Noise Pollution in Mosul Medical City Center Teaching Hospitals
Annals of the College of Medicine, Mosul,
Volume 39, Issue 1, Pages 32-37
Context: High levels of noise in hospitals may interfere with patient care services, the doctor-patient relationship and medical education activities.
Aim: To measure the noise level and to determine the time-place patterns at Mosul Medical City Center Teaching Hospitals.
Materials and methods: Sound levels of different places inside the stated hospitals were recorded, using a Digital Sound Level Meter. A total of 80 readings were taken at different locations of hospitals. The time for each measurement was 5 minutes, repeated for three times in each location, and then the average reading was recorded. Three noise parameters were recorded in every measurement (in dBA): equivalent noise level (Leq), maximum noise level (L max) and minimum noise level (L min). Neither the staff nor the patients in the four institutions were aware of the recordings.
Indoor noise levels on weekdays (Saturday through Thursday) were compared to noise levels on weekends (Friday). Outdoor noise levels were measured near each hospital facet, too. Time-patterns of noise pollution were established by recordings at 08:00 a.m., 09:00 a.m., 11:00 a.m., and 02:00 p.m.
Results: The mean equivalent sound level was 93.44 ± 6.55 dBA, including hospitals facet. The maximum equivalent sound level was observed in the casualty department (97.80 ± 2.91 dBA) and the minimum equivalent sound level was in Ibn-Sena General Teaching Hospital (89.16 ± 6.83 dBA) (p = 0.001). During morning hours, the mean equivalent noise level (94.35 dBA) was higher than the afternoon level (90.14 dBA) (p=0.037). The mean equivalent noise levels were higher on the weekdays (94.05 dBA) than on the weekend (88.57 dBA) (p = 0.002).
Conclusion: The noise pollution in Mosul Medical City center greatly exceeded the WHO guideline level for hospitals. This study highlights the need for noise monitoring and control measures inside hospital areas.
Keywords: Noise pollution, hospitals, patterns.
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