ReviewEnvironmental monitoring and assessment2021
Risk assessment approaches for evaluating cumulative exposures to multiple pesticide residues in agro-products using seasonal vegetable monitoring data from Hainan, China: a case study.
Review in Environmental monitoring and assessment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Risks from combined exposure to multiple chemicals in food have prompted a growing concern for their effect on human health. Risk management of chemical mixtures should be based on developing and harmonizing methodologies to scientifically evaluate their cumulative adverse effects. In this study, a simplified tiered approach of cumulative exposure assessment is described along with a case study of vegetables in China's Hainan province during 2012-2014. This case study could be a reference for the Chinese National Risk Assessment Programs for vegetable and fruit products. In the proposed assessment approach, Tier 1 acts as a screening tier to categorize and evaluate chemicals under a conservative scenario, and it prioritizes the pesticides of most concern. Tier 2 refines the grouping of substances from Tier 1 and normalizes the toxic potency of the chemicals to sum the exposure of chemical mixtures in a given assessment group. Tier 3 applies the refined exposure model and the input parameter distribution to create probabilistic models using Monte Carlo simulation. This approach will be helpful in the cumulative exposure assessment where data on pesticide residues are sufficient, but the individual dietary consumption is inadequate.
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Registered trials
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