Identifying gender differences in reported occupational information from three US population-based case-control studies.

OBJECTIVES: Growing evidence suggests that gender-blind assessment of exposure may introduce exposure misclassification, but few studies have characterised gender differences across occupations and industries. We pooled control responses to job-specific, industry-specific and exposure-specific questionnaires (modules) that asked detailed questions about work activities from three US population-based case-control studies to examine gender differences in work tasks and their frequencies. METHODS: We calculated the ratio of female-to-male controls that completed each module. For four job modules (assembly worker, machinist, health professional, janitor/cleaner) and for subgroups of jobs that completed those modules, we evaluated gender differences in task prevalence and frequency using χ(2) and Mann-Whitney U tests, respectively. RESULTS: The 1360 female and 2245 male controls reported 6033 and 12 083 jobs, respectively. Gender differences in female:male module completion ratios were observed for 39 of 45 modules completed by ≥20 controls. Gender differences in task prevalence varied in direction and magnitude. For example, female janitors were significantly more likely to polish furniture (79% vs 44%), while male janitors were more likely to strip floors (73% vs 50%). Women usually reported more time spent on tasks than men. For example, the median hours per week spent degreasing for production workers in product manufacturing industries was 6.3 for women and 3.0 for men. CONCLUSIONS: Observed gender differences may reflect actual differences in tasks performed or differences in recall, reporting or perception, all of which contribute to exposure misclassification and impact relative risk estimates. Our findings reinforce the need to capture subject-specific information on work tasks.

The Diesel Exhaust in Miners Study: V. Evaluation of the Exposure Assessment Methods.

Exposure to respirable elemental carbon (REC), a component of diesel exhaust (DE), was assessed for an epidemiologic study investigating the association between DE and mortality, particularly from lung cancer, among miners at eight mining facilities from the date of dieselization (1947-1967) through 1997. To provide insight into the quality of the estimates for use in the epidemiologic analyses, several approaches were taken to evaluate the exposure assessment process and the quality of the estimates. An analysis of variance was conducted to evaluate the variability of 1998-2001 REC measurements within and between exposure groups of underground jobs. Estimates for the surface exposure groups were evaluated to determine if the arithmetic means (AMs) of the REC measurements increased with increased proximity to, or use of, diesel-powered equipment, which was the basis on which the surface groups were formed. Estimates of carbon monoxide (CO) (another component of DE) air concentrations in 1976-1977, derived from models developed to predict estimated historical exposures, were compared to 1976-1977 CO measurement data that had not been used in the model development. Alternative sets of estimates were developed to investigate the robustness of various model assumptions. These estimates were based on prediction models using: (i) REC medians rather AMs, (ii) a different CO:REC proportionality than a 1:1 relation, and (iii) 5-year averages of historical CO measurements rather than modeled historical CO measurements and DE-related determinants. The analysis of variance found that in three of the facilities, most of the between-group variability in the underground measurements was explained by the use of job titles. There was relatively little between-group variability in the other facilities. The estimated REC AMs for the surface exposure groups rose overall from 1 to 5 µg m(-3) as proximity to, and use of, diesel equipment increased. The alternative estimates overall were highly correlated (∼0.9) with the primary set of estimates. The median of the relative differences between the 1976-1977 CO measurement means and the 1976-1977 estimates for six facilities was 29%. Comparison of estimated CO air concentrations from the facility-specific prediction models with historical CO measurement data found an overall agreement similar to that observed in other epidemiologic studies. Other evaluations of components of the exposure assessment process found moderate to excellent agreement. Thus, the overall evidence suggests that the estimates were likely accurate representations of historical personal exposure levels to DE and are useful for epidemiologic analyses.

Suicide and pesticide use among pesticide applicators and their spouses in the agricultural health study.

BACKGROUND: An association may exist between pesticide exposure and suicide. OBJECTIVE: We sought to evaluate the existence of an association between pesticide use and suicide using data from the Agricultural Health Study (AHS), a prospective cohort study of licensed pesticide applicators and their spouses in Iowa and North Carolina. METHODS: Via linkage to state mortality files and the National Death Index, we identified 110 suicides occurring between enrollment in the AHS (from 1993 to 1997) and 31 May 2009, among 81,998 cohort members contributing 1,092,943 person-years of follow-up. The average length of follow-up was 13.3 years. AHS participants provided data on pesticide use and potential confounders via self-administered questionnaires at enrollment. We evaluated several measures of pesticide use: use of any pesticide, ever use of 50 specific pesticides, cumulative lifetime days of use and intensity-adjusted cumulative lifetime days of use of 22 specific pesticides, and ever use of 10 functional and chemical classes of pesticides. We used Cox proportional hazards regression models to estimate adjusted hazard ratios and 95% confidence intervals. RESULTS: After adjusting for age at enrollment, sex, number of children in family, frequency of alcohol consumption during the past 12 months, and smoking status, we found no association between prior pesticide use and suicide in applicators and their spouses. Results were the same for applicators and spouses together or for applicators alone and were consistent across several measures of pesticide use. CONCLUSIONS: Our findings do not support an association between moderate pesticide use and suicide.

Comparison of occupational exposure assessment methods in a case-control study of lead, genetic susceptibility and risk of adult brain tumours.

OBJECTIVES: There is great interest in evaluating gene-environment interactions with chemical exposures, but exposure assessment poses a unique challenge in case-control studies. Expert assessment of detailed work history data is usually considered the best approach, but it is a laborious and time-consuming process. We set out to determine if a less intensive method of exposure assessment (a job exposure matrix (JEM)) would produce similar results to a previous analysis that found evidence of effect modification of the association between expert-assessed lead exposure and risk of brain tumours by a single nucleotide polymorphism in the ALAD gene (rs1800435). METHODS: We used data from a study of 355 patients with glioma, 151 patients with meningioma and 505 controls. Logistic regression models were used to examine associations between brain tumour risk and lead exposure and effect modification by genotype. We evaluated Cohen's κ, sensitivity and specificity for the JEM compared to the expert-assessed exposure metrics. RESULTS: Although effect estimates were imprecise and driven by a small number of cases, we found evidence of effect modification between lead exposure and ALAD genotype when using expert- but not JEM-derived lead exposure estimates. κ Values indicated only modest agreement (<0.5) for the exposure metrics, with the JEM indicating high specificity (∼0.9) but poor sensitivity (∼0.5). Disagreement between the two methods was generally due to having additional information in the detailed work history. CONCLUSION: These results provide preliminary evidence suggesting that high quality exposure data are likely to improve the ability to detect genetic effect modification.

The diesel exhaust in miners study: I. Overview of the exposure assessment process.

This report provides an overview of the exposure assessment process for an epidemiologic study that investigated mortality, with a special focus on lung cancer, associated with diesel exhaust (DE) exposure among miners. Details of several components are provided in four other reports. A major challenge for this study was the development of quantitative estimates of historical exposures to DE. There is no single standard method for assessing the totality of DE, so respirable elemental carbon (REC), a component of DE, was selected as the primary surrogate in this study. Air monitoring surveys at seven of the eight study mining facilities were conducted between 1998 and 2001 and provided reference personal REC exposure levels and measurements for other agents and DE components in the mining environment. (The eighth facility had closed permanently prior to the surveys.) Exposure estimates were developed for mining facility/department/job/year combinations. A hierarchical grouping strategy was developed for assigning exposure levels to underground jobs [based on job titles, on the amount of time spent in various areas of the underground mine, and on similar carbon monoxide (CO, another DE component) concentrations] and to surface jobs (based on the use of, or proximity to, diesel-powered equipment). Time trends in air concentrations for underground jobs were estimated from mining facility-specific prediction models using diesel equipment horsepower, total air flow rates exhausted from the underground mines, and, because there were no historical REC measurements, historical measurements of CO. Exposures to potentially confounding agents, i.e. respirable dust, silica, radon, asbestos, and non-diesel sources of polycyclic aromatic hydrocarbons, also were assessed. Accuracy and reliability of the estimated REC exposures levels were evaluated by comparison with several smaller datasets and by development of alternative time trend models. During 1998-2001, the average measured REC exposure level by facility ranged from 40 to 384 µg m⁻³ for the underground workers and from 2 to 6 µg m⁻³ for the surface workers. For one prevalent underground job, 'miner operator', the maximum annual REC exposure estimate by facility ranged up to 685% greater than the corresponding 1998-2001 value. A comparison of the historical CO estimates from the time trend models with 1976-1977 CO measurements not used in the modeling found an overall median relative difference of 29%. Other comparisons showed similar levels of agreement. The assessment process indicated large differences in REC exposure levels over time and across the underground operations. Method evaluations indicated that the final estimates were consistent with those from alternative time trend models and demonstrated moderate to high agreement with external data.

Occupation and multiple myeloma: an occupation and industry analysis.

BACKGROUND: Multiple myeloma (MM) is an incurable plasma cell malignancy with a poorly understood etiology. The purpose of our research was to examine the relationships between lifetime occupations and MM in a relatively large case-control study. METHODS: MM cases (n = 180) were identified through cancer registries in the Seattle-Puget Sound area and Detroit. Population-based controls (n = 481) were identified using random digit dialing and Medicare and Medicaid Services files. In-person interviews were conducted to ascertain occupational histories. Standard occupational classification (SOC) and standard industrial classification (SIC) codes were assigned to each job held by each participant. Unconditional logistic regression was used to generate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between MM and having ever worked in each occupation/industry and according to duration of employment in an occupation/industry. RESULTS: The risk of MM was associated with several manufacturing occupations and industries, including machine operators and tenders, not elsewhere classified (SOC 76) (OR = 1.8, CI = 1.0-3.3); textile, apparel, and furnishing machine operators and tenders (SOC 765) (OR = 6.0, CI = 1.7-21); and machinery manufacturing, except electrical (SIC 35) (OR = 3.3, CI = 1.7-6.7). Several service occupations and industries, such as food and beverage preparation (SOC 521) (OR = 2.0, CI = 1.1-3.8), were also associated with MM. One occupation that has been associated with MM in several previous studies, painters, paperhangers, and plasterers (SOC 644) was associated with a non-significantly elevated risk (OR = 3.6, CI = 0.7-19). CONCLUSIONS: We found associations between the risk of MM and employment in several manufacturing and service-related occupations and industries.

Assessment of a pesticide exposure intensity algorithm in the agricultural health study.

The accuracy of the exposure assessment is a critical factor in epidemiological investigations of pesticide exposures and health in agricultural populations. However, few studies have been conducted to evaluate questionnaire-based exposure metrics. The Agricultural Health Study (AHS) is a prospective cohort study of pesticide applicators who provided detailed questionnaire information on their use of specific pesticides. A field study was conducted for a subset of the applicators enrolled in the AHS to assess a pesticide exposure algorithm through comparison of algorithm intensity scores with measured exposures. Pre- and post-application urinary biomarker measurements were made for 2,4-D (n=69) and chlorpyrifos (n=17) applicators. Dermal patch, hand wipe, and personal air samples were also collected. Intensity scores were calculated using information from technician observations and an interviewer-administered questionnaire. Correlations between observer and questionnaire intensity scores were high (Spearman's r=0.92 and 0.84 for 2,4-D and chlorpyrifos, respectively). Intensity scores from questionnaires for individual applications were significantly correlated with post-application urinary concentrations for both 2,4-D (r=0.42, P<0.001) and chlorpyrifos (r=0.53, P=0.035) applicators. Significant correlations were also found between intensity scores and estimated hand loading, estimated body loading, and air concentrations for 2,4-D applicators (r-values 0.28-0.50, P-values<0.025). Correlations between intensity scores and dermal and air measures were generally lower for chlorpyrifos applicators using granular products. A linear regression model indicated that the algorithm factors for individual applications explained 24% of the variability in post-application urinary 2,4-D concentration, which increased to 60% when the pre-application urine concentration was included. The results of the measurements support the use of the algorithm for estimating questionnaire-based exposure intensities in the AHS for liquid pesticide products. Refinement of the algorithm may be possible using the results from this and other measurement studies.