粉尘接触人数与原煤产量相关关系的多水平模型构建

Construction of a multi-level model for evaluating the association between the number of dust exposed workers and raw coal production

目的基于“职业病危害项目申报系统”(以下简称“申报系统”)的数据,构建在省级行政区水平估算煤炭开采和洗选业企业职业性接触粉尘工人数量(以下简称“接尘人数”)的方法。方法采用典型抽样方法,以申报系统中2020年山西省、内蒙古自治区、陕西省、新疆维吾尔自治区1808家煤炭企业为研究对象。基于其中1217家单纯采煤或采煤和洗选一体化企业的数据,建立接尘人数与原煤产量相关关系的多水平模型,分析两者关系;并基于企业规模构成比设置两种场景,估算漏报的接尘人数,以校正各省级行政区接尘人数。结果2020年申报系统的数据显示,原煤产量与接尘人数由多到少的排序均为山西省、内蒙古自治区、陕西省和新疆维吾尔自治区,共有接尘人数1002842人。本研究采用原煤产量、企业规模及其交互项建立的随机截距模型拟合效果相对最优,-2倍的对数似然值为2005.96,赤池信息准则值为2017.95。影响接尘人数的因素为原煤产量及其与企业规模的交互项,原煤产量每变化1.00%,小微企业的接尘人数变化0.62%,大中企业较小微的接尘人数多变化0.13%。在两种假设的场景下,4个省级行政区的校正总接尘人数分别为1125515和1089321人。结论以4个省级行政区的原煤产量和企业规模及其交互项数据构建的多水平模型能够相对准确地估计接尘人数,可较好地校正各省级行政区的接尘人数。

Objective Based on the data from the″Occupational Diseases Hazardous Items Reporting System″(hereinafter referred to as the″Reporting System″),a method was constructed to estimate the number of occupational dust exposed workers in coal mining and washing enterprises(hereinafter referred to as"coal workers")at the provincial administrative level.Methods A typical sampling method was used to study 1808 coal enterprises in Shanxi Province,Inner Mongolia Autonomous Region,Shaanxi Province,and Xinjiang Uygur Autonomous Region in 2020 in the Reporting System.Based on the data of 1217coal enterprises,that were coal mining or integrated coal mining and washing enterprises,a multi-level model was established to analyze the association between the number of coal workers and raw coal production.Two scenarios were set up based on the enterprise scale composition ratio to estimate the number of underreported coal workers,and the number of coal workers in each provincial administrative region was corrected.Results The data of the Reporting System in 2020 showed that the ranking of raw coal production and the number of coal workers from most to least were Shanxi Province,Inner Mongolia Autonomous Region,Shaanxi Province and Xinjiang Uygur Autonomous Region,with a total of 1002842 coal workers.The random intercept model using raw coal production,enterprise scale and their interaction terms was fitted optimally with a-2 log likelihood value of 2005.96 and Akaike information criterion value of 2017.95.The factors affecting the number of coal workers included raw coal production and its interaction with the scale of enterprises.For every 1.00%change in raw coal production,the number of coal workers in small and micro enterprises changed by 0.62%,and the number of coal workers in large and medium enterprises changed by 0.13%more than that in small and micro enterprises.The corrected total number of coal workers for the four provincial administrative regions was 1125515 and 1089321 for the two hypothetical scenarios,respectively.Conclusion The multi-level model constructed with the data of raw coal production,enterprise scale and their interaction terms of four provincial administrative regions could estimate the number of coal workers accurately,and could better correct the number of coal workers in each provincial administrative region.