BackgroundNoise energy has been well-established to increase the risk of occupational noise-induced hearing loss (NIHL). However, the role of noise temporal structure (expressed by kurtosis) or its combination with energy metrics (e.g., kurtosis-adjusted cumulative noise exposure, adj-CNE) in occupational NIHL was still unclear.MethodsA cross-sectional survey of 867 Chinese workers, including 678 metal manufacturing workers and 189 workers exposed to Gaussian noise, was conducted. Noise energy metrics, including LAeq,8h and CNE, kurtosis (β), and adj-CNE were used to quantify noise exposure levels. Noise-induced permanent threshold shift at frequencies 3, 4, and 6 kHz (NIPTS346) and the prevalence of high-frequency NIHL (HFNIHL%) were calculated for each participant. The dose–response relationship between kurtosis or adj-CNE and occupational NIHL was observed.ResultsAmong 867 workers, different types of work had specific and independent noise energy and kurtosis values (p > 0.05). HFNIHL% increased with an increase in exposure duration (ED), LAeq,8h, CNE, or kurtosis (p < 0.01), and there were strong linear relationships between HFNIHL% and ED (coefficient of determination [R2] = 0.963), CNE (R2 = 0.976), or kurtosis (R2 = 0.938, when CNE < 100 dB(A)∙year). The “V” shape notching extent in NIPTS became deeper with increasing kurtosis when CNE < 100 dB(A)∙year and reached the notching bottom at the frequency of 4 or 6 kHz. The workers exposed to complex noise (β ≥ 10) had a higher risk of NIHL than those exposed to Gaussian noise (β < 10) at the frequencies of 3, 4, 6, and 8 kHz (OR > 2, p < 0.01). Moreover, HFNIHL% increased with adj-CNE (p < 0.001). There were strong linear relationships between NIHL and adj-CNE or CNE when β ≥ 10 (R2adj-CNE > R2CNE). After CNE was adjusted by kurtosis, average differences in NIPTS346 or HFNIHL% between the complex and Gaussian noise group were significantly reduced (p < 0.05).ConclusionKurtosis was a key factor influencing occupational NIHL among metal manufacturing workers, and its combination with energy metrics could assess the risk of NIHL more effectively than CNE alone.