Exposure–Response Associations of Household Air Pollution and Buccal Cell Telomere Length in Women Using Biomass Stoves
Bibliographic record
Abstract
BACKGROUND: Telomere shortening is associated with early mortality and chronic disease. Recent studies indicate that environmental exposures, including urban and traffic-related air pollution, may shorten telomeres. Associations between exposure to household air pollution from solid fuel stoves and telomere length have not been evaluated. METHODS: Among 137 rural Chinese women using biomass stoves ([Formula: see text] of age), we measured 48-h personal exposures to fine particulate matter [PM [Formula: see text] in aerodynamic diameter ([Formula: see text])] and black carbon and collected oral DNA on up to three occasions over a period of 2.5 y. Relative telomere length (RTL) was quantified using a modified real-time polymerase chain reaction protocol. Mixed effects regression models were used to investigate the exposure–response associations between household air pollution and RTL, adjusting for key sociodemographic, behavioral, and environmental covariates. RESULTS: Women's daily exposures to air pollution ranged from [Formula: see text] for [Formula: see text] ([Formula: see text]) and [Formula: see text] for black carbon ([Formula: see text]). Natural cubic spline models indicated a mostly linear association between increased exposure to air pollution and shorter RTL, except at very high concentrations where there were few observations. We thus modeled the linear associations with all observations, excluding the highest 3% and 5% of exposures. In covariate-adjusted models, an interquartile range (IQR) increase in exposure to black carbon ([Formula: see text]) was associated with shorter RTL [all observations: [Formula: see text] (95% CI: [Formula: see text], [Formula: see text]); excluding highest 5% exposures: [Formula: see text] (95% CI: [Formula: see text], [Formula: see text])]. Further adjustment for outdoor temperature brought the estimates closer to zero [all observations: [Formula: see text] (95% CI: [Formula: see text], 0.06); excluding highest 5% exposures: [Formula: see text] (95% CI: [Formula: see text], [Formula: see text])]. Models with [Formula: see text] as the exposure metric followed a similar pattern. CONCLUSION: Telomere shortening, which is a biomarker of biological aging and chronic disease, may be associated with exposure to air pollution in settings where household biomass stoves are commonly used. https://doi.org/10.1289/EHP4041.
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 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) | 0.000 | 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".