BACKGROUND: Equations using variance components in exposure data to predict attenuation and standard error of exposure--response slopes have been published recently. However, to date, no comparisons have been made between results of applying these equations to a real data set with the exposure-response relations estimated directly. METHODS: Data on lung function parameters and personal inhalable and respirable dust exposure levels from the European carbon black respiratory health study were used. The predicted attenuation and standard error of the relation between current inhalable and respirable dust levels and lung function parameters (FVC and FEV(1)) were calculated for various exposure grouping schemes. These results were compared with the observed exposure-response relations. Workers were grouped by Job Category, the combination of factory and Job Category and five a posteriori created Exposure Groups. In addition, the individual approach was also used, as exposure data were available for each worker. RESULTS: The rank orders of the coefficients from the regression analyses using the different grouping schemes were similar to those predicted by the equations, although the differences were larger than predicted. When using inhalable dust exposure, the predicted standard errors of the exposure-response slopes were slightly lower than those estimated directly; for respirable dust the predicted standard errors were about a factor two to three smaller than those from the regression analyses. When considering FVC, the predicted exposure-response relations were all statistically significant, whilst the observed relation was only significant when using the five a posteriori Exposure Groups. When reviewing the relations between dust exposure and level of FEV(1), all relations were statistically significant, with the exception of the (observed) relation between respirable dust and FEV(1), when the individual approach was used. CONCLUSIONS: Using different grouping schemes for estimating exposure can have large effects on the slope and standard error of the exposure-response relation. It is, therefore, important that the effect of the different grouping schemes on the level and precision of the exposure-response slope be estimated. Despite violation of most of the assumptions when applying the equations to predict attenuation and the standard error of the exposure-response slope, the similarities in predicted and observed exposure-response relations and standard errors are indicative of the robustness of these equations. Therefore, the equations appear to be a useful tool in establishing the most efficient way of utilizing exposure measurements. Copyright 1999 Wiley-Liss, Inc.
BACKGROUND: Equations using variance components in exposure data to predict attenuation and standard error of exposure--response slopes have been published recently. However, to date, no comparisons have been made between results of applying these equations to a real data set with the exposure-response relations estimated directly. METHODS: Data on lung function parameters and personal inhalable and respirable dust exposure levels from the European carbon black respiratory health study were used. The predicted attenuation and standard error of the relation between current inhalable and respirable dust levels and lung function parameters (FVC and FEV(1)) were calculated for various exposure grouping schemes. These results were compared with the observed exposure-response relations. Workers were grouped by Job Category, the combination of factory and Job Category and five a posteriori created Exposure Groups. In addition, the individual approach was also used, as exposure data were available for each worker. RESULTS: The rank orders of the coefficients from the regression analyses using the different grouping schemes were similar to those predicted by the equations, although the differences were larger than predicted. When using inhalable dust exposure, the predicted standard errors of the exposure-response slopes were slightly lower than those estimated directly; for respirable dust the predicted standard errors were about a factor two to three smaller than those from the regression analyses. When considering FVC, the predicted exposure-response relations were all statistically significant, whilst the observed relation was only significant when using the five a posteriori Exposure Groups. When reviewing the relations between dust exposure and level of FEV(1), all relations were statistically significant, with the exception of the (observed) relation between respirable dust and FEV(1), when the individual approach was used. CONCLUSIONS: Using different grouping schemes for estimating exposure can have large effects on the slope and standard error of the exposure-response relation. It is, therefore, important that the effect of the different grouping schemes on the level and precision of the exposure-response slope be estimated. Despite violation of most of the assumptions when applying the equations to predict attenuation and the standard error of the exposure-response slope, the similarities in predicted and observed exposure-response relations and standard errors are indicative of the robustness of these equations. Therefore, the equations appear to be a useful tool in establishing the most efficient way of utilizing exposure measurements. Copyright 1999 Wiley-Liss, Inc.
Authors: Melissa C Friesen; Joseph B Coble; Hormuzd A Katki; Bu-Tian Ji; Shouzheng Xue; Wei Lu; Patricia A Stewart Journal: Ann Occup Hyg Date: 2011-04-21
Authors: I Liljelind; S Rappaport; K Eriksson; J Andersson; I A Bergdahl; A-L Sunesson; B Järvholm Journal: Occup Environ Med Date: 2003-08 Impact factor: 4.402