The relationship between particulate matter and kidney biomarkers in pregnant women: A case study in Yazd city
| Autor: | Reman Mohammed Mahgoob Al-Azzawi, Atefeh Chamani |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Environmental Health Engineering and Management, Vol 11, Iss 2, Pp 137-146 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2423-3765 2423-4311 |
| DOI: | 10.34172/EHEM.2024.14 |
| Popis: | Background: Cities negatively affect the environment. Urban pollution levels have risen considerably, affecting sensitive groups such as pregnant women. Methods: This study aimed to investigate the relationship between particulate matter and kidney biomarkers of pregnant women in Yazd from September to November 2023. Urea, uric acid, and creatinine levels were measured in 30 pregnant women (third trimester). The concentration of PM2.5 was estimated using the land use regression (LUR) model and 5 independent variables of road networks, distance from the city center, building density, elevation, and slope. For each mother, the mean concentration of the modeled PM2.5 was measured in multiple buffer rings drawn around her residential location. Generalized additive model (GAM) was employed to establish a relationship between PM2.5 concentrations with physiological indicators. Results: Average urea, uric acid, and creatinine were 18.06 ± 5.74, 3.65 ± 1.11, and 0.79 ± 0.12 mg/dL, respectively. The LUR model identified road networks and distance from the city center as critical factors contributing to increased particulate matter concentration. The GAM R2 was 0.79, 0.31, and 0.28 for urea, uric acid, and creatinine, respectively. The mean PM2.5 within a radius of 2000 m was identified as the most significant independent variable and showed an increasing impact on the renal parameters. Conclusion: According to the results, reducing pollutant levels and preventing the creation of pollution hotspots via lowering road density are vital urban planning strategies to protect vulnerable groups, especially pregnant women. |
| Databáze: | Directory of Open Access Journals |
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