Asbestos burden in lung tissue from the general population: a systematic review
Bibliographic record
Abstract
Asbestos, a group of naturally occurring fibrous silicate minerals, is known for its fire-resistant and insulating properties but is also recognized as a cause of several diseases, including mesothelioma and lung cancer. Lung content analysis using electron microscopy is considered the most reliable method for assessing past asbestos exposure, especially in medico-legal settings. However, there is no universally accepted reference value to distinguish between background and risk-associated exposure levels. This systematic review evaluates the quantification and time trends of asbestos lung burden in the general population over recent decades. Twenty studies published between 1980 and 2023 were included, analysing asbestos lung content from autopsies performed between 1967 and 2023 on 890 individuals from diverse geographic regions. All studies detected asbestos in lung tissue, with concentrations ranging from 3187 to 7,310,000 fibres per gram of dry weight (ff/gdw). Most studies reported values above thresholds often cited for background exposure. No clear trend in asbestos concentration or fibre type was observed over time. Recent studies from Italy, conducted after the national asbestos ban, showed variable results: one reported concentrations above 100,000 ff/gdw in Milan, while another found much lower levels elsewhere in Northern Italy. Amphiboles such as tremolite may contaminate chrysotile, and their presence in lung tissue could reflect either industrial use or other environmental sources. Amphiboles have lower solubility in the respiratory tract, whereas chrysotile may dissolve more rapidly. Data comparability across studies and laboratories is limited due to methodological differences, as previously noted in the literature. This review summarizes studies conducted in US, Canada, Japan, Korea and Europe, based on autopsies from individuals without occupational asbestos exposure. Asbestos is consistently found in lung tissue from the general population, with no evident decline in concentrations over the past five decades. The persistence of non-commercial amphiboles, even after regulatory bans, highlights ongoing environmental exposure and complicates disease attribution in medico-legal contexts. The current literature is limited and methodologically heterogeneous, underscoring the need for standardized laboratory methods and updated reference values. However, surveillance of asbestos-related diseases, especially mesothelioma, requires detailed exposure assessment, including patient interviews, as mineral particle levels alone may not capture individual susceptibility or exposure history.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".