Excess risk of SARS-CoV-2 infection among in-person nonhealthcare workers in six states, September 2020-June 2021.

BACKGROUND: While the occupational risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection for healthcare personnel in the United States has been relatively well characterized, less information is available on the occupational risk for workers employed in other settings. Even fewer studies have attempted to compare risks across occupations and industries. Using differential proportionate distribution as an approximation, we evaluated excess risk of SARS-CoV-2 infection by occupation and industry among non-healthcare workers in six states. METHODS: We analyzed data on occupation and industry of employment from a six-state callback survey of adult non-healthcare workers with confirmed SARS-CoV-2 infection and population-based reference data on employment patterns, adjusted for the effect of telework, from the U.S. Bureau of Labor Statistics. We estimated the differential proportionate distribution of SARS-CoV-2 infection by occupation and industry using the proportionate morbidity ratio (PMR). RESULTS: Among a sample of 1111 workers with confirmed SARS-CoV-2 infection, significantly higher-than-expected proportions of workers were employed in service occupations (PMR 1.3, 99% confidence interval [CI] 1.1-1.5) and in the transportation and utilities (PMR 1.4, 99% CI 1.1-1.8) and leisure and hospitality industries (PMR 1.5, 99% CI 1.2-1.9). CONCLUSIONS: We found evidence of significant differences in the proportionate distribution of SARS-CoV-2 infection by occupation and industry among respondents in a multistate, population-based survey, highlighting the excess risk of SARS-CoV-2 infection borne by some worker populations, particularly those whose jobs require frequent or prolonged close contact with other people.

Work: A Social Determinant of Health Worth Capturing.

Work is a recognized social determinant of health. This became most apparent during the COVID-19 pandemic. Workers, particularly those in certain industries and occupations, were at risk due to interaction with the public and close proximity to co-workers. The purpose of this study was to assess how states collected work and employment data on COVID-19 cases, characterizing the need for systematic collection of case-based specific work and employment data, including industry and occupation, of COVID-19 cases. A survey was distributed among state occupational health contacts and epidemiologists in all 50 states to assess current practices in state public health surveillance systems. Twenty-seven states collected some kind of work and employment information from COVID-19 cases. Most states (93%) collected industry and/or occupation information. More than half used text-only fields, a predefined reference or dropdown list, or both. Use of work and employment data included identifying high risk populations, prioritizing vaccination efforts, and assisting with reopening plans. Reported barriers to collecting industry and occupation data were lack of staffing, technology issues, and funding. Scientific understanding of work-related COVID-19 risk requires the systematic, case-based collection of specific work and employment data, including industry and occupation. While this alone does not necessarily indicate a clear workplace exposure, collection of these data elements can help to determine and further prevent workplace outbreaks, thereby ensuring the viability of the nation's critical infrastructure.

Reported Exposures Among In-Person Workers With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection in 6 States, September 2020-June 2021.

BACKGROUND: Surveillance systems lack detailed occupational exposure information from workers with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The National Institute for Occupational Safety and Health partnered with 6 states to collect information from adults diagnosed with SARS-CoV-2 infection who worked in person (outside the home) in non-healthcare settings during the 2 weeks prior to illness onset. METHODS: The survey captured demographic, medical, and occupational characteristics and work- and non-work-related risk factors for SARS-CoV-2 infection. Reported close contact with a person known or suspected to have SARS-CoV-2 infection was categorized by setting as exposure at work, exposure outside of work only, or no known exposure/did not know. Frequencies and percentages of exposure types are compared by respondent characteristics and risk factors. RESULTS: Of 1111 respondents, 19.4% reported exposure at work, 23.4% reported exposure outside of work only, and 57.2% reported no known exposure/did not know. Workers in protective service occupations (48.8%) and public administration industries (35.6%) reported exposure at work most often. More than one third (33.7%) of respondents who experienced close contact with ≥10 coworkers per day and 28.8% of respondents who experienced close contact with ≥10 customers/clients per day reported exposures at work. CONCLUSIONS: Exposure to occupational SARS-CoV-2 was common among respondents. Examining differences in exposures among different worker groups can help identify populations with the greatest need for prevention interventions. The benefits of recording employment characteristics as standard demographic information will remain relevant as new and reemerging public health issues occur.

Identifying Barriers and Supports to Breastfeeding in the Workplace Experienced by Mothers in the New Hampshire Special Supplemental Nutrition Program for Women, Infants, and Children Utilizing the Total Worker Health Framework.

Variations in the barriers and contributors to breastfeeding across industries have not been well characterized for vulnerable populations such as mothers participating in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). Our study used the Total Worker Health Framework to characterize workplace factors acting as barriers and/or contributors to breastfeeding among women participating in the New Hampshire WIC. Surveys were collected from WIC mothers (n = 682), which asked about employment, industry, and workplace accommodation and supports related to breastfeeding in the workplace. We found workplace policy factors supporting breastfeeding (i.e., having paid maternity leave, other maternity leave, and a breastfeeding policy) varied by industry. Women in specific service-oriented industries (i.e., accommodation and retail) reported the lowest rates of breastfeeding initiation and workplace supports for breastfeeding and pumping. Further, how a woman hoped to feed and having a private pumping space at work were significantly associated with industry, breastfeeding initiation, and breastfeeding duration. A substantial portion of women reported being not sure about their workplace environment, policies, and culture related to breastfeeding. Additional studies with larger sample sizes of women participating in WIC are needed to further characterize the barriers to breastfeeding associated with specific industries.

Elevated Bladder Cancer in Northern New England: The Role of Drinking Water and Arsenic.

BACKGROUND: Bladder cancer mortality rates have been elevated in northern New England for at least five decades. Incidence rates in Maine, New Hampshire, and Vermont are about 20% higher than the United States overall. We explored reasons for this excess, focusing on arsenic in drinking water from private wells, which are particularly prevalent in the region. METHODS: In a population-based case-control study in these three states, 1213 bladder cancer case patients and 1418 control subjects provided information on suspected risk factors. Log transformed arsenic concentrations were estimated by linear regression based on measurements in water samples from current and past homes. All statistical tests were two-sided. RESULTS: Bladder cancer risk increased with increasing water intake (Ptrend = .003). This trend was statistically significant among participants with a history of private well use (Ptrend = .01). Among private well users, this trend was apparent if well water was derived exclusively from shallow dug wells (which are vulnerable to contamination from manmade sources, Ptrend = .002) but not if well water was supplied only by deeper drilled wells (Ptrend = .48). If dug wells were used pre-1960, when arsenical pesticides were widely used in the region, heavier water consumers (>2.2 L/day) had double the risk of light users (<1.1 L/day, Ptrend = .01). Among all participants, cumulative arsenic exposure from all water sources, lagged 40 years, yielded a positive risk gradient (Ptrend = .004); among the highest-exposed participants (97.5th percentile), risk was twice that of the lowest-exposure quartile (odds ratio = 2.24, 95% confidence interval = 1.29 to 3.89). CONCLUSIONS: Our findings support an association between low-to-moderate levels of arsenic in drinking water and bladder cancer risk in New England. In addition, historical consumption of water from private wells, particularly dug wells in an era when arsenical pesticides were widely used, was associated with increased bladder cancer risk and may have contributed to the New England excess.

Computer-based coding of free-text job descriptions to efficiently identify occupations in epidemiological studies.

BACKGROUND: Mapping job titles to standardised occupation classification (SOC) codes is an important step in identifying occupational risk factors in epidemiological studies. Because manual coding is time-consuming and has moderate reliability, we developed an algorithm called SOCcer (Standardized Occupation Coding for Computer-assisted Epidemiologic Research) to assign SOC-2010 codes based on free-text job description components. METHODS: Job title and task-based classifiers were developed by comparing job descriptions to multiple sources linking job and task descriptions to SOC codes. An industry-based classifier was developed based on the SOC prevalence within an industry. These classifiers were used in a logistic model trained using 14 983 jobs with expert-assigned SOC codes to obtain empirical weights for an algorithm that scored each SOC/job description. We assigned the highest scoring SOC code to each job. SOCcer was validated in 2 occupational data sources by comparing SOC codes obtained from SOCcer to expert assigned SOC codes and lead exposure estimates obtained by linking SOC codes to a job-exposure matrix. RESULTS: For 11 991 case-control study jobs, SOCcer-assigned codes agreed with 44.5% and 76.3% of manually assigned codes at the 6-digit and 2-digit level, respectively. Agreement increased with the score, providing a mechanism to identify assignments needing review. Good agreement was observed between lead estimates based on SOCcer and manual SOC assignments (κ 0.6-0.8). Poorer performance was observed for inspection job descriptions, which included abbreviations and worksite-specific terminology. CONCLUSIONS: Although some manual coding will remain necessary, using SOCcer may improve the efficiency of incorporating occupation into large-scale epidemiological studies.

Combining Decision Rules from Classification Tree Models and Expert Assessment to Estimate Occupational Exposure to Diesel Exhaust for a Case-Control Study.

OBJECTIVES: To efficiently and reproducibly assess occupational diesel exhaust exposure in a Spanish case-control study, we examined the utility of applying decision rules that had been extracted from expert estimates and questionnaire response patterns using classification tree (CT) models from a similar US study. METHODS: First, previously extracted CT decision rules were used to obtain initial ordinal (0-3) estimates of the probability, intensity, and frequency of occupational exposure to diesel exhaust for the 10 182 jobs reported in a Spanish case-control study of bladder cancer. Second, two experts reviewed the CT estimates for 350 jobs randomly selected from strata based on each CT rule's agreement with the expert ratings in the original study [agreement rate, from 0 (no agreement) to 1 (perfect agreement)]. Their agreement with each other and with the CT estimates was calculated using weighted kappa (κ w) and guided our choice of jobs for subsequent expert review. Third, an expert review comprised all jobs with lower confidence (low-to-moderate agreement rates or discordant assignments, n = 931) and a subset of jobs with a moderate to high CT probability rating and with moderately high agreement rates (n = 511). Logistic regression was used to examine the likelihood that an expert provided a different estimate than the CT estimate based on the CT rule agreement rates, the CT ordinal rating, and the availability of a module with diesel-related questions. RESULTS: Agreement between estimates made by two experts and between estimates made by each of the experts and the CT estimates was very high for jobs with estimates that were determined by rules with high CT agreement rates (κ w: 0.81-0.90). For jobs with estimates based on rules with lower agreement rates, moderate agreement was observed between the two experts (κ w: 0.42-0.67) and poor-to-moderate agreement was observed between the experts and the CT estimates (κ w: 0.09-0.57). In total, the expert review of 1442 jobs changed 156 probability estimates, 128 intensity estimates, and 614 frequency estimates. The expert was more likely to provide a different estimate when the CT rule agreement rate was <0.8, when the CT ordinal ratings were low to moderate, or when a module with diesel questions was available. CONCLUSIONS: Our reliability assessment provided important insight into where to prioritize additional expert review; as a result, only 14% of the jobs underwent expert review, substantially reducing the exposure assessment burden. Overall, we found that we could efficiently, reproducibly, and reliably apply CT decision rules from one study to assess exposure in another study.

Modification of Occupational Exposures on Bladder Cancer Risk by Common Genetic Polymorphisms.

Few studies have demonstrated gene/environment interactions in cancer research. Using data on high-risk occupations for 2258 case patients and 2410 control patients from two bladder cancer studies, we observed that three of 16 known or candidate bladder cancer susceptibility variants displayed statistically significant and consistent evidence of additive interactions; specifically, the GSTM1 deletion polymorphism (P interaction ≤ .001), rs11892031 (UGT1A, P interaction = .01), and rs798766 (TMEM129-TACC3-FGFR3, P interaction = .03). There was limited evidence for multiplicative interactions. When we examined detailed data on a prevalent occupational exposure associated with increased bladder cancer risk, straight metalworking fluids, we also observed statistically significant additive interaction for rs798766 (TMEM129-TACC3-FGFR3, P interaction = .02), with the interaction more apparent in patients with tumors positive for FGFR3 expression. All statistical tests were two-sided. The interaction we observed for rs798766 (TMEM129-TACC3-FGFR3) with specific exposure to straight metalworking fluids illustrates the value of integrating germline genetic variation, environmental exposures, and tumor marker data to provide insight into the mechanisms of bladder carcinogenesis.

Comparison of ordinal and nominal classification trees to predict ordinal expert-based occupational exposure estimates in a case-control study.

OBJECTIVES: To evaluate occupational exposures in case-control studies, exposure assessors typically review each job individually to assign exposure estimates. This process lacks transparency and does not provide a mechanism for recreating the decision rules in other studies. In our previous work, nominal (unordered categorical) classification trees (CTs) generally successfully predicted expert-assessed ordinal exposure estimates (i.e. none, low, medium, high) derived from occupational questionnaire responses, but room for improvement remained. Our objective was to determine if using recently developed ordinal CTs would improve the performance of nominal trees in predicting ordinal occupational diesel exhaust exposure estimates in a case-control study. METHODS: We used one nominal and four ordinal CT methods to predict expert-assessed probability, intensity, and frequency estimates of occupational diesel exhaust exposure (each categorized as none, low, medium, or high) derived from questionnaire responses for the 14983 jobs in the New England Bladder Cancer Study. To replicate the common use of a single tree, we applied each method to a single sample of 70% of the jobs, using 15% to test and 15% to validate each method. To characterize variability in performance, we conducted a resampling analysis that repeated the sample draws 100 times. We evaluated agreement between the tree predictions and expert estimates using Somers' d, which measures differences in terms of ordinal association between predicted and observed scores and can be interpreted similarly to a correlation coefficient. RESULTS: From the resampling analysis, compared with the nominal tree, an ordinal CT method that used a quadratic misclassification function and controlled tree size based on total misclassification cost had a slightly better predictive performance that was statistically significant for the frequency metric (Somers' d: nominal tree = 0.61; ordinal tree = 0.63) and similar performance for the probability (nominal = 0.65; ordinal = 0.66) and intensity (nominal = 0.65; ordinal = 0.65) metrics. The best ordinal CT predicted fewer cases of large disagreement with the expert assessments (i.e. no exposure predicted for a job with high exposure and vice versa) compared with the nominal tree across all of the exposure metrics. For example, the percent of jobs with expert-assigned high intensity of exposure that the model predicted as no exposure was 29% for the nominal tree and 22% for the best ordinal tree. CONCLUSIONS: The overall agreements were similar across CT models; however, the use of ordinal models reduced the magnitude of the discrepancy when disagreements occurred. As the best performing model can vary by situation, researchers should consider evaluating multiple CT methods to maximize the predictive performance within their data.

Using hierarchical cluster models to systematically identify groups of jobs with similar occupational questionnaire response patterns to assist rule-based expert exposure assessment in population-based studies.

OBJECTIVES: Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure. METHODS: Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m(-3) respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters' homogeneity (defined as >75% with the same estimate) was examined compared to a dichotomized probability estimate (<5 versus ≥5%; <50 versus ≥50%). Second, for the ordinal probability metric and continuous intensity and frequency metrics, we calculated the intraclass correlation coefficients (ICCs) between each job's estimate and the mean estimate for all jobs within the cluster. RESULTS: Within-cluster homogeneity increased when more clusters were used. For example, ≥80% of the clusters were homogeneous when 500 clusters were used. Similarly, ICCs were generally above 0.7 when ≥200 clusters were used, indicating minimal within-cluster variability. The most within-cluster variability was observed for the frequency metric (ICCs from 0.4 to 0.8). We estimated that using an expert to assign exposure at the cluster-level assignment and then to review each job in non-homogeneous clusters would require ~2000 decisions per expert, in contrast to evaluating 4255 unique questionnaire patterns or 14983 individual jobs. CONCLUSIONS: This proof-of-concept shows that using cluster models as a data reduction step to identify jobs with similar response patterns prior to obtaining expert ratings has the potential to aid rule-based assessment by systematically reducing the number of exposure decisions needed. While promising, additional research is needed to quantify the actual reduction in exposure decisions and the resulting homogeneity of exposure estimates within clusters for an exposure assessment effort that obtains cluster-level expert assessments as part of the assessment process.

Estimation of the probability of exposure to machining fluids in a population-based case-control study.

We describe an approach for estimating the probability that study subjects were exposed to metalworking fluids (MWFs) in a population-based case-control study of bladder cancer. Study subject reports on the frequency of machining and use of specific MWFs (straight, soluble, and synthetic/semi-synthetic) were used to estimate exposure probability when available. Those reports also were used to develop estimates for job groups, which were then applied to jobs without MWF reports. Estimates using both cases and controls and controls only were developed. The prevalence of machining varied substantially across job groups (0.1->0.9%), with the greatest percentage of jobs that machined being reported by machinists and tool and die workers. Reports of straight and soluble MWF use were fairly consistent across job groups (generally 50-70%). Synthetic MWF use was lower (13-45%). There was little difference in reports by cases and controls vs. controls only. Approximately, 1% of the entire study population was assessed as definitely exposed to straight or soluble fluids in contrast to 0.2% definitely exposed to synthetic/semi-synthetics. A comparison between the reported use of the MWFs and U.S. production levels found high correlations (r generally >0.7). Overall, the method described here is likely to have provided a systematic and reliable ranking that better reflects the variability of exposure to three types of MWFs than approaches applied in the past. [Supplementary materials are available for this article. Go to the publisher's online edition of Journal of Occupational and Environmental Hygiene for the following free supplemental resources: a list of keywords in the occupational histories that were used to link study subjects to the metalworking fluids (MWFs) modules; recommendations from the literature on selection of MWFs based on type of machining operation, the metal being machined and decade; popular additives to MWFs; the number and proportion of controls who reported various MWF responses by job group; the number and proportion of controls assigned to the MWF types by job group and exposure category; and the distribution of cases and controls assigned various levels of probability by MWF type.].

A case-control study of occupational exposure to metalworking fluids and bladder cancer risk among men.

OBJECTIVES: Metalworking has been associated with an excess risk of bladder cancer in over 20 studies. Metalworking fluids (MWFs) are suspected as the responsible exposure, but epidemiological data are limited. We investigated this association among men in the New England Bladder Cancer Study using state-of-the-art, quantitative exposure assessment methods. METHODS: Cases (n=895) and population controls (n=1031) provided occupational histories during personal interviews. For selected jobs, exposure-oriented modules were administered to collect information on use of three MWF types: (1) straight (mineral oil, additives), (2) soluble (mineral oil, water, additives) and (3) synthetic (water, organics, additives) or semisynthetic (hybrid of soluble and synthetic). We computed ORs and 95% CIs relating bladder cancer risk to a variety of exposure metrics, adjusting for smoking and other factors. Non-metalworkers who had held jobs with possible exposure to mineral oil were analysed separately. RESULTS: Bladder cancer risk was elevated among men who reported using straight MWFs (OR=1.7, 95% CI 1.1 to 2.8); risk increased monotonically with increasing cumulative exposure (p=0.041). Use of soluble MWFs was associated with a 50% increased risk (95% CI 0.96 to 2.5). ORs were non-significantly elevated for synthetic/semisynthetic MWFs based on a small number of exposed men. Non-metalworkers holding jobs with possible exposure to mineral oil had a 40% increased risk (95% CI 1.1 to 1.8). CONCLUSIONS: Exposure to straight MWFs was associated with a significantly increased bladder cancer risk, as was employment in non-metalworking jobs with possible exposure to mineral oil. These findings strengthen prior evidence for mineral oil as a bladder carcinogen.

Developing estimates of frequency and intensity of exposure to three types of metalworking fluids in a population-based case-control study of bladder cancer.

BACKGROUND: A systematic, transparent, and data-driven approach was developed to estimate frequency and intensity of exposure to straight, soluble, and synthetic/semi-synthetic metalworking fluids (MWFs) within a case-control study of bladder cancer in New England. METHODS: We assessed frequency using individual-level information from job-specific questionnaires wherever possible, then derived and applied job group-level patterns to likely exposed jobs with less information. Intensity estimates were calculated using a statistical model developed from measurements and determinants extracted from the published literature. RESULTS: For jobs with probabilities of exposure≥0.5, median frequencies were 8-10 hr/week, depending on MWF type. Median intensities for these jobs were 2.5, 2.1, and 1.0 mg/m3 for soluble, straight, and synthetic/semi-synthetic MWFs, respectively. CONCLUSIONS: Compared to case-by-case assessment, these data-driven decision rules are transparent and reproducible and may result in less biased estimates. These rules can also aid future exposure assessments of MWFs in population-based studies.

0084†A Case-Control Study of Occupational Exposure to Metalworking Fluids and Bladder Cancer Risk among Men.

OBJECTIVES: Metalworking has been associated with bladder cancer risk in many studies. Metalworking fluids (MWFs) are suspected as the putative exposure, but epidemiologic data are limited. Based on state-of-the-art, quantitative exposure assessment, we examined MWF exposure and bladder cancer risk in the New England Bladder Cancer Study. METHOD: Male cases (n = 895) and population controls (n = 1031) provided occupational histories and information on use of each of three MWF types: (1) straight (mineral oil, additives), (2) soluble (mineral oil, water, additives), and (3) synthetic (water, organics, additives) or semi-synthetic (soluble/synthetic hybrid), in response to exposure-oriented modules administered during personal interviews. We estimated the probability, frequency, and intensity of exposure to each MWF type and, if probability exceeded 50%, cumulative exposure. Logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for smoking and other risk factors. RESULTS: Risk was increased for men reporting use of straight MWFs (OR=1.7, 95% CI=1.1-2.8), with a significant trend with increasing cumulative exposure (p = 0.024). Use of soluble MWFs conferred a 50% elevated risk (95% CI=0.96-2.5). ORs were nonsignificantly elevated for synthetic MWFs, based on small numbers. Men who were never metalworkers, but held jobs with possible exposure to mineral oil, had a 40% increased risk (95% CI=1.1-1.8). CONCLUSIONS: In the most comprehensive assessment of MWF exposure in a bladder cancer case-control study, exposure to straight MWFs significantly increased bladder cancer risk, as did employment in non-metalworking jobs with possible mineral oil exposure. Our results strengthen prior evidence for mineral oil as a bladder carcinogen.

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.

Improving the quality of industry and occupation data at a central cancer registry.

BACKGROUND: Central cancer registries are required to collect industry and occupation (I/O) information when available, but the data reported are often incomplete. METHODS: We audited the completeness of I/O data in the New Hampshire State Cancer Registry (NHSCR) database for diagnosis year 2005, and reviewed medical records for a convenience sample of 474 of these cases. We compared I/O data quality before and after a statewide registrar training session on occupationally related cancers. RESULTS: The original 2005 data contained both I/O data in 11.5% of cases, and lacked any I/O data in 74.5%. Corresponding figures for cases selected for audit were 15.2% and 77.2%, which improved to 54.2% and 11.8% after medical record review. After registrar training, 47% of reports contained both I/O data, and only 14.4% of cases lacked any I/O data. CONCLUSIONS: Statewide training to highlight the importance of I/O data is an effective method to improve I/O data quality.

Reliability of rapid reporting of cancers in New Hampshire.

OBJECTIVE: The New Hampshire State Cancer Registry (NHSCR) has a 2-phase reporting system. An abbreviated, "rapid" report of cancer diagnosis or treatment is due to the central registry within 45 days of diagnosis and a more detailed, definitive report is due within 180 days. Rapid reports are used for various research studies, but researchers who contact patients are warned that the rapid reports may contain inaccuracies. This study aimed to assess the reliability of rapid cancer reports. METHODS: For diagnosis years 2000-2004, we compared the rapid and definitive reports submitted to NHSCR. We calculated the sensitivity and positive predictive value of rapid reports; the reliability of key data items overall and for major sites; and the time between diagnosis and submission of the report. RESULTS: Rapid reports identified incident cancer cases with a sensitivity of 88.5%. The overall accuracy of key data items was high. The accuracy of primary sites identified by rapid reports was high generally but lower for ovarian and unknown primaries. A subset analysis showed that 47% of cancers were reported within 90 days of diagnosis. CONCLUSION: Rapid reports submitted to NHSCR are generally of high quality and present a useful opportunity for research investigations in New Hampshire.

Joint occupational and environmental pollution prevention strategies: a model for primary prevention.

Occupational and environmental health issues are not always considered simultaneously when attempting to reduce or eliminate hazardous materials from our environment. Methods used to decrease exposure to hazardous chemicals in the workplace often lead to increased exposure in the environment and to the community outside the workplace. Conversely, efforts to control emissions of hazardous chemicals into the environment often lead to increased exposure to the workers inside the plant. There are government regulations in place that ensure a safe work environment or a safe outside environment; however, there is little integration of both approaches when considering the public's health as a whole. This article examines some of the reasons behind this dichotomy, focusing on the regulatory and policy frameworks with respect to workplace and environment that have resulted in the inability of the Occupational Safety and Health Administration (OSHA) and the Environmental Protection Agency (EPA) to coordinate their efforts to protect public health. The components of the Pollution Prevention Act and its potential to serve as a model for integrating occupational and environmental health are discussed. Limitations regarding enforcement of pollution prevention, as well as its disconnection from the work environment are equally highlighted. The article finishes by examining the barriers to integrating the occupational and environmental health paradigms and the promotion of primary prevention in public health.