Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA.
Risk Anal. 2021 Apr;41(4):627-644. doi: 10.1111/risa.13604. Epub 2020 Oct 18.
The ubiquitous presence of more than 80,000 chemicals in thousands of consumer products used on a daily basis stresses the need for screening a broader set of chemicals than the traditional well-studied suspect chemicals. This high-throughput screening combines stochastic chemical-product usage with mass balance-based exposure models and toxicity data to prioritize risks associated with household products. We first characterize product usage using the stochastic SHEDS-HT model and chemical content in common household products from the CPDat database, the chemical amounts applied daily varying over more than six orders of magnitude, from mg to kg. We then estimate multi-pathways near- and far-field exposures for 5,500 chemical-product combinations, applying an extended USEtox model to calculate product intake fractions ranging from 0.001 to ∼1, and exposure doses varying over more than nine orders of magnitude. Combining exposure doses with chemical-specific dose-responses and reference doses shows that risks can be substantial for multiple home maintenance products, such as paints or paint strippers, for some home-applied pesticides, leave-on personal care products, and cleaning products. Sixty percent of the chemical-product combinations have hazard quotients exceeding 1, and 9% of the combinations have lifetime cancer risks exceeding 10 . Population-level impacts of household products ingredients can be substantial, representing 5 to 100 minutes of healthy life lost per day, with users' exposures up to 10 minutes per day. To address this issue, present mass balance-based models are already able to provide exposure estimates for both users and populations. This screening study shows large variations of up to 10 orders of magnitude in impact across both chemicals and product combinations, demonstrating that prioritization based on hazard only is not acceptable, since it would neglect orders of magnitude variations in both product usage and exposure that need to be quantified. To address this, the USEtox suite of mass balance-based models is already able to provide exposure estimates for thousands of product-chemical combinations for both users and populations. The present study calls for more scrutiny of most impacting chemical-product combinations, fully ensuring from a regulatory perspective consumer product safety for high-end users and using protective measures for users.
日常使用的数以千计的消费品中存在着超过 80000 种化学物质,这使得我们需要筛选出比传统研究的可疑化学物质更广泛的化学物质。这种高通量筛选将随机的化学品使用与基于质量平衡的暴露模型和毒性数据相结合,对与家庭产品相关的风险进行优先级排序。我们首先使用随机 SHEDS-HT 模型对产品使用情况进行特征描述,然后使用 CPDat 数据库中常见家用产品的化学成分来描述产品使用情况,每天使用的化学物质数量超过六个数量级,从毫克到千克不等。然后,我们为 5500 种化学-产品组合估算多途径近场和远场暴露情况,应用扩展的 USEtox 模型计算产品摄入量分数,范围从 0.001 到约 1,暴露剂量超过九个数量级。将暴露剂量与化学特异性剂量反应和参考剂量相结合表明,对于多种家庭维护产品(如油漆或油漆剥离剂)、一些家庭应用的农药、留置个人护理产品和清洁产品,风险可能相当大。60%的化学-产品组合的危害系数超过 1,9%的组合终生癌症风险超过 10%。家庭产品成分对人群的影响可能相当大,代表每天失去 5 到 100 分钟的健康寿命,使用者的暴露量高达每天 10 分钟。为了解决这个问题,现有的基于质量平衡的模型已经能够为用户和人群提供暴露估计。这项筛选研究表明,在化学物质和产品组合方面,影响的差异高达十个数量级,这表明仅基于危害进行优先级排序是不可接受的,因为它忽略了产品使用和暴露方面需要量化的数量级变化。为了解决这个问题,USEtox 系列基于质量平衡的模型已经能够为用户和人群提供数千种产品-化学物质组合的暴露估计。本研究呼吁对影响最大的化学-产品组合进行更严格的审查,从监管角度充分确保高端用户的消费产品安全,并为用户使用保护措施。