Personal Exposure To Particulate Matter And Heart Rate Variability Among Informal Electronic Waste Workers At Agbogbloshie: A Longitudinal Study
Bibliographic record
Abstract
Abstract Background: Informal electronic waste recycling activities are major contributors to ambient air pollution, yet studies assessing the effects or relationship between direct/continuous exposure of informal e-waste workers to particulate matter and cardiovascular function are rare. Methods: Repeated measurements of fractions of PM 2.5 , PM 10-2.5 , and PM 10 in personal air of informal e-waste workers, (n=142) and a comparable group (n=65) were taken over a period of 20 months (March 2017 to November, 2018). Concurrently, 5-minute resting electrocardiogram was performed on each participant to assess resting heart rate variability indices. Linear mixed-effects models were used to assess the association between PM fractions and cardiac function. Results : SDNN, RMSSD, LF, HF and LH/HF ratio were all associated with PM. Significant associations were observed for PM 2.5 and MEANNN ( p = 0.039), PM10 and SDNN ( p = 0.035) and PM 10-2.5 and LH/HF ( p = 0.039). A 10µg/m 3 increase in the concentrations of PM 2.5 , PM 10-2.5 , and PM 10 in personal air was associated with reduced HRV indices and increased resting HR. A 10µg/m 3 per interquartile (IQR) increase in PM 10-2.5 and PM 10 , decreased SDNN by 11% [(95% CI: -0.002- 0.000); ( p = 0.187)] and 34% [(95% CI:-0.002-0.001); ( p = 0.035)] respectively. However, PM 2.5 increased SDNN by 34 % (95% CI: -1.32-0.64); ( p = 0.493). Also, 10µg/m 3 increase in PM 2.5 , PM 10-2.5 and PM 10 decreased RMSSD by 27% [(-1.34-0.79); ( p = 0.620)], 11% [(-1.73, 0.95); ( p = 0.846)] and 0.57% [(-1.56-0.46); ( p = 0.255%)]. Conclusion : Informal e-waste workers are at increased risk of developing cardiovascular disease from cardiac autonomic dysfunction as seen in reduced HRV and increased heart rate.
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".