Department of Environmental Science, Baylor University, Waco, TX, USA; School of Environment, Jinan University, Guangzhou, China.
Department of Environmental Science, Baylor University, Waco, TX, USA.
Environ Int. 2019 Apr;125:399-417. doi: 10.1016/j.envint.2019.01.079. Epub 2019 Feb 8.
Though numerous chemical ingredients are used in cleaning products, empirical mammalian toxicology information is often limited for many substances. Such limited data inherently presents challenges to environmental health practitioners performing hazard and risk assessments. Probabilistic hazard assessment using chemical toxicity distributions (CTDs) is an alternative approach for assessments of chemicals when toxicity information is lacking. The CTD concept allows for derivation of thresholds of toxicological concern (TTCs) to predict adverse effect thresholds for mammalian species. Unfortunately, comparative health hazard assessment of cleaning product ingredients in common use categories such as all-purpose cleaners (APC), dish care products (DCP) and laundry care products (LCP) has not been well studied. However, APC, DCP, and LCP are used routinely for household and industrial applications, resulting in residential and industrial occupational exposures. Therefore, we reviewed and then examined hazard information (median lethal dose (LD50), lowest-observed-adverse-effect level (LOAEL), and no-observed-adverse-effect level (NOAEL)) from different types of standard mammalian toxicity studies for oral toxicity in the rat model from the unique Cleaning Product Ingredient Safety Initiative mammalian toxicology database. Probabilistic distributions (CTDs) were subsequently constructed using LD50, NOAEL and LOAEL data from a specific toxicity study type for all available ingredients in these three use categories. Based on data availability, product type-specific and chemical category-specific CTDs were also generated and compared. For each CTD, threshold concentrations (TCs) and their 95% confidence intervals (95% CIs) at 1st, 5th, 10th, 50th, 90th, 95th and 99th percentiles were calculated using the log-normal model. To test whether the common default uncertainty factor (UF) approach (e.g., 3, 10) in mammalian health risk assessment provides sufficient protection, UFs were also derived for LOAEL-to-NOAEL and exposure duration (e.g., subchronic-to-chronic) extrapolations. Relationships between CTDs of acute LD50s and sublethal LOAELs/NOAELs were also examined for acute-to-chronic ratio calculations, which may be useful in extreme circumstances. Results from our critical review and meta-analysis appear particularly useful for hazard and risk practitioners when identifying TTCs for ingredients in product use categories, and other chemical classes. This approach can also support development of regulatory data dossiers through read across, chemical substitutions and screening-level health risk assessments when limited or no empirical toxicity information exists for industrial chemicals.
尽管清洁产品中使用了许多化学成分，但对于许多物质，经验性哺乳动物毒理学信息通常有限。这种有限的数据本质上给进行危害和风险评估的环境卫生工作者带来了挑战。当毒性信息缺乏时，使用化学毒性分布 (CTD) 进行概率危害评估是评估化学品的另一种方法。CTD 概念允许推导出毒理学关注阈值 (TTC)，以预测哺乳动物物种的不良影响阈值。不幸的是，对于在通用清洁剂 (APC)、餐具护理产品 (DCP) 和衣物护理产品 (LCP) 等常见用途类别中使用的清洁产品成分的比较健康危害评估尚未进行充分研究。然而，APC、DCP 和 LCP 通常用于家庭和工业应用，导致住宅和工业职业暴露。因此，我们审查并检查了来自独特的清洁产品成分安全倡议哺乳动物毒理学数据库中大鼠模型口服毒性的不同类型标准哺乳动物毒性研究的危害信息（半数致死剂量 (LD50)、最低观察到的不良效应水平 (LOAEL) 和无观察到的不良效应水平 (NOAEL)）。随后，使用来自特定毒性研究类型的 LD50、NOAEL 和 LOAEL 数据为这三种用途类别中的所有可用成分构建概率分布 (CTD)。基于数据可用性，还生成并比较了产品类型特异性和化学类别特异性 CTD。对于每个 CTD，使用对数正态模型计算了浓度阈值 (TCs) 及其 95%置信区间 (95%CI) 在第 1、5、10、50、90、95 和 99 百分位的浓度阈值。为了测试哺乳动物健康风险评估中常用的默认不确定性因素 (UF) 方法（例如 3、10）是否提供足够的保护，还针对 LOAEL-NOAEL 和暴露持续时间（例如亚慢性-慢性）外推导出 UF。还检查了急性 LD50 的 CTD 和亚致死 LOAEL/NOAEL 之间的关系，以计算急性到慢性比值，这在极端情况下可能有用。我们的批判性审查和荟萃分析的结果对于危害和风险从业者在确定产品用途类别和其他化学类别的成分的 TTC 时特别有用。当对工业化学品的毒性信息有限或不存在时，这种方法还可以通过读通、化学替代和筛选水平健康风险评估来支持监管数据文件的开发。
