Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Feb 28, 2024
Date Accepted: Sep 3, 2024
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Epidemiological characteristics and Spatiotemporal Analysis of Occupational Noise-induced Deafness from 2006 to 2022 in Guangdong, China
ABSTRACT
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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