Epidemiological characteristics and Spatiotemporal Analysis of Occupational Noise-induced Deafness from 2006 to 2022 in Guangdong, China (Preprint)

Le résumé fourni par la source

BACKGROUND Occupational noise-induced deafness (ONID) has replaced occupational poisoning as the second most common occupational disease in China since 2015. However, there is a limited number of literatures on epidemiological characteristics of legally diagnosed ONID. OBJECTIVE We conducted a comprehensive analysis of the epidemiological and spatiotemporal characteristics of ONID in Guangdong Province from 2006 to 2022, with the aim of providing a scientific foundation for policy formulation and health resource allocation. METHODS Surveillance data of ONID cases in Guangdong Province from 2006, to 2022, were obtained from the “Occupational Diseases and Health Hazard Factors Monitoring Information System”. Joinpoint regression analysis was applied to access the long-term trends in cases of ONID for the period 2006-2022. Global spatial autocorrelation analysis was performed to measure the overall degree of similarity of the attribute values of spatially adjacent or neighboring regional units. The local indicators of spatial autocorrelation (LISA) plots were then employed to identify the local clusters of ONID in Guangdong. RESULTS It has been reported that there were 3,761 ONID cases in Guangdong Province from 2006 to 2022, showing a significantly increased trend in cases across the entire study period (average annual percentage change:21.9, 95% CI:18.7, 35.1). The Moran's I values for the period of 2006 to 2022 ranged from 0.202 to 0.649 (all P < 0.001), indicating a positive spatial correlation of ONID across regions each year in Guangdong Province. Fifteen high-high clustering were notably concentrated in specific counties within the Pearl River Delta. CONCLUSIONS ONID in Guangdong Province has experienced a dramatic increase followed by a stabilization from 2006 to 2022. The distribution of ONID shows spatiotemporal clustering. Our results could help prioritize the allocation of resources for targeted prevention and control measures for ONID.

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