Association of the interaction between occupational hazard factors and IL-1β gene polymorphism with cognitive function in electrolytic aluminum workers
Bibliographic record
Abstract
Background Various occupational hazards in the electrolytic aluminum environment have been linked to cognitive decline. However, the interactive effects of these hazards and genetic factors on cognitive function remain unclear. Objective This study aimed to identify the primary occupational hazards, examine their interaction with IL-1β gene polymorphisms in relation to cognitive function. Methods A cross-sectional study was conducted in June 2024 at an electrolytic aluminum company in China, involving 478 male workers. Cognitive function was assessed using the Montreal Cognitive Assessment. Calculate the cumulative exposure dose of harmful factors such as aluminum dust. Additionally, IL-1β gene polymorphisms (rs1143627, rs1143643, rs16944, rs3917356) and serum protein levels were analyzed. The associations between environmental exposure, genetic factors, and cognitive function were examined using multivariate stepwise linear regression, restricted cubic splines, generalized linear models, and hierarchical analysis. Covariance analysis and independent sample t-tests were employed to assess the potential mediating effect of peripheral blood IL-1β levels. Results Cumulative exposure to aluminum dust was significantly associated with cognitive decline (β = −0.18, 95% CI: 0.27, −0.10), and the relationship was linear. Compared to the wild genotype, individuals carrying rs1143627 G/G, rs1143643 C/C, and rs16944 A/A exhibited significantly lower cognitive scores (P < 0.01), whereas rs3917356 C/T and T/T conferred a protective effect (P < 0.01). The model was adjusted for age, body mass index, and cumulative aluminum dust exposure. The genetic effect associated with IL-1β was more pronounced in individuals with high aluminum exposure (>2.37 mg/m3 × year). IL-1β serum protein levels showed no significant association with cognitive function (P > 0.05). Conclusion Cumulative exposure to aluminum dust is a key risk factor for cognitive decline. IL-1β polymorphisms influence susceptibility, with the effect becoming more pronounced under high aluminum exposure. However, peripheral blood IL-1β levels do not mediate this association with cognitive decline.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".