0379 Should we take major macro-economic and political developments into account when assessing long-term occupational exposures for epidemiological research?
研究分析了三个数据库中的职业暴露数据，发现宏观经济危机和政治变革会中断暴露浓度的下降趋势，建议在长期暴露建模中考虑这些因素以提高风险估计的准确性。
<h3>Objectives</h3> Recent analyses of long-term trends in respirable dust and quartz concentrations from the long term monitoring program of the European Industrial Minerals Association (IMA-Europe) Dust Monitoring Program (covering the years 2000–2013) showed striking downward temporal trends in exposure which came to a halt at around the year 2009. Careful analyses and discussion with occupational health and safety representatives pointed at a direct detrimental effect of the current economic crisis on measured concentrations. This observation led us to hypothesise that similar disruptions of downward temporal trends in occupational exposures might also be visible in other large databases with longitudinal exposure measurements. <h3>Method</h3> Temporal time trends were estimated in two additional databases (ExpoSYN and URALASBEST) each covering more than 50 years of occupational exposure monitoring. More flexible spline analyses rather than standard log linear (multiplicative) models were used to look for reversed trends. <h3>Results</h3> In all three databases macro-economic and political developments seemed to influence downward trends in occupational exposure concentrations. Effects of economic crises like those of the early 1980s, early 1990s and the most recent one as well as the period of political and economic reform in Russia were clearly visible as reduced downward or even reversed temporal trends in occupational exposure concentrations. <h3>Conclusions</h3> In exposure assessment for occupational epidemiological studies long term exposures are often modelled as log linear trends. Approaches allowing for disruptions of these trends by macro-economic and/or political developments are needed for more accurate and precise estimations of long-term exposure and will result in more reliable quantitative risk estimates.