Health Watch exposure estimates: do they underestimate benzene exposure?

A nested case-control study found that the excess of leukemia, identified among the male members of the Health Watch cohort, was associated with benzene exposure. Exposure had been retrospectively estimated for each individual occupational history using an algorithm in a relational database. Benzene exposure measurements, supplied by Australian petroleum companies, were used to estimate exposure for specific tasks. The tasks carried out within each job, the products handled, and the technology used, were identified from structured interviews with contemporary colleagues. More than half of the subjects started work after 1965 and had an average exposure period of 20 years. Exposure was low; nearly 85% of the cumulative exposure estimates were at or below 10 ppm-years. Matched analyses showed that leukemia risk increased with increasing cumulative benzene exposures and with increasing exposure intensity of the highest-exposed job. Non-Hodgkin lymphoma and multiple myeloma were not associated with benzene exposure. A reanalysis reported here, showed that for the 7 leukemia case-sets with greater than 16 ppm-years cumulative exposure, the odds ratio was 51.9 (5.6-477) when compared to the 2 lowest exposed categories combined to form a new reference category. The addition of occasional high exposures, e.g. as a result of spillages, increased exposure for 25% of subjects but for most, the increase was less than 5% of total exposure. The addition of these exposures reduced the odds ratios. Cumulative exposures did not range as high as those in comparable studies; however, the recent nature of the cohort and local handling practices can explain these differences.

Estimating mean exposures from censored data: exposure to benzene in the Australian petroleum industry.

A retrospective assessment of exposure to benzene was carried out for a nested case control study of lympho-haematopoietic cancers, including leukaemia, in the Australian petroleum industry. Each job or task in the industry was assigned a Base Estimate (BE) of exposure derived from task-based personal exposure assessments carried out by the company occupational hygienists. The BEs corresponded to the estimated arithmetic mean exposure to benzene for each job or task and were used in a deterministic algorithm to estimate the exposure of subjects in the study. Nearly all of the data sets underlying the BEs were found to contain some values below the limit of detection (LOD) of the sampling and analytical methods and some were very heavily censored; up to 95% of the data were below the LOD in some data sets. It was necessary, therefore, to use a method of calculating the arithmetic mean exposures that took into account the censored data. Three different methods were employed in an attempt to select the most appropriate method for the particular data in the study. A common method is to replace the missing (censored) values with half the detection limit. This method has been recommended for data sets where much of the data are below the limit of detection or where the data are highly skewed; with a geometric standard deviation of 3 or more. Another method, involving replacing the censored data with the limit of detection divided by the square root of 2, has been recommended when relatively few data are below the detection limit or where data are not highly skewed. A third method that was examined is Cohen's method. This involves mathematical extrapolation of the left-hand tail of the distribution, based on the distribution of the uncensored data, and calculation of the maximum likelihood estimate of the arithmetic mean. When these three methods were applied to the data in this study it was found that the first two simple methods give similar results in most cases. Cohen's method on the other hand, gave results that were generally, but not always, higher than simpler methods and in some cases gave extremely high and even implausible estimates of the mean. It appears that if the data deviate substantially from a simple log-normal distribution, particularly if high outliers are present, then Cohen's method produces erratic and unreliable estimates. After examining these results, and both the distributions and proportions of censored data, it was decided that the half limit of detection method was most suitable in this particular study.

Validation of exposure estimation for benzene in the Australian petroleum industry.

A nested case-control study was undertaken to investigate whether an excess of lympho-haematopoietic cancers in the Australian petroleum industry was associated with benzene exposure. The benzene exposures of the cases and controls were estimated using a quantitative algorithm based largely on exposures measured in the Australian petroleum industry. The algorithm was used to estimate, for each subject, the benzene exposure in parts per million (ppm) for each job held in the industry, and the cumulative exposure in ppm years. Because of the critical importance of the exposure assessment in this design of epidemiological study, particular attention was paid to the reliability of the inputs to the algorithm. The inputs [base estimates (BEs) of exposure and technology-specific exposure modifiers (EMs)] were compared to data from other sources including the occupational hygiene literature. Where such comparison data were available, they were generally found to confirm the values used in the algorithm, although four input values were changed as a result of the validation exercise. The integrity of the task-based algorithm was validated by employing it to calculate the exposures of the tanker drivers in the study and comparing these with measured daily exposure for tanker drivers in the Australian petroleum industry and exposure values found in the occupational hygiene literature. After adjustment for the mix of products carried by the Australian tanker drivers, the estimates from the algorithm were found to be comparable to the measured and literature values. This exercise provided evidence that the exposure assessment for the epidemiological study was reliable and that the results of the study can be used as the basis for evaluating the relationship between exposure to benzene and the risk of lympho-haematopoietic cancer.