Background: Chemicals in consumer products are a major contributor to human chemical co-exposures. Consumers purchase and use a wide variety of products containing potentially thousands of chemicals. There is a need to identify potential real-world chemical co-exposures in order to prioritize in vitro toxicity screening. However, due to the vast number of potential chemical combinations, this has been a major challenge. Objectives: We aim to develop and implement a data-driven procedure for identifying prevalent chemical combinations to which humans are exposed through purchase and use of consumer products. Methods: We applied frequent itemset mining on an integrated dataset linking consumer product chemical ingredient data with product purchasing data from sixty thousand households to identify chemical combinations resulting from co-use of consumer products. Results: We identified co-occurrence patterns of chemicals over all households as well as those specific to demographic groups based on race/ethnicity, income, education, and family composition. We also identified chemicals with the highest potential for aggregate exposure by identifying chemicals occurring in multiple products used by the same household. Lastly, a case study of chemicals active in estrogen and androgen receptor in silico models revealed priority chemical combinations co-targeting receptors involved in important biological signaling pathways. Discussion: Integration and comprehensive analysis of household purchasing data and product-chemical information provided a means to assess human near-field exposure and inform selection of chemical combinations for high-throughput screening in in vitro assays. This dataset is associated with the following publication: Stanfield, Z., C. Addington, K. Dionisio, D. Lyons, R. Tornero-Velez, K. Phillips, T. Buckley, and K. Isaacs. Mining of consumer product and purchasing data to identify potential chemical co-exposures.. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 129(6): N/A, (2021).

Data for publication Turley et al. "Applying the RISK21 approach to assess predictivity of new approach methodologies in toxicity testing and exposure assessment: a case study on food contact chemicals". Includes food concentration predictions from the model of Biryol et al. (2017) and SHEDS-HT exposure predictions. This dataset is associated with the following publication: Turley, A., K. Isaacs, B. Wetmore, A. Karmaus, M. Embry, and M. Krishan. Incorporating new approach methodologies in toxicity testing and exposure assessment for tiered risk assessment using the RISK21 approach: Case studies on food contact chemicals. FOOD AND CHEMICAL TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 134: 110819, (2019).

We created a consensus, meta-model using the Systematic Empirical Evaluation of Models framework in which the predictors of exposure were combined by pathway and weighted according to predictive ability for chemical intake rates inferred from human biomonitoring data for 114 chemicals. This dataset is associated with the following publication: Ring, C., J. Arnot, D. Bennett, P. Egeghy, P. Fantke, L. Huang, K. Isaacs, O. Jolliet, K. Phillips, P. Price, H. Shin, J. Westgate, R. Setzer, and J. Wambaugh. Consensus Modeling of Median Chemical Intake for the U.S. Population Based on Predictions of Exposure Pathways. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53(2): 719-732, (2019).

The Chemical and Product Categories database (CPCat) catalogs the use of over 40,000 chemicals and their presence in different consumer products. The chemical use information is compiled from multiple sources while product information is gathered from publicly available Material Safety Data Sheets (MSDS). EPA researchers are evaluating the possibility of expanding the database with additional product and use information.

Chemical concentration, exposure, and health risk data for U.S. census tracts from National Scale Air Toxics Assessment (NATA). This dataset is associated with the following publication: Huang, H., R. Tornero-Velez, and T. Barzyk. Associations between socio-demographic characteristics and chemical concentrations contributing to cumulative exposures in the United States. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 27(6): 544-550, (2017).

이 데이터는 보건환경연구원에서 실시하는 다양한 검사 항목의 수수료 정보를 정리한 자료입니다.항목별로 ‘구분’, ‘카테고리’, 검사 대상 ‘항목’, 그리고 해당 검사에 부과되는 ‘수수료’가 명확히 제시되어 있습니다.수질검사, 식품검사, 식품첨가물 검사, 의약품 검사, 폐기물 검사, 토양오염 검사 등 여러 분야에 걸친 검사 항목이 포함되어 있어 이용자가 필요한 검사 종류와 비용을 정확히 확인할 수 있습니다.이 자료는 민원인, 사업장, 행정기관이 검사 비용을 사전에 파악하여 행정 절차를 준비하는 데 활용되며, 공공 검사 서비스의 투명성을 높이는 데 기초 자료로 사용할 수 있습니다.

A suspect screening analysis method is presented to rapidly characterize chemicals in 100 consumer products -- whether they be formulations (shampoos, paints), articles (upholsteries, shower curtains), or foods (cereals) – and therefore supports broader efforts to prioritize chemicals based on potential human health risks. A two-dimensional gas chromatography-time of flight/mass spectrometry method was used to screen for chemicals in selected products. Analysis yielded 4270 unique chemical signatures across the products, with 1602 signatures tentatively identified using the National Institute of Standards and Technology 2008 spectral database. Chemical standards confirmed the presence of 119 compounds. Of the 1602 chemicals, 1404 were not present in a public database of known consumer product chemicals. This dataset is associated with the following publication: Phillips, K., A. Yau, K. Favela, K. Isaacs, A. McEachran, C. Grulke, A. Richard, A. Williams, J. Sobus, R. Thomas, and J. Wambaugh. Suspect Screening Analysis of Chemicals in Consumer Products. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(5): 3125-3135, (2018).