Abstract
We simultaneously assessed the associations for a range of outdoor environmental exposures with prevalent tuberculosis (TB) cases in a population-based health program with 1940,622 participants ≥ 15 years of age. TB status was confirmed through bacteriological and clinical assessment. We measured 14 outdoor environmental exposures at residential addresses. An exposome-wide association study (ExWAS) approach was used to estimate cross-sectional associations between environmental exposures and prevalent TB, an adaptive elastic net model (AENET) was implemented to select important exposure(s), and the Extreme Gradient Boosting algorithm was subsequently applied to assess their relative importance. In ExWAS analysis, 12 exposures were significantly associated with prevalent TB. Eight of the exposures were selected as predictors by the AENET model: particulate matter ≤ 2.5 µm (odds ratio [OR]=1.01, p = 0.3295), nitrogen dioxide (OR=1.09, p < 0.0001), carbon monoxide (OR=1.19, p < 0.0001), and wind speed (OR=1.08, p < 0.0001) were positively associated with the odds of prevalent TB while sulfur dioxide (OR=0.95, p = 0.0017), altitude (OR=0.97, p < 0.0001), artificial light at night (OR=0.98, p = 0.0001), and proportion of forests, shrublands, and grasslands (OR=0.95, p < 0.0001) were negatively associated with the odds of prevalent TB. Air pollutants had higher relative importance than meteorological and geographical factors, and the outdoor environment collectively explained 11% of TB prevalence.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin > Institut und Poliklinik für Arbeits-, Sozial- und Umweltmedizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 03043894 |
Sprache: | Englisch |
Dokumenten ID: | 119728 |
Datum der Veröffentlichung auf Open Access LMU: | 30. Jul. 2024, 08:50 |
Letzte Änderungen: | 30. Jul. 2024, 08:50 |