Validity of empirical models of exposure in asphalt paving

Abstract

Aims: To investigate the validity of empirical models of exposure to bitumen fume and benzo(a)pyrene, developed for a historical cohort study of asphalt paving in Western Europe. Methods: Validity was evaluated using data from the USA, Italy, and Germany not used to develop the original models. Correlation between observed and predicted exposures was examined. Bias and precision were estimated. Results: Models were imprecise. Furthermore, predicted bitumen fume exposures tended to be lower (−70%) than concentrations found during paving in the USA. This apparent bias might be attributed to differences between Western European and USA paving practices. Evaluation of the validity of the benzo(a)pyrene exposure model revealed a similar to expected effect of re-paving and a larger than expected effect of tar use. Overall, benzo(a)pyrene models underestimated exposures by 51%. Conclusions: Possible bias as a result of underestimation of the impact of coal tar on benzo(a)pyrene exposure levels must be explored in sensitivity analysis of the exposure-response relation. Validation of the models, albeit limited, increased our confidence in their applicability to exposure assessment in the historical cohort study of cancer risk among asphalt workers. I ncreasingly in occupational and environmental epidemiology the quality of studies and their subsequent usefulness for risk assessors and regulators depends on the validity of their exposure assessment. This trend is in part a result of the recognition of the fact that most of the remaining unidentified health risks from occupational and environmental factors are likely to be low (relative risks of the order of 2-3) and can be easily missed because of misclassification of exposure.1 These weak associations, however, can have a profound public health impact if their causative agents are highly prevalent. 1Two examples illustrate the crucial role that exposure assessment plays in modern occupational epidemiology. Between 1976 and 1993, 20 studies of cancer risk among asphalt workers (mostly road pavers) have been conducted, many of which suggested that this occupation entailed an increased lung cancer risk.2 However, these studies suffered from failure to differentiate between coal tar and bitumen (or asphalt, as it is known in the USA) exposures. As a result, this substantial 17 year research effort has been proven to be of limited use in the evaluation of carcinogenicity of the main agent that asphalt workers are currently exposed to-bitumen, 3 4 hampering any preventive measures through setting scientifically based exposure limits and exposure controls.Another example is that of exposure to electromagnetic fields and occupational cancer. A study's ability to detect an association between electromagnetic fields and increased cancer risks to a large extent depends on assumptions made in exposure modelling, emphasising the importance of validating exposure models. [5][6][7] Consequently, analyses of sensitivity of risk estimates to assumptions made in exposure assessment are be...

Variability of environmental exposures to volatile organic compounds

“…The cumulative distributions suggest that VOC exposure typically varies about three-to four-fold between persons in a given city, but varies more than 20-fold in about a quarter of the cases. These systematic differences in exposure to a particular VOC across city residents can be identified and used for epidemiological purposes in much the same manner that tasks or work locations are exploited to assign groups in occupational epidemiology (e.g., see Burstyn et al, 2002, Kromhout et al, 1994;Kromhout and Heederik, 1995). Nonetheless, Hoffmann et al (2000) reported models that explained 39% of the variation in environmental exposure levels for benzene and 60% of the variation in exposure levels for ethylbenzene and the xylenes.…”

Sensitization and chronic beryllium disease at a primary manufacturing facility, part 2: validation of historical exposures

“…We reconstructed personal beryllium exposure estimates for an epidemiologic study at a beryllium manufacturing facility (4) and validated those estimates. Although reconstructed beryllium exposure tended to be slightly higher than the measured mean, it is important to note that the overestimation of reconstructed exposures would lead to underestimated risk per unit of exposure (16,39). Furthermore, any biases in reconstructed exposure estimates in this study were non-differential (unrelated to outcome status), which would attenuate the exposure-response relationship, but the magnitude of the attenuation cannot be estimated (39).…”

“…In contrast, Hornung et al (15) reported an overall relative bias of -24% in a model used to predict ethylene oxide exposures, when compared to an internal validation dataset. Burstyn et al (16) used external datasets obtained from the different countries to validate exposure estimates from a model for benzo(a)pyrene in asphalt paving. They found weak correlation (r p =0.28) and high relative bias (approximately -70% to -50%).…”

“…However, internal validation is rarely conducted often due to lack of adequate sample size. Many exposure reconstruction studies have used external datasets such as published literature (16)(17)(18) or additional exposure data from the same or different workplaces (19)(20)(21) for validation. In instances where validation using external data is not feasible, re-sampling using Monte Carlo methods has been used (22).…”

Bladder cancer incidence and exposure to polycyclic aromatic hydrocarbons among asphalt pavers

“…13 The contextual information coded for each exposure measurement included production characteristics within a job (using a classification similar to that used in the company questionnaire), repeated measurements within a worker, and country. We constructed 4 14 and validated 15 mixed-effects exposure assessment models, with production characteristics as fixed effects and repeated measurements on the same worker as random effects, to predict quantitative exposures to benzo(a)pyrene among asphalt paving workers. Use of coal tar was the strongest determinant of exposure to benzo(a)pyrene, but time period, mastic laying, re-paving, surface dressing and oil gravel paving were also important predictors.…”