Advocating for healthy environments is a matter of justice. Changes in environments have tremendous impacts on the health of communities, and oftentimes, individuals are unable to safeguard themselves through individual actions alone. Efforts frequently require collective action and are often most effective when led by the communities most impacted. In this spirit, we launched "Vibrations", an African environment photo essay contest. Through funding and publicity, we aimed to support community-led environmental improvement and education initiatives presently taking place on the continent. We received nearly two dozen submissions and selected eight winners. The winners come from five countries (Ghana, Kenya, Mozambique, Nigeria, and South Africa) and have taken on a range of projects aimed at improving environments across a variety of African regions. Projects included efforts to combat pollution, create environmentally conscious school curricula, utilize clean energy sources, and spread awareness about environmental justice concerns in local communities. It is our hope that this report highlights these transformative community-driven efforts, promotes continued conversations on environmental justice in Africa, and encourages meaningful action via policy changes and collaborations throughout the African continent and beyond.

BACKGROUND: Exposure data with repeated measures from occupational studies are frequently right-skewed and left-censored. To address right-skewed data, data are generally log-transformed and analyses modeling the geometric mean operate under the assumption the data are log-normally distributed. However, modeling the mean of exposure may lead to bias and loss of efficiency if the transformed data do not follow a known distribution. In addition, left censoring occurs when measurements are below the limit of detection (LOD). OBJECTIVE: To present a complete illustration of the entire conditional distribution of an exposure outcome by examining different quantiles, rather than modeling the mean. METHODS: We propose an approach combining the quantile regression model, which does not require any specified error distributions, with the substitution method for skewed data with repeated measurements and non-detects. RESULTS: In a simulation study and application example, we demonstrate that this method performs well, particularly for highly right-skewed data, as parameter estimates are consistent and have smaller mean squared error relative to existing approaches. SIGNIFICANCE: The proposed approach provides an alternative insight into the conditional distribution of an exposure outcome for repeated measures models.

In June 2018, the National Institute of Diabetes and Digestive and Kidney Diseases and the National Institute of Environmental Health Sciences sponsored a workshop to identify research gaps in an increasingly common form of chronic kidney disease in agricultural communities, often termed "CKDu." The organizers invited a broad range of experts who provided diverse expertise and perspectives, many of whom had never addressed this particular epidemic. Discussion was focused around selected topics, including identifying and mitigating barriers to research in CKDu, creating a case definition, and defining common data elements. All hypotheses regarding etiology were entertained, and meeting participants discussed potential research strategies, choices in study design, and novel tools that may prove useful in this disease. Achievements of the workshop included robust cross-disciplinary discussion and preliminary planning of research goals and design. Specific challenges in implementing basic and clinical research and interventions in low- and middle-income countries were recognized. A balanced approach to leveraging local resources and capacity building without overreaching was emphasized.

Flavorings are substances that alter or enhance the taste of food. Workers in the food-manufacturing industry, where flavorings are added to many products, may be exposed to any number of flavoring compounds. Although thousands of flavoring substances are in use, little is known about most of these in terms of worker health effects, and few have occupational exposure guidelines. Exposure assessment surveys were conducted at nine food production facilities and one flavor manufacturer where a total of 105 area and 74 personal samples were collected for 13 flavoring compounds including five ketones, five aldehydes, and three acids. The majority of the samples were below the limit of detection (LOD) for most compounds. Diacetyl had eight area and four personal samples above the LOD, whereas 2,3-pentanedione had three area samples above the LOD. The detectable values ranged from 25-3124 ppb and 15-172 ppb for diacetyl and 2,3-pentanedione respectively. These values exceed the proposed National Institute for Occupational Safety and Health (NIOSH) recommended exposure limit for these compounds. The aldehydes had the most detectable samples, with each of them having >50% of the samples above the LOD. Acetaldehyde had all but two samples above the LOD, however, these samples were below the OSHA PEL. It appears that in the food-manufacturing facilities surveyed here, exposure to the ketones occurs infrequently, however levels above the proposed NIOSH REL were found. Conversely, aldehyde exposure appears to be ubiquitous.

Twenty-nine commercial pesticide applicator households in eastern Iowa were enrolled to investigate in-home contamination of atrazine, the most commonly used corn herbicide in the Unites States. From each home, four vacuum dust samples were collected during atrazine application season (Visit 1) and again 6 months later during winter months (Visit 2). Samples were taken from the following locations: primary entryway for pesticide applicator, living room, master bedroom, and kitchen. The applicator completed an atrazine handling log and household questionnaire with spouse. Of the 230 dust samples, only 2 were below the level of detection, 2 ng of atrazine per gram (ng/g) of fine dust (dust particle size 5-150 mcm). Dust levels were standardized to chemical loading. During application season the entryway (2.68 ng/cm(2)) and kitchen (0.47 ng/cm(2)) had the highest geometric mean atrazine chemical loading. The entryway chemical loading during Visit 2 was the second highest aggregate (0.55 ng/cm(2)). Aggregate concentrations were significantly higher at Visit 1 compared with Visit 2 when paired by location (p≤0.02). Analysis showed that job (application, mixing/loading, or both) was not associated with in-home atrazine contamination. Linear regression showed a strong positive association between atrazine handling (number of acres applied with atrazine, number of days atrazine handled, and pounds of atrazine handled) and aggregate dust chemical loading from both visits (p = 0.06, 0.03, and 0.10, respectively). Frequency of vacuuming was inversely associated with Visit 2 concentrations (p = 0.10) and showed a weaker association with Visit 1 (p = 0.30). Removing shoes outside the home was associated with lower atrazine chemical loading (p = 0.03), and applicators changing work clothes in the master bedroom had significantly increased atrazine chemical loading in master bedrooms (p = 0.01). Changes in hygiene practices for commercial pesticide applicators could significantly reduce atrazine and, likely, other pesticide contaminations in the home.

The hazards of chronic low-level pesticide exposures inside homes have received little attention. Research to date does not provide answers regarding the long-term potential bioavailability of pesticides in homes and its risk factors. The purpose of this study was to investigate pesticide levels in Iowa homes during one year and assess the relationship between exposure levels and potential sources of pesticide contamination. The study involved sampling surveys of the target pesticide atrazine among 32 farm families in a three-county area of Iowa during the planting season (April–June) and nonplanting season (November-December). Dust samples were collected, and information gathered through questionnaires to evaluate pesticide migration inside homes. This study found that dust in every farm home surveyed was contaminated with atrazine during both seasons and these concentrations significantly decreased by the nonplanting season. Pesticide amounts, acreage, and spraying time determined the presence and persistence of this herbicide inside farm homes.

An algorithm developed to estimate pesticide exposure intensity for use in epidemiologic analyses was revised based on data from two exposure monitoring studies. In the first study, we estimated relative exposure intensity based on the results of measurements taken during the application of the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) (n = 88) and the insecticide chlorpyrifos (n = 17). Modifications to the algorithm weighting factors were based on geometric means (GM) of post-application urine concentrations for applicators grouped by application method and use of chemically-resistant (CR) gloves. Measurement data from a second study were also used to evaluate relative exposure levels associated with airblast as compared to hand spray application methods. Algorithm modifications included an increase in the exposure reduction factor for use of CR gloves from 40% to 60%, an increase in the application method weight for boom spray relative to in-furrow and for air blast relative to hand spray, and a decrease in the weight for mixing relative to the new weights assigned for application methods. The weighting factors for the revised algorithm now incorporate exposure measurements taken on Agricultural Health Study (AHS) participants for the application methods and personal protective equipment (PPE) commonly reported by study participants.

This study presents exposure data for various metal oxides in facilities that produce or use nanoscale metal oxides. Exposure assessment surveys were conducted at seven facilities encompassing small, medium, and large manufacturers and end users of nanoscale (particles <0.1 mum diameter) metal oxides, including the oxides of titanium, magnesium, yttrium, aluminum, calcium, and iron. Half- and full-shift sampling consisting of various direct-reading and mass-based area and personal aerosol sampling was employed to measure exposure for various tasks. Workers in large facilities performing handling tasks had the highest mass concentrations for all analytes. However, higher mass concentrations occurred in medium facilities and during production for all analytes in area samples. Medium-sized facilities had higher particle number concentrations in the air, followed by small facilities for all particle sizes measured. Production processes generally had the highest particle number concentrations, particularly for the smaller particles. Similar to particle number, the medium-sized facilities and production process had the highest particle surface area concentration. TEM analysis confirmed the presence of the specific metal oxides particles of interest, and the majority of the particles were agglomerated, with the predominant particle size being between 0.1 and 1 mum. The greatest potential for exposure to workers occurred during the handling process. However, the exposure is occurring at levels that are well below established and proposed limits.

Urine samples were collected from 51 participants in a study investigating pesticide exposure among farm families in Iowa. Aliquots from the samples were sent to two different labs and analyzed for metabolites of atrazine (atrazine mercapturate), metolachlor (metolachlor mercapturate) and chlorpyrifos (TCP) by two different analytical methods: immunoassay and high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS). HPLC-MS/MS methods tend to be highly specific, but are costly and time consuming. Immunoassay methods are cheaper and faster, but can be less sensitive due to cross reactivity and matrix effects. Three statistical methods were employed to compare the two analytical methods. Each statistical method differed in how the samples that had results below the limit of detection (LOD) were treated. The first two methods involved an imputation procedure and the third method used maximum likelihood estimation (MLE). A fourth statistical method that modeled each lab separately using MLE was used for comparison. The immunoassay and HPLC-MS/MS methods were moderately correlated (correlation 0.40-0.49), but the immunoassay methods consistently had significantly higher geometric mean (GM) estimates for each pesticide metabolite. The GM estimates for atrazine mercapturate, metolachlor mercapturate, and TCP by immunoassay ranged from 0.16-0.98 microg l(-1), 0.24-0.45 microg l(-1) and 14-14 microg l(-1), respectively and by HPLC-MS/MS ranged from 0.0015-0.0039 microg l(-1), 0.12-0.16 microg l(-1), and 2.9-3.0 microg l(-1), respectively. Immunoassays tend to be cheaper and faster than HPLC-MS/MS, however, they may result in an upward bias of urinary pesticide metabolite levels.