Effect of poverty on the relationship between personal exposures and ambient concentrations of air pollutants in Ho Chi Minh City
Bibliographic record
Abstract
Socioeconomic factors often affect the distribution of exposure to air pollution. The relationships between health, air pollution, and poverty potentially have important public health and policy implications, especially in areas of Asia where air pollution levels are high and income disparity is large. The objective of the study was to characterize the levels, determinants of exposure, and relationships between children personal exposures and ambient concentrations of multiple air pollutants amongst different socioeconomic segments of the population of Ho Chi Minh City, Vietnam. Using repeated (N = 9) measures personal exposure monitoring and determinants of exposure modeling, we compared daily average PM2.5, PM10, PM2.5 absorbance and NO2 concentrations measured at ambient monitoring sites to measures of personal exposures for (N = 64) caregivers of young children from high and low socioeconomic groups in two districts (urban and peri-urban), across two seasons. Personal exposures for both PM sizes were significantly higher among the poor compared to non-poor participants in each district. Absolute levels of personal exposures were under-represented by ambient monitors with median individual longitudinal correlations between personal exposures and ambient concentrations of 0.4 for NO2, 0.6 for PM2.5 and PM10 and 0.7 for absorbance. Exposures of the non-poor were more highly correlated with ambient concentrations for both PM size fractions and absorbance while those for NO2 were not significantly affected by socioeconomic position. Determinants of exposure modeling indicated the importance of ventilation quality, time spent in the kitchen, air conditioner use and season as important determinant of exposure that are not fully captured by the differences in socioeconomic position. Our results underscore the need to evaluate how socioeconomic position affects exposure to air pollution. Here, differential exposure to major sources of pollution, further influenced by characteristics of Ho Chi Minh City's rapidly urbanizing landscape, resulted in systematically higher PM exposures among the poor.
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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 | 0.001 | 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".