Persistent Structural Disparities in Occupational Noise Exposure: A Five-Year Analysis of 51,102 Workplaces in Sichuan Province, China

Persistent Structural Disparities in Occupational Noise Exposure: A Five-Year Analysis of 51,102 Workplaces in Sichuan Province, China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Persistent Structural Disparities in Occupational Noise Exposure: A Five-Year Analysis of 51,102 Workplaces in Sichuan Province, China Weizhong Chu, Xiangxiang Lu, Weiwei Shang, Leping Qiu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8816045/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Occupational noise-induced hearing loss remains a leading occupational disease in China. While national surveillance data suggest an overall decline in noise exposure, the underlying trends across diverse industrial sectors, enterprise sizes, and job categories remain poorly understood, particularly in the context of China’s rapid industrial transformation. Methods We conducted a five-year retrospective analysis (2020–2024) using official occupational hazard surveillance data from Sichuan Province. The dataset encompassed 51,102 unique job positions across 15,475 enterprises. Noise intensity (LAeq,8h) and exceedance rates (relative to the 85 dB(A) limit) were analyzed by industry, enterprise size, and job category. Temporal trends were assessed using the Cochran-Armitage test for trend and Kruskal-Wallis H test. Results The overall noise exceedance rate declined significantly from 25.0% in 2020 to 16.0% in 2024 (Ptrend < 0.001). However, this progress masked profound structural disparities. Medium and large enterprises exhibited higher exceedance rates (28.0% and 26.0%, respectively) than micro/small enterprises (21.1% and 19.1%), revealing an “enterprise size paradox.” By industry, mining (25.0%) and metallurgy & building materials (21.3%) had the highest risk, yet showed significant annual declines (Ptrend < 0.05). In stark contrast, the chemical production industry showed no improvement over five years (Ptrend = 0.67), indicating a persistent “risk blind spot.” At the job level, high-risk roles such as mining/excavation and melting/casting demonstrated no significant change in their exceedance rates (P = 0.49), highlighting technological path dependency. Conclusion The reduction in occupational noise exposure in Sichuan is highly uneven and structurally determined. The convergence of an “enterprise size paradox,” a chemical industry “risk blind spot,” and stagnant high-risk occupations reflects the differential impact of China’s industrial upgrading strategy. Future public health interventions must adopt a precision approach that targets support to lagging traditional sectors while ensuring that the transition to emerging industries is inclusive of worker health. Occupational noise exposure Noise-induced hearing loss Workplace surveillance Enterprise size Job category Industry China 1. Background Noise is one of the most prevalent occupational hazards in industrial production, capable of causing irreversible noise-induced hearing loss (NIHL) and increasing the risk of cardiovascular diseases and other health issues [ 1 , 2 ] . As the second most reported occupational disease in China, after pneumoconiosis, the prevention and control of NIHL remains a severe challenge [ 3 ] . Sichuan Province, a major industrial hub in China, hosts a concentration of noise-prone industries such as mining, metallurgy, building materials, and machinery manufacturing. However, a systematic analysis of the current status of workplace noise hazards across the entire province is lacking. Previous studies have suggested that noise hazards vary significantly across different industries, enterprise scales, and job types, with micro- and small enterprises (MSEs) typically considered at higher risk due to insufficient protective facilities [ 4 ] . However, this perception may obscure the unique challenges faced by large heavy-industrial enterprises within their complex production systems. Therefore, this study leverages large-scale monitoring data from 2020 to 2024, covering over 50,000 job positions in key industries across Sichuan, to comprehensively reveal the overall situation, dynamic evolution, and deep-seated structural risk characteristics of noise exposure. This will provide critical data support for optimizing occupational health supervision and formulating precise, differentiated engineering prevention and control strategies. 2. Methods Study population: The study population comprised job positions where workers were exposed to noise sources with an intensity of ≥ 70 dB(A), drawn from the Sichuan Workplace Occupational Hazard Surveillance Information System between 2020 and 2024. Data collection and processing: Basic information on employers, industry classification, enterprise scale, monitored job positions, and noise monitoring results were exported from the surveillance system. According to the Occupational Exposure Limits for Hazardous Agents in the Workplace (GBZ 2.2–2007), monitoring results were classified as "exceeding the limit" (≥ 85 dB(A)) or "compliant". Industries were categorized into four groups: (1) Mining; (2) Chemical/Petrochemical and Pharmaceutical (referred to as "Chemical Production"); (3) Metallurgy and Building Materials; and (4) Others (including machinery manufacturing, power, construction, transportation, etc., referred to as "Finished Product Application"). Enterprise scale was classified according to the National Bureau of Statistics of China standards into large, medium, small, and micro enterprises. Statistical analysis: SPSS 30.0 software was used for analysis. Noise intensity, which did not follow a normal distribution, was expressed as the median and interquartile range [ M ( Q 1, Q 3)]. Differences in noise intensity between groups were compared using the Kruskal-Wallis H test and Mann-Whitney U test. Differences and trend analyses for exceedance rates were performed using the chi-square test, chi-square test for trend, and Fisher's exact test. A P -value of < 0.05 was considered statistically significant. 3. Results 3.1 Basic characteristics A total of 15,475 enterprise-years and 51,102 noise-exposed job positions were included in the study. Enterprises in the Metallurgy and Building Materials (6,721 enterprise-years) and Finished Product Application (6,267 enterprise-years) sectors were dominant. Micro-enterprises (6,773 enterprise-years) and small enterprises (7,170 enterprise-years) together accounted for 87.1% of all enterprises. 3.2 Overall monitoring results From 2020 to 2024, among the 51,102 tested positions, 10,435 were found to exceed the limit, resulting in an overall exceedance rate of 20.4%. The median noise intensity was 80.3 dB(A) [IQR: 76.7–84.2]. The specific details of the above two subsections are summarized in Table 1 . Table 1 Overall noise monitoring results in workplaces in Sichuan Province, 2020–2024 Classification No. of Positions M [( Q 1, Q 3), dB(A)] Exceedance Rate (%) Chi-square test Kruskal-Wallis H test χ 2 /χ 2 trend P value H value P value Industry 108.301 b < 0.001 197.675 a < 0.001 Mining 6926 80.8(77.3, 84.7) 25.0 Chemical Production 1102 78.4(74.7, 81.8) 10.9 Metallurgy & BM 21959 80.3(76.5, 84.3) 21.3 Finished Product App. 21115 80.4(76.8, 83.9) 19.3 Year 105.866 c < 0.001 33.435 a < 0.001 2020 12280 80.4(77.0, 84.4) 25.0 2021 12301 80.3(76.7, 84.4) 21.3 2022 9629 80.1(76.3, 84.0) 20.3 2023 8691 80.4(76.5, 84.3) 20.6 2024 8201 80.5(76.7, 83.7) 16.0 Enterprise Size 5.358 c 0.021 4426 a < 0.001 Micro 18326 80.2(76.5, 84.2) 21.1 Small 25533 80.3(76.7, 84.0) 19.1 Medium 6010 80.7(76.8, 84.6) 28.0 Large 1233 81.0(77.6, 85.3) 26.0 Work process 186920 b < 0.001 3509.241 a < 0.001 Welding 3686 80.4(76.9, 83.6) 17.3 Surface treatment 8448 81.8(77.9, 85.8) 28.5 Mechanical processing 3817 81.3(78.2, 85.1) 25.3 Material handling 11249 81.9(78.4, 86.0) 28.6 Molding and packaging 5864 79.1(75.4, 87.0) 14.8 Printing and coating 1023 79.3(76.2, 85.0) 10.0 Material preparation 2846 79.2(75.8, 84.0) 11.0 Mixing and stirring 1846 79.6(75.3, 88.0) 12.0 Melting and casting 4154 79.0(75.3, 85.0) 13.7 Patrol inspection and monitoring 1881 78.8(74.8, 87.0) 14.1 Operation and control 2122 78.9(74.4, 83.3) 18.2 Transportation and handling 1912 78.4(75.7, 80.7) 5.1 Mining and excavation 1013 82.0(78.4, 85.2) 25.6 Maintenance and repair 1241 76.3(78.0, 80.1) 6.8 Total 51102 80.3(76.7, 84.2) 20.4 Note: a = H value; b = χ² value ; c = χ² test for trend value. 3.3 Changes in noise detection results over time At the industry level, the exceedance rates in mining, metallurgy & building materials, and finished product application showed highly significant annual downward trends ( P 0.05). At the enterprise level, the exceedance rates for micro- and small enterprises showed a highly significant annual downward trend ( P 0.05). At the job level, the exceedance rates for welding and surface treatment jobs significantly decreased ( P 0.05). Specifically, the exceedance rate for mining/excavation jobs remained stable at approximately 25%. Data detailed in the above paragraphs are presented in Table 2 . Table 2 Trend analysis of noise monitoring results by category in Sichuan Province, 2020–2024 Classification 2020 2021 2022 2023 2024 Chi-square test No. of Positions Exceedance Rate (%) No. of Positions Exceedance Rate (%) No. of Positions Exceedance Rate (%) No. of Positions Exceedance Rate (%) No. of Positions Exceedance Rate (%) χ 2 trend P value Industry Mining 1387 30.4 1328 27.9 1392 20.7 1480 18.4 1339 15.5 12580 d < 0.001 Chemical Production 485 12 320 15 105 5.7 48 4.2 144 9.7 447 d 0.118 Metallurgy & BM 4930 23.1 5401 29 4471 20.6 3577 23.2 3580 15.6 50.507 d < 0.001 Finished Product App. 5478 20.8 5252 18.5 3661 20.3 3586 19 3138 17 11.752 d < 0.001 Enterprise Size Micro 987 24.2 1027 24.0 786 20.1 679 21.8 389 14.9 66.752 < 0.001 Small 1395 21.3 1138 19.4 845 19.6 810 19.0 688 15.2 5745 < 0.001 Medium 301 24.0 372 24.9 252 21.6 238 25.0 208 21.0 0.701 0.403 Large 74 26.0 83 23.9 72 30.5 61 25.1 30 24.6 0.006 0.936 Work process Welding 147 21.5 104 15.6 141 19.9 133 16.3 111 13.6 1299 < 0.001 Surface treatment 562 30.9 614 30.5 472 29.4 468 29.0 295 21.1 31.527 < 0.001 Mechanical processing 339 27.7 298 28.5 145 21.2 118 28.0 67 19.2 17.751 < 0.001 Material handling 762 33.4 739 30.1 639 30.7 587 29.1 489 20.3 87.816 < 0.001 Molding and packaging 232 15.0 241 15.8 156 14.6 133 14.7 108 13.1 1.924 0.165 Printing and coating 31 9.7 22 9.6 19 10.7 22 14.0 8 6.6 0.013 0.908 Material preparation 87 18.5 59 15.4 102 11.4 70 10.0 27 6.8 34.53 < 0.001 Mixing and stirring 76 14.9 64 13.5 36 11.2 28 11.7 21 7.0 11.13 < 0.001 Melting and casting 125 13.3 146 13.8 121 15.0 99 15.3 79 11.3 0.322 0.57 Patrol inspection and monitoring 70 18.8 63 14.8 40 10.0 48 14.6 44 14.0 5.241 0.022 Operation and control 199 24.1 153 24.3 16 5.8 14 6.3 4 4.0 91.135 < 0.001 Transportation and handling 44 6.4 25 3.8 7 3.0 16 6.4 6 7.1 0.048 0.827 Mining and excavation 63 26.7 51 24.3 47 30.5 46 23.7 52 23.7 0.478 0.49 Maintenance and repair 20 5.4 41 7.8 14 6.4 6 8.8 4 7.3 0.748 0.387 4. Discussion This five-year analysis of occupational noise exposure across over 51,000 job positions in Sichuan Province reveals a complex and dualistic landscape. On one hand, the significant overall decline in the noise exceedance rate—from 25.0% in 2020 to 16.0% in 2024—demonstrates commendable progress and the potential effectiveness of provincial occupational health initiatives [ 5 ] . However, our granular data uncovers multiple layers of inequality that not only threaten to undermine this aggregate success but also profoundly reflect the structural challenges within China’s ongoing transition from old to new growth drivers [ 6 ] . First, we identified a striking “enterprise size paradox.” Contrary to the common assumption that micro- and small enterprises (MSEs) face the greatest challenges in implementing controls due to resource constraints [ 7 ] , our data show that medium and large enterprises consistently exhibited higher noise intensity and significantly higher exceedance rates (28.0% and 26.0%, respectively) compared to MSEs (21.1% and 19.1%). This paradox likely stems from differences in industrial structure. Our data clearly show that the industries with the highest noise risk are mining (25.0%) and metallurgy & building materials (21.3%), which are precisely the sectors where medium and large enterprises are concentrated [ 8 ] . The scale and complexity of their operations may lead to a reliance on administrative controls and PPE, while the high cost of engineering retrofits creates a barrier to more effective source-level interventions [ 9 ] . This finding aligns with global evidence that large-scale continuous-process industries often exhibit entrenched noise hazards resistant to conventional control measures [ 10 ] . Most intriguingly, different traditional industries have shown divergent trajectories in noise control, challenging the simplistic view of “traditional industries” as a homogeneous group. Our data clearly show that the mining and metallurgy & building materials sectors have achieved highly significant annual declines in their noise exceedance rates ( P < 0.05). This positive change is likely attributable to the strong national push in recent years for work safety special rectification campaigns and green mine/factory construction initiatives [ 11 ] . For instance, in mining, the increased proportion of open-pit mining, the adoption of large automated drilling rigs, and the upgrading of underground ventilation and noise reduction systems may have effectively lowered workers' noise exposure levels [ 12 ] . Similar automation-driven improvements have been documented in global heavy industry contexts [ 13 ] . However, in stark contrast, the chemical production industry’s exceedance rate has shown no statistically significant change over the five years ( P > 0.05). This “stagnation” warrants high alert. Although chemical processes do not involve the violent physical impacts seen in mining or smelting, they possess unique high-noise sources (e.g., large compressors, vacuum pumps, high-pressure reactor venting, turbulent fluid flow in pipelines) that are often overlooked [ 14 ] . These noise sources are typically continuous, insidious, and widespread, making them difficult to mitigate with simple local acoustic enclosures [ 15 ] . The “zero improvement” in the chemical industry may reflect a long-standing focus of its occupational health management on acute risks like chemical toxins and fire/explosion, with relatively insufficient attention and investment in chronic physical hazards like noise, creating a neglected risk blind spot [ 16 ] . This is particularly concerning given the potential synergistic ototoxic effects of certain chemical solvents (e.g., toluene, styrene) and noise, which can accelerate hearing loss beyond what either hazard would cause alone [ 17 , 18 ] . Regulatory frameworks in many countries, including China, have been slow to integrate such combined exposure assessments into routine practice [ 19 ] . Second, the stagnation of specific high-risk occupations further confirms the existence of these structural challenges. The fact that mining/excavation and melting/casting jobs have shown no improvement in their exceedance rates over five years ( P = 0.49) is no coincidence. These jobs represent the core processes of the aforementioned traditional heavy industries, whose production models are far removed from the emerging intelligent manufacturing paradigm [ 20 ] . This technological path dependency locks workers into hazardous environments, as the capital-intensive nature of these processes makes rapid transformation economically unfeasible without external support [ 21 ] . Studies in other middle-income countries have similarly found that legacy industrial sectors exhibit “occupational inertia,” where health risks persist despite overall economic modernization [ 22 ] . Placing our findings within the context of the national industrial upgrading strategy gives them even greater significance. China is currently vigorously cultivating four new industrial clusters centered on artificial intelligence, new energy vehicles, low-altitude economy, and integrated circuits/hard technology [ 23 ] . The working environments in these “future industries” stand in sharp contrast to traditional heavy industry: they rely more on clean rooms, precision instruments, and digital control, which inherently carry much lower physical hazards (such as high-intensity noise and dust) [ 24 ] . Therefore, the “enterprise size paradox,” the chemical industry’s “risk blind spot,” and the “stagnation” of high-risk jobs we observe are essentially different facets of traditional industries being “left behind” in the wave of industrial transformation [ 25 ] . Traditional enterprises that fail to timely embrace intelligent and green transformations are seeing their workers’ occupational health and safety left vulnerable to being forgotten by the times—a phenomenon increasingly recognized as “occupational health inequality in the era of Industry 4.0” [ 26 ] . Strengths and limitations of this study A major strength of this study is its scale and representativeness. By analyzing data from 15,475 enterprise-years and 51,102 unique job positions, it provides one of the most comprehensive pictures of occupational noise exposure in Western China to date. The use of official surveillance data enhances its validity and policy relevance. Furthermore, the five-year longitudinal design allows for a robust assessment of temporal trends across multiple strata. However, several limitations must be acknowledged. First, as a cross-sectional analysis of aggregated annual monitoring data, it cannot establish causal relationships between enterprise characteristics or job types and noise risk. Second, the data rely on employer-reported monitoring, which may be subject to reporting bias, although the mandatory nature of the system in China mitigates this to some extent. Third, our analysis did not account for individual-level factors such as the duration of exposure, use of hearing protection, or audiometric outcomes (hearing loss), which are crucial for a complete risk assessment. Finally, while our findings are highly relevant to Sichuan and similar industrial regions in China, their generalizability to other countries with different regulatory and economic contexts may be limited. In conclusion, occupational health issues are no longer merely technical or managerial problems but are a barometer of macroeconomic transformation. Future public health strategies must adopt a two-pronged approach: on one hand, providing strong policy support and technical assistance to traditional industries; and on the other, ensuring a smooth transition of the workforce towards safer and healthier emerging industries. 5. Conclusions Our analysis indicates that the progress in controlling occupational noise exposure in Sichuan Province is highly uneven, underpinned by profound industrial structural changes and internal differentiation within sectors. The “enterprise size paradox” in noise risk centrally reflects the dilemma of traditional heavy industries (e.g., mining, metallurgy & building materials) as the mainstay of medium and large enterprises. It is commendable that, benefiting from strong work safety policies, the mining and metallurgy & building materials sectors have achieved significant improvements. However, our study also reveals a dangerous blind spot: the noise risk in the chemical production industry has shown no progress over five years ( P > 0.05), highlighting a systemic neglect of physical hazards within its occupational health management system. Simultaneously, the long-term stagnation of core high-risk jobs like mining/excavation serves as a warning about the profound impact of technological path dependency on worker health. These findings collectively point to a core proposition: future high-quality development must be inclusive and cannot come at the cost of the health of workers in specific industries. We call for occupational health policies to resonate in harmony with the national industrial strategy. For traditional industries undergoing transformation, targeted support is needed to accelerate their intelligent and green upgrades. For the chemical industry, which harbors a “risk blind spot,” urgent specialized governance is required to fully integrate physical hazards into its process safety management system. Only in this way can we ensure that on the path towards future industries represented by artificial intelligence, new energy, and hard technology, the hearing health of every single worker is not left behind. Declarations Ethics approval and consent to participate: This study used anonymized, aggregated surveillance data with no identifiable individual information. Ethical review was not required per Chinese regulations. Consent for publication: Not applicable. Funding: This work was supported by the Key R&D Program of Sichuan Province in Livelihood and Service Sector (Grant No. 2024YFFK0195). Author Contribution WZC conceived the study, performed data analysis, and drafted the manuscript. XXL and WWS contributed to data curation and statistical validation. LPQ supervised the research and critically revised the manuscript. All authors read and approved the final version. Data Availability The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request. References Salam SNA, Kamaludin NF, Awang N, Ithnin A, Nata DHMS, Mohd Saat NZ. Occupational noise exposure and its effects among mill workers: A narrative review. Noise Health 2024 Oct-Dec 01;26(123):461–73. 10.4103/nah.nah_43_23 Mehrotra A, Shukla SP, Shukla AK, Manar MK, Singh SK, Mehrotra M. A Comprehensive Review of Auditory and Non-Auditory Effects of Noise on Human Health. Noise Health . 2024 Apr-Jun 01;26(121):59–69. 10.4103/nah.nah_124_23 Zhou J, Shi Z, Zhou L, Hu Y, Zhang M. Occupational noise-induced hearing loss in China: a systematic review and meta-analysis. BMJ Open. 2020;10(9):e039576. 10.1136/bmjopen-2020-039576 . Published 2020 Sep 28. Ruan Y, Huang G, Zhang J, et al. Risk analysis of noise-induced hearing loss of workers in the automobile manufacturing industries based on back-propagation neural network model: a cross-sectional study in Han Chinese population. BMJ Open. 2024;14(5):e079955. 10.1136/bmjopen-2023-079955 . Published 2024 May 17. Fuente A, Hickson L, McPherson B. Noise-induced hearing loss in the workplace: A global perspective. Int J Audiol. 2024;63(5):321–30. 10.1080/14992027.2023.2287654 . Liu W, Dijkstra L, Krämer R. The geography of China's new economic geography: Industrial policy and regional divergence. Reg Stud. 2023;57(8):1325–38. 10.1080/00343404.2022.2152221 . Liang Y, Chen Z, Liu Y, et al. Analysis of occupational noise exposure and hearing loss among workers in small and medium-sized enterprises in Guangdong Province. Ind Health. 2023;61(4):456–63. 10.2486/indhealth.2022-0201 . Wang J, Zhang H, Li X, et al. Occupational noise exposure and hearing impairment in Chinese coal miners: A cross-sectional study. Environ Sci Pollut Res Int. 2022;29(34):51234–42. 10.1007/s11356-022-19352-4 . Neitzel RL, Daniell WE, Seixas NS. Estimation of the effect of engineering controls on noise exposures in the US construction industry. Ann Occup Hyg. 2013;57(7):897–907. 10.1093/annhyg/met015 . Morata TC, Dunn DE, Kretschmer LW, et al. Occupational hearing loss: A review of its prevention and compensation. Am J Ind Med. 2022;65(1):5–17. 10.1002/ajim.23335 . Zhao Y, Zhang M, Hu Y, et al. Impact of the Green Mine policy on occupational health and safety in China's mining sector. Saf Sci. 2024;172:106389. 10.1016/j.ssci.2023.106389 . Sun J, Li Q, Wang L, et al. Noise exposure assessment and control strategies in Chinese metal mines. J Occup Environ Hyg. 2021;18(10):521–9. 10.1080/15459624.2021.1935942 . Chen R, Zeng F, Gao X, et al. Prevalence and risk factors of noise-induced hearing loss among workers in a large steel plant in China. Int Arch Occup Environ Health. 2024;97(5):789–97. 10.1007/s00420-024-01987-1 . Sliwinska-Kowalska M, Pawlaczyk-Łuszczyńska M. Noise-induced hearing loss and co-exposure to workplace chemicals. Int J Occup Med Environ Health. 2023;36(1):5–19. 10.13075/ijomeh.1896.02001 . Johnson AC, Morata TC, Chen G, et al. Ototoxicity and noise: A neglected occupational health issue. Noise Health. 2024;26(122):289–95. 10.4103/nah.nah_102_23 . Clerc F, Pouyatos B. A Case Study about Joining Databases for the Assessment of Exposures to Noise and Ototoxic Substances in Occupational Settings. Int J Environ Res Public Health. 2022;19(8). 10.3390/ijerph19084455 . Published 2022 Apr 7. Campo P, Venet T, Cour C, et al. Combined effects of noise and styrene on the auditory system: An animal model study. Toxicol Sci. 2023;191(2):234–45. 10.1093/toxsci/kfac123 . Fechter LD, Gearhart C, Pham N, et al. Synergistic interactions between noise and toluene in the rat cochlea. Hear Res. 2022;415:108345. 10.1016/j.heares.2022.108345 . Lie A, Skogstad M, Johnsen TS, et al. Hearing loss among Norwegian offshore oil industry workers exposed to noise and organic solvents. Occup Environ Med. 2023;80(4):245–52. 10.1136/oemed-2022-108567 . Zhang Y, Liu X, Wang F. Technological lock-in and the challenge of green transition in China's heavy industry. Energy Policy. 2023;183:113876. 10.1016/j.enpol.2023.113876 . Li H, Zhou Y, Wu Y. Path dependency and innovation barriers in China's traditional manufacturing sector. Technol Forecast Soc Change. 2022;184:122015. 10.1016/j.techfore.2022.122015 . Oke SA, Charles-Owaba OE, Adetunji OR. Occupational noise exposure and hearing loss in developing economies: A review of challenges and opportunities. Saf Sci. 2023;167:106245. 10.1016/j.ssci.2023.106245 . National Bureau of Statistics of China. China Statistical Yearbook on High-tech Industry 2024. Beijing: China Statistics; 2024. Chen L, Xu B, Li J. Occupational health risk assessment in China's emerging strategic industries. J Expo Sci Environ Epidemiol. 2025;35(1):45–53. 10.1038/s41370-024-00678-1 . Yang T, Li S, Wang Q. Industrial restructuring and occupational health disparities in China: Evidence from panel data. Soc Sci Med. 2024;342:116589. 10.1016/j.socscimed.2023.116589 . World Health Organization (WHO). Guidelines on safe listening devices and systems for adults and children. Geneva: WHO; 2023. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 23 Mar, 2026 Reviews received at journal 20 Mar, 2026 Reviewers agreed at journal 11 Mar, 2026 Reviewers agreed at journal 09 Mar, 2026 Reviewers invited by journal 09 Mar, 2026 Editor invited by journal 10 Feb, 2026 Editor assigned by journal 10 Feb, 2026 Submission checks completed at journal 10 Feb, 2026 First submitted to journal 07 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8816045","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":604607976,"identity":"2e9e89cb-f3ed-4d44-90b7-212214998d93","order_by":0,"name":"Weizhong Chu","email":"","orcid":"","institution":"Sichuan Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Weizhong","middleName":"","lastName":"Chu","suffix":""},{"id":604607977,"identity":"f217e4a8-7a04-46d6-9fbe-16f730f53a10","order_by":1,"name":"Xiangxiang Lu","email":"","orcid":"","institution":"Sichuan Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Xiangxiang","middleName":"","lastName":"Lu","suffix":""},{"id":604607978,"identity":"6774a110-1d30-4617-a7fa-b95ab79fa2b9","order_by":2,"name":"Weiwei Shang","email":"","orcid":"","institution":"Sichuan Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Weiwei","middleName":"","lastName":"Shang","suffix":""},{"id":604607980,"identity":"573a754b-943e-49da-b5d4-25303506c28f","order_by":3,"name":"Leping Qiu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuElEQVRIiWNgGAWjYBACNmbG9s9/DGrk+NkbiNTCx858jIGn4pixZM8BIrXI8bOlMfCcYU7ccCOBaIfxmD2QbGMzNrj5eOMNhhqbaGK0mBsYtsnISd5OK7ZgOJaW20CEFgOJRKAtfLdzzCQYGw4TqeVgG3Niw80zRGthS5NsAHp/wg0eorUwHzZmAAcy0C8JxPhFvv9g42MGcFQe3njjQ40NYS3IwEAigRTlEC2k6hgFo2AUjIKRAQD6MznIL9q5eQAAAABJRU5ErkJggg==","orcid":"","institution":"Sichuan Center for Disease Control and Prevention","correspondingAuthor":true,"prefix":"","firstName":"Leping","middleName":"","lastName":"Qiu","suffix":""}],"badges":[],"createdAt":"2026-02-07 14:08:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8816045/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8816045/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104516573,"identity":"3fa955c8-a678-4740-988c-403b64cf7071","added_by":"auto","created_at":"2026-03-12 17:40:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":912062,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8816045/v1/702ee124-317a-45e2-be41-699be47da5cf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Persistent Structural Disparities in Occupational Noise Exposure: A Five-Year Analysis of 51,102 Workplaces in Sichuan Province, China","fulltext":[{"header":"1. Background","content":"\u003cp\u003eNoise is one of the most prevalent occupational hazards in industrial production, capable of causing irreversible noise-induced hearing loss (NIHL) and increasing the risk of cardiovascular diseases and other health issues\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. As the second most reported occupational disease in China, after pneumoconiosis, the prevention and control of NIHL remains a severe challenge\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Sichuan Province, a major industrial hub in China, hosts a concentration of noise-prone industries such as mining, metallurgy, building materials, and machinery manufacturing. However, a systematic analysis of the current status of workplace noise hazards across the entire province is lacking.\u003c/p\u003e \u003cp\u003ePrevious studies have suggested that noise hazards vary significantly across different industries, enterprise scales, and job types, with micro- and small enterprises (MSEs) typically considered at higher risk due to insufficient protective facilities\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. However, this perception may obscure the unique challenges faced by large heavy-industrial enterprises within their complex production systems. Therefore, this study leverages large-scale monitoring data from 2020 to 2024, covering over 50,000 job positions in key industries across Sichuan, to comprehensively reveal the overall situation, dynamic evolution, and deep-seated structural risk characteristics of noise exposure. This will provide critical data support for optimizing occupational health supervision and formulating precise, differentiated engineering prevention and control strategies.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eStudy population: The study population comprised job positions where workers were exposed to noise sources with an intensity of \u0026ge;\u0026thinsp;70 dB(A), drawn from the Sichuan Workplace Occupational Hazard Surveillance Information System between 2020 and 2024.\u003c/p\u003e \u003cp\u003eData collection and processing: Basic information on employers, industry classification, enterprise scale, monitored job positions, and noise monitoring results were exported from the surveillance system. According to the \u003cem\u003eOccupational Exposure Limits for Hazardous Agents in the Workplace\u003c/em\u003e (GBZ 2.2\u0026ndash;2007), monitoring results were classified as \"exceeding the limit\" (\u0026ge;\u0026thinsp;85 dB(A)) or \"compliant\". Industries were categorized into four groups: (1) Mining; (2) Chemical/Petrochemical and Pharmaceutical (referred to as \"Chemical Production\"); (3) Metallurgy and Building Materials; and (4) Others (including machinery manufacturing, power, construction, transportation, etc., referred to as \"Finished Product Application\"). Enterprise scale was classified according to the National Bureau of Statistics of China standards into large, medium, small, and micro enterprises.\u003c/p\u003e \u003cp\u003eStatistical analysis: SPSS 30.0 software was used for analysis. Noise intensity, which did not follow a normal distribution, was expressed as the median and interquartile range [\u003cem\u003eM\u003c/em\u003e (\u003cem\u003eQ\u003c/em\u003e1, \u003cem\u003eQ\u003c/em\u003e3)]. Differences in noise intensity between groups were compared using the Kruskal-Wallis H test and Mann-Whitney U test. Differences and trend analyses for exceedance rates were performed using the chi-square test, chi-square test for trend, and Fisher's exact test. A \u003cem\u003eP\u003c/em\u003e-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Basic characteristics\u003c/h2\u003e \u003cp\u003eA total of 15,475 enterprise-years and 51,102 noise-exposed job positions were included in the study. Enterprises in the Metallurgy and Building Materials (6,721 enterprise-years) and Finished Product Application (6,267 enterprise-years) sectors were dominant. Micro-enterprises (6,773 enterprise-years) and small enterprises (7,170 enterprise-years) together accounted for 87.1% of all enterprises.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Overall monitoring results\u003c/h2\u003e \u003cp\u003eFrom 2020 to 2024, among the 51,102 tested positions, 10,435 were found to exceed the limit, resulting in an overall exceedance rate of 20.4%. The median noise intensity was 80.3 dB(A) [IQR: 76.7\u0026ndash;84.2].\u003c/p\u003e \u003cp\u003eThe specific details of the above two subsections are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOverall noise monitoring results in workplaces in Sichuan Province, 2020\u0026ndash;2024\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClassification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo. of Positions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e[(\u003cem\u003eQ\u003c/em\u003e1, \u003cem\u003eQ\u003c/em\u003e3), dB(A)]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExceedance Rate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eChi-square test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eKruskal-Wallis H test\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e/χ\u003csup\u003e2\u003c/sup\u003e\u003csub\u003etrend\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eH value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndustry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e108.301\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e197.675\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.8(77.3, 84.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemical Production\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.4(74.7, 81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetallurgy \u0026amp; BM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21959\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.3(76.5, 84.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFinished Product App.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.4(76.8, 83.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e105.866\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.435\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.4(77.0, 84.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.3(76.7, 84.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.1(76.3, 84.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8691\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.4(76.5, 84.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.5(76.7, 83.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnterprise Size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.358\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4426\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.2(76.5, 84.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.3(76.7, 84.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.7(76.8, 84.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.0(77.6, 85.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWork process\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186920\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3509.241\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWelding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.4(76.9, 83.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurface treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.8(77.9, 85.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical processing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.3(78.2, 85.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaterial handling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.9(78.4, 86.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMolding and packaging\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5864\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79.1(75.4, 87.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrinting and coating\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79.3(76.2, 85.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaterial preparation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79.2(75.8, 84.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixing and stirring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79.6(75.3, 88.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMelting and casting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79.0(75.3, 85.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatrol inspection and monitoring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1881\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.8(74.8, 87.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOperation and control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.9(74.4, 83.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransportation and handling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.4(75.7, 80.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMining and excavation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82.0(78.4, 85.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaintenance and repair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76.3(78.0, 80.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.3(76.7, 84.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNote: a\u0026thinsp;=\u0026thinsp;H value; b\u0026thinsp;=\u0026thinsp;χ\u0026sup2; \u003csub\u003evalue\u003c/sub\u003e; c\u0026thinsp;=\u0026thinsp;χ\u0026sup2; test for trend value.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Changes in noise detection results over time\u003c/h2\u003e \u003cp\u003eAt the industry level, the exceedance rates in mining, metallurgy \u0026amp; building materials, and finished product application showed highly significant annual downward trends (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while the chemical production industry showed no statistical change over the five years (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eAt the enterprise level, the exceedance rates for micro- and small enterprises showed a highly significant annual downward trend (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas medium- and large-sized enterprises showed no statistical change (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eAt the job level, the exceedance rates for welding and surface treatment jobs significantly decreased (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but high-risk jobs like mining/excavation and melting/casting showed no improvement over the five years (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Specifically, the exceedance rate for mining/excavation jobs remained stable at approximately 25%.\u003c/p\u003e \u003cp\u003eData detailed in the above paragraphs are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTrend analysis of noise monitoring results by category in Sichuan Province, 2020\u0026ndash;2024\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClassification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eChi-square test\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo. of Positions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExceedance Rate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo. of Positions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExceedance Rate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo. of Positions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eExceedance Rate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo. of Positions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eExceedance Rate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo. of Positions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eExceedance Rate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003csub\u003etrend\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndustry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e12580\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemical Production\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e447\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetallurgy \u0026amp; BM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e50.507\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFinished Product App.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e11.752\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnterprise Size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e66.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e688\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e15.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e21.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.403\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e24.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.936\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWork process\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWelding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurface treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e31.527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical processing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e21.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e19.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e17.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaterial handling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e87.816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMolding and packaging\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrinting and coating\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaterial preparation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e34.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixing and stirring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e11.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMelting and casting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatrol inspection and monitoring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5.241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOperation and control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e91.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransportation and handling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMining and excavation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e23.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaintenance and repair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.387\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis five-year analysis of occupational noise exposure across over 51,000 job positions in Sichuan Province reveals a complex and dualistic landscape. On one hand, the significant overall decline in the noise exceedance rate\u0026mdash;from 25.0% in 2020 to 16.0% in 2024\u0026mdash;demonstrates commendable progress and the potential effectiveness of provincial occupational health initiatives\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. However, our granular data uncovers multiple layers of inequality that not only threaten to undermine this aggregate success but also profoundly reflect the structural challenges within China\u0026rsquo;s ongoing transition from old to new growth drivers\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFirst, we identified a striking \u0026ldquo;enterprise size paradox.\u0026rdquo; Contrary to the common assumption that micro- and small enterprises (MSEs) face the greatest challenges in implementing controls due to resource constraints\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e, our data show that medium and large enterprises consistently exhibited higher noise intensity and significantly higher exceedance rates (28.0% and 26.0%, respectively) compared to MSEs (21.1% and 19.1%). This paradox likely stems from differences in industrial structure. Our data clearly show that the industries with the highest noise risk are mining (25.0%) and metallurgy \u0026amp; building materials (21.3%), which are precisely the sectors where medium and large enterprises are concentrated\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. The scale and complexity of their operations may lead to a reliance on administrative controls and PPE, while the high cost of engineering retrofits creates a barrier to more effective source-level interventions\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. This finding aligns with global evidence that large-scale continuous-process industries often exhibit entrenched noise hazards resistant to conventional control measures\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMost intriguingly, different traditional industries have shown divergent trajectories in noise control, challenging the simplistic view of \u0026ldquo;traditional industries\u0026rdquo; as a homogeneous group. Our data clearly show that the mining and metallurgy \u0026amp; building materials sectors have achieved highly significant annual declines in their noise exceedance rates (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This positive change is likely attributable to the strong national push in recent years for work safety special rectification campaigns and green mine/factory construction initiatives\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. For instance, in mining, the increased proportion of open-pit mining, the adoption of large automated drilling rigs, and the upgrading of underground ventilation and noise reduction systems may have effectively lowered workers' noise exposure levels\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Similar automation-driven improvements have been documented in global heavy industry contexts\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, in stark contrast, the chemical production industry\u0026rsquo;s exceedance rate has shown no statistically significant change over the five years (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). This \u0026ldquo;stagnation\u0026rdquo; warrants high alert. Although chemical processes do not involve the violent physical impacts seen in mining or smelting, they possess unique high-noise sources (e.g., large compressors, vacuum pumps, high-pressure reactor venting, turbulent fluid flow in pipelines) that are often overlooked\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. These noise sources are typically continuous, insidious, and widespread, making them difficult to mitigate with simple local acoustic enclosures\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. The \u0026ldquo;zero improvement\u0026rdquo; in the chemical industry may reflect a long-standing focus of its occupational health management on acute risks like chemical toxins and fire/explosion, with relatively insufficient attention and investment in chronic physical hazards like noise, creating a neglected risk blind spot\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. This is particularly concerning given the potential synergistic ototoxic effects of certain chemical solvents (e.g., toluene, styrene) and noise, which can accelerate hearing loss beyond what either hazard would cause alone\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Regulatory frameworks in many countries, including China, have been slow to integrate such combined exposure assessments into routine practice\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSecond, the stagnation of specific high-risk occupations further confirms the existence of these structural challenges. The fact that mining/excavation and melting/casting jobs have shown no improvement in their exceedance rates over five years (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.49) is no coincidence. These jobs represent the core processes of the aforementioned traditional heavy industries, whose production models are far removed from the emerging intelligent manufacturing paradigm\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. This technological path dependency locks workers into hazardous environments, as the capital-intensive nature of these processes makes rapid transformation economically unfeasible without external support\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Studies in other middle-income countries have similarly found that legacy industrial sectors exhibit \u0026ldquo;occupational inertia,\u0026rdquo; where health risks persist despite overall economic modernization\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePlacing our findings within the context of the national industrial upgrading strategy gives them even greater significance. China is currently vigorously cultivating four new industrial clusters centered on artificial intelligence, new energy vehicles, low-altitude economy, and integrated circuits/hard technology\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. The working environments in these \u0026ldquo;future industries\u0026rdquo; stand in sharp contrast to traditional heavy industry: they rely more on clean rooms, precision instruments, and digital control, which inherently carry much lower physical hazards (such as high-intensity noise and dust) \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Therefore, the \u0026ldquo;enterprise size paradox,\u0026rdquo; the chemical industry\u0026rsquo;s \u0026ldquo;risk blind spot,\u0026rdquo; and the \u0026ldquo;stagnation\u0026rdquo; of high-risk jobs we observe are essentially different facets of traditional industries being \u0026ldquo;left behind\u0026rdquo; in the wave of industrial transformation\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Traditional enterprises that fail to timely embrace intelligent and green transformations are seeing their workers\u0026rsquo; occupational health and safety left vulnerable to being forgotten by the times\u0026mdash;a phenomenon increasingly recognized as \u0026ldquo;occupational health inequality in the era of Industry 4.0\u0026rdquo; \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStrengths and limitations of this study\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA major strength of this study is its scale and representativeness. By analyzing data from 15,475 enterprise-years and 51,102 unique job positions, it provides one of the most comprehensive pictures of occupational noise exposure in Western China to date. The use of official surveillance data enhances its validity and policy relevance. Furthermore, the five-year longitudinal design allows for a robust assessment of temporal trends across multiple strata.\u003c/p\u003e \u003cp\u003eHowever, several limitations must be acknowledged. First, as a cross-sectional analysis of aggregated annual monitoring data, it cannot establish causal relationships between enterprise characteristics or job types and noise risk. Second, the data rely on employer-reported monitoring, which may be subject to reporting bias, although the mandatory nature of the system in China mitigates this to some extent. Third, our analysis did not account for individual-level factors such as the duration of exposure, use of hearing protection, or audiometric outcomes (hearing loss), which are crucial for a complete risk assessment. Finally, while our findings are highly relevant to Sichuan and similar industrial regions in China, their generalizability to other countries with different regulatory and economic contexts may be limited.\u003c/p\u003e \u003cp\u003eIn conclusion, occupational health issues are no longer merely technical or managerial problems but are a barometer of macroeconomic transformation. Future public health strategies must adopt a two-pronged approach: on one hand, providing strong policy support and technical assistance to traditional industries; and on the other, ensuring a smooth transition of the workforce towards safer and healthier emerging industries.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eOur analysis indicates that the progress in controlling occupational noise exposure in Sichuan Province is highly uneven, underpinned by profound industrial structural changes and internal differentiation within sectors. The \u0026ldquo;enterprise size paradox\u0026rdquo; in noise risk centrally reflects the dilemma of traditional heavy industries (e.g., mining, metallurgy \u0026amp; building materials) as the mainstay of medium and large enterprises. It is commendable that, benefiting from strong work safety policies, the mining and metallurgy \u0026amp; building materials sectors have achieved significant improvements. However, our study also reveals a dangerous blind spot: the noise risk in the chemical production industry has shown no progress over five years (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), highlighting a systemic neglect of physical hazards within its occupational health management system. Simultaneously, the long-term stagnation of core high-risk jobs like mining/excavation serves as a warning about the profound impact of technological path dependency on worker health.\u003c/p\u003e \u003cp\u003eThese findings collectively point to a core proposition: future high-quality development must be inclusive and cannot come at the cost of the health of workers in specific industries. We call for occupational health policies to resonate in harmony with the national industrial strategy. For traditional industries undergoing transformation, targeted support is needed to accelerate their intelligent and green upgrades. For the chemical industry, which harbors a \u0026ldquo;risk blind spot,\u0026rdquo; urgent specialized governance is required to fully integrate physical hazards into its process safety management system. Only in this way can we ensure that on the path towards future industries represented by artificial intelligence, new energy, and hard technology, the hearing health of every single worker is not left behind.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e \u003cp\u003eThis study used anonymized, aggregated surveillance data with no identifiable individual information. Ethical review was not required per Chinese regulations.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication:\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work was supported by the Key R\u0026amp;D Program of Sichuan Province in Livelihood and Service Sector (Grant No. 2024YFFK0195).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eWZC conceived the study, performed data analysis, and drafted the manuscript. XXL and WWS contributed to data curation and statistical validation. LPQ supervised the research and critically revised the manuscript. All authors read and approved the final version.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSalam SNA, Kamaludin NF, Awang N, Ithnin A, Nata DHMS, Mohd Saat NZ. Occupational noise exposure and its effects among mill workers: A narrative review. Noise Health 2024 Oct-Dec 01;26(123):461\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/nah.nah_43_23\u003c/span\u003e\u003cspan address=\"10.4103/nah.nah_43_23\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMehrotra A, Shukla SP, Shukla AK, Manar MK, Singh SK, Mehrotra M. A Comprehensive Review of Auditory and Non-Auditory Effects of Noise on Human Health. \u003cem\u003eNoise Health\u003c/em\u003e. 2024 Apr-Jun 01;26(121):59\u0026ndash;69. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/nah.nah_124_23\u003c/span\u003e\u003cspan address=\"10.4103/nah.nah_124_23\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou J, Shi Z, Zhou L, Hu Y, Zhang M. Occupational noise-induced hearing loss in China: a systematic review and meta-analysis. BMJ Open. 2020;10(9):e039576. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2020-039576\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2020-039576\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2020 Sep 28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRuan Y, Huang G, Zhang J, et al. Risk analysis of noise-induced hearing loss of workers in the automobile manufacturing industries based on back-propagation neural network model: a cross-sectional study in Han Chinese population. BMJ Open. 2024;14(5):e079955. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2023-079955\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2023-079955\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2024 May 17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFuente A, Hickson L, McPherson B. Noise-induced hearing loss in the workplace: A global perspective. Int J Audiol. 2024;63(5):321\u0026ndash;30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/14992027.2023.2287654\u003c/span\u003e\u003cspan address=\"10.1080/14992027.2023.2287654\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu W, Dijkstra L, Kr\u0026auml;mer R. The geography of China's new economic geography: Industrial policy and regional divergence. Reg Stud. 2023;57(8):1325\u0026ndash;38. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/00343404.2022.2152221\u003c/span\u003e\u003cspan address=\"10.1080/00343404.2022.2152221\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiang Y, Chen Z, Liu Y, et al. Analysis of occupational noise exposure and hearing loss among workers in small and medium-sized enterprises in Guangdong Province. Ind Health. 2023;61(4):456\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2486/indhealth.2022-0201\u003c/span\u003e\u003cspan address=\"10.2486/indhealth.2022-0201\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang J, Zhang H, Li X, et al. Occupational noise exposure and hearing impairment in Chinese coal miners: A cross-sectional study. Environ Sci Pollut Res Int. 2022;29(34):51234\u0026ndash;42. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11356-022-19352-4\u003c/span\u003e\u003cspan address=\"10.1007/s11356-022-19352-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeitzel RL, Daniell WE, Seixas NS. Estimation of the effect of engineering controls on noise exposures in the US construction industry. Ann Occup Hyg. 2013;57(7):897\u0026ndash;907. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/annhyg/met015\u003c/span\u003e\u003cspan address=\"10.1093/annhyg/met015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorata TC, Dunn DE, Kretschmer LW, et al. Occupational hearing loss: A review of its prevention and compensation. Am J Ind Med. 2022;65(1):5\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/ajim.23335\u003c/span\u003e\u003cspan address=\"10.1002/ajim.23335\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao Y, Zhang M, Hu Y, et al. Impact of the Green Mine policy on occupational health and safety in China's mining sector. Saf Sci. 2024;172:106389. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ssci.2023.106389\u003c/span\u003e\u003cspan address=\"10.1016/j.ssci.2023.106389\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun J, Li Q, Wang L, et al. Noise exposure assessment and control strategies in Chinese metal mines. J Occup Environ Hyg. 2021;18(10):521\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/15459624.2021.1935942\u003c/span\u003e\u003cspan address=\"10.1080/15459624.2021.1935942\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen R, Zeng F, Gao X, et al. Prevalence and risk factors of noise-induced hearing loss among workers in a large steel plant in China. Int Arch Occup Environ Health. 2024;97(5):789\u0026ndash;97. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00420-024-01987-1\u003c/span\u003e\u003cspan address=\"10.1007/s00420-024-01987-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSliwinska-Kowalska M, Pawlaczyk-Łuszczyńska M. Noise-induced hearing loss and co-exposure to workplace chemicals. Int J Occup Med Environ Health. 2023;36(1):5\u0026ndash;19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.13075/ijomeh.1896.02001\u003c/span\u003e\u003cspan address=\"10.13075/ijomeh.1896.02001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnson AC, Morata TC, Chen G, et al. Ototoxicity and noise: A neglected occupational health issue. Noise Health. 2024;26(122):289\u0026ndash;95. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/nah.nah_102_23\u003c/span\u003e\u003cspan address=\"10.4103/nah.nah_102_23\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClerc F, Pouyatos B. A Case Study about Joining Databases for the Assessment of Exposures to Noise and Ototoxic Substances in Occupational Settings. Int J Environ Res Public Health. 2022;19(8). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph19084455\u003c/span\u003e\u003cspan address=\"10.3390/ijerph19084455\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2022 Apr 7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCampo P, Venet T, Cour C, et al. Combined effects of noise and styrene on the auditory system: An animal model study. Toxicol Sci. 2023;191(2):234\u0026ndash;45. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/toxsci/kfac123\u003c/span\u003e\u003cspan address=\"10.1093/toxsci/kfac123\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFechter LD, Gearhart C, Pham N, et al. Synergistic interactions between noise and toluene in the rat cochlea. Hear Res. 2022;415:108345. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.heares.2022.108345\u003c/span\u003e\u003cspan address=\"10.1016/j.heares.2022.108345\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLie A, Skogstad M, Johnsen TS, et al. Hearing loss among Norwegian offshore oil industry workers exposed to noise and organic solvents. Occup Environ Med. 2023;80(4):245\u0026ndash;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/oemed-2022-108567\u003c/span\u003e\u003cspan address=\"10.1136/oemed-2022-108567\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Y, Liu X, Wang F. Technological lock-in and the challenge of green transition in China's heavy industry. Energy Policy. 2023;183:113876. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.enpol.2023.113876\u003c/span\u003e\u003cspan address=\"10.1016/j.enpol.2023.113876\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi H, Zhou Y, Wu Y. Path dependency and innovation barriers in China's traditional manufacturing sector. Technol Forecast Soc Change. 2022;184:122015. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.techfore.2022.122015\u003c/span\u003e\u003cspan address=\"10.1016/j.techfore.2022.122015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOke SA, Charles-Owaba OE, Adetunji OR. Occupational noise exposure and hearing loss in developing economies: A review of challenges and opportunities. Saf Sci. 2023;167:106245. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ssci.2023.106245\u003c/span\u003e\u003cspan address=\"10.1016/j.ssci.2023.106245\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Bureau of Statistics of China. China Statistical Yearbook on High-tech Industry 2024. Beijing: China Statistics; 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen L, Xu B, Li J. Occupational health risk assessment in China's emerging strategic industries. J Expo Sci Environ Epidemiol. 2025;35(1):45\u0026ndash;53. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41370-024-00678-1\u003c/span\u003e\u003cspan address=\"10.1038/s41370-024-00678-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang T, Li S, Wang Q. Industrial restructuring and occupational health disparities in China: Evidence from panel data. Soc Sci Med. 2024;342:116589. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.socscimed.2023.116589\u003c/span\u003e\u003cspan address=\"10.1016/j.socscimed.2023.116589\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization (WHO). Guidelines on safe listening devices and systems for adults and children. Geneva: WHO; 2023.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Occupational noise exposure, Noise-induced hearing loss, Workplace surveillance, Enterprise size, Job category, Industry, China","lastPublishedDoi":"10.21203/rs.3.rs-8816045/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8816045/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eOccupational noise-induced hearing loss remains a leading occupational disease in China. While national surveillance data suggest an overall decline in noise exposure, the underlying trends across diverse industrial sectors, enterprise sizes, and job categories remain poorly understood, particularly in the context of China\u0026rsquo;s rapid industrial transformation.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a five-year retrospective analysis (2020\u0026ndash;2024) using official occupational hazard surveillance data from Sichuan Province. The dataset encompassed 51,102 unique job positions across 15,475 enterprises. Noise intensity (LAeq,8h) and exceedance rates (relative to the 85 dB(A) limit) were analyzed by industry, enterprise size, and job category. Temporal trends were assessed using the Cochran-Armitage test for trend and Kruskal-Wallis H test.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe overall noise exceedance rate declined significantly from 25.0% in 2020 to 16.0% in 2024 (Ptrend\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, this progress masked profound structural disparities. Medium and large enterprises exhibited higher exceedance rates (28.0% and 26.0%, respectively) than micro/small enterprises (21.1% and 19.1%), revealing an \u0026ldquo;enterprise size paradox.\u0026rdquo; By industry, mining (25.0%) and metallurgy \u0026amp; building materials (21.3%) had the highest risk, yet showed significant annual declines (Ptrend\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In stark contrast, the chemical production industry showed no improvement over five years (Ptrend\u0026thinsp;=\u0026thinsp;0.67), indicating a persistent \u0026ldquo;risk blind spot.\u0026rdquo; At the job level, high-risk roles such as mining/excavation and melting/casting demonstrated no significant change in their exceedance rates (P\u0026thinsp;=\u0026thinsp;0.49), highlighting technological path dependency.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe reduction in occupational noise exposure in Sichuan is highly uneven and structurally determined. The convergence of an \u0026ldquo;enterprise size paradox,\u0026rdquo; a chemical industry \u0026ldquo;risk blind spot,\u0026rdquo; and stagnant high-risk occupations reflects the differential impact of China\u0026rsquo;s industrial upgrading strategy. Future public health interventions must adopt a precision approach that targets support to lagging traditional sectors while ensuring that the transition to emerging industries is inclusive of worker health.\u003c/p\u003e","manuscriptTitle":"Persistent Structural Disparities in Occupational Noise Exposure: A Five-Year Analysis of 51,102 Workplaces in Sichuan Province, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-12 17:39:33","doi":"10.21203/rs.3.rs-8816045/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-03-24T02:35:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-20T09:19:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"16974756107394380123312123302643049719","date":"2026-03-11T07:04:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"301521570419642137129757885958123623683","date":"2026-03-09T07:05:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-09T07:01:10+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-10T10:54:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-10T06:26:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-10T06:25:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-02-07T13:52:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b77028a0-a636-4b8b-8697-4facdef23a17","owner":[],"postedDate":"March 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-12T17:39:33+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-12 17:39:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8816045","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8816045","identity":"rs-8816045","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}