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Meta Analysis ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 1 ? Systematic review or meta-analysis. Synthesizes findings across many studies. Strongest evidence. Environmental Sources Gut & Microbiome Human Health Effects Policy & Risk Reproductive & Development Sign in to save

Risk Assessment of Microplastics in Humans: Distribution, Exposure, and Toxicological Effects

Polymers 2025 10 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 78 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Yifei Li, Wei Ling, Yi Xing, Jian Yang

Summary

This meta-analysis tracked the rapid growth of research on microplastics and human health, finding a shift from studying environmental pollution toward understanding direct human exposure and health effects. Emerging concerns include reproductive toxicity, neurotoxicity, and immune system disruption from microplastic exposure.

Polymers
Models
Study Type Review

Microplastics are widely present in the environment, and their potential risks to human health have attracted increasing attention. Research on microplastics has exhibited exponential growth since 2014, with a fast-growing focus on human health risks. Keyword co-occurrence networks indicate a research shift from environmental pollution toward human exposure and health effects. Additionally, Trend Factor analysis reveals emerging research topics such as reproductive toxicity, neurotoxicity, and impacts on gut microbiota. This meta-analysis included 125 studies comprising 2977 data samples. The results demonstrated that cytotoxicity in experimental systems was primarily concentrated in Grade I (non-toxic, 62.8%) and Grade II (mildly toxic, 27.6%). Notably, inhibitory effects on cells were significantly enhanced when microplastic concentrations exceeded 40 μg/mL or particle sizes were smaller than 0.02 μm. The Gradient Boosting Decision Tree (GBDT) model was applied to predict cell viability, achieving an R<sup>2</sup> value of 0.737 for the test set and a classification accuracy of 81.5%. Furthermore, reproductive- and circulatory-system cells exhibited the highest sensitivity to microplastics, whereas connective-tissue cells had the lowest survival rates. The study also identified an overuse of polystyrene (PS) polymers and spherical particles in experimental designs, deviating from realistic exposure scenarios.

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