Evaluating sufficient similarity for drinking-water disinfection by-product (DBP) mixtures with bootstrap hypothesis test procedures

Wrangling Whole Mixtures Risk Assessment: Recent Advances in Determining Sufficient Similarity

Human health risk assessments for complex mixtures can address real-world exposures and protect public health. While risk assessors typically prefer whole mixture approaches over component-based approaches, data from the precise exposure of interest are often unavailable and surrogate data from a sufficiently similar mixture(s) are required. This review describes recent advances in determining sufficient similarity of whole, complex mixtures spanning the comparison of chemical features, bioactivity profiles, and statistical evaluation to determine "thresholds of similarity". Case studies, including water disinfection byproducts, botanical ingredients, and wildfire emissions, are used to highlight tools and methods. Limitations to application of sufficient similarity in risk-based decision making are reviewed and recommendations presented for developing best practice guidelines.

Potential risks and approaches to reduce the toxicity of disinfection by-product - A review

Water contamination through anthropogenic and industrial activities has led to the emergence and necessity of disinfection methods. Chlorine and bromine gases, often used to disinfect water, resulted in the by-product formation by reacting with organic matter. The Disinfectant by-products (DBP) led to the formation of Trihaloaceticacid (TAA), Trihalomethane (THM), and other minor components. The release of chemicals has also led to the outbreak of diseases like infertility, asthma, stillbirth, and types of cancer. There are new approaches that are found to be useful to compensate for the generation of toxic by-products and involve membrane technologies, namely reverse osmosis, ultrafiltration, and nanofiltration. This review mainly focuses on the toxicology effects of DBPs and various approaches to mitigate the same. The health hazards caused by different DBPs and the various treatment techniques available for the removal are discussed. In addition, a critical comparison of the different removal techniques was discussed.

The Joint Effect of Prenatal Exposure to Metal Mixtures on Neurodevelopmental Outcomes at 20-40 Months of Age: Evidence from Rural Bangladesh

BACKGROUND

Exposure to chemical mixtures is recognized as the real-life scenario in all populations, needing new statistical methods that can assess their complex effects.

OBJECTIVES

We aimed to assess the joint effect of in utero exposure to arsenic, manganese, and lead on children's neurodevelopment.

METHODS

We employed a novel statistical approach, Bayesian kernel machine regression (BKMR), to study the joint effect of coexposure to arsenic, manganese, and lead on neurodevelopment using an adapted Bayley Scale of Infant and Toddler Development™. Third Edition, in 825 mother-child pairs recruited into a prospective birth cohort from two clinics in the Pabna and Sirajdikhan districts of Bangladesh. Metals were measured in cord blood using inductively coupled plasma-mass spectrometry.

RESULTS

Analyses were stratified by clinic due to differences in exposure profiles. In the Pabna district, which displayed high manganese levels [interquartile range (IQR): 4.8, 18 μg/dl], we found a statistically significant negative effect of the mixture of arsenic, lead, and manganese on cognitive score when cord blood metals concentrations were all above the 60th percentile (As≥0.7 μg/dl, Mn≥6.6 μg/dl, Pb≥4.2 μg/dl) compared to the median (As=0.5 μg/dl, Mn=5.8 μg/dl, Pb=3.1 μg/dl). Evidence of a nonlinear effect of manganese was found. A change in log manganese from the 25th to the 75th percentile when arsenic and manganese were at the median was associated with a decrease in cognitive score of −0.3 (−0.5, −0.1) standard deviations. Our study suggests that arsenic might be a potentiator of manganese toxicity.

CONCLUSIONS

Employing a novel statistical method for the study of the health effects of chemical mixtures, we found evidence of neurotoxicity of the mixture, as well as potential synergism between arsenic and manganese. https://doi.org/10.1289/EHP614.

Biological and statistical approaches for modeling exposure to specific trihalomethanes and bladder cancer risk

Lifetime exposure to trihalomethanes (THM) has been associated with increased risk of bladder cancer. We explored methods of analyzing bladder cancer risk associated with 4 THM (chloroform, bromodichloromethane, dibromochloromethane, and bromoform) as surrogates for disinfection by-product (DBP) mixtures in a case-control study in Spain (1998-2001). Lifetime average concentrations of THM in the households of 686 incident bladder cancer cases and 750 matched hospital-based controls were calculated. Several exposure metrics were modeled through conditional logistic regression, including the following analyses: total THM (μg/L), cytotoxicity-weighted sum of total THM (pmol/L), 4 THM in separate models, 4 THM in 1 model, chloroform and the sum of brominated THM in 1 model, and a principal-components analysis. THM composition, concentrations, and correlations varied between areas. The model for total THM was stable and showed increasing dose-response trends. Models for separate THM provided unstable estimates and inconsistent dose-response relationships. Risk estimation for specific THM is hampered by the varying composition of the mixture, correlation between species, and imprecision of historical estimates. Total THM (μg/L) provided a proxy measure of DBPs that yielded the strongest dose-response relationship with bladder cancer risk. A variety of metrics and statistical approaches should be used to evaluate this association in other settings.

Pollution trees: identifying similarities among complex pollutant mixtures in water and correlating them to mutagenicity

There are relatively few tools available for computing and visualizing similarities among complex mixtures and in correlating the chemical composition clusters with toxicological clusters of mixtures. Using the "intersection and union ratio (IUR)" and other traditional distance matrices on contaminant profiles of 33 specific water samples, we used "pollution trees" to compare these mixtures. The "pollution trees" constructed by neighbor-joining (NJ), maximum parsimony (MP), and maximum likelihood (ML) methods allowed comparison of similarities among these samples. The mutagenicity of each sample was then mapped to the "pollution tree". The IUR-distance-based measure proved effective in comparing chemical composition and compound level differences between mixtures. We found a robust "pollution tree" containing seven major lineages with certain broad characteristics: treated municipal water samples were different from raw water samples and untreated rural drinking water samples were similar with local water sources. The IUR-distance-based tree was more highly correlated to mutagenicity than were other distance matrices, i.e., MP/ML methods, sampling group, region, or water type. IUR-distance-based "pollution trees" may become important tools for identifying similarities among real mixtures and examining chemical composition clusters in a toxicological context.

Bayesian statistical modeling of disinfection byproduct (DBP) bromine incorporation in the ICR database

Statistical models are developed for bromine incorporation in the trihalomethane (THM), trihaloacetic acids (THAA), dihaloacetic acid (DHAA), and dihaloacetonitrile (DHAN) subclasses of disinfection byproducts (DBPs) using distribution system samples from plants applying only free chlorine as a primary or residual disinfectant in the Information Collection Rule (ICR) database. The objective of this study is to characterize the effect of water quality conditions before, during, and post-treatment on distribution system bromine incorporation into DBP mixtures. Bayesian Markov Chain Monte Carlo (MCMC) methods are used to model individual DBP concentrations and estimate the coefficients of the linear models used to predict the bromine incorporation fraction for distribution system DBP mixtures in each of the four priority DBP classes. The bromine incorporation models achieve good agreement with the data. The most important predictors of bromine incorporation fraction across DBP classes are alkalinity, specific UV absorption (SUVA), and the bromide to total organic carbon ratio (Br:TOC) at the first point of chlorine addition. Free chlorine residual in the distribution system, distribution system residence time, distribution system pH, turbidity, and temperature only slightly influence bromine incorporation. The bromide to applied chlorine (Br:Cl) ratio is not a significant predictor of the bromine incorporation fraction (BIF) in any of the four classes studied. These results indicate that removal of natural organic matter and the location of chlorine addition are important treatment decisions that have substantial implications for bromine incorporation into disinfection byproduct in drinking waters.

Evaluating sufficient similarity for disinfection by-product (DBP) mixtures: multivariate statistical procedures

For evaluation of the adverse health effects associated with exposures to complex chemical mixtures in the environment, the U.S. Environmental Protection Agency (EPA) (2000) states, "if no data are available on the mixture of concern, but health effects data are available on a similar mixture ... a decision must be made whether the mixture on which health effects are available is 'sufficiently' similar to the mixture of concern to permit a risk assessment." This article provides a detailed discussion of statistical considerations for evaluation of the similarity of mixtures. Multivariate statistical procedures are suggested to determine whether individual samples of drinking-water disinfection by-products (DBPs) vary significantly from a group of samples that are considered to be similar. The application of principal components analysis to (1) reduce the dimensionality of the vectors of water samples and (2) permit visualization and statistical comparisons in lower dimensional space is suggested. Formal analysis of variance tests of homogeneity are illustrated. These multivariate statistical procedures are applied to a data set describing samples from multiple water treatment plants. Essential data required for carrying out sensitive analyses include (1) identification and measurement of toxicologically sensitive process input and output characteristics, and (2) estimates of variability within the data to construct statistically efficient estimates and tests.

Evaluating the similarity of complex drinking-water disinfection by-product mixtures: overview of the issues

Humans are exposed daily to complex mixtures of environmental chemical contaminants, which arise as releases from sources such as engineering procedures, degradation processes, and emissions from mobile or stationary sources. When dose-response data are available for the actual environmental mixture to which individuals are exposed (i.e., the mixture of concern), these data provide the best information for dose-response assessment of the mixture. When suitable data on the mixture itself are not available, surrogate data might be used from a sufficiently similar mixture or a group of similar mixtures. Consequently, the determination of whether the mixture of concern is "sufficiently similar" to a tested mixture or a group of tested mixtures is central to the use of whole mixture methods. This article provides an overview for a series of companion articles whose purpose is to develop a set of biostatistical, chemical, and toxicological criteria and approaches for evaluating the similarity of drinking-water disinfection by-product (DBPs) complex mixtures. Together, the five articles in this series serve as a case study whose techniques will be relevant to assessing similarity for other classes of complex mixtures of environmental chemicals. Schenck et al. (2009) describe the chemistry and mutagenicity of a set of DBP mixtures concentrated from five different drinking-water treatment plants. Bull et al. (2009a, 2009b) describe how the variables that impact the formation of DBP affect the chemical composition and, subsequently, the expected toxicity of the mixture. Feder et al. (2009a, 2009b) evaluate the similarity of DBP mixture concentrates by applying two biostatistical approaches, principal components analysis, and a nonparametric "bootstrap" analysis. Important factors for determining sufficient similarity of DBP mixtures found in this research include disinfectant used; source water characteristics, including the concentrations of bromide and total organic carbon; concentrations and proportions of individual DBPs with known toxicity data on the same endpoint; magnitude of the unidentified fraction of total organic halides; similar toxicity outcomes for whole mixture testing (e.g., mutagenicity); and summary chemical measures such as total trihalomethanes, total haloacetic acids, total haloacetonitriles, and the levels of bromide incorporation in the DBP classes.

Chemical measures of similarity among disinfection by-product mixtures

There are few measures that can be used to distinguish among mixtures of disinfection by-products (DBPs) produced in the chlorination or chloramination of drinking water. Objective measures of similarities among DBP mixtures would greatly simplify judgments about the risk that may be associated with exposure to DBPs in a given water supply. Major by-products of chlorination/chloramination include the trihalomethanes (THMs) and haloacetic acids (HAAs), which are routinely measured for compliance to regulations. A key question is whether measurement of similar amounts of these DBPs is indicative of the myriad other DBPs that are known to be produced. This article utilized data from a survey of 35 utilities in the United States that included several additional parameters, including members of the haloacetonitrile, trihaloacetaldehyde, and halopropanone classes. Based upon the distribution of bromine in the THM class, the concentrations of unmeasured brominated and bromochlorinated compounds could be determined. This allowed determination of whether measures of the THM and/or HAA classes reflected the amounts of these less abundant classes. Variations in relative yields among DBP classes were observed with water source type and with whether chlorine or chloramine was used as the disinfectant. However, most of the variability was attributable to geographic location. The relative abundance of brominated by-products also varied among water sources. Recent documentation that potent by-products, such as nitrosamines, are selectively produced in particular water systems and preferentially with chloramination indicates that more measures of individual DBP are needed to evaluate similarity among DBPs mixtures.

Determinants of whether or not mixtures of disinfection by-products are similar

Reactive chemicals have been used to disinfect drinking waters for over a century. In the 1970s, it was first observed that the reaction of these chemicals with the natural organic matter (NOM) in source waters results in the production of variable, complex mixtures of disinfection by-products (DBP). Because limited toxicological and epidemiological data are available to assess potential human health risks from complex DBP mixture exposures, methods are needed to determine when health effects data on a specific DBP mixture may be used as a surrogate for evaluating another environmental DBP mixture of interest. Before risk assessors attempt such efforts, a set of criteria needs to be in place to determine whether two or more DBP mixtures are similar in composition and toxicological potential. This study broadly characterizes the chemical and toxicological measures that may be used to evaluate similarities among DBP mixtures. Variables are discussed that affect qualitative and quantitative shifts in the types of DBP that are formed, including disinfectants used, their reactions with NOM and with bromide/iodide, pH, temperature, time, and changes in the water distribution system. The known toxicological activities of DBP mixtures and important single DBPs are also presented in light of their potential for producing similar toxicity. While DBP exposures are associated with a number of health effects, this study focuses on (1) mutagenic activity of DBP mixtures, (2) DBP cancer epidemiology, and (3) toxicology studies to evaluate similarity among DBP mixtures. Data suggest that further chemical characterization of DBP mixtures and more systematic study of DBP toxicology will improve the quality and usefulness of similarity criteria.