2020—2024 年上海市工作场所职业病危害因素监测情况与空间自相关分析

Monitoring and spatial autocorrelation analysis of occupational hazards in workplaces in Shanghai from 2020 to 2024

关键词: 工作场所  职业病危害因素  空间自相关分析  时空分析

Keywords: workplace  occupational hazard factors  spatial autocorrelation analysis  spatiotemporal analysis

摘 要: 目的 分析 2020—2024 年上海市职业病危害因素监测数据趋势及空间分布特征,评估监测成效,为精准治理提供依据。方法 采用 SPSS 26.0 软件对 2020—2024 年上海市重点行业用人单位工作场所职业病危害因素监测信息进行趋势分析,Arc GIS 10.8 进行地图绘制和空间自相关分析,探究近 5 年职业病危害因素监测结果是否存在空间聚集性。结果 上海市近 5 年共监测重点职业病危害因素企业 2 350 家次, 监测岗位 26 220 个, 2022 年后粉尘接触人次占比呈 下降趋势,化学因素和噪声接触人次占比呈上升趋势,粉尘中以矽尘岗位超标率(24.89%)最高(均 P<0.01),化学有害因素中甲苯、二甲苯岗位超标率呈上升趋势(均 P<0.01)。全局空间自相关分析显示, 近 5 年上海市区职业病危害因素监测岗位超标率分布呈空间正相关;局部空间自相关分析显示, 上海市区职业病危害因素监测岗位超标呈“低—低”和“高—低”聚集特征;热点分析显示,热点区由青浦区向崇明区转变,嘉定区、宝山区、闵行区 2020 年后退出冷点区。结论 2020—2024 年上海市接触矽尘岗位超标率最高,中心城区监测岗位超标率较低且呈聚集特征,青浦区仅 2020 年为热点区域,监测岗位超标表现出一定空间聚集性,且热点区域有转移趋势。

Abstract: Objective Based on the trend and spatial distribution characteristics of occupational hazard factors monitoring data in Shanghai from 2020 to 2024, this study assesses the effectiveness of monitoring and provides a basis for precise governance. Methods Using the monitoring information on occupational hazard factors in workplaces of key industry monitoring employers in Shanghai from 2020 to 2024, SPSS 26.0 was used for trend analysis, and Arc GIS 10.8 was used for map drawing and spatial autocorrelation analysis to explore whether there is spatial clustering in the monitoring results of occupational hazard factors over the past five years. Results In the past five years, Shanghai has monitored 2 350 enterprises with key occupational hazard factors, covering 26 220 monitoring positions. The proportion of personnel exposed to dust showed a downward trend after 2022, while the proportions of personnel exposed to chemical factors and noise showed upward trend. Among the dust exposure positions, the over-standard rate for silica dust exposure positions was the highest (24.89%) (P<0.01). Among the positions exposed to chemical factors that exceeded standards, the over-standard rates for toluene and xylene positions showed upward trend (P<0.01). Global spatial autocorrelation analysis indicated that the distribution of over-standard rates for occupational hazard factors monitoring positions in Shanghai urban area over the past five years exhibited a positive spatial correlation. Local spatial autocorrelation analysis revealed that the over-standard rates for occupational hazard factors monitoring positions in Shanghai urban area were characterized by “low—low” and “high—low” clusters. Hotspot analysis showed that the hotspot area shifted from Qingpu district to Chongming district, with Jiading district, Baoshan district, and Minhang district exiting the coldspot area after 2020. Conclusion From 2020 to 2024, the over-standard rate of jobs exposed to silica dust was the highest. The over-standard rate of monitoring jobs in the central urban area of the city was relatively low and exhibited spatial clustering characteristic. In Qingpu district, it was a hotspot area only in 2020; the over-standard rate of monitoring jobs showed a certain degree of spatial clustering, with a trend of hotspot migration.