[Analysis on the quality control of suspected occupational disease from the characteristics of applicants diagnosed with noise deafness].

X Li, W Shang, S Q Li, Z M Zhao, Y M Zheng, L Guan
Author Information
  1. X Li: Department of Occupational Disease, Peking University Third Hospital, Beijing Occupational Health Inspection Quality Control and Improvement Center, Beijing 100191, China.
  2. W Shang: Department of Occupational Disease, Nuclear Industry 417 Hospital, Xi'an 710600, China.
  3. S Q Li: Department of Occupational Disease, Peking University Third Hospital, Beijing Occupational Health Inspection Quality Control and Improvement Center, Beijing 100191, China.
  4. Z M Zhao: Department of Occupational Disease, Peking University Third Hospital, Beijing Occupational Health Inspection Quality Control and Improvement Center, Beijing 100191, China.
  5. Y M Zheng: Department of Occupational Disease, Peking University Third Hospital, Beijing Occupational Health Inspection Quality Control and Improvement Center, Beijing 100191, China.
  6. L Guan: Department of Occupational Disease, Peking University Third Hospital, Beijing Occupational Health Inspection Quality Control and Improvement Center, Beijing 100191, China.

Abstract

To analyze the audiology and occupational health data of applicants diagnosed of occupational noise deafness, and to explore the influencing factors in the diagnosis of suspected occupational noise deafness. In May 2022, the information of patients diagnosed with occupational noise deafness in Peking University Third Hospital from January 2018 to December 2021 was collected, and the occupational health data of their working environment, clinical audiological examination results and diagnosis basis of occupational noise deafness were collected and analyzed. Multi-factor unconditional logistic regression analysis was used to analyze independent risk factors for the diagnosis of occupational noise deafness. A total of 129 subjects were included, all of which were suspected cases of occupational noise deafness found in various occupational health examination institutions. Eight cases (6.20%) were diagnosed as occupational noise deafness, and 121 cases (93.80%) were non-occupational noise deafness. After hearing examination, only 27.27% (24/88) of the patients' audiological changes were consistent with the starting point of occupational noise deafness diagnosis. Further analysis of the noise intensity in the workplace showed that 16 patients were identified as non-occupational noise deafness because the noise intensity of the working environment was less than 85 dB. Logistic regression analysis showed that the working hours were more than 8 hours (=9.274, 95%: 1.388-61.950, =0.022) and the noise intensity of the working environment (=1.189, 95%: 1.059-1.334, =0.003) were independent risk factors for the diagnosis of occupational noise deafness. The exclusion rate of suspected occupational noise deafness found in occupational health examination is higher after adequate rest. The test results of working environment noise intensity provided by the employer can help to determine occupational noise deafness.

Keywords

Grants

  1. Occupational Disease Specialty/National Key Clinical Specialty Construction Project
  2. 2017HDPMA08/Project of Preventive Medicine Association of Haidian District, Beijing

MeSH Term

Humans
Occupational Diseases
Hearing Loss, Noise-Induced
Noise, Occupational
Deafness
Quality Control
Occupational Exposure

Word Cloud

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