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1.  Inside the black box: starting to uncover the underlying decision rules used in one-by-one expert assessment of occupational exposure in case-control studies 
Objectives
Evaluating occupational exposures in population-based case-control studies often requires exposure assessors to review each study participants' reported occupational information job-by-job to derive exposure estimates. Although such assessments likely have underlying decision rules, they usually lack transparency, are time-consuming and have uncertain reliability and validity. We aimed to identify the underlying rules to enable documentation, review, and future use of these expert-based exposure decisions.
Methods
Classification and regression trees (CART, predictions from a single tree) and random forests (predictions from many trees) were used to identify the underlying rules from the questionnaire responses and an expert's exposure assignments for occupational diesel exhaust exposure for several metrics: binary exposure probability and ordinal exposure probability, intensity, and frequency. Data were split into training (n=10,488 jobs), testing (n=2,247), and validation (n=2,248) data sets.
Results
The CART and random forest models' predictions agreed with 92–94% of the expert's binary probability assignments. For ordinal probability, intensity, and frequency metrics, the two models extracted decision rules more successfully for unexposed and highly exposed jobs (86–90% and 57–85%, respectively) than for low or medium exposed jobs (7–71%).
Conclusions
CART and random forest models extracted decision rules and accurately predicted an expert's exposure decisions for the majority of jobs and identified questionnaire response patterns that would require further expert review if the rules were applied to other jobs in the same or different study. This approach makes the exposure assessment process in case-control studies more transparent and creates a mechanism to efficiently replicate exposure decisions in future studies.
doi:10.1136/oemed-2012-100918
PMCID: PMC3975600  PMID: 23155187
diesel exhaust; classification; data mining; occupational exposure
2.  Comparison of two expert-based assessments of diesel exhaust exposure in a case-control study: Programmable decision rules versus expert review of individual jobs 
Objectives
Professional judgment is necessary to assess occupational exposure in population-based case-control studies; however, the assessments lack transparency and are time-consuming to perform. To improve transparency and efficiency, we systematically applied decision rules to the questionnaire responses to assess diesel exhaust exposure in the New England Bladder Cancer Study, a population-based case-control study.
Methods
2,631 participants reported 14,983 jobs; 2,749 jobs were administered questionnaires (‘modules’) with diesel-relevant questions. We applied decision rules to assign exposure metrics based solely on the occupational history responses (OH estimates) and based on the module responses (module estimates); we combined the separate OH and module estimates (OH/module estimates). Each job was also reviewed one at a time to assign exposure (one-by-one review estimates). We evaluated the agreement between the OH, OH/module, and one-by-one review estimates.
Results
The proportion of exposed jobs was 20–25% for all jobs, depending on approach, and 54–60% for jobs with diesel-relevant modules. The OH/module and one-by-one review had moderately high agreement for all jobs (κw=0.68–0.81) and for jobs with diesel-relevant modules (κw=0.62–0.78) for the probability, intensity, and frequency metrics. For exposed subjects, the Spearman correlation statistic was 0.72 between the cumulative OH/module and one-by-one review estimates.
Conclusions
The agreement seen here may represent an upper level of agreement because the algorithm and one-by-one review estimates were not fully independent. This study shows that applying decision-based rules can reproduce a one-by-one review, increase transparency and efficiency, and provide a mechanism to replicate exposure decisions in other studies.
doi:10.1136/oemed-2011-100524
PMCID: PMC3439531  PMID: 22843440
3.  Chronic and Acute Effects of Coal Tar Pitch Exposure and Cardiopulmonary Mortality Among Aluminum Smelter Workers 
American Journal of Epidemiology  2010;172(7):790-799.
Air pollution causes several adverse cardiovascular and respiratory effects. In occupational studies, where levels of particulate matter and polycyclic aromatic hydrocarbons (PAHs) are higher, the evidence is inconsistent. The effects of acute and chronic PAH exposure on cardiopulmonary mortality were examined within a Kitimat, Canada, aluminum smelter cohort (n = 7,026) linked to a national mortality database (1957–1999). No standardized mortality ratio was significantly elevated compared with the province's population. Smoking-adjusted internal comparisons were conducted using Cox regression for male subjects (n = 6,423). Ischemic heart disease (IHD) mortality (n = 281) was associated with cumulative benzo[a]pyrene (B(a)P) exposure (hazard ratio = 1.62, 95% confidence interval: 1.06, 2.46) in the highest category. A monotonic but nonsignificant trend was observed with chronic B(a)P exposure and acute myocardial infarction (n = 184). When follow-up was restricted to active employment, the hazard ratio for IHD was 2.39 (95% confidence interval: 0.95, 6.05) in the highest cumulative B(a)P category. The stronger associations observed during employment suggest that risk may not persist after exposure cessation. No associations with recent or current exposure were observed. IHD was associated with chronic (but not current) PAH exposure in a high-exposure occupational setting. Given the widespread workplace exposure to PAHs and heart disease's high prevalence, even modest associations produce a high burden.
doi:10.1093/aje/kwq208
PMCID: PMC2984260  PMID: 20702507
air pollutants; cohort studies; heart diseases; occupational diseases; polycyclic hydrocarbons, aromatic
4.  Comparison of two indices of exposure to polycyclic aromatic hydrocarbons in a retrospective aluminium smelter cohort 
Background
The association between coal tar‐derived substances, a complex mixture of polycyclic aromatic hydrocarbons, and cancer is well established. However, the specific aetiological agents are unknown.
Objective
To compare the dose–response relationships for two common measures of coal tar‐derived substances, benzene‐soluble material (BSM) and benzo(a)pyrene (BaP), and to evaluate which among these is more strongly related to the health outcomes.
Methods
The study population consisted of 6423 men with ⩾3 years of work experience at an aluminium smelter (1954–97). Three health outcomes identified from national mortality and cancer databases were evaluated: incidence of bladder cancer (n = 90), incidence of lung cancer (n = 147) and mortality due to acute myocardial infarction (AMI, n = 184). The shape, magnitude and precision of the dose–response relationships and cumulative exposure levels for BSM and BaP were evaluated. Two model structures were assessed, where 1n(relative risk) increased with cumulative exposure (log‐linear model) or with log‐transformed cumulative exposure (log–log model).
Results
The BaP and BSM cumulative exposure metrics were highly correlated (r = 0.94). The increase in model precision using BaP over BSM was 14% for bladder cancer and 5% for lung cancer; no difference was observed for AMI. The log‐linear BaP model provided the best fit for bladder cancer. The log–log dose–response models, where risk of disease plateaus at high exposure levels, were the best‐fitting models for lung cancer and AMI.
Conclusion
BaP and BSM were both strongly associated with bladder and lung cancer and modestly associated with AMI. Similar conclusions regarding the associations could be made regardless of the exposure metric.
doi:10.1136/oem.2006.028928
PMCID: PMC2078451  PMID: 17053015
5.  Metalworking fluid exposure and cancer risk in a retrospective cohort of female autoworkers 
Cancer causes & control : CCC  2012;23(7):1075-1082.
Objectives
Metalworking fluids (MWFs) have been associated with cancer of several sites, but the risks have been primarily examined in men or in studies that adjusted for gender in analyses. To evaluate whether risks were similar in women, we report cancer mortality risk among 4,825 female autoworkers within the united autoworkers–general motors autoworkers cohort.
Methods
Standardized mortality rates (SMRs) were calculated based on Michigan death rates (1980–2004). Internal comparisons (1941–2004) were examined using Cox regression for straight, soluble, and synthetic MWFs, and their corresponding oil- and water-based fractions.
Results
MWF exposure levels in the female cohort were generally less than two-third the MWF levels in the male cohort. Female autoworkers had an excess of cancer from all sites (SMR, 1.10; 95 % confidence interval (CI), 0.98–1.22) and lung cancer (SMR, 2.08; 95 % CI, 1.71–2.52). Colon cancer risk increased with straight (mineral oil) MWF exposure (exposure>median; hazard ratio = 3.1; 95 % CI, 1.2–8.0). A protective effect was observed for ovarian cancer with the soluble MWFs and water-based MWF metrics. Although bladder, rectal, and laryngeal cancers and malignant melanoma have been associated with straight MWF exposure and pancreatic cancer with synthetic MWF in men, there were too few deaths in this female subcohort to examine exposure-response relations for these sites. Results were null for lung and breast cancer.
Conclusions
Our findings support an association between colon cancer and straight MWFs, but we found limited evidence of risk for other tumor sites at the lower exposure levels experienced by the female autoworkers.
doi:10.1007/s10552-012-9976-z
PMCID: PMC3370111  PMID: 22562220
Metalworking fluids; Cancer mortality; Colon cancer; Women's health; Cohort studies
6.  A multi-day environmental study of polycyclic aromatic hydrocarbon exposure in a high-risk region for esophageal cancer in China 
Linzhou, China has one of the highest rates of esophageal squamous cell carcinoma in the world. Exposure to carcinogenic polycyclic aromatic hydrocarbons (PAHs), such as benzo[a]pyrene (BaP), may play a role in this increased risk. To better understand PAH sources, we measured PAHs in the air and food of 20 non-smokers over multiple days and compared the concentrations to a urinary PAH biomarker, 1-hydroxypyrene glucuronide (1-OHPG). Sampling occurred over four consecutive days. Kitchen air samples (days 2–3) and duplicate diet samples (days 1–4) were analyzed for 14 or more unique PAHs, including BaP. Daily urine samples (days 1–3) were analyzed for 1-OHPG. Mixed-effects models were used to evaluate the associations between air or food PAH concentrations and urine 1-OHPG concentrations. The median kitchen air BaP concentration was 10.2 ng/m3 (inter-quartile range (IQR): 5.1–20.2 ng/m3). The median daily food BaP concentration and intake were 0.08 ng/g (IQR=0.04–0.16 ng/g) and 86 ng/day (IQR=41–142 ng/day), respectively. The median 1-OHPG concentration was 3.36 pmol/mL (IQR=2.09–6.98 pmol/mL). In mixed-effects models, 1-OHPG concentration increased with same-day concentration of food BaP (p=0.07). Though PAH concentrations in air were not associated with 1-OHPG concentrations, the high concentrations of PAHs in both air and food suggest that they are both important routes of exposure to PAHs in this population. Further evaluation of the role of PAH exposure from air and food in the elevated rates of esophageal cancer in this region is warranted.
doi:10.1038/jes.2012.73
PMCID: PMC3504638  PMID: 22805987
polycyclic aromatic hydrocarbons; cancer; China; dietary exposure; inhalation exposure; biomonitoring; multimedia exposure assessment
7.  Temporal Variability of Pesticide Concentrations in Homes and Implications for Attenuation Bias in Epidemiologic Studies 
Environmental Health Perspectives  2013;121(5):565-571.
Background: Residential pesticide exposure has been linked to adverse health outcomes in adults and children. High-quality exposure estimates are critical for confirming these associations. Past epidemiologic studies have used one measurement of pesticide concentrations in carpet dust to characterize an individual’s average long-term exposure. If concentrations vary over time, this approach could substantially misclassify exposure and attenuate risk estimates.
Objectives: We assessed the repeatability of pesticide concentrations in carpet dust samples and the potential attenuation bias in epidemiologic studies relying on one sample.
Methods: We collected repeated carpet dust samples (median = 3; range, 1–7) from 21 homes in Fresno County, California, during 2003–2005. Dust was analyzed for 13 pesticides using gas chromatography–mass spectrometry. We used mixed-effects models to estimate between- and within-home variance. For each pesticide, we computed intraclass correlation coefficients (ICCs) and the estimated attenuation of regression coefficients in a hypothetical case–control study collecting a single dust sample.
Results: The median ICC was 0.73 (range, 0.37–0.95), demonstrating higher between-home than within-home variability for most pesticides. The expected magnitude of attenuation bias associated with using a single dust sample was estimated to be ≤ 30% for 7 of the 13 compounds evaluated.
Conclusions: For several pesticides studied, use of one dust sample to represent an exposure period of approximately 2 years would not be expected to substantially attenuate odds ratios. Further study is needed to determine if our findings hold for longer exposure periods and for other pesticides.
doi:10.1289/ehp.1205811
PMCID: PMC3672902  PMID: 23462689
dust; environmental exposure; pesticides; reliability
8.  Combining a Job-Exposure Matrix with Exposure Measurements to Assess Occupational Exposure to Benzene in a Population Cohort in Shanghai, China 
Annals of Occupational Hygiene  2011;56(1):80-91.
Background:
Generic job-exposure matrices (JEMs) are often used in population-based epidemiologic studies to assess occupational risk factors when only the job and industry information of each subject is available. JEM ratings are often based on professional judgment, are usually ordinal or semi-quantitative, and often do not account for changes in exposure over time. We present an empirical Bayesian framework that combines ordinal subjective JEM ratings with benzene measurements. Our aim was to better discriminate between job, industry, and time differences in exposure levels compared to using a JEM alone.
Methods:
We combined 63 221 short-term area air measurements of benzene exposure (1954–2000) collected during routine health and safety inspections in Shanghai, China, with independently developed JEM intensity ratings for each job and industry using a mixed-effects model. The fixed-effects terms included the JEM intensity ratings for job and industry (both ordinal, 0–3) and a time trend that we incorporated as a b-spline. The random-effects terms included job (n = 33) and industry nested within job (n = 399). We predicted the benzene concentration in two ways: (i) a calibrated JEM estimate was calculated using the fixed-effects model parameters for calendar year and JEM intensity ratings; (ii) a job-/industry-specific estimate was calculated using the fixed-effects model parameters and the best linear unbiased predictors from the random effects for job and industry using an empirical Bayes estimation procedure. Finally, we applied the predicted benzene exposures to a prospective population-based cohort of women in Shanghai, China (n = 74 942).
Results:
Exposure levels were 13 times higher in 1965 than in 2000 and declined at a rate that varied from 4 to 15% per year from 1965 to 1985, followed by a small peak in the mid-1990s. The job-/industry-specific estimates had greater differences between exposure levels than the calibrated JEM estimates (97.5th percentile/2.5th percentile exposure level, BGR95B: 20.4 versus 3.0, respectively). The calibrated JEM and job-/industry-specific estimates were moderately correlated in any given year (Pearson correlation, rp = 0.58). We classified only those jobs and industries with a job or industry JEM exposure probability rating of 3 (>50% of workers exposed) as exposed. As a result, 14.8% of the subjects and 8.7% of the employed person-years in the study population were classified as benzene exposed. The cumulative exposure metrics based on the calibrated JEM and job-/industry-specific estimates were highly correlated (rp = 0.88).
Conclusions:
We provide a useful framework for combining quantitative exposure data with expert-based exposure ratings in population-based studies that maximized the information from both sources. Our framework calibrated the ratings to a concentration scale between ratings and across time and provided a mechanism to estimate exposure when a job/industry group reported by a subject was not represented in the exposure database. It also allowed the job/industry groups’ exposure levels to deviate from the pooled average for their respective JEM intensity ratings.
doi:10.1093/annhyg/mer080
PMCID: PMC3259038  PMID: 21976309
benzene; job-exposure matrix; mixed-effects models; retrospective exposure assessment
9.  Validity and Reliability of Exposure Assessors’ Ratings of Exposure Intensity by Type of Occupational Questionnaire and Type of Rater 
Annals of Occupational Hygiene  2011;55(6):601-611.
Background: In epidemiologic studies that rely on professional judgment to assess occupational exposures, the raters’ accurate assessment is vital to detect associations. We examined the influence of the type of questionnaire, type of industry, and type of rater on the raters’ ability to reliably and validly assess within-industry differences in exposure. Our aim was to identify areas where improvements in exposure assessment may be possible.
Methods: Subjects from three foundries (n = 72) and three textile plants (n = 74) in Shanghai, China, completed an occupational history (OH) and an industry-specific questionnaire (IQ). Six total dust measurements were collected per subject and were used to calculate a subject-specific measurement mean, which was used as the gold standard. Six raters independently ranked the intensity of each subject’s current job on an ordinal scale (1–4) based on the OH alone and on the OH and IQ together. Aggregate ratings were calculated for the group, for industrial hygienists, and for occupational physicians. We calculated intra-class correlation coefficients (ICCs) to evaluate the reliability of the raters. We calculated the correlation between the subject-specific measurement means and the ratings to evaluate the raters’ validity. Analyses were stratified by industry, type of questionnaire, and type of rater. We also examined the agreement between the ratings by exposure category, where the subject-specific measurement means were categorized into two and four categories.
Results: The reliability and validity measures were higher for the aggregate ratings than for the ratings from the individual raters. The group’s performance was maximized with three raters. Both the reliability and validity measures were higher for the foundry industry than for the textile industry. The ICCs were consistently lower in the OH/IQ round than in the OH round in both industries. In contrast, the correlations with the measurement means were higher in the OH/IQ round than in the OH round for the foundry industry (group rating, OH/IQ: Spearman rho = 0.77; OH: rho = 0.64). No pattern by questionnaire type was observed for the textile industry (group rating, Spearman rho = 0.50, both assessment rounds). For both industries, the agreement by exposure category was higher when the task was reduced to discriminating between two versus four exposure categories.
Conclusions: Assessments based on professional judgment may reduce misclassification by using two or three raters, by using questionnaires that systematically collect task information, and by defining intensity categories that are distinguishable by the raters. However, few studies have the resources to use multiple raters and these additional efforts may not be adequate for obtaining valid subjective ratings. Thus, improving exposure assessment approaches for studies that rely on professional judgment remain an important research need.
doi:10.1093/annhyg/mer019
PMCID: PMC3131504  PMID: 21511891
dust; exposure assessment; foundry industry; population-based studies; professional judgment; reliability; textile industry; validity
10.  Distinguishing the common components of oil- and water-based metalworking fluids for assessment of cancer incidence risk in autoworkers 
Background
Metalworking fluids (MWF) — straight, soluble, and synthetic — have overlapping components. We derived constituent-based metrics of polycyclic aromatic hydrocarbons (PAHs), water-based MWF, biocides, and nitrosamines to account for this overlap and examined their relations with cancer incidence.
Methods
An autoworkers cohort of 30,000 was followed for cancer incidence. Hazard ratios were estimated for each cancer and cumulative exposure (lagged) to each new metric; soluble MWF contributed variably to several metrics with weight k=0–1.
Results
For most cancer sites, the constituent-based metrics resulted in stronger exposure-disease associations than the MWF classes alone. Laryngeal and bladder cancer were most strongly associated with PAH (k=0). Protective effects for stomach and lung cancer were observed with biocide, a component that may be a surrogate for endotoxin.
Conclusions
Our findings provide support and clarification of possible etiologies for previous positive associations and provide support for distinguishing exposure from oil- and water-based MWF in epidemiologic studies.
doi:10.1002/ajim.20932
PMCID: PMC3301446  PMID: 21328414
Metalworking Fluids; Polycyclic Aromatic Hydrocarbons; Cancer Incidence; Cohort Study; Endotoxin; Biocides; Nitrosamines
11.  OccIDEAS: Retrospective Occupational Exposure Assessment in Community-Based Studies Made Easier 
Assessing occupational exposure in retrospective community-based case-control studies is difficult as measured exposure data are very seldom available. The expert assessment method is considered the most accurate way to attribute exposure but it is a time consuming and expensive process and may be seen as subjective, nonreproducible, and nontransparent. In this paper, we describe these problems and outline our solutions as operationalized in a web-based software application (OccIDEAS). The novel aspects of OccIDEAS are combining all steps in the assessment into one software package; enmeshing the process of assessment into the development of questionnaires; selecting the exposure(s) of interest; specifying rules for exposure assignment; allowing manual or automatic assessments; ensuring that circumstances in which exposure is possible for an individual are highlighted for review; providing reports to ensure consistency of assessment. Development of this application has the potential to make high-quality occupational assessment more efficient and accessible for epidemiological studies.
doi:10.1155/2009/957023
PMCID: PMC2778192  PMID: 20041014

Results 1-11 (11)