Model choice for estimating the association between exposure to chemical mixtures and health outcomes: A simulation study.
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ABSTRACT:
SUBMITTER: Hoskovec L
PROVIDER: S-EPMC7993848 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Non-cancer risk assessment traditionally assumes a threshold of effect, below which there is a negligible risk of an adverse effect. The Agency for Toxic Substances and Disease Registry derives health-based guidance values known as Minimal Risk Levels (MRLs) as estimates of the toxicity threshold for non-carcinogens. Although the definition of an MRL, as well as EPA reference dose values (RfD and RfC), is a level that corresponds to "negligible risk," they represent daily exposure doses or concentrations, not risks. We present a new approach to calculate the risk at exposure to specific doses for chemical mixtures, the assumption in this approach is to assign de minimis risk at the MRL. The assigned risk enables the estimation of parameters in an exponential model, providing a complete dose-response curve for each compound from the chosen point of departure to zero. We estimated parameters for 27 chemicals. The value of k, which determines the shape of the dose-response curve, was moderately insensitive to the choice of the risk at the MRL. The approach presented here allows for the calculation of a risk from a single substance or the combined risk from multiple chemical exposures in a community. The methodology is applicable from point of departure data derived from quantal data, such as data from benchmark dose analyses or from data that can be transformed into probabilities, such as lowest-observed-adverse-effect level. The individual risks are used to calculate risk ratios that can facilitate comparison and cost-benefit analyses of environmental contamination control strategies.
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Project description:BackgroundChemicals found in personal care products and plastics have been associated with asthma, allergies, and lung function, but methods to address real life exposure to mixtures of these chemicals have not been applied to these associations.MethodsWe quantified urinary concentrations of eleven phthalate metabolites, four parabens, and five other phenols in mothers twice during pregnancy and assessed probable asthma, aeroallergies, and lung function in their age seven children. We implemented Bayesian Profile Regression (BPR) to cluster women by their exposures to these chemicals and tested the clusters for differences in outcome measurements. We used Bayesian Kernel Machine Regression (BKMR) to fit biomarkers into one model as joint independent variables.ResultsBPR clustered women into seven groups characterized by patterns of personal care product and plastic use, though there were no significant differences in outcomes across clusters. BKMR showed that monocarboxyisooctyl phthalate and 2,4-dichlorophenol were associated with probable asthma (predicted probability of probable asthma per IQR of biomarker z-score (standard deviation) = 0.08 (0.09) and 0.11 (0.12), respectively) and poorer lung function (predicted probability per IQR = -0.07 (0.05) and -0.07 (0.06), respectively), and that mono(3-carboxypropyl) phthalate and bisphenol A were associated with aeroallergies (predicted probability per IQR = 0.13 (0.09) and 0.11 (0.08), respectively). Several biomarkers demonstrated positive additive effects on other associations.ConclusionsBPR and BKMR are useful tools to evaluate associations of biomarker concentrations within a mixture of exposure and should supplement single-chemical regression models when data allow.
| S-EPMC7255953 | biostudies-literature
Project description:Inhibition, one of the building blocks of executive function, is the ability to focus one's attention despite interference from external stimuli. It undergoes substantial development during adolescence and may be susceptible to adverse impacts of prenatal exposure to chemical mixtures, yet few studies have explored this association. The New Bedford Cohort (NBC) is a birth cohort of residents living near the New Bedford Harbor Superfund site in Massachusetts. Among adolescents from the NBC, we investigated the association of biomarkers of prenatal exposure to organochlorines (DDE, HCB, PCBs) and metals (Pb, Mn) with inhibition, assessed with the Delis-Kaplan Executive Function System Design Fluency (non-verbal task) and Color-Word Interference (verbal task) subtests. An exploratory mixtures analysis using Bayesian kernel machine regression (BKMR) informed a traditional multivariable regression approach. NBC adolescents are diverse with 29% non-white and 31% in a low-income household at birth. Cord serum organochlorine concentrations and cord blood metals concentrations were generally similar to other birth cohorts. In BKMR models, we observed a suggestive adverse association of the chemical mixture with Color-Word Interference but not Design Fluency. In covariate-adjusted linear regression models including all five chemical exposure measures, a doubling of cord blood Mn was associated with poorer Color-Word Interference completion time scaled scores (difference = -0.74; 95% CI: -1.34, -0.14). This study provided evidence of an adverse joint association between prenatal exposure to a five-chemical mixture and verbal inhibition in adolescence with exposure to Mn potentially driving this overall association.
| S-EPMC8619850 | biostudies-literature
Project description:Since the National Institute of Environmental Health Sciences (NIEHS) declared conducting combined exposure research as a priority area, literature on chemical mixtures has grown dramatically. However, a systematic evaluation of the current literature investigating the impacts of metal mixtures on cardiovascular disease (CVD) risk factors and outcomes has thus far not been performed. This scoping review aims to summarize published epidemiology literature on the cardiotoxicity of exposure to multiple metals. We performed systematic searches of MEDLINE (PubMed), Scopus, and Web of Science to identify peer-reviewed studies employing statistical mixture analysis methods to evaluate the impact of metal mixtures on CVD risk factors and outcomes among nonoccupationally exposed populations. The search was limited to papers published on or after 1998, when the first dedicated funding for mixtures research was granted by NIEHS, through 1 October 2021. Twenty-nine original research studies were identified for review. A notable increase in relevant mixtures publications was observed starting in 2019. The majority of eligible studies were conducted in the United States (n = 10) and China (n = 9). Sample sizes ranged from 127 to 10,818. Many of the included studies were cross-sectional in design. Four primary focus areas included: (i) blood pressure and/or diagnosis of hypertension (n = 15), (ii) risk of preeclampsia (n = 3), (iii) dyslipidemia and/or serum lipid markers (n = 5), and (iv) CVD outcomes, including stroke incidence or coronary heart disease (n = 8). The most frequently investigated metals included cadmium, lead, arsenic, and cobalt, which were typically measured in blood (n = 15). The most commonly utilized multipollutant analysis approaches were Bayesian kernel machine regression (BKMR), weighted quantile sum regression (WQSR), and principal component analysis (PCA). To our knowledge, this is the first scoping review to assess exposure to metal mixtures in relation to CVD risk factors and outcomes. Recommendations for future studies evaluating the associations of exposure to metal mixtures with risk of CVDs and related risk factors include extending environmental mixtures epidemiologic studies to populations with wider metals exposure ranges, including other CVD risk factors or outcomes outside hypertension or dyslipidemia, using repeated measurement of metals to detect windows of susceptibility, and further examining the impacts of potential effect modifiers and confounding factors, such as fish and seafood intake.
| S-EPMC8955637 | biostudies-literature
Project description:Water is the most important non-organic compound for living cells, and the life of all living organisms depends on it. Water is not found purely in nature, but it always contains some solutes, suspended matters and soluble gases. In this study, 11 bottled water brands (500 mL) were sampled across the Kashan city market to determine the concentration of selected heavy metals (Cr, Cd, Pb, Ni and As) and evaluated their potential risks following consumption. The concentration range of Cr, Cd, Pb, Ni and As were 5-34 μg/L, 1.5-7 μg/L, 1-7 μg/L, 2-29 μg/L, <LOD - 3.5 μg/L, respectively. The heavy metals (HMs) concentration in this study was compared with other national and international studies on bottled water and other drinking water sources. Additionally, the results of non-carcinogenic health risk assessments using point estimations and Monte Carlo Simulations (MCS) showed that the concentration of HMs in none of the samples pose adverse health effects. However, it was found that drinking the studied bottled water may potentially lead to carcinogenicity over the lifetime. Lack of including spring water and larger-sized (1.5 L) bottled water samples, though less consumed than the samples of this study and lack of study on children's exposure level can be mentioned as potential limitations.
| S-EPMC10568088 | biostudies-literature
Project description:The control of ambient air quality in the United States has been a major public health success since the passing of the Clean Air Act, with particulate matter (PM) reductions resulting in an estimated 160 000 premature deaths prevented in 2010 alone. Currently, public policy is oriented around lowering the levels of individual pollutants and this focus has driven the nature of much epidemiological research. Recently, attention has been given to viewing air pollution as a complex mixture and to developing a multi-pollutant approach to controlling ambient concentrations. We present a statistical approach for estimating the health impacts of complex environmental mixtures using a mixture-altering contrast, which is any comparison, intervention, policy, or natural experiment that changes a mixture's composition. We combine the notion of mixture-altering contrasts with sliced inverse regression, propensity score matching, and principal stratification to assess the health effects of different air pollution chemical mixtures. We demonstrate the application of this approach in an analysis of the health effects of wildfire PM air pollution in the Western US.
| S-EPMC9303396 | biostudies-literature
Project description:Working memory is the ability to keep information in one's mind and mentally manipulate it. Decrements in working memory play a key role in many behavioral and psychiatric disorders, therefore identifying modifiable environmental risk factors for such decrements is important for mitigating these disorders. There is some evidence that prenatal exposure to individual chemicals may adversely impact working memory among children, but few studies have explored the association of co-exposure to multiple chemicals with this outcome in adolescence, a time when working memory skills undergo substantial development. We investigated the association of organochlorines (DDE, HCB, PCBs) and metals (lead, manganese) measured in cord serum and cord blood, respectively, with working memory measured with the Wide Range Assessment of Memory and Learning, 2nd Edition among 373 adolescents living near a Superfund site in New Bedford, Massachusetts. We used Bayesian Kernel Machine Regression (BKMR) and linear regression analyses and assessed effect modification by sex and prenatal social disadvantage. In BKMR models, we observed an adverse joint association of the chemical mixture with Verbal, but not Symbolic, Working Memory. In co-exposure and covariate-adjusted linear regression models, a twofold increase in cord blood manganese was associated with lower working memory scaled scores, with a stronger association with Verbal Working Memory (difference = -0.75; 95% CI: -1.29, -0.20 points) compared to Symbolic Working Memory (difference = -0.44; 95% CI: -1.00, 0.12 points). There was little evidence of effect modification by sex and some evidence associating organochlorine pesticides with poorer working memory scores among those with greater prenatal social disadvantage. This study provided evidence of an adverse joint association of a chemical mixture with a verbal working memory task among adolescents, as well as an adverse association of prenatal manganese exposure with working memory.
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Project description:Cognitive flexibility, the ability to smoothly adapt to changing circumstances, is a skill that is vital to higher-level executive functions such as problem-solving, planning, and reasoning. As it undergoes substantial development during adolescence, decrements in cognitive flexibility may not become apparent until this time. There is evidence that prenatal exposure to individual chemicals may adversely impact executive functions in children, but few studies have explored the association of co-exposure to multiple chemicals with cognitive flexibility specifically among adolescents. We investigated this association among a diverse group of adolescents living near a Superfund site in New Bedford, Massachusetts. Specifically, using Bayesian kernel machine regression (BKMR) and multivariable regression analyses, we investigated the association of biomarkers of prenatal exposure to organochlorines (DDE, HCB, PCBs) and metals (lead, manganese) with cognitive flexibility, measured with four subtests of the Delis-Kaplan Executive Function System. In BKMR models, we observed adverse joint associations of the chemical mixture with two of the four cognitive flexibility subtests. In covariate-adjusted linear regression models, a two-fold increase in cord blood Mn was associated with poorer performance on two of the subtests: Trail-Making (scaled score difference = -0.60; 95% CI: -1.16, -0.05 points) and Color-Word Interference (scaled score difference = -0.53; 95% CI: -1.08, 0.01 points). These adverse Mn-cognitive flexibility associations were supported by the results of the BKMR. There was little evidence of effect modification by sex and some evidence of effect modification by a measure of social disadvantage, particularly for the associations between HCB and cognitive flexibility. This study is among the first to provide evidence of an adverse association of prenatal exposure to a chemical mixture with cognitive flexibility in adolescence.
| S-EPMC8708222 | biostudies-literature
Project description:ObjectiveTo investigate the extent to which antibiotic exposure in the first 2 years of life is associated with the risk of immunological, metabolic, and neurobehavioral health conditions with childhood onset.Patients and methodsIn this population-based cohort study, we identified all children born in Olmsted County, Minnesota, between January 1, 2003, and December 31, 2011, through the Rochester Epidemiology Project medical records-linkage system. Demographic characteristics, antibiotic prescriptions, and diagnostic codes through June 30, 2017, were retrieved using the Rochester Epidemiology Project infrastructure. Time-to-event analysis was performed to assess the impact of antibiotic exposure on the risk of several adverse health conditions.ResultsThis study included 14,572 children (7026 girls and 7546 boys), of whom 70% (10,220) received at least 1 antibiotic prescription during the first 2 years of life. Early antibiotic exposure was associated with an increased risk of childhood-onset asthma, allergic rhinitis, atopic dermatitis, celiac disease, overweight, obesity, and attention deficit hyperactivity disorder (hazard ratios ranging from 1.20 to 2.89; P<.05 for all). The associations were influenced by the number, type, and timing of antibiotic exposure. Moreover, children exposed to antibiotics had a higher probability of having combinations of conditions, particularly when given multiple prescriptions.ConclusionThe present study finds significant associations between early life antibiotic exposure and several distinct health conditions with childhood onset. Additional research is warranted to establish practical guidelines to optimize the benefit and minimize the risk of antibiotics in children.
| S-EPMC7796951 | biostudies-literature
Project description:The spraying of liquid multicomponent mixtures is common in many professional and industrial settings. Typical examples are cleaning agents, additives, coatings, and biocidal products. In all of these examples, hazardous substances can be released in the form of aerosols or vapours. For occupational and consumer risk assessment in regulatory contexts, it is therefore important to know the exposure which results from the amount of chemicals in the surrounding air. In this research, a mechanistic mass balance model has been developed that covers the spraying of (semi)-volatile substances, taking into account combined exposure to spray mist, evaporation from droplets, and evaporation from surfaces as well as the nonideal behaviour of components in liquids and backpressure effects. For wall-spraying scenarios, an impaction module has been developed that quantifies the amount of overspray and the amount of material that lands on the wall. Mechanistically, the model is based on the assumption that continuous spraying can be approximated by a number of sequentially released spray pulses, each characterized by a certain droplet size, where the total aerosol exposure is obtained by summation over all release pulses. The corresponding system of differential equations is solved numerically using an extended Euler algorithm that is based on a discretisation of time and space. Since workers typically apply the product continuously, the treated area and the corresponding evaporating surface area grows over time. Time-dependent concentration gradients within the sprayed liquid films that may result from different volatilities of the components are therefore addressed by the proposed model. A worked example is presented to illustrate the calculated exposure for a scenario where aqueous solutions of H2O2 are sprayed onto surfaces as a biocidal product. The results reveal that exposure to H2O2 aerosol reaches relevant concentrations only during the spraying phase. Evaporation from sprayed surfaces takes place over much longer time periods, where backpressure effects caused by large emission sources can influence the shape of the concentration time curves significantly. The influence of the activity coefficients is not so pronounced. To test the plausibility of the developed model algorithm, a comparison of model estimates of SprayExpo, SprayEva, and ConsExpo with measured data is performed. Although the comparison is based on a limited number (N = 19) of measurement data, the results are nevertheless regarded as supportive and acceptable for the plausibility and predictive power of SprayEva.
| S-EPMC9603233 | biostudies-literature