Predicting personal PAH exposure using high dimensional questionnaire and wristband data.

BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs) are a class of pervasive environmental pollutants with a variety of known health effects. While significant work has been completed to estimate personal exposure to PAHs, less has been done to identify sources of these exposures. Comprehensive characterization of reported sources of personal PAH exposure is a critical step to more easily identify individuals at risk of high levels of exposure and for developing targeted interventions based on source of exposure. OBJECTIVE: In this study, we leverage data from a New York (NY)-based birth cohort to identify personal characteristics or behaviors associated with personal PAH exposure and develop models for the prediction of PAH exposure. METHODS: We quantified 61 PAHs measured using silicone wristband samplers in association with 75 questionnaire variables from 177 pregnant individuals. We evaluated univariate associations between each compound and questionnaire variable, conducted regression tree analysis for each PAH compound and completed a principal component analysis of for each participant's entire PAH exposure profile to determine the predictors of PAH levels. RESULTS: Regression tree analyses of individual compounds and exposure mixture identified income, time spent outdoors, maternal age, country of birth, transportation type, and season as the variables most frequently predictive of exposure.

Post transition metal substituted Keggin-type POMs as thin film chemiresistive sensors for H2O and CO2 detection.

Chemiresitive sensing allows the affordable and facile detection of small molecules such as H2O and CO2. Herein, we report a novel class of Earth-abundant post transition metal substituted Keggin polyoxometalates (POMs) for chemiresistive sensing applications, with conductivities up to 0.01 S cm-1 under 100% CO2 and 65% Relative Humidity (RH).

Improving the Conductivity of Amide-Based Small Molecules through Enhanced Molecular Packing and Their Application as Hole Transport Mediators in Perovskite Solar Cells.

Organic-inorganic hybrid halide perovskite solar cells (PSCs) have attracted substantial attention from the photovoltaic research community, with the power conversion efficiency (PCE) already exceeding 26%. Current state-of-the-art devices rely on Spiro-OMeTAD as the hole-transporting material (HTM); however, Spiro-OMeTAD is costly due to its complicated synthesis and expensive product purification, while its low conductivity ultimately limits the achievable device efficiency. In this work, we build upon our recently introduced family of low-cost amide-based small molecules and introduce a molecule (termed TPABT) that results in high conductivity values (∼10-5 S cm-1 upon addition of standard ionic additives), outperforming our previous amide-based material (EDOT-Amide-TPA, ∼10-6 S cm-1) while only costing an estimated $5/g. We ascribe the increased optoelectronic properties to favorable molecular packing, as shown by single-crystal X-ray diffraction, which results in close spacing between the triphenylamine blocks. This, in turn, results in a short hole-hopping distance between molecules and therefore good mobility and conductivity. In addition, TPABT exhibits a higher bandgap and is as a result more transparent in the visible range of the solar spectrum, leading to lower parasitic absorption losses than Spiro-OMeTAD, and has increased moisture stability. We applied the molecule in perovskite solar cells and obtained good efficiency values in the ∼15% range. Our approach shows that engineering better molecular packing may be the key to developing high-efficiency, low-cost HTMs for perovskite solar cells.

Menstrual cycle length variation by demographic characteristics from the Apple Women's Health Study.

Menstrual characteristics are important signs of women's health. Here we examine the variation of menstrual cycle length by age, ethnicity, and body weight using 165,668 cycles from 12,608 participants in the US using mobile menstrual tracking apps. After adjusting for all covariates, mean menstrual cycle length is shorter with older age across all age groups until age 50 and then became longer for those age 50 and older. Menstrual cycles are on average 1.6 (95%CI: 1.2, 2.0) days longer for Asian and 0.7 (95%CI: 0.4, 1.0) days longer for Hispanic participants compared to white non-Hispanic participants. Participants with BMI ≥ 40 kg/m2 have 1.5 (95%CI: 1.2, 1.8) days longer cycles compared to those with BMI between 18.5 and 25 kg/m2. Cycle variability is the lowest among participants aged 35-39 but are considerably higher by 46% (95%CI: 43%, 48%) and 45% (95%CI: 41%, 49%) among those aged under 20 and between 45-49. Cycle variability increase by 200% (95%CI: 191%, 210%) among those aged above 50 compared to those in the 35-39 age group. Compared to white participants, those who are Asian and Hispanic have larger cycle variability. Participants with obesity also have higher cycle variability. Here we confirm previous observations of changes in menstrual cycle pattern with age across reproductive life span and report new evidence on the differences of menstrual variation by ethnicity and obesity status. Future studies should explore the underlying determinants of the variation in menstrual characteristics.

Pentafluorosulfanyl-functionalised BODIPY push-pull dyes for p-type dye-sensitized solar cells.

We report a push-pull BODIPY-based dye functionalised with an electronegative SF5 group at the meso position for applications in photocathodes in tandem dye-sensitized solar cells (DSSCs). The push-pull character enhances charge-transfer from the mesoporous NiO cathode surface towards the redox mediator. A Knoevenagel condensation reaction was used to introduce the carboxylic acid to anchor the dye to the oxide surface, via a styryl linker which increases the conjugation in the molecule and shifts the absorption to the red. The room-temperature synthesis and high yields, make the dye promising for manufacture on a large scale. The dye was applied in p-DSSCs giving a power conversion efficiency (0.066%), a short circuit photocurrent (J SC) of 3.84 mA cm-2, open circuit voltage (V OC) of 58 mV and fill factor of 30%.

Covid-19 vaccination and menstrual cycle length in the Apple Women's Health Study.

COVID-19 vaccination may be associated with change in menstrual cycle length following vaccination. We estimated covariate-adjusted differences in mean cycle length (MCL), measured in days, between pre-vaccination cycles, vaccination cycles, and post-vaccination cycles within vaccinated participants who met eligibility criteria in the Apple Women's Health Study, a longitudinal mobile-application-based cohort of people in the U.S. with manually logged menstrual cycles. A total of 9652 participants (8486 vaccinated; 1166 unvaccinated) contributed 128,094 cycles (median = 10 cycles per participant; inter-quartile range: 4-22). Fifty-five percent of vaccinated participants received Pfizer-BioNTech's mRNA vaccine, 37% received Moderna's mRNA vaccine, and 8% received the Johnson & Johnson/Janssen (J&J) vaccine. COVID-19 vaccination was associated with a small increase in MCL for cycles in which participants received the first dose (0.50 days, 95% CI: 0.22, 0.78) and cycles in which participants received the second dose (0.39 days, 95% CI: 0.11, 0.67) of mRNA vaccines compared with pre-vaccination cycles. Cycles in which the single dose of J&J was administered were, on average, 1.26 days longer (95% CI: 0.45, 2.07) than pre-vaccination cycles. Post-vaccination cycles returned to average pre-vaccination length. Estimated follicular phase vaccination was associated with increased MCL in cycles in which participants received the first dose (0.97 days, 95% CI: 0.53, 1.42) or the second dose (1.43 days, 95% CI: 1.06, 1.80) of mRNA vaccines or the J&J dose (2.27 days, 95% CI: 1.04, 3.50), compared with pre-vaccination cycles. Menstrual cycle change following COVID-19 vaccination appears small and temporary and should not discourage individuals from becoming vaccinated.

Principal Component Pursuit for Pattern Identification in Environmental Mixtures.

BACKGROUND: Environmental health researchers often aim to identify sources or behaviors that give rise to potentially harmful environmental exposures. OBJECTIVE: We adapted principal component pursuit (PCP)-a robust and well-established technique for dimensionality reduction in computer vision and signal processing-to identify patterns in environmental mixtures. PCP decomposes the exposure mixture into a low-rank matrix containing consistent patterns of exposure across pollutants and a sparse matrix isolating unique or extreme exposure events. METHODS: We adapted PCP to accommodate nonnegative data, missing data, and values below a given limit of detection (LOD). We simulated data to represent environmental mixtures of two sizes with increasing proportions

Long-term Traffic-related Air Pollutant Exposure and Amyotrophic Lateral Sclerosis Diagnosis in Denmark: A Bayesian Hierarchical Analysis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. Limited evidence suggests ALS diagnosis may be associated with air pollution exposure and specifically traffic-related pollutants. METHODS: In this population-based case-control study, we used 3,937 ALS cases from the Danish National Patient Register diagnosed during 1989-2013 and matched on age, sex, year of birth, and vital status to 19,333 population-based controls free of ALS at index date. We used validated predictions of elemental carbon (EC), nitrogen oxides (NO x ), carbon monoxide (CO), and fine particles (PM 2.5 ) to assign 1-, 5-, and 10-year average exposures pre-ALS diagnosis at study participants' present and historical residential addresses. We used an adjusted Bayesian hierarchical conditional logistic model to estimate individual pollutant associations and joint and average associations for traffic-related pollutants (EC, NO x , CO). RESULTS: For a standard deviation (SD) increase in 5-year average concentrations, EC (SD = 0.42 µg/m 3 ) had a high probability of individual association with increased odds of ALS (11.5%; 95% credible interval [CrI] = -1.0%, 25.6%; 96.3% posterior probability of positive association), with negative associations for NO x (SD = 20 µg/m 3 ) (-4.6%; 95% CrI = 18.1%, 8.9%; 27.8% posterior probability of positive association), CO (SD = 106 µg/m 3 ) (-3.2%; 95% CrI = 14.4%, 10.0%; 26.7% posterior probability of positive association), and a null association for nonelemental carbon fine particles (non-EC PM 2.5 ) (SD = 2.37 µg/m 3 ) (0.7%; 95% CrI = 9.2%, 12.4%). We found no association between ALS and joint or average traffic pollution concentrations. CONCLUSIONS: This study found high probability of a positive association between ALS diagnosis and EC concentration. Further work is needed to understand the role of traffic-related air pollution in ALS pathogenesis.

Covid-19 vaccination and menstrual cycle length in the Apple Women's Health Study.

Background: COVID-19 vaccination may be associated with change in menstrual cycle length following vaccination. Methods: We conducted a longitudinal analysis within a subgroup of 14,915 participants in the Apple Women's Health Study (AWHS) who enrolled between November 2019 and December 2021 and met the following eligibility criteria: were living in the U.S., met minimum age requirements for consent, were English speaking, actively tracked their menstrual cycles, and responded to the COVID-19 Vaccine Update survey. In the main analysis, we included tracked cycles recorded when premenopausal participants were not pregnant, lactating, or using hormonal contraceptives. We used conditional linear regression and multivariable linear mixed-effects models with random intercepts to estimate the covariate-adjusted difference in mean cycle length, measured in days, between pre-vaccination cycles, cycles in which a vaccine was administered, and post-vaccination cycles within vaccinated participants, and between vaccinated and unvaccinated participants. We further compared associations between vaccination and menstrual cycle length by the timing of vaccine dose within a menstrual cycle (i.e., in follicular or luteal phase). We present Bonferroni-adjusted 95% confidence intervals to account for multiple comparisons. Results: A total of 128,094 cycles (median = 10 cycles per participant; interquartile range: 4-22) from 9,652 participants (8,486 vaccinated; 1,166 unvaccinated) were included. The average within-individual standard deviation in cycle length was 4.2 days. Fifty-five percent of vaccinated participants received Pfizer-BioNTech's mRNA vaccine, 37% received Moderna's mRNA vaccine, and 7% received the Johnson & Johnson/Janssen vaccine (J&J). We found no evidence of a difference between mean menstrual cycle length in the unvaccinated and vaccinated participants prior to vaccination (0.24 days, 95% CI: -0.34, 0.82).Among vaccinated participants, COVID-19 vaccination was associated with a small increase in mean cycle length (MCL) for cycles in which participants received the first dose (0.50 days, 95% CI: 0.22, 0.78) and cycles in which participants received the second dose (0.39 days, 95% CI: 0.11, 0.67) of mRNA vaccines compared with pre-vaccination cycles. Cycles in which the single dose of J&J was administered were, on average, 1.26 days longer (95% CI: 0.45, 2.07) than pre-vaccination cycles. Post-vaccination cycles returned to average pre-vaccination length. Estimates for pre vs post cycle lengths were 0.14 days (95% CI: -0.13, 0.40) in the first cycle following vaccination, 0.13 days (95% CI: -0.14, 0.40) in the second, -0.17 days (95% CI: -0.43, 0.10) in the third, and -0.25 days (95% CI: -0.52, 0.01) in the fourth cycle post-vaccination. Follicular phase vaccination was associated with an increase in MCL in cycles in which participants received the first dose (0.97 days, 95% CI: 0.53, 1.42) or the second dose (1.43 days, 95% CI: 1.06, 1.80) of mRNA vaccines or the J&J dose (2.27 days, 95% CI: 1.04, 3.50), compared with pre-vaccination cycles. Conclusions: COVID-19 vaccination was associated with an immediate short-term increase in menstrual cycle length overall, which appeared to be driven by doses received in the follicular phase. However, the magnitude of this increase was small and diminished in each cycle following vaccination. No association with cycle length persisted over time. The magnitude of change associated with vaccination was well within the natural variability in the study population. Menstrual cycle change following COVID-19 vaccination appears small and temporary and should not discourage individuals from becoming vaccinated.

Evaluating predictive relationships between wristbands and urine for assessment of personal PAH exposure.

During events like the COVID-19 pandemic or a disaster, researchers may need to switch from collecting biological samples to personal exposure samplers that are easy and safe to transport and wear, such as silicone wristbands. Previous studies have demonstrated significant correlations between urine biomarker concentrations and chemical levels in wristbands. We build upon those studies and use a novel combination of descriptive statistics and supervised statistical learning to evaluate the relationship between polycyclic aromatic hydrocarbon (PAH) concentrations in silicone wristbands and hydroxy-PAH (OH-PAH) concentrations in urine. In New York City, 109 participants in a longitudinal birth cohort wore one wristband for 48 h and provided a spot urine sample at the end of the 48-hour period during their third trimester of pregnancy. We compared four PAHs with the corresponding seven OH-PAHs using descriptive statistics, a linear regression model, and a linear discriminant analysis model. Five of the seven PAH and OH-PAH pairs had significant correlations (Pearson's r = 0.35-0.64, p ≤ 0.003) and significant chi-square tests of independence for exposure categories (p ≤ 0.009). For these five comparisons, the observed PAH or OH-PAH concentration could predict the other concentration within a factor of 1.47 for 50-80% of the measurements (depending on the pair). Prediction accuracies for high exposure categories were at least 1.5 times higher compared to accuracies based on random chance. These results demonstrate that wristbands and urine provide similar PAH exposure assessment information, which is critical for environmental health researchers looking for the flexibility to switch between biological sample and wristband collection.

Mixed metals exposure and cognitive function in Bangladeshi adolescents.

BACKGROUND: Over 57 million people in Bangladesh have been chronically exposed to arsenic-contaminated drinking water. They also face environmental exposure to elevated levels of cadmium (Cd), manganese (Mn), and lead (Pb), all of which have been previously observed in environmental and biological samples for this population. These metals have been linked to adverse neurocognitive outcomes in adults and children, though their effects on adolescents are not yet fully characterized. Additionally, previous studies have linked selenium (Se) to protective effects against the toxicity of these other metals. OBJECTIVES: To examine the associations between mixed metals exposure and cognitive function in Bangladeshi adolescents. METHODS: The Metals, Arsenic, & Nutrition in Adolescents study (MANAs) is a cross-sectional study of 572 Bangladeshi adolescents aged 14-16 years, whose parents were enrolled in the Health Effects of Arsenic Longitudinal Study (HEALS). Biosamples were collected from these adolescents for measurement of whole blood metalloid/metal levels of As, Cd, Mn, Pb, and Se. Participants also completed an abbreviated version of The Cambridge Neuropsychological Test Automated Battery (CANTAB), a cognitive function test designed to measure performance across several aspects of executive function. Linear regression was used to examine associations for each metal while controlling for the other metals. Bayesian Kernel Machine Regression (BKMR) assessed the overall mixture effect in addition to confirming the effects of individual metal components observed via linear regression. RESULTS: Linear regression revealed negative associations for Spatial Working Memory and both As and Mn (As B=-2.40, Mn B=-5.31, p < 0.05). We also observed negative associations between Cd and Spatial Recognition Memory (B=-2.77, p < 0.05), and Pb and Delayed Match to Sample, a measure of visual recognition and memory (B=-3.67, p < 0.05). Finally, we saw a positive association for Se and Spatial Span Length (B=0.92, p < 0.05). BKMR results were largely consistent with the regression analysis, showing meaningful associations for individual metals and CANTAB subtests, but no overall mixture effect. Via BKMR, we observed negative associations between Pb and Delayed Match to Sample, and Cd and Spatial Recognition Memory; this analysis also showed positive associations for Se and the Planning, Reaction Time, and Spatial Span subtests. BKMR posterior inclusion probability consistently reported that Se, the only component of the mixture to show a positive association with cognition, was the most important member of the mixture. CONCLUSIONS: Overall, we found Se to be positively associated with cognition, while Mn and As were linked to poorer working memory, and Cd and Pb were associated with poorer visual recognition and memory. Our observations are consistent with previous reports on the effects of these metal exposures in adults and children. Our findings also suggest agreement between linear regression and BKMR methods for analyzing metal mixture exposures. Additional studies are needed to evaluate the impact of mixed metals exposure on adverse health and poorer cognition later in life for those exposed during adolescence. Findings also suggest that metal exposure mitigation efforts aimed at adolescents might influence lifelong cognitive outcomes in regions where environmental exposure to metals is endemic.

Dye-sensitized solar cells strike back.

Dye-sensitized solar cells (DSCs) are celebrating their 30th birthday and they are attracting a wealth of research efforts aimed at unleashing their full potential. In recent years, DSCs and dye-sensitized photoelectrochemical cells (DSPECs) have experienced a renaissance as the best technology for several niche applications that take advantage of DSCs' unique combination of properties: at low cost, they are composed of non-toxic materials, are colorful, transparent, and very efficient in low light conditions. This review summarizes the advancements in the field over the last decade, encompassing all aspects of the DSC technology: theoretical studies, characterization techniques, materials, applications as solar cells and as drivers for the synthesis of solar fuels, and commercialization efforts from various companies.

Reflection on modern methods: good practices for applied statistical learning in epidemiology.

Statistical learning includes methods that extract knowledge from complex data. Statistical learning methods beyond generalized linear models, such as shrinkage methods or kernel smoothing methods, are being increasingly implemented in public health research and epidemiology because they can perform better in instances with complex or high-dimensional data-settings in which traditional statistical methods fail. These novel methods, however, often include random sampling which may induce variability in results. Best practices in data science can help to ensure robustness. As a case study, we included four statistical learning models that have been applied previously to analyze the relationship between environmental mixtures and health outcomes. We ran each model across 100 initializing values for random number generation, or 'seeds', and assessed variability in resulting estimation and inference. All methods exhibited some seed-dependent variability in results. The degree of variability differed across methods and exposure of interest. Any statistical learning method reliant on a random seed will exhibit some degree of seed sensitivity. We recommend that researchers repeat their analysis with various seeds as a sensitivity analysis when implementing these methods to enhance interpretability and robustness of results.

Tuning Photoinduced Electron Transfer in POM-Bodipy Hybrids by Controlling the Environment: Experiment and Theory.

The optical and electrochemical properties of a series of polyoxometalate (POM) oxoclusters decorated with two bodipy (boron-dipyrromethene) light-harvesting units were examined. Evaluated here in this polyanionic donor-acceptor system is the effect of the solvent and associated counterions on the intramolecular photoinduced electron transfer. The results show that both solvents and counterions have a major impact upon the energy of the charge-transfer state by modifying the solvation shell around the POMs. This modification leads to a significantly shorter charge separation time in the case of smaller counterion and slower charge recombination in a less polar solvent. These results were rationalized in terms of Marcus theory and show that solvent and counterion both affect the driving force for photoinduced electron transfer and the reorganization energy. This was corroborated with theoretical investigations combining DFT and molecular dynamics simulations.

Ruthenium Assemblies for CO2 Reduction and H2 Generation: Time Resolved Infrared Spectroscopy, Spectroelectrochemistry and a Photocatalysis Study in Solution and on NiO.

Two novel supramolecular complexes RuRe ([Ru(dceb)2(bpt)Re(CO)3Cl](PF6)) and RuPt ([Ru(dceb)2(bpt)PtI(H2O)](PF6)2) [dceb = diethyl(2,2'-bipyridine)-4,4'-dicarboxylate, bpt = 3,5-di(pyridine-2-yl)-1,2,4-triazolate] were synthesized as new catalysts for photocatalytic CO2 reduction and H2 evolution, respectively. The influence of the catalytic metal for successful catalysis in solution and on a NiO semiconductor was examined. IR-active handles in the form of carbonyl groups on the peripheral ligand on the photosensitiser were used to study the excited states populated, as well as the one-electron reduced intermediate species using infrared and UV-Vis spectroelectrochemistry, and time resolved infrared spectroscopy. Inclusion of ethyl-ester moieties led to a reduction in the LUMO energies on the peripheral bipyridine ligand, resulting in localization of the 3MLCT excited state on these peripheral ligands following excitation. RuPt generated hydrogen in solution and when immobilized on NiO in a photoelectrochemical (PEC) cell. RuRe was inactive as a CO2 reduction catalyst in solution, and produced only trace amounts of CO when the photocatalyst was immobilized on NiO in a PEC cell saturated with CO2.

Probing the dye-semiconductor interface in dye-sensitized NiO solar cells.

The development of p-type dye-sensitized solar cells (p-DSSCs) offers an opportunity to assemble tandem photoelectrochemical solar cells with higher efficiencies than TiO2-based photoanodes, pioneered by O'Regan and Grätzel [Nature 353, 737-740 (1991)]. This paper describes an investigation into the behavior at the interfaces in p-DSSCs, using a series of BODIPY dyes, BOD1-3. The three dyes have different structural and electronic properties, which lead to different performances in p-DSSCs. We have applied photoelectron spectroscopy and transient absorption spectroscopy to rationalize these differences. The results show that the electronic orbitals of the dyes are appropriately aligned with the valence band of the NiO semiconductor to promote light-induced charge transfer, but charge-recombination is too fast for efficient dye regeneration by the electrolyte. We attribute this fast recombination, which limits the efficiency of the solar cells, to the electronic structure of the dye and the presence of Ni3+ recombination sites at the NiO surface.

Photosensitizers for H2 Evolution Based on Charged or Neutral Zn and Sn Porphyrins.

We report a comparison between a series of zinc and tin porphyrins as photosensitizers for photochemical hydrogen evolution using cobaloxime complexes as molecular catalysts. Among all the chromophores tested, only the positively charged zinc porphyrin, [ZnTMePyP4+]Cl4, and the neutral tin porphyrin derivatives, Sn(OH)2TPyP, Sn(Cl2)TPP-[COOMe]4, and Sn(Cl2)TPP-[PO(OEt)2]4, were photocatalytically active. Hydrogen evolution was strongly affected by the pH value as well as the different concentrations of both the sensitizer and the catalyst. A comprehensive photophysical and electrochemical investigation was conducted in order to examine the mechanism of photocatalysis. The results derived from this study establish fundamental criteria with respect to the design and synthesis of porphyrin derivatives for their application as photosensitizers in photoinduced hydrogen evolution.

Early life and adolescent arsenic exposure from drinking water and blood pressure in adolescence.

OBJECTIVES: Evidence of the association between inorganic arsenic (As) exposure, especially early-life exposure, and blood pressure (BP) in adolescence is limited. We examined the association of As exposure during early childhood, childhood, and adolescence with BP in adolescence. METHODS: We conducted a cross-sectional study of 726 adolescents aged 14-17 (mean 14.75) years whose mothers were participants in the Bangladesh Health Effects of Arsenic Longitudinal Study (HEALS). Adolescents' BP was measured at the time of their recruitment between December 2012 and December 2016. We considered maternal urinary As (UAs), repeatedly measured during childhood, as proxy measures of early childhood (<5 years old, A1) and childhood (5-12 years old, A2) exposure. Adolescents' current UAs was collected at the time of recruitment (14-17 years of age, A3). RESULTS: Every doubling of UAs at A3 and maternal UAs at A1 was positively associated with a difference of 0.7-mmHg (95% confidence interval [CI]: 0.1, 1.3) and a 0.7-mmHg (95% CI: 0.05, 1.4) in SBP, respectively. These associations were stronger in adolescents with a BMI above the median (17.7 kg/m2) than those with a BMI below the median (P for interaction = 0.03 and 0.03, respectively). There was no significant association between any of the exposure measures and DBP. The Weighted Quantile Sum (WQS) regression confirmed that adolescents' UAs at A3 and maternal UAs at A1 contributed the most to the overall effect of As exposure at three life stages on SBP. Mixture analyses using Bayesian Kernel Machine Regression identified UAs at A3 as a significant contributor to SBP and DBP independent of other concurrent blood levels of cadmium, lead, manganese, and selenium. CONCLUSION: Our findings suggest an association of current exposure and early childhood exposure to As with higher BP in adolescents, which may be exacerbated by higher BMI at adolescence.

An overview of methods to address distinct research questions on environmental mixtures: an application to persistent organic pollutants and leukocyte telomere length.

BACKGROUND: Numerous methods exist to analyze complex environmental mixtures in health studies. As an illustration of the different uses of mixture methods, we employed methods geared toward distinct research questions concerning persistent organic chemicals (POPs) as a mixture and leukocyte telomere length (LTL) as an outcome. METHODS: With information on 18 POPs and LTL among 1,003 U.S. adults (NHANES, 2001-2002), we used unsupervised methods including clustering to identify profiles of similarly exposed participants, and Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) to identify common exposure patterns. We also employed supervised learning techniques, including penalized, weighted quantile sum (WQS), and Bayesian kernel machine (BKMR) regressions, to identify potentially toxic agents, and characterize nonlinear associations, interactions, and the overall mixture effect. RESULTS: Clustering separated participants into high, medium, and low POP exposure groups; longer log-LTL was found among those with high exposure. The first PCA component represented overall POP exposure and was positively associated with log-LTL. Two EFA factors, one representing furans and the other PCBs 126 and 118, were positively associated with log-LTL. Penalized regression methods selected three congeners in common (PCB 126, PCB 118, and furan 2,3,4,7,8-pncdf) as potentially toxic agents. WQS found a positive overall effect of the POP mixture and identified six POPs as potentially toxic agents (furans 1,2,3,4,6,7,8-hxcdf, 2,3,4,7,8-pncdf, and 1,2,3,6,7,8-hxcdf, and PCBs 99, 126, 169). BKMR found a positive linear association with furan 2,3,4,7,8-pncdf, suggestive evidence of linear associations with PCBs 126 and 169, and a positive overall effect of the mixture, but no interactions among congeners. CONCLUSIONS: Using different methods, we identified patterns of POP exposure, potentially toxic agents, the absence of interaction, and estimated the overall mixture effect. These applications and results may serve as a guide for mixture method selection based on specific research questions.