Soil Ingestion Distributions for Monte Carlo Risk Assessment in Children

Monte Carlo environmental risk assessment requires estimates of the exposure distributions. An exposure of principal concern is often soil ingestion among children. We estimate the long-term (annual) average soil ingestion exposure distribution using daily soil ingestion estimates from children who participated in a mass-balance study at Anaconda, MT. The estimated distribution is accompanied by uncertainty estimates. The estimates take advantage of developing knowledge about bias in soil ingestion estimates and are robust. The estimates account for small particle size soil, use the median trace element estimate for subject days, account for the small sample variance of the median estimates, and use best linear unbiased predictors to estimate the cumulative long term soil ingestion distribution. Bootstrapping is used to estimate the uncertainty of the distribution estimates. The median soil ingestion is estimated as 24?mg/d (sd = 4?mg/d), with the 95 percentile soil ingestion estimated as 91?mg/d (sd = 16.6?mg/d). Strategies are discussed for use of these estimates in Monte Carlo risk assessment.     

Soil ingestion estimates for use in site evaluations based on the best tracer method

This paper develops a novel methodology, the Best Tracer method (BTM), that substantially overcomes the principal limitations (intertracer inconsistencies, and poor precision of recovery) of estimating soil ingestion by specific soil‐based tracers in massbalance studies. The BTM incorporates a biological and statistical framework that improves precision of recovery of tracer estimates, markedly reducing input‐output misalignment error resulting from a lack of correspondence between food tracer input and fecal tracer output.

This method is then used to re‐estimate the soil ingestion distribution of previously published soil ingestion estimates from two children studies (Calabrese et al. 1989; Davis et al., 1990) and one adult study (Calabrese et al., 1990). Revised estimates of soil ingestion are provided for each study. In addition, the results from the two children's studies are combined to form a single estimate of the soil ingestion distribution. These collective findings result in more reliable quantitative estimates of soil ingestion than trace element specific estimates, as well as providing improved understanding of current published soil ingestion studies, and improved methods that will enhance the design and interpretation of future soil ingestion studies.

With respect to children, the data indicate that the Calabrese et al. (1989) study provides the most reliable estimates of soil ingestion based on the estimated precision of recovery. However, estimates for the combined data of the Calabrese et al. (1989) and Davis et al. (1990) studies include all available children's data from mass balance studies, and thus provide more robust estimates. The collective data suggest that the median child in these studies ingested 30–40 mg/day of soil, while the upper 95% estimate is approximately 200 mg/day. Current data are insufficient to distinguish the children's soil ingestion distribution from that of adults. The revised and improved estimates of soil ingestion for children and adults have important implications for contaminant exposure estimates used in site evaluation risk assessment procedures.     

A Guide to Interpreting Soil Ingestion Studies. 2. Qualitative and Quantitative Evidence of Soil Ingestion

Abstract

Four major studies have attempted to qualitatively and quantitatively assess the extent of soil ingestion in children using the soil tracer methodology. The validity of the estimates of soil ingestion of each study was reevaluated in light of the inherent strengths and limitations of study design and/or execution as well as via a novel methodology to estimate the soil recovery variance of each tracer which then lead to the estimation of soil ingestion detection limits of each tracer for studies performing mass-balance analyses. Based on these analyses it is concluded that the Binder et al. (1986) and Van Wijnen et al. (1990) studies provide no convincing evidence to support qualitative and quantitative estimates of soil ingestion due to inherent limitations of their respective study designs. The Davis et al. (1990) and Calabrese et al. (1989) studies displayed convincing qualitative evidence of soil ingestion. However, the results indicate that the median soil ingestion estimates of Davis et al. were less reliable than those of Calabrese et al. The range of detection limits vary according to the tracer and the assumption of acceptable precision in recovery estimation. The minimum detection level of soil ingestion in children in the Calabrese et al. study with a variance in recovery of 100% ± 20% was 16 mg day^?1 based on Zr.

These findings are of particular regulatory significance since they provide: (1) a method of assessing the level of detection inherent in soil ingestion studies, (2) a reevaluation of the major soil ingestion studies in light of new methodology, and (3) guidance for future studies so that detection capacity can now be included in the presentation of study findings.     

Methodological Considerations in Soil Ingestion Estimation

Abstract

Methodological considerations play an important role in forming population estimates of soil ingestion in children. Two important areas of controversy are the hypothesized log-normal distribution of ingested soil and the identificatbn and appropriateness of methods for handling outliers. Each of these issues is discussed in the context of data collected on soil ingestion in Amherst, Massachusetts. Non-parametric methods are recommended as most suitable and appropriate for analysis of soil ingestion studies.     

Revisiting Dust and Soil Ingestion Rates Based on Hand-to-Mouth Transfer

Soil ingestion rates calculated using a tracer-based mass balance approach may carry considerable study errors, insensitivities, and “artefacts” of analysis that result in significant uncertainty. These same soil ingestion rates are often used as surrogates for dust ingestion rates. Therefore, a more direct and mechanistic method was developed to estimate soil and dust ingestion rates. The soil and dust ingestion rates were calculated using measures of: particle loading to indoor surfaces; fraction transferred to the hands; hand surface area; fraction of hand surface area that may be mouthed or contact food; frequency of hand-to-mouth events, amount dissolved by saliva; and exposure time. Adapted specifically for the Canadian context, estimated mean indoor dust ingestion rates range from 2.2 mg/d for teenagers to 41 mg/d for toddlers; mean soil ingestion rates range from 1.2 mg/d for seniors to 23 mg/d for children. Combined soil and dust ingestion rates ranged from 3.8 mg/d for seniors to 61 mg/d for toddlers. These ingestion rates are lower than values adopted by most agencies. These ingestion rates are mechanistic, can be adjusted on a site-specific basis, can be modified into an hourly rate and are presented as a more realistic alternative to traditional mass balance approaches.

[Supplementary materials are available for this article. Go to the publisher's online edition of Human and Ecological Risk Assessment to view the free supplementary files.]     

Soil ingestion rates in children identified by parental observation as likely high soil ingesters

Soil ingestion was estimated over seven consecutive days in a soil tracer‐based mass‐balance methodology in 12 children, aged 1 to 3 years. The children had been identified by parents as likely high soil ingesters based on retrospective observation of daily soil ingestion behavior over the past 30 d. While one of the 12 children displayed high soil ingestion (0.5 to 3.05 g/d) on 4 of 7 d, median soil ingestion rates for the 12 children were comparable to those published in other soil ingestion studies of young children selected for studies based on age and not assumed or observed soil ingestion behavior. The lack of ability of parental judgments to predict high soil ingestion rates represents both an important observation and a significant limitation in current methods to efficiently and accurately identify children who ingest high amounts of soil.     

Soil Ingestion Estimates for Children in Anaconda Using Trace Element Concentrations in Different Particle Size Fractions

This investigation assessed the effect of soil particle size on soil ingestion estimates of children residing at a superfund site. Earlier research indicated that wide intertracer variability in soil ingestion estimates are based on soil concentrations with a soil particle size of 0 to 2?µm was markedly reduced when the estimates were based on soil tracer concentrations for a soil particle size of 0-250?µm. The reduced intertracer variation was principally attributed to changes in soil concentrations of only three of the soil tracers (i.e., Ce, La, Nd) which became concentrated in the finer particle size by approximately 2.5 to 4.0-fold. It was hypothesized that the intertracer agreement in soil ingestion estimates may continue to improve if the estimates are based on concentrations of tracers at finer particle sizes assuming that children ingest finer particles and that the above three tracers would continue to be further concentrated in the finer sized soil particles. The principal findings indicate: 1. The soil concentrations of Al, Si, and Ti do not increase at the two finer particle size ranges measured. 2. The soil concentrations of Ce, La, and Nd increased by a factor 2.5 to 4.0 in the 100 to 250?µm particle size range when compared with the 0 to 2?µm particle size range. No further substantial increase in concentration was observed in the 53 to 100 |jm particle size range. 3. The soil ingestion estimates are consistently and markedly changed only between the estimates based in 0 to 2?µm and 100 to 250?µm for Ce, La, and Nd. These changes reduced the intertracer variability in estimating soil ingestion, suggesting that the children eat finer soil particle sizes. 4. Because the particle sizes for all tracers (except Zr) were only modestly affected at the 53 to 100?µm range, it was not possible to confidently resolve the particle size of soil ingested by the children. 5. Residual intertracer variability in soil ingestion estimates based on Ce, La, Nd are likely to be significantly affected by non-food, non-soil sources of these tracers (i.e., source error). 6. Soil ingestion estimates of this study will be more reliable when derived from the finer-sized particles.     

A Guide to Interpreting Soil Ingestion Studies. 1. Development of a Model to Estimate the Soil Ingestion Detection Level of Soil Ingestion Studies

Abstract

This paper provides a model to predict soil ingestion recovery values in soil ingestion studies either retrospectively or prospectively. The predictive equations generated from the model can be used to estimate minimum soil ingestion detection levels from soil ingestion studies which use mass-balance methods. The model is derived from data assessing soil recovery efficiencies in adults using eight different predictive tracer elements. The results constitute a methodology to determine minimum detection levels of soil ingestion, and hence have important regulatory significance.     

Limits in soil ingestion data: The potential for imputing data when soil ingestion estimates are below the detection limit

The formation of a soil ingestion distribution based on pooling data from current soil ingestion studies is appealing. An important issue in forming such a distribution is what to do with negative soil ingestion estimates for particular subjects, because they comprise approximately 10 to 40% of the total soil ingestion estimates. A method of correcting for the negative estimates of soil ingestion is to make use of the “soil ingestion detection limit”;. An appropriate methodology for forming estimates of such detection limits is available in the literature. This paper discusses appropriate use of the existing soil ingestion detection limit methodology in forming a pooled database using current soil ingestion study data. The discussion focuses attention on the current limitations of children's soil ingestion data and potential pitfalls in applying the detection limit model when generating a soil ingestion distribution. In summary, currently available soil ingestion data are not sufficiently reliable to impute individual soil ingestion estimates below the detection limit. Research directed toward identifying and quantifying individual error in soil ingestion estimates is needed to overcome this limitation.     

Prevalence of Soil Mouthing/Ingestion among Healthy Children Aged 1 to 6

Ingestion of non-food items/mouthing behavior results in exposure of children to contaminants in soil/dust. We characterize the prevalence of such behaviors in healthy children. The relative frequency of such behaviors was assessed by parent interviews for 533 children age 1 to 6. Thirty-eight percent of children put soil in their mouths at least monthly, 24% at least weekly, and 11% daily. High-risk behavior decreased quickly for children aged 2 or more, but was still reported at least monthly by 3 to 9% of parents of children up through age 6. Highest outdoor object mouthing rates occur among 1-year-old children, who are reported to play daily in sand/dirt and have generally high levels of mouthing. Such children may have higher soil/dust ingestion and higher exposure to contaminants when soil/dust contains lead or other agents. These high-risk groups may help focus educational interventions and/or risk assessments.     

Blood-sucking bugs as a gentle method for blood-collection in water budget studies using doubly labelled water

During doubly-labelled water (DLW) experiments, blood collection by venous puncture may traumatize animals and consequently affect the animals' behaviour and energy budget. Recent studies have shown that blood-sucking bugs (Triatominae; Heteroptera) can be used instead of conventional needles to obtain blood from animals. In this paper, we validate the bug method in captive nectar-feeding bats, Glossophaga soricina, for water budget analysis by comparing the daily water flux estimated with the DLW method with values measured by an energy balance method. As the mean daily water flux of the DLW method was not significantly deviating from the expected value, blood-sucking bugs may substitute more invasive methods of blood collection in DLW experiments. Based on the DLW estimates, daily energy and water intake rates were calculated and compared to values measured with the energy balance method. The DLW method and the energy balance method yielded on average similar results regarding the daily energy intake (DLW method: 48.8+/-14.2 kJ d(-1) versus energy balance method: 48.1+/-9.9 kJ d(-1)) and daily water intake (DLW method: 13.7+/-2.4 mL d(-1) versus energy balance method: 14.7+/-3.0 mL d(-1)). Based on the calculated water and sugar intake per day, we estimated the sugar concentration of ingested nectar to equal on average 16.2+/-2.4% (mass/mass), which fell close to the measured sugar concentration of 17% (mass/mass) bats fed on during the experiment. We conclude that it is possible to extrapolate mean daily energy and water intake for animal groups, populations and species based on DLW estimates, but due to the large variance of results (low accuracy), it seems inadequate to calculate values for single individuals.     

An Arsenic Exposure Model: Probabilistic Validation Using Empirical Data

This paper describes development of a multi-pathway arsenic exposure model. The model uses information on arsenic concentrations in food, water, soil, and dust, combined with estimates of intake and medium-specific absorption. Urinary arsenic is predicted assuming that 60% of absorbed arsenic is excreted in urine under steady state conditions. Fecal arsenic is predicted assuming all unabsorbed arsenic is excreted in feces. We applied this model at a former copper smelter site. Site specific distributions were available for the following parameters: soil and dust arsenic concentration (geometric mean approximately 100 to 200?ppm and 50 to 100?ppm, respectively); the combined childhood soil and dust ingestion rate (geometric mean of 20?mg/d); soil and dust arsenic relative bioavailability (geometric mean 0.20 and 0.28, respectively); exposure duration; water arsenic concentration; air arsenic concentration; and total arsenic in food. Monte Carlo simulation was used to predict daily arsenic uptake and excretion in urine and feces for children. Predicted urine arsenic levels were less than measured levels (73% to 88% of measured values, depending on region of site). On the other hand, predicted fecal arsenic levels exceeded measured levels by a factor of 1.7 to 4.6. We were able to improve the correspondence between predicted and measured arsenic excretion rates by decreasing the assumed value of the combined soil and dust ingestion rate, and increasing the assumed bioavailability of arsenic in soil and dust.     

Bias and the detection limit model for soil ingestion

The observation that Zr provided an estimate of soil ingestion 80% lower than estimates provided by seven other elements for 1 week in a soil‐pica child in light of the apparent high detection capability for the element resulted in a reexamination of the validity of a current modeling approach advocated for use in estimating soil ingestion detection limits. This examination reveals that for high levels of soil ingestion, possible biases in soil ingestion methodology may be inadequately accounted for in the soil detection limit model. The extent of this limitation is explored and placed in the context of reported limitations in trace element measurement methodology.     

Estimation of Sediment Ingestion Rates Based on Hand-to-Mouth Contact and Incidental Surface Water Ingestion

There is a lack of scientifically justified approaches for assessing sediment ingestion rates of people exposed to contaminated sediments. Consequently, a method was developed to estimate sediment ingestion rates from: (1) hand-to-mouth contact with sediments and (2) incidental ingestion of surface water containing suspended sediments. In the case of hand-to-mouth contact, a mechanistic approach was used based on established principles and assumptions previously used for estimation of soil and dust ingestion rates. A key modification of the approach was to account for greater adherence of sediments to hands as compared to soil and dusts. For estimation of sediment ingestion from surface water contact, a method was developed that considered the unique aspects of suspended sediments. The analysis indicated that hand-to-mouth contact is the dominant pathway for ingestion of sediment. When people use aquatic areas for recreational purposes, the analysis has indicated that mean sediment ingestion rates may range from 18 to 72 mg/h for various receptor age groups. For sites where people spend more than 1 h per day on a consistent basis in direct contact with sediments, the results indicate that sediment ingestion rates may be greater than those typically assumed in Canadian human health risk assessment guidance for soils.     

Simplified methods of estimating daily mean stream water temperature

SUMMARY. 1. It was assumed that the average of twenty-four hourly temperature readings is the'true'daily mean. For a small stream in upper Tees-dale, northern England, estimates of the daily mean were obtained from: (a) The mean of temperature readings taken at regular but less frequent intervals than hourly (twelve, six and three times per day), (b) The daily mid-point (=¹/₂(maximum + minimum)). (c)Spot temperatures at the two times in the day when the daily temperature trace usually crosses the daily mean value. These estimates were then compared with the'true'mean.
2. The accuracy of the estimate of daily mean decreased with reduced frequency of reading but, even at only three readings per day, was always within ±0.5°C of the true value. Consolidation of the daily estimates gave estimates of monthly and annual means within ±0.1°C of the true values.
3. Nearly 96% of estimates of the daily mean based on the daily midpoint were within ±0.5°C of the true value. The estimates showed a small but statistically significant positive bias.
4. Over 80% of estimates of the daily mean based on the'first mean crossing'were within ±0.5°C of the true value and no bias could be shown.
5. Estimation of daily means from temperature at the time of the 'second mean crossing'was relatively complicated and gave less satisfactory results than did the first mean crossing.
6. The daily mid-point and the temperature at the time of the first mean crossing both gave a good general indication of daily mean temperatures. When consolidated to monthly or annual means the estimates were within ±0.25°C and ±0.10°C, respectively, of the true values.     

A Caution for Monte Carlo Risk Assessment of Long Term Exposures based on Short-Term Exposure Study Data

Monte Carlo risk assessments commonly take as input empirical or parametric exposure distributions from specially designed exposure studies. The exposure studies typically have limited duration, since their design is based on statistical and practical factors (such as cost and respondent burden). For these reasons, the exposure period studied rarely corresponds to the biologic exposure period, which we define as the time at risk that is relevant for quantifying exposure that may result in health effects. Both the exposure period studied and the biologic exposure period will often differ from the exposure interval used in a Monte Carlo analysis. Such time period differences, which are often not accounted for, can have dramatic effects on the ultimate risk assessment. When exposure distributions are right skewed and/or follow a lognormal distribution, exposure will usually be overestimated for percentiles above the median by direct use of exposure study empirical data, since biologic exposure periods are generally longer than the exposure periods in exposure assessment studies. We illustrate the effect that biologic exposure time period and response error can have on exposure distributions, using soil ingestion as an example. Beginning with variance components from lognormally distributed soil ingestion estimates, we illustrate the effect of different modeling assumptions, and the sensitivity of the resulting analyses to these assumptions. We develop a strategy for determining appropriate exposure input distributions for soil ingestion, and illustrate this using data on soil ingestion in children.     

Locus-specific heritability estimation via the bootstrap in linkage scans for quantitative trait loci

BACKGROUND/AIMS: In genome-wide linkage analysis of quantitative trait loci (QTL), locus-specific heritability estimates are biased when the original data are used to both localize linkage and estimate effects, due to maximization of the LOD score over the genome. Positive bias is increased by adoption of stringent significance levels to control genome-wide type I error. We propose multi-locus bootstrap resampling estimators for bias reduction in the situation in which linkage peaks at more than one QTL are of interest. METHODS: Bootstrap estimates were based on repeated sample splitting in the original dataset. We conducted simulation studies in nuclear families with 0 to 5 QTLs and applied the methods in a genome-wide analysis of a blood pressure phenotype in extended pedigrees from the Framingham Heart Study (FHS). RESULTS: Compared to na?ve estimates in the original simulation samples, bootstrap estimates had reduced bias and smaller mean squared error. In the FHS pedigrees, the bootstrap yielded heritability estimates as much as 70% smaller than in the original sample. CONCLUSIONS: Because effect estimates obtained in an initial study are typically inflated relative to those expected in an independent replication study, successful replication will be more likely when sample size requirements are based on bias-reduced estimates.     

Do Current Standards of Practice in Canada Measure What is Relevant to Human Exposure at Contaminated Sites? I: A Discussion of Soil Particle Size and Contaminant Partitioning in Soil

Human health risk estimates for sites with contaminated soils are often based on the assumption that the bulk concentration of substances in outdoor soil samples is a reasonable predictor of exposures via incidental soil ingestion, soil particle inhalation, and dermal absorption. Most underlying conceptual models are grossly simplistic, however, when considered in light of (i) biases in the distribution of contaminants across soil particle sizes, (ii) the size range of particles in soils and dusts that is environmentally available, and (iii) factors that influence desorption from particles and uptake into humans. The available studies indicate that contaminant distribution across soil particle size fractions varies widely between different soil types and contaminant delivery mechanisms, and it cannot be assumed that higher masses of contaminants per unit mass of soil are correlated with smaller particles sizes. Soil data gathered in support of detailed human health risk assessments, therefore, should allow for the examination of distribution across particle sizes of contaminants of concern, and consider those size fractions most critical to human exposure. Soil evaluations for health risk assessments of metals/metalloids should also consider mineralogical characterization.     

Ingestion patterns and daily energy intake on a sugary diet: the Red Lory Eos bornea and the Malachite Sunbird Nectarinia famosa

This study examines whether nectarivorous birds regulate daily energy intake as proposed by Lloyd in 1991. Two Old World nectarivorous species, a large non-passerine, the Red Lory Eos bornea, and a small passerine, the Malachite Sunbird Nectarinia famosa, were fed 0.25 mol/1 sucrose (9%), 0.73 mol/1 sucrose [24%] or 0.73 mol/1 glucose in separate laboratory trials to determine hourly and overall daily rate of sugar intake and consumption. Overall daily energy intake rates of the Malachite Sunbird and the Red Lory support the hypothesis of regulated energy intake for nectarivorous Old World birds. However, the species differ in their ingestion patterns through the day. The Red Lory ingests large volumes initially, regardless of sugar type. This is possibly a consequence of their large size and having a crop in which food can be stored. The Malachite Sunbird showed more regular hourly consumption through the day, and no change in mass during the day. Intake rates of both species were greater on lower sugar concentrations.     

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth’s surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, K_s. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function.