Symanski E, Kupper L L, Hertz-Picciotto I, Rappaport S M
University of Texas Health Science Center, Houston, School of Public Health 77030, USA.
Occup Environ Med. 1998 May;55(5):310-6. doi: 10.1136/oem.55.5.310.
To explore the effects of various factors related to the industry, the contaminant, and the period and type of sampling on long term declining trends in occupational exposure.
Linear regression analyses were used to assess the relation between reductions in exposure and geographical location, industrial sector, type of contaminant, type of monitoring, carcinogenic classification, calendar period, duration of sampling, and number of reductions in the threshold limit value during the sampling period. Both univariable and multivariable models were applied.
Based on univariable analyses, the findings suggest that exposures declined more rapidly in manufacturing than in mining, more rapidly for aerosol contaminants than for vapours, and more rapidly when biological, rather than airborne, monitoring was conducted. Exposures collected more recently (first year of sampling in 1972 or later) fell more rapidly than exposures first evaluated during earlier periods. Irrespective of when the data were collected, the results also suggest that the longer the duration of sampling the slower the rate of decline. Taken together, we found that characteristics related to the contaminant, the industry, the sampling period, and the type of sampling explained a substantial proportion of the variability for exposures evaluated before 1972 (R2 = 0.78) and for sites evaluated both before and after 1972 (R2 = 0.91), but explained essentially no variation for data gathered exclusively after 1972 (R2 = 0.04).
By identifying factors that have affected the rates of reduction in a consistent fashion, the results should guide investigators in estimating historical levels when studies assessing exposure-response relations are carried out.
探讨与行业、污染物、采样时期及类型相关的各种因素对职业暴露长期下降趋势的影响。
采用线性回归分析评估暴露减少与地理位置、工业部门、污染物类型、监测类型、致癌分类、日历时期、采样持续时间以及采样期间阈限值降低次数之间的关系。应用了单变量和多变量模型。
基于单变量分析,研究结果表明,制造业的暴露下降速度比采矿业更快,气溶胶污染物的暴露下降速度比蒸气更快,进行生物监测而非空气监测时暴露下降速度更快。近期收集的暴露数据(采样第一年为1972年或之后)比早期首次评估的暴露数据下降更快。无论数据何时收集,结果还表明采样持续时间越长,下降速度越慢。综合来看,我们发现与污染物、行业、采样时期和采样类型相关的特征解释了1972年之前评估的暴露变异性的很大一部分(R2 = 0.78)以及1972年之前和之后评估的场所的很大一部分(R2 = 0.91),但对于1972年之后专门收集的数据基本没有解释变异性(R2 = 0.04)。
通过识别以一致方式影响下降速率的因素,这些结果应能指导研究人员在开展评估暴露 - 反应关系的研究时估计历史水平。