Ensuring comparability of benzene exposure estimates across three nested case-control studies in the petroleum industry in support of a pooled epidemiological analysis.

BACKGROUND: Three case-control studies each nested within a cohort of petroleum workers assessed exposure to benzene in relation to risk of haematopoietic cancers. These studies have each been updated and the cases will be pooled to derive a more powerful study. The benzene exposure of new leukemia cases and controls was estimated in accordance with each respective study's original methods. An essential component of the process of pooling the data was comparison and rationalisation of the exposure estimates to ensure accuracy and consistency of approach. This paper describes this process and presents comparative estimates before and after appropriate revision took place. The original petroleum industry studies, in Canada, the UK and Australia, were conducted at different points in time by different study teams, but the industry used similar technology in similar eras in each of these countries. METHODS: A job history for each subject giving job title, dates of starting and leaving the job and location of work, was assembled. For each job or task, the average benzene exposure (Base Estimate (BE) in ppm) was derived from measurements collected at applicable worksites. Estimates of exposure intensity (workplace exposure estimates (WE)) were then calculated for each line of work history by adjusting the BEs for site- and era-specific exposure-related variables such as loading technology and percentage benzene in the product. To ensure that the exposure estimates were comparable among the studies, the WEs were allocated to generic Job Categories, e.g. Tanker Driver (by technology used e.g. bottom loading), Motor Mechanic. The WEs were stratified into eras, reflecting technological changes in the industry. The arithmetic mean (AM), geometric mean (GM) and range of the stratified WEs were calculated, by study, for each generic Job Category. These were then compared. The AMs of the WEs were regarded as substantially similar if they were within 20% in all three studies in one era or for at least two studies in two eras. If the AM of the WE group differed by more than 20%, the data were examined to see whether the difference was justified by differences in local exposure conditions, such as an enclosure versus open work area. Estimates were adjusted in the absence of justification for the difference. RESULTS: Reconciliation of differences resulted in changes to a small number of underlying BEs, particularly the background values, also the BEs attributed to some individuals and changes to the allocation of jobs between Job Categories. Although the studies covered some differing sectors of the industry and different time periods, for 22 Job Categories there was sufficient overlap, particularly in the downstream distribution sector, to make comparisons possible. After adjustment 12 Job Categories were judged to be similar and 10 were judged to be justifiably different. Job-based peak and skin exposure estimates were applied in a uniform way across the studies and a single approach to scoring the certainty of the exposure estimates was identified. CONCLUSIONS: The revised exposure estimates will be used in the pooled analysis to examine the risk of haematopoietic cancers and benzene exposure. This exercise provided an important quality control check on the exposure estimates and identified similarly exposed Job Categories that could be grouped for risk assessment analyses.

Retrospective estimation of exposure to benzene in a leukaemia case-control study of petroleum marketing and distribution workers in the United Kingdom.

OBJECTIVE: To provide quantitative estimates of exposure to benzene for cases and controls in an epidemiology study to investigate the risk of leukaemia in petroleum distribution workers. METHODS: Work histories were obtained for cases and controls together with detailed information on the distribution sites. For each job in the work history, an estimate of exposure (parts per million (ppm)) was obtained by multiplying a measure derived from exposure data by modifying factors to reflect the differences between the conditions that existed at the time of measurement and those at the time of interest. The modifying factors used related to job activity, the number of road tankers loaded, the benzene content of the gasoline, the mixture of products handled, temperature, and loading technology. Cumulative exposures for each case and control were obtained by multiplying the exposure estimates for each job by the duration of time in the respective jobs, and summing these over all jobs in the work history. Peak exposure and exposure through dermal contact were quantitatively classified for each job. RESULTS: Measured exposures were obtained for 30 job categories, and ranged from 0.003 to 8.20 ppm. 40% of work histories were assigned background exposures, with a further 34% assigned the exposure estimate for a driver carrying out top submerged loading of motor fuel into road tankers. Cumulative exposures ranged from < 1 to > 200 ppm-years, although 81% were < 5 ppm-years. Comparison of the exposure estimates for selected jobs with data from sources not used in the study showed similar results. CONCLUSION: The estimates of exposure to benzene in this study provide a sound basis for the epidemiological analyses.

The relationship between low-level benzene exposure and leukemia in Canadian petroleum distribution workers.

This study was conducted to evaluate the relationship between leukemia occurrence and long-term, low-level benzene exposures in petroleum distribution workers. Fourteen cases were identified among a previously studied cohort [Schnatter et al., Environ Health Perspect 101 (Suppl 6):85-89 (1993)]. Four controls per case were selected from the same cohort, controlling for birth year and time at risk. Industrial hygienists estimated workplace exposures for benzene, without knowledge of case-control status. Average benzene concentrations ranged from 0.01 to 6.2 ppm. Company medical records were used to abstract information on other potential confounders such as cigarette smoking. Odds ratios were calculated for several exposure metrics. Conditional logistic regression modeling was used to control for potential confounders. The risk of leukemia was not associated with increasing cumulative exposure to benzene for these exposure levels. Duration of benzene exposure was more closely associated with leukemia risk than other exposure metrics, although results were not statistically significant. A family history of cancer and cigarette smoking were the two strongest risk factors for leukemia, with cumulative benzene exposure showing no additional risk when considered in the same models. This study is consistent with other data in that it was unable to demonstrate a relationship between leukemia and long-term, low-level benzene exposures. The power of the study was limited. Thus, further study on benzene exposures in this concentration range are warranted.

Lymphohaematopoietic malignancies and quantitative estimates of exposure to benzene in Canadian petroleum distribution workers.

OBJECTIVE: To evaluate the relation between mortality from lymphohaematopoietic cancer and long term, low level exposures to benzene among male petroleum distribution workers. METHODS: This nested case control study identified all fatal cases of lymphohaematopoietic cancer among a previously studied cohort. Of the 29 cases, 14 had leukaemia, seven multiple myeloma, and eight non-Hodgkin's lymphoma. A four to one matching ratio was used to select a stratified sample of controls from the same cohort, controlling for year of birth and time at risk. Industrial hygienists estimated workplace exposures for benzene and total hydrocarbons, without knowledge of case or control status, for combinations of job, location, and era represented in all work histories. Average daily benzene concentrations ranged from 0.01 to 6.2 parts per million (ppm) for all jobs. Company medical records were used to abstract information on other potential confounders such as cigarette smoking, although the data were incomplete. Odds ratios (ORs) were calculated with conditional logistic regression techniques for several exposure variables. RESULTS: Risks of leukaemia, non-Hodgkin's lymphoma, and multiple myeloma were not associated with increasing cumulative exposure to benzene or total hydrocarbons. For leukaemia, the logistic regression model predicted an OR of 1.002 (P < 0.77) for each ppm-y of exposure to benzene. Duration of exposure to benzene was more closely associated with risk of leukaemia than other exposure variables. It was not possible to completely control for other risk factors, although there was suggestive evidence that smoking and a family history of cancer may have played a part in the risk of leukaemia. CONCLUSION: This study did not show a relation between lymphohaematopoietic cancer and long term, low level exposures to benzene. The power of the study to detect low-such as twofold-risks was limited. Thus, further study on exposures to benzene in this concentration range are warranted.

A nested case-control study of kidney cancer among refinery/petrochemical workers.

A nested case-control study was designed to evaluate whether a nearly twofold excess of kidney cancer among workers at a refinery/petrochemical plant was associated with cumulative exposure to C2-C5 saturated, C2-C5 unsaturated, C6-C10 aliphatic saturated, C6-C10 aliphatic unsaturated, and C6-C10 aromatic process streams. Nonoccupational risk factors were body mass index (BMI), blood pressure (both measured at about age 28), and smoking. There was no significant association with cumulative exposure or tenure as estimated by conditional logistic regression and adjusted for nonoccupational risk factors. Categorical analysis showed increased odds ratios only in the second (low) and fourth (high) quartiles compared to the first quartile reference group of lowest exposed workers, and a three-quarter-fold increased odds ratio for > 32 years' tenure compared to the < 25-year reference group. The number of cases was small with wide confidence intervals around estimate of risk, so the possibility of an exposure-response trend cannot be ruled out. Multivariate analysis identified overweight (high BMI; p < 0.01) as the most important risk factor in this data set, followed by tenure and increased blood pressure. There was a weak association with current smoking, but not with pack-years smoked. The risk of kidney cancer for a nonsmoker with normal blood pressure but 25% overweight was increased about 2.6-fold (95% CI = 1.2-5.4). The risk of kidney cancer for a nonsmoker of normal weight with high blood pressure (e.g., 150/110), was increased about 4.5 (95% CI, 0.8-26).

Retrospective benzene and total hydrocarbon exposure assessment for a petroleum marketing and distribution worker epidemiology study.

A quantitative exposure-estimating algorithm for benzene and total hydrocarbons was developed for a case control study of petroleum marketing and distribution workers. The algorithm used a multiplicative model to adjust recently measured quantitative exposure data to past scenarios for which representative exposure measurement data did not exist. This was accomplished through the development of exposure modifiers to account for differences in the workplace, the materials handled, the environmental conditions, and the tasks performed. Values for exposure modifiers were obtained empirically and through physical/chemical relationships. Dates for changes that altered exposure potential were obtained from archive records, retired employee interviews, and from current operations personnel. Exposure modifiers were used multiplicatively, adjusting available measured data to represent the relevant exposure scenario and time period. Changes in exposure modifiers translated to step changes in exposure estimates. Though limited by availability of data, a validation exercise suggested that the algorithm provided accurate exposure estimates for benzene (compared with measured data in industrial hygiene survey reports); the estimates generally differed by an average of less than 20% from the measured values. This approach is proposed to quantify exposures retrospectively where there are sufficient data to develop reliable current era estimates and where a historical accounting of key exposure modifiers can be developed, but where there are insufficient historic exposure measurements to directly assess historic exposures.