Characterizing the patterns and predictors of exposure to urban air pollution and environmental noise among retired adults in Bucaramanga, Colombia
Bibliographic record
Abstract
Background: Air pollution and environmental noise are major environmental pollutants, though most studies have been conducted in European and North American cities.By comparison, there are very few studies of exposure to air pollution and environmental noise in Latin American cities, which are rapidly urbanizing.Setting-specific exposure assessment studies are needed to understand the sources and determinants of air pollution and environmental noise exposures, which vary within and between cities and regions.Objective: The aim of my thesis was to characterize levels and determinants of exposure to fine particulate matter (PM2.5),black carbon (BC), and indoor noise among retired adults living in Bucaramanga, a medium-sized city in Colombia.Methods: We enrolled 78 retired adults from four neighbourhoods in Bucaramanga that represented a range of traffic settings including high traffic/high diesel, low traffic/high diesel, high traffic/low diesel, and low traffic/low diesel/high braking.We measured 48-hr personal exposure to PM2.5 and BC; 48-hr indoor levels of PM2.5, BC, and noise; 5-day outdoor levels of PM2.5 and BC; and administered detailed questionnaires related to potential housing and sociodemographic determinants of these pollutants.To explore potential determinants of personal exposure to PM2.5, personal exposure to BC, and indoor equivalent sound pressure level (Leq), we built multivariable random effects regression models with a neighborhood-specific randomintercept.Results: Mean (± SD) personal exposures to PM2.5 and BC were 13.5 ± 5.9 g/m 3 and 2.4 ± 0.5 g/m 3 , respectively, and were very similar to indoor PM2.5 (12.7 ± 5.6 g/m 3 ) and BC (2.5 ± 0.5 g/m 3 ) concentrations.Traffic or diesel levels did not correlate with levels of PM2.5 or BC.However, the neighbourhood that was high traffic/high diesel had the highest PM2.5 levels.Mean indoor Leq in the four neighbourhoods ranged from 53.0-57.1 dB(A)) and indoor Leq was only weakly correlated with indoor air pollution (range of Pearson's r: -0.34-0.20).Higher level of indoor (household) air pollution and higher socioeconomic position (SEP) were determinants of higher personal exposure to PM2.5 and BC, whereas natural household ventilation predicted lower levels.Women, compared to men, tended to also have notably higher exposure to PM2.5, d'exposition personnelle plus élevée aux PM2.5 et BC, tandis que la ventilation naturelle des ménages prévoyait des niveaux plus bas.Les femmes, comparativement aux hommes, avaient également tendance à être considérablement plus exposées à PM2.5, mais ce n'était pas le cas pour BC.Un SEP plus élevé et une ventilation mécanique domestique (c'est-à-dire l'utilisation d'un ventilateur) prédisaient des niveaux plus élevés de Leq intérieur.Conclusion: Les expositions à PM2.5 chez les participants adultes à la retraite dans notre étude à Bucaramanga en Colombie étaient bien-dessous la ligne directrice quotidienne recommandé par l'OMS, mais leur exposition au BC et au bruit était élevée.Ces résultats indiquent que la prise en compte uniquement de l'exposition à PM2.5 peut sous-estimer les risques pour la santé de la pollution de l'environnement dans notre cadre d'étude.Les efforts visant à réduire les expositions environnementales de cette population vulnérable devraient viser les concentrations de pollution de l'air intérieur (domestique), les sources de bruit intérieur et les facteurs de ventilation domestique.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".