%) (aOR 2.19, 95% CI 1.62-2.97). The rs7216389 SNP in gasdermin B gene (GSDMB) increased the risk of childhood asthma with each C to T substitution in a dose-dependent pattern (additive model, aOR 1.32, 95% CI 1.11-1.57). Children carrying the rs7216389 T allele and exposed to visible mold dramatically increased the risk of childhood asthma (aOR 3.21; 95% CI 1.77-5.99). The attributable proportion due to the interaction (AP: 0.47, 95% CI 0.03-0.90) and the relative excess risk due to the interaction (RERI: 1.49, 95% CI 0-2.99) were statistically significant.

CONCLUSIONS

In the present study, there was a significant additive interaction between visible mold exposure and rs7216389 SNP on childhood asthma. Future studies need to consider the gene-environment interactions when exploring the risk factors of childhood asthma.

Modeled Impacts of Drinking Water Pb Reduction Scenarios on Children's Exposures and Blood Lead Levels

In recent years, environmental lead (Pb) exposure through drinking water has resulted in community public health concerns. To understand potential impacts on blood Pb levels (BLLs) from drinking water Pb reduction actions (i.e., combinations of lead service lines [LSL] and corrosion control treatment [CCT] scenarios), EPA's Stochastic Human Exposure and Dose Simulation (SHEDS)-Multimedia/Integrated Exposure Uptake and Biokinetic (IEUBK) model was applied for U.S. children aged 0 to <6 years. The results utilizing a large drinking water sequential sampling data set from 15 cities to estimate model input concentration distributions demonstrated lowest predicted BLLs for the "no LSLs" with "combined CCT" scenario and highest predicted BLLs for the "yes LSLs" and "no CCT" scenario. Modeled contribution to BLLs from ingestion of residential drinking water ranged from ∼10 to 80%, with the highest estimated for formula-fed infants (age 0 to <1 year). Further analysis using a "bounding" data set spanning a range of realistic water Pb concentrations and variabilities showed BLL predictions consistent with the sequential sampling-derived inputs. Our study illustrates (1) effectiveness of LSL replacement coupled with CCT for reducing Pb in drinking water and children's BLLs, and (2) in some age groups, under realistic local and residential water use conditions, drinking water can be the dominant exposure pathway.

Calibrating an agent-based model of longitudinal human activity patterns using the Consolidated Human Activity Database

Patterns of human behavior over extended periods of time are important for characterizing human exposure to hazardous chemicals. Because longitudinal behavior patterns for an individual are difficult to obtain, exposure-assessors have characterized such patterns by linking daily records from multiple individuals. In an earlier publication, we developed an alternative strategy that was based on agent-based simulation modeling. Specifically, we created a software program, Agent-Based Model of Human Activity Patterns (ABMHAP), that generates year-long longitudinal behavior patterns. In this paper, we both calibrate and evaluate ABMHAP using human behavior data from the U.S. Environmental Protection Agency's Consolidated Human Activity Database (CHAD). We use the longitudinal data (data on individuals' activities over multiple days) in CHAD to parameterize ABMHAP, and we use single-day behavior data from CHAD to evaluate ABMHAP predictions. We evaluate ABMHAP's ability to simulate sleeping, eating, commuting, and working (or attending school) for four populations: working adults, nonworking adults, school-age children, and preschool children. The results demonstrate that ABMHAP, when parameterized with empirical data, can capture both interindividual and intraindividual variation in behaviors in different types of individuals. We propose that simulating annual activity patterns via ABMHAP may allow exposure-assessors to characterize exposure-related behavior in ways not possible with traditional survey methods.

Personal measurement of exposure to black carbon and ultrafine particles in schoolchildren from PARIS cohort (Paris, France)

This study aimed to measure in French children personal exposure concentrations of black carbon (BC) and ultrafine particles (UFP) and to quantify the contribution of different microenvironments (home, school, places of extracurricular activities, transport) to their total exposure. It was conducted on 96 9-year-old children from the PARIS birth cohort. BC and UFP were continuously measured by portable devices (microAeth^® AE51 and DiSCmini^® ) for a minimum of 24 hours, while participating families simultaneously filled in a space-time-activities-budget questionnaire. BC exposure concentration was higher during trips (principally metro/train and bus), while UFP exposure concentration was higher during indoor activities (mainly eating at restaurants) and in trips. The most important UFP peaks were measured at home, especially during cooking. Home and school together accounted for much of the total exposure, 83.8% for BC and 85.3% for UFP. The contribution of transport to total exposure was 12.4% for BC and 9.7% for UFP, while extracurricular activities were responsible for 3.8% and 5% of the total exposure to BC and UFP, respectively.

Characterizing the impact of projected changes in climate and air quality on human exposures to ozone

The impact of climate change on human and environmental health is of critical concern. Population exposures to air pollutants both indoors and outdoors are influenced by a wide range of air quality, meteorological, behavioral, and housing-related factors, many of which are also impacted by climate change. An integrated methodology for modeling changes in human exposures to tropospheric ozone (O₃) owing to potential future changes in climate and demographics was implemented by linking existing modeling tools for climate, weather, air quality, population distribution, and human exposure. Human exposure results from the Air Pollutants Exposure Model (APEX) for 12 US cities show differences in daily maximum 8-h (DM8H) exposure patterns and levels by sex, age, and city for all scenarios. When climate is held constant and population demographics are varied, minimal difference in O₃ exposures is predicted even with the most extreme demographic change scenario. In contrast, when population is held constant, we see evidence of substantial changes in O₃ exposure for the most extreme change in climate. Similarly, we see increases in the percentage of the population in each city with at least one O₃ exposure exceedance above 60 p.p.b and 70 p.p.b thresholds for future changes in climate. For these climate and population scenarios, the impact of projected changes in climate and air quality on human exposure to O₃ are much larger than the impacts of changing demographics. These results indicate the potential for future changes in O₃ exposure as a result of changes in climate that could impact human health.

Noise Annoyance in Urban Children: A Cross-Sectional Population-Based Study

Acoustical and non-acoustical factors influencing noise annoyance in adults have been well-documented in recent years; however, similar knowledge is lacking in children. The aim of this study was to quantify the annoyance caused by chronic ambient noise at home in children and to assess the relationship between these children's noise annoyance level and individual and contextual factors in the surrounding urban area. A cross sectional population-based study was conducted including 517 children attending primary school in a European city. Noise annoyance was measured using a self-report questionnaire adapted for children. Six noise exposure level indicators were built at different locations at increasing distances from the child's bedroom window using a validated strategic noise map. Multilevel logistic models were constructed to investigate factors associated with noise annoyance in children. Noise indicators in front of the child's bedroom (p ≤ 0.01), family residential satisfaction (p ≤ 0.03) and socioeconomic characteristics of the individuals and their neighbourhood (p ≤ 0.05) remained associated with child annoyance. These findings illustrate the complex relationships between our environment, how we may perceive it, social factors and health. Better understanding of these relationships will undoubtedly allow us to more effectively quantify the actual effect of noise on human health.

Activity Pattern of Urban Adult Students in an Eastern Mediterranean Society

Knowledge of human activity patterns is needed in air pollution exposure and health risk assessment. However, human activity patterns have never been evaluated in the Eastern Mediterranean societies. Therefore, we investigated the activity pattern of 285 subjects (17-63 years) in Amman, Jordan during October to November, 2015. The subjects spent >80% of their time indoors during weekend days and >85% on workdays. They spent ~4.8% and ~5.7% in transportation during weekend days and workdays, respectively. Males had a different activity pattern than females on weekend days, but both genders had similar activity patterns on workdays. On workdays, males spent less time indoors than females. The activity pattern found in this study is a bit different than that for North Americans and Europeans, who spend more time indoors and in transit. The activity pattern found in this study was very different than that observed for Koreans, who spent about 59% and 67% indoors on workdays and weekend, respectively. The main outcomes of this survey can be utilized in human exposure studies. This study and the upcoming future studies have been encouraged and supported by the regional WHO office in Amman.

Bedroom air quality and vacuuming frequency are associated with repeat child asthma hospital admissions

OBJECTIVE

Indoor environment factors have been associated with risk of asthma exacerbations in children but little is known about their role on asthma hospital readmissions. As children in Western societies continually spend more time indoors, understanding the influence of these factors on asthma exacerbation is important. We examined the role of indoor environmental and lifestyle characteristics on child asthma readmissions.

METHODS

A hospital-based case-control study recruited 22 children readmitted for asthma and 22 controls not readmitted for asthma. Logistic regression models were used to examine the association between aeroallergens and fungi in the bedroom and indoor lifestyle characteristics factors for asthma readmissions. To determine the best possible set of predictors among a large set of risk factors, we used random forests (RF) techniques.

RESULTS

Higher levels of airborne Cladosporium and yeast in the child's bedroom increased risk of readmission (OR = 1.68, 95% CI 1.04-2.72 and OR = 1.52, 95% CI 0.99-2.34, respectively). Carpeted floors in the bedroom and synthetic doonas were also associated with increase in asthma readmissions (OR = 4.07, 95% CI 1.03-16.06 and OR = 14.6, 95% CI 1.26-169.4, respectively). In the home, frequent vacuuming using bagged cleaners increased risk of asthma readmission OR = 15.7 (95% CI 2.82-87.2).

CONCLUSIONS

Factors in the child's bedroom play an important role in increasing the risk of asthma hospital readmissions. These findings have major clinical implications as the identified potential risk factors may be modifiable. Further epidemiological studies with larger samples are necessary to evaluate these associations further.

Assessment of the effect of population and diary sampling methods on estimation of school-age children exposure to fine particles

Population and diary sampling methods are employed in exposure models to sample simulated individuals and their daily activity on each simulation day. Different sampling methods may lead to variations in estimated human exposure. In this study, two population sampling methods (stratified-random and random-random) and three diary sampling methods (random resampling, diversity and autocorrelation, and Markov-chain cluster [MCC]) are evaluated. Their impacts on estimated children's exposure to ambient fine particulate matter (PM2.5 ) are quantified via case studies for children in Wake County, NC for July 2002. The estimated mean daily average exposure is 12.9 μg/m(3) for simulated children using the stratified population sampling method, and 12.2 μg/m(3) using the random sampling method. These minor differences are caused by the random sampling among ages within census tracts. Among the three diary sampling methods, there are differences in the estimated number of individuals with multiple days of exposures exceeding a benchmark of concern of 25 μg/m(3) due to differences in how multiday longitudinal diaries are estimated. The MCC method is relatively more conservative. In case studies evaluated here, the MCC method led to 10% higher estimation of the number of individuals with repeated exposures exceeding the benchmark. The comparisons help to identify and contrast the capabilities of each method and to offer insight regarding implications of method choice. Exposure simulation results are robust to the two population sampling methods evaluated, and are sensitive to the choice of method for simulating longitudinal diaries, particularly when analyzing results for specific microenvironments or for exposures exceeding a benchmark of concern.

Statistical properties of longitudinal time-activity data for use in human exposure modeling

Understanding the longitudinal properties of the time spent in different locations and activities is important in characterizing human exposure to pollutants. The results of a four-season longitudinal time-activity diary study in eight working adults are presented, with the goal of improving the parameterization of human activity algorithms in EPA's exposure modeling efforts. Despite the longitudinal, multi-season nature of the study, participant non-compliance with the protocol over time did not play a major role in data collection. The diversity (D)--a ranked intraclass correlation coefficient (ICC)-- and lag-one autocorrelation (A) statistics of study participants are presented for time spent in outdoor, motor vehicle, residential, and other-indoor locations. Day-type (workday versus non-workday, and weekday versus weekend), season, temperature, and gender differences in the time spent in selected locations and activities are described, and D & A statistics are presented. The overall D and ICC values ranged from approximately 0.08-0.26, while the mean population rank A values ranged from approximately 0.19-0.36. These statistics indicate that intra-individual variability exceeds explained inter-individual variability, and low day-to-day correlations among locations. Most exposure models do not address these behavioral characteristics, and thus underestimate population exposure distributions and subsequent health risks associated with environmental exposures.

Understanding the physical and social contexts of children's nonschool sedentary behavior: an ecological momentary assessment study

BACKGROUND

Research on children's sedentary behavior has relied on recall-based self-report or accelerometer methods, which do not assess the context of such behavior.

PURPOSE

This study used ecological momentary assessment (EMA) to determine where and with whom children's sedentary behavior occurs during their nonschool time.

METHODS

Children (N = 120) ages 9-13 years (51% male, 33% Hispanic) wore mobile phones that prompted surveys (20 total) for 4 days. Surveys measured current activity (eg, exercise, watching TV), physical location (eg, home, outdoors), and social company (eg, family, friends).

RESULTS

Children engaged in a greater percentage of leisure-oriented (eg, watching TV) than productive (eg, reading, doing homework) sedentary behavior (70% vs 30%, respectively). Most of children's sedentary activity occurred at home (85%). Children's sedentary activity took place most often with family members (58%). Differences in physical context of sedentary behavior were found for older vs. younger children (P < .05). Type of sedentary behavior differed by gender, racial/ethnic group, and social context (P < .05).

CONCLUSION

Children may prefer or have greater opportunities to be sedentary in some contexts than others. Research demonstrates the potential for using EMA to capture real-time information about children's sedentary behavior during their nonschool time.

Simulation of longitudinal exposure data with variance-covariance structures based on mixed models

Longitudinal data are important in exposure and risk assessments, especially for pollutants with long half-lives in the human body and where chronic exposures to current levels in the environment raise concerns for human health effects. It is usually difficult and expensive to obtain large longitudinal data sets for human exposure studies. This article reports a new simulation method to generate longitudinal data with flexible numbers of subjects and days. Mixed models are used to describe the variance-covariance structures of input longitudinal data. Based on estimated model parameters, simulation data are generated with similar statistical characteristics compared to the input data. Three criteria are used to determine similarity: the overall mean and standard deviation, the variance components percentages, and the average autocorrelation coefficients. Upon the discussion of mixed models, a simulation procedure is produced and numerical results are shown through one human exposure study. Simulations of three sets of exposure data successfully meet above criteria. In particular, simulations can always retain correct weights of inter- and intrasubject variances as in the input data. Autocorrelations are also well followed. Compared with other simulation algorithms, this new method stores more information about the input overall distribution so as to satisfy the above multiple criteria for statistical targets. In addition, it generates values from numerous data sources and simulates continuous observed variables better than current data methods. This new method also provides flexible options in both modeling and simulation procedures according to various user requirements.

Individual dose and exposure of Italian children to ultrafine particles

Time-activity patterns and the airborne pollutant concentrations encountered by children each day are an important determinant of individual exposure to airborne particles. This is demonstrated in this work by using hand-held devices to measure the real-time individual exposure of more than 100 children aged 8-11 years to particle number concentrations and average particle diameter, as well as alveolar and tracheobronchial deposited surface area concentration. A GPS-logger and activity diaries were also used to give explanation to the measurement results. Children were divided in three sample groups: two groups comprised of urban schools (school time from 8:30 am to 1:30 pm) with lunch and dinner at home, and the third group of a rural school with only dinner at home. The mean individual exposure to particle number concentration was found to differ between the three groups, ranging from 6.2 × 10(4)part.cm(-3) for children attending one urban school to 1.6 × 10(4)part.cm(-3) for the rural school. The corresponding daily alveolar deposited surface area dose varied from about 1.7 × 10(3)mm(2) for urban schools to 6.0 × 10(2)mm(2) for the rural school. For all of the children monitored, the lowest particle number concentrations are found during sleeping time and the highest were found during eating time. With regard to alveolar deposited surface area dose, a child's home was the major contributor (about 70%), with school contributing about 17% for urban schools and 27% for the rural school. An important contribution arises from the cooking/eating time spent at home, which accounted for approximately 20% of overall exposure, corresponding to more than 200 mm(2). These activities represent the highest dose received per time unit, with very high values also encountered by children with a fireplace at home, as well as those that spend considerable time stuck in traffic jams.

Childhood exposure to fine particulate matter and black carbon and the development of new wheeze between ages 5 and 7 in an urban prospective cohort

BACKGROUND

While exposures to urban fine particulate matter (PM(2.5)) and soot-black carbon (soot-BC) have been associated with asthma exacerbations, there is limited evidence on whether these pollutants are associated with the new development of asthma or allergy among young inner city children. We hypothesized that childhood exposure to PM(2.5) and the soot-BC component would be associated with the report of new wheeze and development of seroatopy in an inner city birth cohort.

METHODS

As part of the research being conducted by the Columbia Center of Children's Environmental Health (CCCEH) birth cohort study in New York City, two-week integrated residential monitoring of PM(2.5), soot-BC (based on a multi-wavelength integrating sphere method), and modified absorption coefficient (Abs*; based on the smoke stain reflectometer) was conducted between October 2005 and May 2011 for 408 children at ages 5-6 years old. Residential monitoring was repeated 6 months later (n=262) to capture seasonal variability. New wheeze was identified through the International Study of Asthma and Allergies in Childhood (ISAAC) questionnaires during up to 3 years of follow-up and compared to a reference group that reported never wheeze, remitted wheeze, or persistent wheeze. Specific immunoglobulin (Ig) E against cockroach, mouse, cat, and dust mite and total IgE levels was measured in sera at ages 5 and 7 years.

RESULTS

PM(2.5), soot-BC, and Abs* measured at the first visit were correlated moderately with those at the second visit (Pearson r>0.44). Using logistic regression models, a positive association between PM(2.5) and new wheeze was found with adjusted odds ratio [95% confidence intervals] of 1.51 [1.05-2.16] per interquartile range (IQR). Positive but non-significant association was found between the development of new wheeze and soot-BC and (OR 1.40 [0.96-2.05]), and Abs* (OR 1.57 [0.91-2.68]); Significantly positive associations were found between air pollutant measurements and new wheeze when restricting to those participants with repeat home indoor measurements 6 months apart. Associations between pollutants and IgE levels were not detected.

CONCLUSIONS

Our findings suggest that childhood exposure to indoor air pollution, much of which penetrated readily from outdoor sources, may contribute to the development of wheeze symptoms among children ages 5 to 7 years.

Activity pattern of a selected group of school occupants and their family members in Helsinki-Finland

The daily time-spent in different environments is an important factor in calculation of personal exposure to air pollutants. Despite this importance, the amount of research done on this topic is rather limited, especially in North Europe where the climate is rather cold. In this study, we gathered detailed information via a standard questionnaire to report the residence time and place of 167 subjects (between 2 and 93 years old) lived in Helsinki during three time periods in winter and spring 2009. Subjects spent 81%-92% of their time indoors and up to ~15% of their time outdoors. The daily time-spent in different environments was affected by several factors: ambient temperature, type of day (workday or weekend/holiday), gender, and age. Therefore, the differences occur individually and can be explained by these factors. For example, subjects spent more time at home on weekends than workdays because obviously the majority of our subjects did not have work on weekends. The time-spent at kindergarten/school/work increased with age until retirement. Females spent more time at home than males. After all, the activity pattern found in this study is rather similar to those previously reported in Germany and North America.

Assessing the social and physical contexts of children's leisure-time physical activity: an ecological momentary assessment study

PURPOSE

To use Ecological Momentary Assessment with mobile phones to describe where and with whom children's leisure-time physical activity occurs.

DESIGN

Repeated assessments across 4 days (Friday-Monday) during nonschool time (20 total).

SETTING

Chino, California, and surrounding communities.

SUBJECTS

Primarily low to middle income children (N =121; aged 9-13 years; x¯=11.0 years, SD =1.2 years; 52% male, 38% Hispanic/Latino).

MEASURES

Electronic surveys measured current activity (e.g., active play/sports/exercise, watching TV/movies), social company (e.g., family, friends, alone), physical location (e.g., home, outdoors, school), and other perceived contextual features (e.g., safety, traffic, vegetation, distance from home). Analysis . Multilevel linear and multinomial logistic regression.

RESULTS

Most of children's physical activity occurred outdoors (away from home) (42%), followed by at home (indoors) (30%), front/backyard (at home) (8%), someone else's house (8%), at a gym/recreation center (3%), and other locations (9%). Children's physical activity took place most often with multiple categories of people together (e.g., friends and family) (39%), followed by family members only (32%), alone (15%), and with friends only (13%). Age, weight status, income, and racial/ethnic differences in physical activity contexts were observed.

CONCLUSIONS

The most frequently reported contexts for children's leisure time physical activity were outdoors and with family members and friends together.

Quantifying children's aggregate (dietary and residential) exposure and dose to permethrin: application and evaluation of EPA's probabilistic SHEDS-Multimedia model

Reliable, evaluated human exposure and dose models are important for understanding the health risks from chemicals. A case study focusing on permethrin was conducted because of this insecticide's widespread use and potential health effects. SHEDS-Multimedia was applied to estimate US population permethrin exposures for 3- to 5-year-old children from residential, dietary, and combined exposure routes, using available dietary consumption data, food residue data, residential concentrations, and exposure factors. Sensitivity and uncertainty analyses were conducted to identify key factors, pathways, and research needs. Model evaluation was conducted using duplicate diet data and biomonitoring data from multiple field studies, and comparison to other models. Key exposure variables were consumption of spinach, lettuce, and cabbage; surface-to-skin transfer efficiency; hand mouthing frequency; fraction of hand mouthed; saliva removal efficiency; fraction of house treated; and usage frequency. For children in households using residential permethrin, the non-dietary exposure route was most important, and when all households were included, dietary exposure dominated. SHEDS-Multimedia model estimates compared well to real-world measurements data; this exposure assessment tool can enhance human health risk assessments and inform children's health research. The case study provides insights into children's aggregate exposures to permethrin and lays the foundation for a future cumulative pyrethroid pesticides risk assessment.

Neurobehavioral effects of exposure to traffic-related air pollution and transportation noise in primary schoolchildren

BACKGROUND

Children living close to roads are exposed to both traffic noise and traffic-related air pollution. There are indications that both exposures affect cognitive functioning. So far, the effects of both exposures have only been investigated separately.

OBJECTIVES

To investigate the relationship between air pollution and transportation noise on the cognitive performance of primary schoolchildren in both the home and school setting.

METHODS

Data acquired within RANCH from 553 children (aged 9-11 years) from 24 primary schools were analysed using multilevel modelling with adjustment for a range of socio-economic and life-style factors.

RESULTS

Exposure to NO(2) (which is in urban areas an indicator for traffic-related air pollution) at school was statistically significantly associated with a decrease in the memory span length measured during DMST (χ(2)=6.8, df=1, p=0.01). This remained after additional adjustment for transportation noise. Statistically significant associations were observed between road and air traffic noise exposure at school and the number of errors made during the 'arrow' (χ(2)=7.5, df=1, p=0.006) and 'switch' (χ(2)=4.8, df=1, p=0.028) conditions of the SAT. This remained after adjustment for NO(2). No effects of air pollution exposure or transportation noise exposure at home were observed. Combined exposure of air pollution and road traffic noise had a significant effect on the reaction times measured during the SRTT and the 'block' and the 'arrow' conditions of the SAT.

CONCLUSIONS

Our results provide some support that prolonged exposure to traffic-related air pollution as well as to noise adversely affects cognitive functioning.

Passive sampling methods to determine household and personal care product use

Traditionally, use of household and personal care products has been collected through questionnaires, which is very time consuming, a burden on participants, and prone to recall bias. As part of the SUPERB Project (Study of Use of Products and Exposure-Related Behaviors), a novel platform was developed using bar codes to quickly and reliably determine what household and personal care products people have in their homes and determine the amount used over a 1-week period. We evaluated the acceptability and feasibility of our methodology in a longitudinal field study that included 47 California households, 30 with young children and 17 with an older adult. Acceptability was defined by refusal rates; feasibility was evaluated in terms of readable bar codes, useful product information in our database for all readable barcodes, and ability to find containers at both the start and end of the week. We found 63% of personal care products and 87% of the household care products had readable barcodes with 47% and 41% having sufficient data for product identification, respectively and secondly, the amount used could be determined most of the time. We present distributions for amount used by product category and compare inter- and intra-person variability. In summary, our method appears to be appropriate, acceptable, and useful for gathering information related to potential exposures stemming from the use of personal and household care products. A very low drop-out rate suggests that this methodology can be useful in longitudinal studies of exposure to household and personal care products.

Longitudinal variability of time-location/activity patterns of population at different ages: a longitudinal study in California

BACKGROUND

Longitudinal time-activity data are important for exposure modeling, since the extent to which short-term time-activity data represent long-term activity patterns is not well understood. This study was designed to evaluate longitudinal variations in human time-activity patterns.

METHOD

We report on 24-hour recall diaries and questionnaires collected via the internet from 151 parents of young children (mostly under age 55), and from 55 older adults of ages 55 and older, for both a weekday and a weekend day every three months over an 18-month period. Parents also provided data for their children. The self-administrated diary and questionnaire distinguished ~30 frequently visited microenvironments and ~20 activities which we selected to represent opportunities for exposure to toxic environmental compounds. Due to the non-normal distribution of time-location/activity data, we employed generalized linear mixed-distribution mixed-effect models to examine intra- and inter-individual variations. Here we describe variation in the likelihood of and time spent engaging in an activity or being in a microenvironment by age group, day-type (weekday/weekend), season (warm/cool), sex, employment status, and over the follow-up period.

RESULTS

As expected, day-type and season influence time spent in many location and activity categories. Longitudinal changes were also observed, e.g., young children slept less with increasing follow-up, transit time increased, and time spent on working and shopping decreased during the study, possibly related to human physiological changes with age and changes in macro-economic factors such as gas prices and the economic recession.

CONCLUSIONS

This study provides valuable new information about time-activity assessed longitudinally in three major age groups and greatly expands our knowledge about intra- and inter-individual variations in time-location/activity patterns. Longitudinal variations beyond weekly and seasonal patterns should be taken into account in simulating long-term time-activity patterns in exposure modeling.

The role of annoyance in the relation between transportation noise and children's health and cognition

On the basis of this study it cannot be ruled out that the appraisal of the noise affects the association between air and road traffic noise exposure and children's health and cognition. However, the conclusion is limited due to the relatively small group of annoyed children, which may have influenced our group comparisons. Furthermore, the observed relation between annoyance and perceived health is possibly biased due to the fact that both were measured within the same questionnaire. These are the main conclusions of a cross-sectional multi-center study carried out among 2,844 schoolchildren (age 9-11 years) attending 89 primary schools around three European airports. The aim was to investigate how annoyance affects the relation between air and road traffic noise exposure and children's health and cognition. Different, sometimes competing, working mechanisms of how noise affects children's health are suggested. Some effects are supposed to be precipitated through (chronic) stress, while others may arise directly. There is still no theory that can adequately account for the circumstances in which noise will affect cognitive performance.

Childhood incident asthma and traffic-related air pollution at home and school

BACKGROUND

Traffic-related air pollution has been associated with adverse cardiorespiratory effects, including increased asthma prevalence. However, there has been little study of effects of traffic exposure at school on new-onset asthma.

OBJECTIVES

We evaluated the relationship of new-onset asthma with traffic-related pollution near homes and schools.

METHODS

Parent-reported physician diagnosis of new-onset asthma (n = 120) was identified during 3 years of follow-up of a cohort of 2,497 kindergarten and first-grade children who were asthma- and wheezing-free at study entry into the Southern California Children's Health Study. We assessed traffic-related pollution exposure based on a line source dispersion model of traffic volume, distance from home and school, and local meteorology. Regional ambient ozone, nitrogen dioxide (NO(2)), and particulate matter were measured continuously at one central site monitor in each of 13 study communities. Hazard ratios (HRs) for new-onset asthma were scaled to the range of ambient central site pollutants and to the residential interquartile range for each traffic exposure metric.

RESULTS

Asthma risk increased with modeled traffic-related pollution exposure from roadways near homes [HR 1.51; 95% confidence interval (CI), 1.25-1.82] and near schools (HR 1.45; 95% CI, 1.06-1.98). Ambient NO(2) measured at a central site in each community was also associated with increased risk (HR 2.18; 95% CI, 1.18-4.01). In models with both NO(2) and modeled traffic exposures, there were independent associations of asthma with traffic-related pollution at school and home, whereas the estimate for NO(2) was attenuated (HR 1.37; 95% CI, 0.69-2.71).

CONCLUSIONS

Traffic-related pollution exposure at school and homes may both contribute to the development of asthma.

Characterization of particle number concentrations and PM2.5 in a school: influence of outdoor air pollution on indoor air

BACKGROUND, AIM AND SCOPE

The impact of air pollution on school children's health is currently one of the key foci of international and national agencies. Of particular concern are ultrafine particles which are emitted in large quantities, contain large concentrations of toxins and are deposited deeply in the respiratory tract.

MATERIALS AND METHODS

In this study, an intensive sampling campaign of indoor and outdoor airborne particulate matter was carried out in a primary school in February 2006 to investigate indoor and outdoor particle number (PN) and mass concentrations (PM(2.5)), and particle size distribution, and to evaluate the influence of outdoor air pollution on the indoor air.

RESULTS

For outdoor PN and PM(2.5), early morning and late afternoon peaks were observed on weekdays, which are consistent with traffic rush hours, indicating the predominant effect of vehicular emissions. However, the temporal variations of outdoor PM(2.5) and PN concentrations occasionally showed extremely high peaks, mainly due to human activities such as cigarette smoking and the operation of mower near the sampling site. The indoor PM(2.5) level was mainly affected by the outdoor PM(2.5) (r = 0.68, p < 0.01), whereas the indoor PN concentration had some association with outdoor PN values (r = 0.66, p < 0.01) even though the indoor PN concentration was occasionally influenced by indoor sources, such as cooking, cleaning and floor polishing activities. Correlation analysis indicated that the outdoor PM(2.5) was inversely correlated with the indoor to outdoor PM(2.5) ratio (I/O ratio; r = -0.49, p < 0.01), while the indoor PN had a weak correlation with the I/O ratio for PN (r = 0.34, p < 0.01).

DISCUSSION AND CONCLUSIONS

The results showed that occupancy did not cause any major changes to the modal structure of particle number and size distribution, even though the I/O ratio was different for different size classes. The I/O curves had a maximum value for particles with diameters of 100-400 nm under both occupied and unoccupied scenarios, whereas no significant difference in I/O ratio for PM(2.5) was observed between occupied and unoccupied conditions. Inspection of the size-resolved I/O ratios in the preschool centre and the classroom suggested that the I/O ratio in the preschool centre was the highest for accumulation mode particles at 600 nm after school hours, whereas the average I/O ratios of both nucleation mode and accumulation mode particles in the classroom were much lower than those of Aitken mode particles.

RECOMMENDATIONS AND PERSPECTIVES

The findings obtained in this study are useful for epidemiological studies to estimate the total personal exposure of children, and to develop appropriate control strategies for minimising the adverse health effects on school children.

Neurobehavioral effects of transportation noise in primary schoolchildren: a cross-sectional study

BACKGROUND

Due to shortcomings in the design, no source-specific exposure-effect relations are as yet available describing the effects of noise on children's cognitive performance. This paper reports on a study investigating the effects of aircraft and road traffic noise exposure on the cognitive performance of primary schoolchildren in both the home and the school setting.

METHODS

Participants were 553 children (age 9-11 years) attending 24 primary schools around Schiphol Amsterdam Airport. Cognitive performance was measured by the Neurobehavioral Evaluation System (NES), and a set of paper-and-pencil tests. Multilevel regression analyses were applied to estimate the association between noise exposure and cognitive performance, accounting for demographic and school related confounders.

RESULTS

Effects of school noise exposure were observed in the more difficult parts of the Switching Attention Test (SAT): children attending schools with higher road or aircraft noise levels made significantly more errors. The correlational pattern and factor structure of the data indicate that the coherence between the neurobehavioral tests and paper-and-pencil tests is high.

CONCLUSIONS

Based on this study and previous scientific literature it can be concluded that performance on simple tasks is less susceptible to the effects of noise than performance on more complex tasks.

Time-location patterns of a population living in an air pollution hotspot

This study characterized the time-location pattern of 107 residents living in air pollution hotspots, the Waterfront South and Copewood/Davis Streets communities in Camden, NJ. Most residents in the two communities are minority and impoverished individuals. Results showed that employment status played the fundamental role in determining time-location patterns of this study population, and the variations of time-location pattern by season and by day-type were partially attributed to employment status. Compared to the National Human Activity Pattern Survey, the Camden cohort spent significantly more time outdoors (3.8 hours versus 1.8 hours) and less time indoors (19.4 hours versus 20.9 hours) than the general US population, indicating a higher risk of exposure to ambient air pollution for the Camden cohort. The findings of the study are important for understanding exposure routes and sources for the socioeconomically disadvantaged subgroup and ultimately help develop effective strategies to reduce community exposure to ambient air pollution in "hotspots".

Contribution to volatile organic compound exposures from time spent in stores and restaurants and bars

Many people spend time in stores and restaurants, yet there has been little investigation of the influence of these microenvironments on personal exposure. Relative to the outdoors, transportation, and the home, these microenvironments have high concentrations of several volatile organic compounds (VOCs). We developed a stochastic model to examine the effect of VOC concentrations in these microenvironments on total personal exposure for (1) non-smoking adults working in offices who spend time in stores and restaurants or bars and (2) non-smoking adults who work in these establishments. We also compared the effect of working in a smoking versus non-smoking restaurant or bar. Input concentrations for each microenvironment were developed from the literature whereas time activity inputs were taken from the National Human Activity Patterns Survey. Time-averaged exposures were simulated for 5000 individuals over a weeklong period for each analysis. Mean contributions to personal exposure from non-working time spent in stores and restaurants or bars range from <5% to 20%, depending on the VOC and time-activity patterns. At the 95th percentile of the distribution of the proportion of personal exposure attributable to time spent in stores and restaurants or bars, these microenvironments can be responsible for over half of a person's total exposure to certain VOCs. People working in restaurants or bars where smoking is allowed had the highest fraction of exposure attributable to their workplace. At the median, people who worked in stores or restaurants tended to have 20-60% of their total exposures from time spent at work. These results indicate that stores and restaurants can be large contributors to personal exposure to VOCs for both workers in those establishments and for a subset of people who visit these places, and that incorporation of these non-residential microenvironments can improve models of personal exposure distributions.

Intra- and inter-individual variability in location data for two U.S. health-compromised elderly cohorts

This study provides descriptive statistical data on daily time spent in three locations of exposure assessment interest for two panel studies of health-compromised elderly individuals >65-year-old having multiple days of human activity data. The panel studies include individuals living in Los Angeles (CA) and Baltimore (MD) in various housing types. Three general locations are evaluated: outdoors, in vehicles, and total indoors. Of particular interest is providing information regarding the within- and between-individual variability in the time use data for the three locations. The data are analyzed using non-parametric statistics and alternative statistical models. Within and between variability are evaluated using intraclass correlation coefficients (ICCs); daily "lag-one" autocorrelation coefficients are also provided for the two samples. There were significant gender differences for selected seasonal and/or day-of-the-week metrics for: (1) outdoor time in Los Angeles, but not in Baltimore, and (2) in-vehicle time in both areas. Elderly women spent more time in these locations than similarly aged men. The ICC statistic indicates that most of the variability in the time spent in the three locations is due to intraindividual variability rather than to inter-individual variability. The results indicate that US Environmental Protection Agency should consider gender, day-of-the-week, and time-of-day data in its exposure modeling of daily activities undertaken by the health-compromised elderly population.

A new method of longitudinal diary assembly for human exposure modeling

Human exposure time-series modeling requires longitudinal time-activity diaries to evaluate the sequence of concentrations encountered, and hence, pollutant exposure for the simulated individuals. However, most of the available data on human activities are from cross-sectional surveys that typically sample 1 day per person. A procedure is needed for combining cross-sectional activity data into multiple-day (longitudinal) sequences that can capture day-to-day variability in human exposures. Properly accounting for intra- and interindividual variability in these sequences can have a significant effect on exposure estimates and on the resulting health risk assessments. This paper describes a new method of developing such longitudinal sequences, based on ranking 1-day activity diaries with respect to a user-chosen key variable. Two statistics, "D" and "A", are targeted. The D statistic reflects the relative importance of within- and between-person variance with respect to the key variable. The A statistic quantifies the day-to-day (lag-one) autocorrelation. The user selects appropriate target values for both D and A. The new method then stochastically assembles longitudinal diaries that collectively meet these targets. On the basis of numerous simulations, the D and A targets are closely attained for exposure analysis periods >30 days in duration, and reasonably well for shorter simulation periods. Longitudinal diary data from a field study suggest that D and A are stable over time, and perhaps over cohorts as well. The new method can be used with any cohort definitions and diary pool assignments, making it easily adaptable to most exposure models. Implementation of the new method in its basic form is described, and various extensions beyond the basic form are discussed.

Urban road-traffic noise and blood pressure and heart rate in preschool children

Night time noise exposure has very rarely been used in previous studies on the relationship between community noise and children's blood pressure, although children spend a larger part of their night time sleeping at home than adults. For this reason, we focused on night time noise exposure at children's residences and daytime noise at kindergartens. The aim of this study was to investigate the effects of urban road-traffic noise on children's blood pressure and heart rate. A cross-sectional study was performed on 328 preschool children (174 boys and 154 girls) aged 3-7 years, who attended 10 public kindergartens in Belgrade. Equivalent noise levels (Leq) were measured during night in front of children's residences and during day in front of kindergartens. A residence was regarded noisy if Leq exceeded 45 dB (A) during night and quiet if the Leq was < or =45 dB (A). Noisy and quiet kindergartens were those with daily Leq>60 dB (A) and < or =60 dB (A), respectively. Children's blood pressure was measured with mercury sphygmomanometer. Heart rate was counted by radial artery palpitation for 1 min. The prevalence of children with hypertensive values of blood pressure was 3.96% (13 children, including 8 boys and 5 girls) with higher prevalence in children from noisy residences (5.70%), compared to children from quiet residences (1.48%). The difference was borderline significant (p=0.054). Systolic pressure was significantly higher (5 mm Hg on average) among children from noisy residences and kindergartens, compared to children from both quiet environments (p<0.01). Heart rate was significantly higher (2 beats/min on average) in children from noisy residences, compared to children from quiet residences (p<0.05). Multiple regression, after allowing for possible confounders, showed a significant correlation between noise exposure and children's systolic pressure (B=1.056; p=0.009).

Mapping the social and physical contexts of physical activity across adolescence using ecological momentary assessment

BACKGROUND

Research has sought to understand how environmental factors influence adolescent physical activity, yet little is known about where and with whom adolescents are physically active.

PURPOSE

This study used electronic ecological momentary assessment (e.EMA) to map the social and physical contexts of exercise and walking across adolescence. Differences in physical activity contexts by gender, grade in school, day of the week, and season were examined.

METHODS

Twice a year between 9th and 12th grade, 502 adolescents (51% female) of mixed ethnicity (55% White) participated in 4-day e.EMA intervals (Thursday-Sunday) where their primary activity (e.g., exercise, TV, homework), social company (e.g., friends, family, class), and physical location (e.g., home, school, outdoors) were assessed every 30 (+/-10) min during waking hours.

RESULTS

Overall, greater proportions of exercise and walking were reported with friends, outdoors, and at school. However, boys were more likely to report exercising and walking in outdoor locations than girls. Exercising with classmates, family, and at school decreased across high school. Walking with family, friends, and outdoors also decreased. On weekdays compared to weekends, students reported a greater proportion of their exercise and walking at school. Students were more likely to report exercising and walking outdoors in the fall and the spring than in the winter.

CONCLUSION

e.EMA showed that the social and physical contexts of adolescent exercise and walking vary as a function of gender, grade in school, day of the week, and season. Understanding the contexts of physical activity during the high school years can be helpful in designing interventions during adolescence.

Error and bias in determining exposure potential of children at school locations using proximity-based GIS techniques

BACKGROUND

The widespread availability of powerful tools in commercial geographic information system (GIS) software has made address geocoding a widely employed technique in spatial epidemiologic studies.

OBJECTIVE

The objective of this study was to determine the effect of the positional error in geocoding on the analysis of exposure to traffic-related air pollution of children at school locations.

METHODS

For a case study of Orange County, Florida, we determined the positional error of geocoding of school locations through comparisons with a parcel database and digital orthophotography. We used four different geocoding techniques for comparison to establish the repeatability of geocoding, and an analysis of proximity to major roads to determine bias and error in environmental exposure assessment.

RESULTS

RESULTS INDICATE THAT THE POSITIONAL ERROR IN GEOCODING OF SCHOOLS IS VERY SUBSTANTIAL: We found that the 95% root mean square error was 196 m using street centerlines, 306 m using TIGER roads, and 210 and 235 m for two commercial geocoding firms. We found bias and error in proximity analysis to major roads to be unacceptably large at distances of < 500 m. Bias and error are introduced by lack of positional accuracy and lack of repeatability of geocoding of school locations.

CONCLUSIONS

These results suggest that typical geocoding is insufficient for fine-scale analysis of school locations and more accurate alternatives need to be considered.

Indoor time-microenvironment-activity patterns in seven regions of Europe

Personal exposure to environmental substances is largely determined by time-microenvironment-activity patterns while moving across locations or microenvironments. Therefore, time-microenvironment-activity data are particularly useful in modeling exposure. We investigated determinants of workday time-microenvironment-activity patterns of the adult urban population in seven European cities. The EXPOLIS study assessed workday time-microenvironment-activity patterns among a total of 1427 subjects (age 19-60 years) in Helsinki (Finland), Athens (Greece), Basel (Switzerland), Grenoble (France), Milan (Italy), Prague (Czech Republic), and Oxford (UK). Subjects completed time-microenvironment-activity diaries during two working days. We present time spent indoors--at home, at work, and elsewhere, and time exposed to tobacco smoke indoors for all cities. The contribution of sociodemographic factors has been assessed using regression models. More than 90% of the variance in indoor time-microenvironment-activity patterns originated from differences between and within subjects rather than between cities. The most common factors that were associated with indoor time-microenvironment-activity patterns, with similar contributions in all cities, were the specific work status, employment status, whether the participants were living alone, and whether the participants had children at home. Gender and season were associated with indoor time-microenvironment-activity patterns as well but the effects were rather heterogeneous across the seven cities. Exposure to second-hand tobacco smoke differed substantially across these cities. The heterogeneity of these factors across cities may reflect city-specific characteristics but selection biases in the sampled local populations may also explain part of the findings. Determinants of time-microenvironment-activity patterns need to be taken into account in exposure assessment, epidemiological analyses, exposure simulations, as well as in the development of preventive strategies that focus on time-microenvironment-activity patterns that ultimately determine exposures.

Noise exposure and children's blood pressure and heart rate: the RANCH project

BACKGROUND

Conclusions that can be drawn from earlier studies on noise and children's blood pressure are limited due to inconsistent results, methodological problems, and the focus on school noise exposure.

OBJECTIVES

To investigate the effects of aircraft and road traffic noise exposure on children's blood pressure and heart rate.

METHODS

Participants were 1283 children (age 9-11 years) attending 62 primary schools around two European airports. Data were pooled and analysed using multilevel modelling. Adjustments were made for a range of socioeconomic and lifestyle factors.

RESULTS

After pooling the data, aircraft noise exposure at school was related to a statistically non-significant increase in blood pressure and heart rate. Aircraft noise exposure at home was related to a statistically significant increase in blood pressure. Aircraft noise exposure during the night at home was positively and significantly associated with blood pressure. The findings differed between the Dutch and British samples. Negative associations were found between road traffic noise exposure and blood pressure, which cannot be explained.

CONCLUSION

On the basis of this study and previous scientific literature, no unequivocal conclusions can be drawn about the relationship between community noise and children's blood pressure.

Improving environmental exposure analysis using cumulative distribution functions and individual geocoding

Background

Assessments of environmental exposure and health risks that utilize Geographic Information Systems (GIS) often make simplifying assumptions when using: (a) one or more discrete buffer distances to define the spatial extent of impacted regions, and (b) aggregated demographic data at the level of census enumeration units to derive the characteristics of the potentially exposed population. A case-study of school children in Orange County, Florida, is used to demonstrate how these limitations can be overcome by the application of cumulative distribution functions (CDFs) and individual geocoded locations. Exposure potential for 159,923 school children was determined at the childrens' home residences and at school locations by determining the distance to the nearest gasoline station, stationary air pollution source, and industrial facility listed in the Toxic Release Inventory (TRI). Errors and biases introduced by the use of discrete buffer distances and data aggregation were examined.

Results

The use of discrete buffers distances in proximity-based exposure analysis introduced substantial bias in terms of determining the potentially exposed population, and the results are strongly dependent on the choice of buffer distance(s). Comparisons of exposure potential between home and school locations indicated that different buffer distances yield different results and contradictory conclusions. The use of a CDF provided a much more meaningful representation and is not based on the a-priori assumption that any particular distance is more relevant than another. The use of individual geocoded locations also provided a more accurate characterization of the exposed population and allowed for more reliable comparisons among sub-groups. In the comparison of children's home residences and school locations, the use of data aggregated at the census block group and tract level introduced variability as well as bias, leading to incorrect conclusions as to whether exposure potential was higher at school or at home.

Conclusion

The use of CDFs in distance-based environmental exposure assessment provides more robust results than the use of discrete buffer distances. Unless specific circumstances warrant the use of discrete buffer distances, their applcation should be discouraged in favor of CDFs. The use of aggregated data at the census tract or block group level introduces substantial bias in environmental exposure assessment, which can be reduced through individual geocoding. The use of aggregation should be minimized when individual-level data are available. Existing GIS analysis techniques are well suited to determine CDFs as well as reliably geocode large datasets, and computational issues do not present a barrier for their more widespread use in environmental exposure and risk assessment.

A probabilistic arsenic exposure assessment for children who contact CCA-treated playsets and decks, Part 1: Model methodology, variability results, and model evaluation

Concerns have been raised regarding the safety of young children who may contact arsenic residues while playing on and around chromated copper arsenate (CCA)-treated wood playsets and decks. Although CCA registrants voluntarily canceled the production of treated wood for residential use in 2003, the potential for exposure from existing structures and surrounding soil still poses concerns. The EPA's Office of Research and Development developed and applied the probabilistic Stochastic Human Exposure and Dose Simulation model for wood preservatives (SHEDS-Wood) to estimate children's absorbed dose of arsenic from CCA. Skin contact with, and nondietary ingestion of, arsenic in soil and wood residues were considered for the population of children in the United States who frequently contact CCA-treated wood playsets and decks. Model analyses were conducted to assess the range in population estimates and the impact of potential mitigation strategies such as the use of sealants and hand washing after play events. The results show predicted central values for lifetime annual average daily dose values for arsenic ranging from 10(-6) to 10(-5) mg/kg/day, with predicted 95th percentiles on the order of 10(-5) mg/kg/day. There were several orders of magnitude between lower and upper percentiles. Residue ingestion via hand-to-mouth contact was determined to be the most significant exposure route for most scenarios. Results of several alternative scenarios were similar to baseline results, except for the scenario with greatly reduced residue concentrations through hypothetical wood sealant applications; in this scenario, exposures were lower, and the soil ingestion route dominated. SHEDS-Wood estimates are typically consistent with, or within the range of, other CCA exposure models.