Associations of self-reported occupational exposures and settings to ALS: a case-control study.

BACKGROUND: Environmental exposures contribute to the pathogenesis of amyotrophic lateral sclerosis (ALS), a fatal and progressive neurological disease. Identification of these exposures is important for targeted screening and risk factor modification. OBJECTIVE: To identify occupational exposures that are associated with a higher risk of ALS using both survey and standard occupational classification (SOC) coding procedures, and to highlight how exposure surveys can complement SOC coding. METHODS: ALS participants and neurologically healthy controls recruited in Michigan completed a detailed exposure assessment on their four most recent and longest held occupations. Exposure scores were generated from the exposure survey, and occupations were assigned to SOC codes by experienced exposure scientists. RESULTS: This study included 381 ALS and 272 control participants. ALS participants reported higher duration-adjusted occupational exposure to particulate matter (OR = 1.45, 95% CI 1.19-1.78, p < 0.001), volatile organic compounds (OR = 1.22, 95% CI 1.02-1.45, p = 0.029), metals (OR = 1.48, 95% CI 1.21-1.82, p < 0.001), and combustion and diesel exhaust pollutants (OR = 1.20, 95% CI 1.01-1.43, p = 0.041) prior to ALS diagnosis, when adjusted for sex, age, and military service compared to controls. In multivariable models, only occupational exposure to metals remained significant risk (OR = 1.56, 95% CI 1.11-2.20, p = 0.011), although in an adaptive elastic net model, particulate matter (OR = 1.203), pesticides (OR = 1.015), and metals (1.334) were all selected as risk factors. Work in SOC code "Production Occupations" was associated with a higher ALS risk. SOC codes "Building and Grounds Cleaning and Maintenance Occupations", "Construction and Extraction Occupations", "Installation, Maintenance, and Repair Occupations", and "Production Occupations" were all associated with a higher exposure to metals as determined using survey data. DISCUSSION: Occupational exposure to particulate matter, volatile organic compounds, metals, pesticides, and combustion and diesel exhaust and employment in "Production Occupations" was associated with an increased ALS risk in this cohort.

Opportunities and challenges in reducing personal inhalation exposure to air pollution among electronic waste recovery workers in Ghana.

BACKGROUND: Informal sector electronic waste (e-waste) recovery produces toxic emissions resulting from burning e-waste to recover valuable metals. OBJECTIVES: To identify high-risk worker groups by measuring relative levels of personal inhalation exposure to particulate matter (PM) of fine (≤2.5 µm) and coarse (2.5-10 µm) fractions (PM2.5 and PM2.5-10, respectively) across work activities among e-waste workers, and to assess how wind conditions modify levels of PM by activity and site location. METHODS: At the Agbogbloshie e-waste site, 170 partial-shift PM samples and time-activity data were collected from participants (N = 105) enrolled in the GeoHealth cohort study. Personal sampling included continuous measures of size-specific PM from the worker's breathing zone and time-activity derived from wearable cameras. Linear mixed models were used to estimate changes in personal PM2.5 and PM2.5-10 associated with activities and evaluate effect modification by wind conditions. RESULTS: Mean (±standard deviation) personal PM2.5 and PM2.5-10 concentrations were 80 (± 81) and 123 (± 139) µg m-3 , respectively. The adjusted mean PM2.5 concentration for burning e-waste was 88 µg m-3 , a 28% increase above concentrations during non-recovery activities (such as eating). Transportation-related and burning activities were associated with the highest PM2.5-10 concentrations. Frequent changes in wind direction were associated with higher PM2.5 concentrations when burning, and high wind speeds with higher PM2.5-10 concentrations when dismantling e-waste downwind of the burning zone.

Urban-scale variation in pollen concentrations: A single station is insufficient to characterize daily exposure.

Epidemiological analyses of airborne allergenic pollen often use concentration measurements from a single station to represent exposure across a city, but this approach does not account for the spatial variation of concentrations within the city. Because there are few descriptions of urban-scale variation, the resulting exposure measurement error is unknown but potentially important for epidemiological studies. This study examines urban scale variation in pollen concentrations by measuring pollen concentrations of 13 taxa over 24-hr periods twice weekly at 25 sites in two seasons in Detroit, Michigan. Spatio-temporal variation is described using cumulative distribution functions and regression models. Daily pollen concentrations across the 25 stations varied considerably, and the average quartile coefficient of dispersion was 0.63. Measurements at a single site explained 3-85% of the variation at other sites, depending on the taxon, and 95% prediction intervals of pollen concentrations generally spanned one to two orders of magnitude. These results demonstrate considerable heterogeneity of pollen levels at the urban scale, and suggest that the use of a single monitoring site will not reflect pollen exposure over an urban area and can lead to sizable measurement error in epidemiological studies, particularly when a daily time-step is used. These errors might be reduced by using predictive daily pollen levels in models that combine vegetation maps, pollen production estimates, phenology models and dispersion processes, or by using coarser time-steps in the epidemiological analysis.

Pollen production for 13 urban North American tree species: Allometric equations for tree trunk diameter and crown area.

Estimates of airborne pollen concentrations at the urban scale would be useful for epidemiologists, land managers, and allergy sufferers. Mechanistic models could be well suited for this task, but their development will require data on pollen production across cities, including estimates of pollen production by individual trees. In this study, we developed predictive models for pollen production as a function of trunk size, canopy area, and height, which are commonly recorded in tree surveys or readily extracted from remote sensing data. Pollen production was estimated by measuring the number of flowers per tree, the number of anthers per flower, and the number of pollen grains per anther. Variability at each morphological scale was assessed using bootstrapping. Pollen production was estimated for the following species: Acer negundo, Acer platanoides, Acer rubrum, Acer saccharinum, Betula papyrifera, Gleditsia triacanthos, Juglans nigra, Morus alba, Platanus x acerfolia, Populus deltoides, Quercus palustris, Quercus rubra, and Ulmus americana. Basal area predicted pollen production with a mean R2 of 0.72 (range: 0.41 - 0.99), whereas canopy area predicted pollen production with a mean R2 of 0.76 (range: 0.50 - 0.99). These equations are applied to two tree datasets to estimate total municipal pollen production and the spatial distribution of street tree pollen production for the focal species. We present some of the first individual-tree based estimates of pollen production at the municipal scale; the observed spatial heterogeneity in pollen production is substantial and can feasibly be included in mechanistic models of airborne pollen at fine spatial scales.

Impact of community respiratory viral infections in urban children with asthma.

BACKGROUND: Upper respiratory tract viral infections cause asthma exacerbations in children. However, the impact of natural colds on children with asthma in the community, particularly in the high-risk urban environment, is less well defined. OBJECTIVE: We hypothesized that children with high-symptom upper respiratory viral infections have reduced airway function and greater respiratory tract inflammation than children with virus-positive low-symptom illnesses or virus-negative upper respiratory tract symptoms. METHODS: We studied 53 children with asthma from Detroit, Michigan, during scheduled surveillance periods and self-reported respiratory illnesses for 1 year. Symptom score, spirometry, fraction of exhaled nitric oxide (FeNO), and nasal aspirate biomarkers, and viral nucleic acid and rhinovirus (RV) copy number were assessed. RESULTS: Of 658 aspirates collected, 22.9% of surveillance samples and 33.7% of respiratory illnesses were virus-positive. Compared with the virus-negative asymptomatic condition, children with severe colds (symptom score ≥5) showed reduced forced expiratory flow at 25% to 75% of the pulmonary volume (FEF25%-75%), higher nasal messenger RNA expression of C-X-C motif chemokine ligand (CXCL)-10 and melanoma differentiation-associated protein 5, and higher protein abundance of CXCL8, CXCL10 and C-C motif chemokine ligands (CCL)-2, CCL4, CCL20, and CCL24. Children with mild (symptom score, 1-4) and asymptomatic infections showed normal airway function and fewer biomarker elevations. Virus-negative cold-like illnesses demonstrated increased FeNO, minimal biomarker elevation, and normal airflow. The RV copy number was associated with nasal chemokine levels but not symptom score. CONCLUSION: Urban children with asthma with high-symptom respiratory viral infections have reduced FEF25%-75% and more elevations of nasal biomarkers than children with mild or symptomatic infections, or virus-negative illnesses.

Evaluation of Changes in Lead Levels in Drinking Water Due to Replacement of Water Mains: A Comprehensive Study in Chicago, Illinois.

Disturbances to water treatment and distribution systems using lead service lines have been reported to increase water lead levels. This study evaluates effects from one type of physical disturbance, namely, water mains replacement. Lead concentrations at 542 homes in Chicago, Illinois were measured using partial profile sampling (1st, 4th, 6th and 5th min 1-L samples) after 6-h stagnation, both before and after mains replacement; a subset had monthly follow-up sampling for an additional 12 months. Concentrations were correlated from month-to-month and depended on household water consumption, temperature, residence age, and other factors. The sampling event maximum yielded considerably higher concentrations than first-draw samples, and 5 min flush samples had the lowest concentration at nearly all homes. Mains replacement was associated with less than a 1 µg/L increase in median and 90th percentile concentrations; changes were smaller or not seen after controlling for other factors. Transient lead peaks were identified in a subset of residences and visits. These findings in Chicago indicate that mains replacement did not produce large changes in Pb concentrations in samples collected 1 to 12 months following the disturbance. We recommend continued outreach to promote flushing and other actions to minimize lead exposure, and routine use of profile sampling.

Absence of PCB Hot Spot Effect in Walleye Sander vitreus from Lower Green Bay of Lake Michigan.

Under certain conditions, polychlorinated biphenyl (PCB) concentration in individuals of one sex of an adult fish population may exceed that of the other sex by more than a factor of two. This phenomenon, known as the PCB hot spot effect, has been postulated to be contingent upon the following two conditions: (1) presence of a PCB hot spot in the bottom sediments of the aquatic ecosystem, such that prey PCB concentrations in the hot spot region are substantially higher than prey PCB concentrations in locations distant from the hot spot, and (2) habitat use varying between the sexes, such that individuals of one sex inhabit the hot spot region to a considerably greater degree than individuals of the other sex. To test whether PCB concentrations in walleye Sander vitreus from lower Green Bay of Lake Michigan displayed a PCB hot spot effect, whole-fish PCB concentrations were determined in ten female and ten male adult walleye from the population spawning in the Fox River, the main tributary to lower Green Bay. In addition, mark-recapture data for the Fox River walleye population were analyzed to determine differences in spatial distributions between the sexes. Results revealed that the ratio of mean PCB concentration in males to mean PCB concentration in females was only 1.13, indicating the absence of a PCB hot spot effect. This result was corroborated by the mark-recapture data analysis, which showed no significant difference in habitat use between the sexes. Thus, although condition 1 was met, condition 2 was not met. Consequently, the PCB hot spot effect was not observed in the Fox River walleye population. Lack of a significant difference in PCB congener distributions between the sexes further corroborated our conclusions.

Allergenic pollen production across a large city for common ragweed (Ambrosia artemisiifolia).

Predictions of airborne allergenic pollen concentrations at fine spatial scales require information on source plant location and pollen production. Such data are lacking at the urban scale, largely because manually mapping allergenic pollen producing plants across large areas is infeasible. However, modest-sized field surveys paired with allometric equations, remote sensing, and habitat distribution models can predict where these plants occur and how much pollen they produce. In this study, common ragweed (Ambrosia artemisiifolia) was mapped in a field survey in Detroit, MI, USA. The relationship between ragweed presence and habitat-related variables derived from aerial imagery, LiDAR, and municipal data were used to create a habitat distribution model, which was then used to predict ragweed presence across the study area (392 km2). The relationship between inflorescence length and pollen production was used to predict pollen production in the city. Ragweed occurs in 1.7% of Detroit and total pollen production is 312 × 1012 pollen grains annually, but ragweed presence was highly heterogeneous across the city. Ragweed was predominantly found in in vacant lots (75%) and near demolished structures (48%), and had varying associations with land cover types (e.g., sparse vegetation, trees, pavement) detected by remote sensing. These findings also suggest several management strategies that could help reduce levels of allergenic pollen, including appropriate post-demolition management practices. Spatially-resolved predictions for pollen production will allow mechanistic modeling of airborne allergenic pollen and improved exposure estimates for use in epidemiological and other applications.

Influence of viral infection on the relationships between airway cytokines and lung function in asthmatic children.

BACKGROUND: Few longitudinal studies examine inflammation and lung function in asthma. We sought to determine the cytokines that reduce airflow, and the influence of respiratory viral infections on these relationships. METHODS: Children underwent home collections of nasal lavage during scheduled surveillance periods and self-reported respiratory illnesses. We studied 53 children for one year, analyzing 392 surveillance samples and 203 samples from 85 respiratory illnesses. Generalized estimated equations were used to evaluate associations between nasal lavage biomarkers (7 mRNAs, 10 proteins), lung function and viral infection. RESULTS: As anticipated, viral infection was associated with increased cytokines and reduced FVC and FEV1. However, we found frequent and strong interactions between biomarkers and virus on lung function. For example, in the absence of viral infection, CXCL10 mRNA, MDA5 mRNA, CXCL10, IL-4, IL-13, CCL4, CCL5, CCL20 and CCL24 were negatively associated with FVC. In contrast, during infection, the opposite relationship was frequently found, with IL-4, IL-13, CCL5, CCL20 and CCL24 levels associated with less severe reductions in both FVC and FEV1. CONCLUSIONS: In asthmatic children, airflow obstruction is driven by specific pro-inflammatory cytokines. In the absence of viral infection, higher cytokine levels are associated with decreasing lung function. However, with infection, there is a reversal in this relationship, with cytokine abundance associated with reduced lung function decline. While nasal samples may not reflect lower airway responses, these data suggest that some aspects of the inflammatory response may be protective against viral infection. This study may have ramifications for the treatment of viral-induced asthma exacerbations.

Effectiveness of Using Enhanced Filters in Schools and Homes to Reduce Indoor Exposures to PM2.5 from Outdoor Sources and Subsequent Health Benefits for Children with Asthma.

Filters can reduce indoor concentrations of particulate matter (PM2.5), but their benefits have not been well-characterized. This study investigates exposure, health, and cost impacts of high efficiency filters in homes and schools, focusing on the asthma-related outcomes. Reductions in indoor exposures to PM2.5 from outdoor sources with enhanced filters (e.g., MERV 12) are estimated using probabilistic indoor air quality models, and avoided health impacts are quantified using health impact assessment. These methods are applied using data from Detroit, Michigan, an urban region with elevated asthma rates. Replacing inefficient filters with enhanced filters in schools would reduce the PM2.5-attributable asthma burden by 13% annually, with higher benefits for more efficient filters. Marginal costs average $63 per classroom or $32 per child with asthma per year. In homes, using efficient furnace filters or air cleaners yields 11 to 16% reductions in the asthma burden with an annualized marginal costs of $151-494 per household. Additional benefits include reductions in health risk for adults and lower exposures to other contaminants such as PM from indoor sources. On the basis of the included health outcomes, efficient filters in schools in particular is a potentially cost-efficient way to reduce the asthma-related health burden for children.

Distributions of PCB Congeners and Homologues in White Sucker and Coho Salmon from Lake Michigan.

We tested the hypothesis of the proportion of higher chlorinated biphenyl (PCB) congeners increasing with increasing trophic level by comparing the respective PCB homologue distributions in an omnivore, white sucker ( Catostomus commersoni), and a top predator, coho salmon ( Oncorhynchus kisutch), from Lake Michigan. Adult females had the same congener and homologue proportions of total PCB concentration (ΣPCB) as adult males in both species. Hexachlorinated congeners comprised the largest proportion (32%) found in white sucker, followed by heptachlorinated (21%) and octochlorinated (18%) congeners. In contrast, pentachlorinated congeners comprised the largest proportion (33%) of ΣPCB found in coho salmon, followed by hexachlorinated (26%) and tetrachlorinated (24%) congeners. Coho salmon contained significantly higher proportions of tri-, tetra-, and pentachlorinated congeners, whereas white sucker contained significantly higher proportions of hexa- through decachlorinated congeners. Our results were opposite of the hypothesis of greater degree of PCB chlorination with increasing trophic level, and supported the contention that the PCB congener proportions in fish depends mainly on diet, and does not necessarily reflect the trophic level of the fish. Our results also supported the contention that diets do not vary between the sexes in most fish populations.

Operational evaluation of the RLINE dispersion model for studies of traffic-related air pollutants.

Exposure to traffic-related air pollutants (TRAP) remains a key public health issue, and improved exposure measures are needed to support health impact and epidemiologic studies and inform regulatory responses. The recently developed Research LINE source model (RLINE), a Gaussian line source dispersion model, has been used in several epidemiologic studies of TRAP exposure, but evaluations of RLINE's performance in such applications have been limited. This study provides an operational evaluation of RLINE in which predictions of NOx, CO and PM2.5 are compared to observations at air quality monitoring stations located near high traffic roads in Detroit, MI. For CO and NOx, model performance was best at sites close to major roads, during downwind conditions, during weekdays, and during certain seasons. For PM2.5, the ability to discern local and particularly the traffic-related portion was limited, a result of high background levels, the sparseness of the monitoring network, and large uncertainties for certain processes (e.g., formation of secondary aerosols) and non-mobile sources (e.g., area, fugitive). Overall, RLINE's performance in near-road environments suggests its usefulness for estimating spatially- and temporally-resolved exposures. The study highlights considerations relevant to health impact and epidemiologic applications, including the importance of selecting appropriate pollutants, using appropriate monitoring approaches, considering prevailing wind directions during study design, and accounting for uncertainty.

Sensitivity analysis of the near-road dispersion model RLINE - an evaluation at Detroit, Michigan.

The development of accurate and appropriate exposure metrics for health effect studies of traffic-related air pollutants (TRAPs) remains challenging and important given that traffic has become the dominant urban exposure source and that exposure estimates can affect estimates of associated health risk. Exposure estimates obtained using dispersion models can overcome many of the limitations of monitoring data, and such estimates have been used in several recent health studies. This study examines the sensitivity of exposure estimates produced by dispersion models to meteorological, emission and traffic allocation inputs, focusing on applications to health studies examining near-road exposures to TRAP. Daily average concentrations of CO and NOx predicted using the Research Line source model (RLINE) and a spatially and temporally resolved mobile source emissions inventory are compared to ambient measurements at near-road monitoring sites in Detroit, MI, and are used to assess the potential for exposure measurement error in cohort and population-based studies. Sensitivity of exposure estimates is assessed by comparing nominal and alternative model inputs using statistical performance evaluation metrics and three sets of receptors. The analysis shows considerable sensitivity to meteorological inputs; generally the best performance was obtained using data specific to each monitoring site. An updated emission factor database provided some improvement, particularly at near-road sites, while the use of site-specific diurnal traffic allocations did not improve performance compared to simpler default profiles. Overall, this study highlights the need for appropriate inputs, especially meteorological inputs, to dispersion models aimed at estimating near-road concentrations of TRAPs. It also highlights the potential for systematic biases that might affect analyses that use concentration predictions as exposure measures in health studies, e.g., to estimate health impacts.

Air Pollution Exposure Model for Individuals (EMI) in Health Studies: Evaluation for Ambient PM2.5 in Central North Carolina.

Air pollution health studies of fine particulate matter (diameter ≤2.5 µm, PM2.5) often use outdoor concentrations as exposure surrogates. Failure to account for variability of indoor infiltration of ambient PM2.5 and time indoors can induce exposure errors. We developed and evaluated an exposure model for individuals (EMI), which predicts five tiers of individual-level exposure metrics for ambient PM2.5 using outdoor concentrations, questionnaires, weather, and time-location information. We linked a mechanistic air exchange rate (AER) model to a mass-balance PM2.5 infiltration model to predict residential AER (Tier 1), infiltration factors (Tier 2), indoor concentrations (Tier 3), personal exposure factors (Tier 4), and personal exposures (Tier 5) for ambient PM2.5. Using cross-validation, individual predictions were compared to 591 daily measurements from 31 homes (Tiers 1-3) and participants (Tiers 4-5) in central North Carolina. Median absolute differences were 39% (0.17 h(-1)) for Tier 1, 18% (0.10) for Tier 2, 20% (2.0 µg/m(3)) for Tier 3, 18% (0.10) for Tier 4, and 20% (1.8 µg/m(3)) for Tier 5. The capability of EMI could help reduce the uncertainty of ambient PM2.5 exposure metrics used in health studies.

Effects of fuels, engine load and exhaust after-treatment on diesel engine SVOC emissions and development of SVOC profiles for receptor modeling.

Diesel exhaust emissions contain numerous semivolatile organic compounds (SVOCs) for which emission information is limited, especially for idling conditions, new fuels and the new after-treatment systems. This study investigates exhaust emissions of particulate matter (PM), polycyclic aromatic hydrocarbons (PAHs), nitro-PAHs (NPAHs), and sterane and hopane petroleum biomarkers from a heavy-duty (6.4 L) diesel engine at various loads (idle, 600 and 900 kPa BMEP), with three types of fuel (ultra-low sulfur diesel or ULSD, Swedish low aromatic diesel, and neat soybean biodiesel), and with and without a diesel oxidation catalyst (DOC) and diesel particulate filter (DPF). Swedish diesel and biodiesel reduced emissions of PM2.5, Σ15PAHs, Σ11NPAHs, Σ5Hopanes and Σ6Steranes, and biodiesel resulted in the larger reductions. However, idling emissions increased for benzo[k]fluoranthene (Swedish diesel), 5-nitroacenaphthene (biodiesel) and PM2.5 (biodiesel), a significant result given the attention to exposures from idling vehicles and the toxicity of high-molecular-weight PAHs and NPAHs. The DOC + DPF combination reduced PM2.5 and SVOC emissions during DPF loading (>99% reduction) and DPF regeneration (83-99%). The toxicity of diesel exhaust, in terms of the estimated carcinogenic risk, was greatly reduced using Swedish diesel, biodiesel fuels and the DOC + DPF. PAH profiles showed high abundances of three and four ring compounds as well as naphthalene; NPAH profiles were dominated by nitro-naphthalenes, 1-nitropyrene and 9-nitroanthracene. Both the emission rate and the composition of diesel exhaust depended strongly on fuel type, engine load and after-treatment system. The emissions data and chemical profiles presented are relevant to the development of emission inventories and exposure and risk assessments.

Multimedia model for polycyclic aromatic hydrocarbons (PAHs) and nitro-PAHs in Lake Michigan.

Polycyclic aromatic hydrocarbon (PAH) contamination in the U.S. Great Lakes has long been of concern, but information regarding the current sources, distribution, and fate of PAH contamination is lacking, and very little information exists for the potentially more toxic nitro-derivatives of PAHs (NPAHs). This study uses fugacity, food web, and Monte Carlo models to examine 16 PAHs and five NPAHs in Lake Michigan, and to derive PAH and NPAH emission estimates. Good agreement was found between predicted and measured PAH concentrations in air, but concentrations in water and sediment were generally under-predicted, possibly due to incorrect parameter estimates for degradation rates, discharges to water, or inputs from tributaries. The food web model matched measurements of heavier PAHs (≥5 rings) in lake trout, but lighter PAHs (≤4 rings) were overpredicted, possibly due to overestimates of metabolic half-lives or gut/gill absorption efficiencies. Derived PAH emission rates peaked in the 1950s, and rates now approach those in the mid-19th century. The derived emission rates far exceed those in the source inventories, suggesting the need to reconcile differences and reduce uncertainties. Although additional measurements and physiochemical data are needed to reduce uncertainties and for validation purposes, the models illustrate the behavior of PAHs and NPAHs in Lake Michigan, and they provide useful and potentially diagnostic estimates of emission rates.

Cross-shift changes in pulmonary function and occupational exposure to particulate matter among e-waste workers in Ghana.

Introduction: Little is known on the association between cross-shift changes in pulmonary function and personal inhalation exposure to particulate matter (PM) among informal electronic-waste (e-waste) recovery workers who have substantial occupational exposure to airborne pollutants from burning e-waste. Methods: Using a cross-shift design, pre- and post-shift pulmonary function assessments and accompanying personal inhalation exposure to PM (sizes <1, <2.5 µm, and the coarse fraction, 2.5-10 µm in aerodynamic diameter) were measured among e-waste workers (n = 142) at the Agbogbloshie e-waste site and a comparison population (n = 65) in Accra, Ghana during 2017 and 2018. Linear mixed models estimated associations between percent changes in pulmonary function and personal PM. Results: Declines in forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) per hour were not significantly associated with increases in PM (all sizes) among either study population, despite breathing zone concentrations of PM (all sizes) that exceeded health-based guidelines in both populations. E-waste workers who worked "yesterday" did, however, have larger cross-shift declines in FVC [-2.4% (95%CI: -4.04%, -0.81%)] in comparison to those who did not work "yesterday," suggesting a possible role of cumulative exposure. Discussion: Overall, short-term respiratory-related health effects related to PM exposure among e-waste workers were not seen in this sample. Selection bias due to the "healthy worker" effect, short shift duration, and inability to capture a true "pre-shift" pulmonary function test among workers who live at the worksite may explain results and suggest the need to adapt cross-shift studies for informal settings.

Avocational exposure associations with ALS risk, survival, and phenotype: A Michigan-based case-control study.

INTRODUCTION: Environmental exposures strongly influence ALS risk and identification is needed to reduce ALS burden. Participation in hobbies and exercise may alter ALS risk and phenotype, warranting an assessment to understand their contribution to the ALS exposome. METHODS: Participants with ALS and healthy controls were recruited from University of Michigan and self-completed a survey to ascertain hobbies, exercise, and avocational exposures. Exposure variables were associated with ALS risk, survival, onset segment, and onset age. RESULTS: ALS (n = 400) and control (n = 287) participants self-reported avocational activities. Cases were slightly older (median age 63.0 vs. 61.1 years, p = 0.019) and had a lower educational attainment (p < 0.001) compared to controls; otherwise, demographics were well balanced. Risks associating with ALS after multiple comparison correction included golfing (odds ratio (OR) 3.48, padjusted = 0.004), recreational dancing (OR 2.00, padjusted = 0.040), performing gardening or yard work (OR 1.71, padjusted = 0.040) five years prior to ALS and personal (OR 1.76, padjusted = 0.047) or family (OR 2.21, padjusted = 0.040) participation in woodworking, and personal participation in hunting and shooting (OR 1.89, padjusted = 0.040). No exposures associated with ALS survival and onset. Those reporting swimming (3.86 years, padjusted = 0.016) and weightlifting (3.83 years, padjusted = 0.020) exercise 5 years prior to ALS onset had an earlier onset age. DISCUSSION: The identified exposures in this study may represent important modifiable ALS factors that influence ALS phenotype. Thus, exposures related to hobbies and exercise should be captured in studies examining the ALS exposome.

Residential exposure associations with ALS risk, survival, and phenotype: a Michigan-based case-control study.

Background: Environmental exposures impact amyotrophic lateral sclerosis (ALS) risk and progression, a fatal and progressive neurodegenerative disease. Better characterization of these exposures is needed to decrease disease burden. Objective: To identify exposures in the residential setting that associate with ALS risk, survival, and onset segment. Methods: ALS and control participants recruited from University of Michigan completed a survey that ascertained exposure risks in the residential setting. ALS risk was assessed using logistic regression models followed by latent profile analysis to consider exposure profiles. A case-only analysis considered the contribution of the residential exposure variables via a Cox proportional hazards model for survival outcomes and multinomial logistic regression for onset segment, a polytomous outcome. Results: This study included 367 ALS and 255 control participants. Twelve residential variables were associated with ALS risk after correcting for multiple comparison testing, with storage in an attached garage of chemical products including gasoline or kerosene (odds ratio (OR) = 1.14, padjusted < 0.001), gasoline-powered equipment (OR = 1.16, padjusted < 0.001), and lawn care products (OR = 1.15, padjusted < 0.001) representing the top three risk factors sorted by padjusted. Latent profile analysis indicated that storage of these chemical products in both attached and detached garages increased ALS risk. Although residential variables were not associated with poorer ALS survival following multiple testing corrections, storing pesticides, lawn care products, and woodworking supplies in the home were associated with shorter ALS survival using nominal p values. No exposures were associated with ALS onset segment. Conclusion: Residential exposures may be important modifiable components of the ALS susceptibility and prognosis exposome.

Metal mixtures associate with higher amyotrophic lateral sclerosis risk and mortality independent of genetic risk and correlate to self-reported exposures: a case-control study.

Background: The pathogenesis of amyotrophic lateral sclerosis (ALS) involves both genetic and environmental factors. This study investigates associations between metal measures in plasma and urine, ALS risk and survival, and exposure sources. Methods: Participants with and without ALS from Michigan provided plasma and urine samples for metal measurement via inductively coupled plasma mass spectrometry. Odds and hazard ratios for each metal were computed using risk and survival models. Environmental risk scores (ERS) were created to evaluate the association between exposure mixtures and ALS risk and survival and exposure source. ALS (ALS-PGS) and metal (metal-PGS) polygenic risk scores were constructed from an independent genome-wide association study and relevant literature-selected SNPs. Results: Plasma and urine samples from 454 ALS and 294 control participants were analyzed. Elevated levels of individual metals, including copper, selenium, and zinc, significantly associated with ALS risk and survival. ERS representing metal mixtures strongly associated with ALS risk (plasma, OR=2.95, CI=2.38-3.62, p<0.001; urine, OR=3.10, CI=2.43-3.97, p<0.001) and poorer ALS survival (plasma, HR=1.42, CI=1.24-1.63, p<0.001; urine, HR=1.52, CI=1.31-1.76, p<0.001). Addition of the ALS-PGS or metal-PGS did not alter the significance of metals with ALS risk and survival. Occupations with high potential of metal exposure associated with elevated ERS. Additionally, occupational and non-occupational metal exposures associated with measured plasma and urine metals. Conclusion: Metals in plasma and urine associated with increased ALS risk and reduced survival, independent of genetic risk, and correlated with occupational and non-occupational metal exposures. These data underscore the significance of metal exposure in ALS risk and progression.