ReviewToxics2022
Partitioning of Persistent Organic Pollutants between Adipose Tissue and Serum in Human Studies.
Review in Toxics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed.
- Weight loss treatment for COVID-19 in patients with NCDs: a pilot prospective clinical trial.Scientific reports · 2024Trial
- A community-engaged randomized controlled trial assessing the effectiveness of a weight loss aid in reducing the body burden of persistent organic pollutants.Environmental advances · 2026Article
- The aryl hydrocarbon receptor: structure, signaling, physiology and pathology.Signal transduction and targeted therapy · 2026Review
- [Serum levels of polycyclic aromatic hydrocarbons and health risk assessment among children and adolescents].Se pu = Chinese journal of chromatography · 2025Article
- Exposure to 4,4'-DDE in visceral adipose tissue and weight loss in adolescents from the Teen-LABS cohort.Obesity (Silver Spring, Md.) · 2024Article
- Breast Cancer Exposomics.Life (Basel, Switzerland) · 2024Review
- Article
- Linking Prenatal Environmental Exposures to Lifetime Health with Epigenome-Wide Association Studies: State-of-the-Science Review and Future Recommendations.Environmental health perspectives · 2023Review
- Sex, Nutrition, and NAFLD: Relevance of Environmental Pollution.Nutrients · 2023Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Blood is the most widely used matrix for biomonitoring of persistent organic pollutants (POPs). It is assumed that POPs are homogenously distributed within body lipids at steady state; however, the variability underlying the partitioning of POPs between fat compartments is poorly understood. Hence, the objective of this study was to review the state of the science about the relationships of POPs between adipose tissue and serum in humans. We conducted a narrative literature review of human observational studies reporting concentrations of POPs in paired samples of adipose tissue with other lipid-based compartments (e.g., serum lipids). The searches were conducted in SCOPUS and PUBMED. A meta-regression was performed to identify factors responsible for variability. All included studies reported high variability in the partition coefficients of POPs, mainly between adipose tissue and serum. The number of halogen atoms was the physicochemical variable most strongly and positively associated with the partition ratios, whereas body mass index was the main biological factor positively and significantly associated. To conclude, although this study provides a better understanding of partitioning of POPs to refine physiologically based pharmacokinetic and epidemiological models, further research is still needed to determine other key factors involved in the partitioning of POPs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.