The Adverse Health Effects of Air Pollution from Sugarcane Burning: A Scoping Review of Observational and Experimental Evidence
Bibliographic record
Abstract
BACKGROUND: Sugarcane burning is an agricultural practice that is implemented to increase sugar yields. However, sugarcane burning produces air pollutants associated with adverse health outcomes. This review summarizes the current knowledge of the defined exposures and health effects associated with sugarcane burning and identifies research gaps. METHODS: A scoping review was conducted using PubMed, Scopus, and Web-of-Science to identify peer-reviewed literature on health and exposure investigations associated with air pollution from burning sugarcane. Studies were eligible if they included both an air pollution measurement and a health outcome assessment in human workers and surrounding communities or animal studies associated with sugarcane burning. RESULTS: )] and total suspended particulates (TSP). Of the observational studies, 42% (8/19) were prospective cohorts, and 58% (11/19) employed an ecological design and applied variable exposure assessment methods. The experimental studies all used rodent models with varied exposure routes and pollutants. DISCUSSION: This review supports a well-documented link between air pollution from sugarcane burning and adverse health effects in workers and neighboring communities with respiratory, renal, and cardiovascular health effects; however, several knowledge gaps were identified, including the need for expansion of studies geographically, application of more advanced exposure science to characterize and quantify sugarcane emission components, probing of emerging health effects (i.e., kidney disease) and associated biomarkers, and evaluation of vulnerable populations that neighbor sugarcane operations. Furthermore, pairing exposure measurements and health assessments in the same study would increase our knowledge and better inform policies to improve the health of workers and communities impacted by sugarcane burning. https://doi.org/10.1289/EHP14456.
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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 | 0.018 | 0.072 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".