Zhang Meibian, Zeng Anke, Zou Hua, Xin Jiarui, Su Shibiao, Qiu Wei, Sun Xin
National Institute of Occupational Health and Poisoning Control, Beijing, China.
Occupational Health and Radiation Protection Institute, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Ear Hear. 2025;46(1):196-209. doi: 10.1097/AUD.0000000000001571. Epub 2024 Sep 6.
Noise risk control or management based on noise level has been documented, but noise risk management based on a combination of noise level and noise's temporal structure is rarely reported. This study aimed to develop a framework for industrial noise risk management based on noise kurtosis (reflecting noise's temporal structure) and its adjustment for the noise level.
A total of 2805 Chinese manufacturing workers were investigated using a cross-sectional survey. The noise exposure data of each subject included L EX,8h , cumulative noise exposure (CNE), kurtosis, and kurtosis-adjusted L EX,8h (L EX,8h -K). Noise-induced permanent threshold shifts were estimated at 3, 4, and 6 kHz frequencies (NIPTS 346 ) and 1, 2, 3, and 4 kHz frequencies (NIPTS 1234 ). The prevalence of high-frequency noise-induced hearing loss prevalence (HFNIHL%) and noise-induced hearing impairment (NIHI%) were determined. Risk 346 or Risk 1234 was predicted using the ISO 1999 or NIOSH 1998 model. A noise risk management framework based on kurtosis and its adjustment was developed.
Kurtosis could identify the noise type; Kurtosis combining noise levels could identify the homogeneous noise exposure group (HNEG) among workers. Noise kurtosis was a risk factor of HFNIHL or NIHI with an adjusted odds ratio of 1.57 or 1.52 ( p < 0.01). At a similar CNE level, the NIPTS 346 , HFNIHL%, NIPTS 1234 , or NIHI% increased with increasing kurtosis. A nonlinear regression equation (expressed by logistic function) could rebuild a reliable dose-effect relationship between L EX,8h -K and NIPTS 346 at the 70 to 95 dB(A) noise level range. After the kurtosis adjustment, the median L EX,8h was increased by 5.45 dB(A); the predicted Risk 346 and Risk 1234 were increased by 11.2 and 9.5%, respectively; NIPTS 346 -K of complex noise at exposure level <80, 80 to 85, and 85 to 90 dB(A), determined from the nonlinear regression equation, was almost the same as the Gaussian noise. Risk management measures could be recommended based on the exposure risk rating or the kurtosis-adjusted action levels (e.g., the lower and upper action levels were 80 and 85 dB(A), respectively).
The kurtosis and its adjustment for noise levels can be used to develop an occupational health risk management framework for industrial noise. More human studies are needed to verify the risk management framework.
基于噪声水平的噪声风险控制或管理已有文献记载，但基于噪声水平与噪声时间结构相结合的噪声风险管理鲜有报道。本研究旨在建立一个基于噪声峰度（反映噪声时间结构）及其对噪声水平调整的工业噪声风险管理框架。
采用横断面调查对2805名中国制造业工人进行了调查。每个受试者的噪声暴露数据包括LEX,8h、累积噪声暴露（CNE）、峰度以及经峰度调整的LEX,8h（LEX,8h-K）。在3、4和6kHz频率（NIPTS 346）以及1、2、3和4kHz频率（NIPTS 1234）处估计噪声引起的永久性阈移。确定高频噪声性听力损失患病率（HFNIHL%）和噪声性听力损伤（NIHI%）。使用ISO 1999或NIOSH 1998模型预测风险346或风险1234。建立了基于峰度及其调整的噪声风险管理框架。
峰度可识别噪声类型；结合噪声水平的峰度可识别工人中的均匀噪声暴露组（HNEG）。噪声峰度是HFNIHL或NIHI的危险因素，调整后的优势比为1.57或1.52（p<0.01）。在相似的CNE水平下，NIPTS 346、HFNIHL%、NIPTS 1234或NIHI%随峰度增加而增加。在70至95dB（A）噪声水平范围内，非线性回归方程（由逻辑函数表示）可重建LEX,8h-K与NIPTS 346之间可靠的剂量-效应关系。峰度调整后，LEX,8h中位数增加了5.45dB（A）；预测的风险346和风险1234分别增加了11.2%和9.5%；根据非线性回归方程确定的暴露水平<80、80至85和85至90dB（A）的复杂噪声的NIPTS 346-K与高斯噪声几乎相同。可根据暴露风险评级或经峰度调整的行动水平（例如，较低和较高行动水平分别为80和85dB（A））推荐风险管理措施。
峰度及其对噪声水平的调整可用于建立工业噪声职业健康风险管理框架。需要更多人体研究来验证该风险管理框架。
