RESUMO
BACKGROUND: We developed an algorithm to quantitatively estimate endotoxin exposure for farmers in the Biomarkers of Exposure and Effect in Agriculture (BEEA) Study. METHODS: The algorithm combined task intensity estimates derived from published data with questionnaire responses on activity duration to estimate task-specific cumulative endotoxin exposures for 13 tasks during four time windows, ranging from "past 12 months" to "yesterday/today." We applied the algorithm to 1681 participants in Iowa and North Carolina. We examined correlations in endotoxin metrics within- and between-task. We also compared these metrics to prior day full-shift inhalable endotoxin concentrations from 32 farmers. RESULTS: The highest median task-specific cumulative exposures were observed for swine confinement, poultry confinement, and grind feed. Inter-quartile ranges showed substantial between-subject variability for most tasks. Time window-specific metrics of the same task were moderately-highly correlated. Between-task correlation was variable, with moderately-high correlations observed for similar tasks (e.g., between animal-related tasks). Prior day endotoxin concentration increased with the total metric and with task metrics for swine confinement, clean other animal facilities, and clean grain bins. SIGNIFICANCE: This study provides insight into the variability and sources of endotoxin exposure among farmers in the BEEA study and summarizes exposure estimates for future investigations in this population.
Assuntos
Poluentes Ocupacionais do Ar , Exposição Ocupacional , Humanos , Animais , Suínos , Endotoxinas/análise , Poluentes Ocupacionais do Ar/análise , Poeira/análise , Exposição Ocupacional/efeitos adversos , Exposição Ocupacional/análise , Agricultura , Algoritmos , BiomarcadoresRESUMO
BACKGROUND/OBJECTIVE: Farmers conduct numerous tasks with potential for endotoxin exposure. As a first step to characterize endotoxin exposure for farmers in the Biomarkers of Exposure and Effect in Agriculture (BEEA) Study, we used published data to estimate task-specific endotoxin concentrations. METHODS: We extracted published data on task-specific, personal, inhalable endotoxin concentrations for agricultural tasks queried in the study questionnaire. The data, usually abstracted as summary measures, were evaluated using meta-regression models that weighted each geometric mean (GM, natural-log transformed) by the inverse of its within-study variance to obtain task-specific predicted GMs. RESULTS: We extracted 90 endotoxin summary statistics from 26 studies for 9 animal-related tasks, 30 summary statistics from 6 studies for 3 crop-related tasks, and 10 summary statistics from 5 studies for 4 stored grain-related tasks. Work in poultry and swine confinement facilities, grinding feed, veterinarian services, and cleaning grain bins had predicted GMs > 1000 EU/m3 . In contrast, harvesting or hauling grain and other crop-related tasks had predicted GMs below 100 EU/m3 . SIGNIFICANCE: These task-specific endotoxin GMs demonstrated exposure variability across common agricultural tasks. These estimates will be used in conjunction with questionnaire responses on task duration to quantitatively estimate endotoxin exposure for study participants, described in a companion paper.
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Poluentes Ocupacionais do Ar , Exposição Ocupacional , Humanos , Animais , Suínos , Endotoxinas/análise , Poluentes Ocupacionais do Ar/análise , Poeira/análise , Monitoramento Ambiental , Exposição por Inalação/análise , Exposição Ocupacional/análise , Agricultura , AlgoritmosRESUMO
Few studies have evaluated the validity of self-report of work activities because of challenges in obtaining objective measures. In this study, farmers' recall of the previous day's agricultural activities was compared to activities observed by field staff during air monitoring. Recall was assessed in 32 farmers from the Biomarkers of Exposure and Effect in Agriculture Study, a subset of a prospective cohort study. The farmers participated in 56 visits that comprised air monitoring the day before an interview. The answers for 14 agricultural activities were compared to activities observed by field staff during air monitoring (median duration 380 min, range 129-486). For each task, evaluated as yes/no, overall agreement, sensitivity, specificity, and kappa were calculated. Median prevalence of the 14 activities was 8% from observation and 13% from participants (range: 2-54%). Agreement was generally good to perfect, with a median overall agreement of 95% (range: 89-100%), median sensitivity of 84% (50-100%), median specificity of 95% (88-100%), and median kappa of 0.65 (0.31-1.0). Reasons for disagreement included activities occurring when the field staff was not present (i.e., milking cows), unclear timing notes that made it difficult to determine whether the activity occurred the day of and/or day before the interview, definition issues (i.e., participant included hauling in the definition of harvesting), and difficulty in observing details of an activity (i.e., whether hay was moldy). This study provides support for accurate participant recall the day after activities.
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Agricultura , Animais , Bovinos , Humanos , Projetos Piloto , Prevalência , Estudos Prospectivos , AutorrelatoRESUMO
OBJECTIVES: Lead is a suspected carcinogen that has been inconsistently associated with kidney cancer. To clarify this relationship, we conducted an analysis of occupational lead exposure within a population-based study of kidney cancer using detailed exposure assessment methods. METHODS: Study participants (1217 cases and 1235 controls), enrolled between 2002 and 2007, provided information on their occupational histories and, for selected lead-related occupations, answered questions regarding workplace tasks, and use of protective equipment. Industrial hygienists used this information to develop several estimates of occupational lead exposure, including probability, duration and cumulative exposure. Unconditional logistic regression was used to compute ORs and 95% CIs for different exposure metrics, with unexposed subjects serving as the reference group. Analyses were also conducted stratifying on several factors, including for subjects of European ancestry only, single nucleotide polymorphisms in ALAD (rs1805313, rs1800435, rs8177796, rs2761016), a gene involved in lead toxicokinetics. RESULTS: In our study, cumulative occupational lead exposure was not associated with kidney cancer (OR 0.9, 95% CI 0.7 to 1.3 for highest quartile vs unexposed; ptrend=0.80). Other lead exposure metrics were similarly null. We observed no evidence of effect modification for the evaluated ALAD variants (subjects of European ancestry only, 662 cases and 561 controls) and most stratifying factors, although lead exposure was associated with increased risk among never smokers. CONCLUSIONS: The findings of this study do not offer clear support for an association between occupational lead exposure and kidney cancer.
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Neoplasias Renais/epidemiologia , Chumbo/efeitos adversos , Exposição Ocupacional/análise , Adulto , Idoso , Estudos de Casos e Controles , Chicago/epidemiologia , Feminino , Humanos , Masculino , Michigan/epidemiologia , Pessoa de Meia-Idade , Equipamento de Proteção Individual/estatística & dados numéricos , Polimorfismo de Nucleotídeo Único , Sintase do Porfobilinogênio/genética , Fatores de Risco , População Branca/genéticaRESUMO
OBJECTIVES: The validity of surrogate measures of retrospective occupational exposure in population-based epidemiological studies has rarely been evaluated. Using toenail samples as bioindicators of exposure, we assessed whether work tasks and expert assessments of occupational metal exposure obtained from personal interviews were associated with lead and manganese concentrations. METHODS: We selected 609 controls from a case-control study of bladder cancer in New England who had held a job for ≥1 year 8-24 months prior to toenail collection. We evaluated associations between toenail metal concentrations and five tasks extracted from occupational questionnaires (grinding, painting, soldering, welding, working near engines) using linear regression models. For 139 subjects, we also evaluated associations between the toenail concentrations and exposure estimates from three experts. RESULTS: We observed a 1.9-fold increase (95% CI 1.4 to 2.5) in toenail lead concentrations with painting and 1.4-fold increase (95% CI 1.1 to 1.7) in manganese concentrations with working around engines and handling fuel. We observed significant trends with increasing frequency of both activities. For lead, significant trends were observed with the ratings from all three experts. Their average ratings showed the strongest association, with subjects rated as possibly or probably exposed to lead having concentrations that were 2.0 and 2.5 times higher, respectively, than in unexposed subjects (ptrend <0.001). Expert estimates were only weakly associated with manganese toenail concentrations. CONCLUSIONS: Our findings support the ability of experts to identify broad contrasts in previous occupational exposure to lead. The stronger associations with task frequency and expert assessments support using refined exposure characterisation whenever possible.
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Chumbo/análise , Manganês/análise , Exposição Ocupacional/análise , Adulto , Idoso , Monitoramento Biológico/métodos , Estudos de Casos e Controles , Feminino , Humanos , Maine , Masculino , Pessoa de Meia-Idade , Unhas/química , New Hampshire , Estudos Retrospectivos , VermontRESUMO
BACKGROUND: We developed a systematic, data-driven approach to estimate metrics of occupational exposure to lead to aid in epidemiologic analyses in a case-control study of kidney cancer. METHODS: Probability of exposure to ten lead sources was assigned using decision rules developed from an extensive literature review and expert judgement. For jobs with >50% probability of exposure, we assigned source-specific frequency based on subjects' self-reported task frequencies or means of subjects' job-groups and source-specific intensity estimates of blood lead (µg/dL). RESULTS: In our study, 18.7% of employed person-years were associated with high (≥80%) probability of exposure to any lead source. The most common medium (>50%) or high probability source of lead exposure was leaded gasoline (2.5% and 11.5% of employed person-years, respectively). The median blood lead attributed to occupational exposure was 3.1 µg/dL. CONCLUSIONS: These rules can aid in future studies after population-specific adaption for geographic differences and different exposure scenarios.
Assuntos
Técnicas de Apoio para a Decisão , Neoplasias Renais/epidemiologia , Intoxicação por Chumbo/epidemiologia , Doenças Profissionais/epidemiologia , Exposição Ocupacional/análise , Adulto , Estudos de Casos e Controles , Feminino , Humanos , Neoplasias Renais/induzido quimicamente , Chumbo/sangue , Intoxicação por Chumbo/etiologia , Masculino , Pessoa de Meia-Idade , Doenças Profissionais/induzido quimicamente , ProbabilidadeRESUMO
Diesel exhaust has been associated with adverse human health effects. Farmers are often exposed to diesel exhaust; however, their diesel exposure has not been well characterized. In this descriptive study, we measured black carbon concentrations as a proxy for diesel exhaust exposure in 16 farmers over 20 sampling days during harvest in southeast Iowa. Farmers wore a personal aethalometer which measured real-time black carbon levels throughout the working day, and their activities were recorded by a field researcher. Black carbon concentrations were characterized for each farmer, and by activity, vehicle fuel type, and microenvironment. Overall, 574 discrete tasks were monitored with a median task duration of 5.5 min. Of these tasks, 39% involved the presence of a diesel vehicle. Farmers' daily black carbon geometric mean exposures ranged from 0.1-2.3 µg/m3, with a median daily geometric mean of 0.3 µg/m3. The highest black carbon concentrations were measured on farmers who used or worked near diesel vehicles (geometric mean ranged from 0.5 µg/m3 while harvesting to 4.9 µg/m3 during animal work). Higher geometric means were found for near vs. far proximity to diesel-fueled vehicles and equipment (2.9 vs. 0.3 µg/m3). Indoor, bystander proximity to diesel-operated vehicles resulted in the highest geometric mean black carbon concentrations (18 µg/m3). Use of vehicles with open cabs had higher mean black carbon concentrations than closed cabs (2.1-3.2 vs. 0.4-0.9 µg/m3). In summary, our study provided evidence that farmers were frequently exposed to black carbon associated with diesel-related activities at levels above urban ambient concentrations in their daily work during harvest.
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Poluentes Ocupacionais do Ar/análise , Carbono/análise , Fazendeiros , Exposição Ocupacional/análise , Emissões de Veículos , Idoso , Poluição do Ar em Ambientes Fechados/análise , Humanos , Iowa , Masculino , Pessoa de Meia-IdadeRESUMO
OBJECTIVES: Trichloroethylene, a chlorinated solvent widely used for metal degreasing, is classified by the International Agency for Research on Cancer as a kidney carcinogen. Other chlorinated solvents are suspected carcinogens, most notably the cleaning solvent perchloroethylene, although it is unclear whether they are associated with kidney cancer. We investigated kidney cancer associations with occupational exposure to 6 chlorinated solvents (trichloroethylene, perchloroethylene, 1,1,1-trichloroethane, carbon tetrachloride, chloroform, and methylene chloride) within a case-control study using detailed exposure assessment methods. METHODS: Cases (n=1217) and controls (n=1235) provided information on their occupational histories and, for selected occupations, on tasks involving potential exposure to chlorinated solvents through job-specific interview modules. Using this information, an industrial hygienist assessed potential exposure to each solvent. We computed ORs and 95% CIs for different exposure metrics, with unexposed participants as the referent group. RESULTS: 1,1,1-trichloroethane, carbon tetrachloride, chloroform, and methylene chloride were not associated with kidney cancer. Among jobs with high exposure intensity, high cumulative hours exposed to perchloroethylene was associated with increased risk, both overall (third tertile vs unexposed: OR 3.1, 95% CI 1.3 to 7.4) and after excluding participants with ≥50% exposure probability for trichloroethylene (OR 3.0, 95% CI 0.99 to 9.0). A non-significant association with high cumulative hours exposed to trichloroethylene was observed (OR 1.7, 95% CI 0.8 to 3.8). CONCLUSIONS: In this study, high exposure to perchloroethylene was associated with kidney cancer, independent of trichloroethylene. Additional studies are needed to further investigate this finding.
Assuntos
Hidrocarbonetos Clorados/efeitos adversos , Neoplasias Renais/induzido quimicamente , Neoplasias Renais/epidemiologia , Doenças Profissionais/induzido quimicamente , Doenças Profissionais/epidemiologia , Exposição Ocupacional/efeitos adversos , Adulto , Estudos de Casos e Controles , Feminino , Humanos , Hidrocarbonetos Clorados/análise , Entrevistas como Assunto , Modelos Logísticos , Masculino , Michigan/epidemiologia , Pessoa de Meia-Idade , Solventes , Tetracloroetileno/efeitos adversos , Tetracloroetileno/análise , Tricloroetileno/efeitos adversos , Tricloroetileno/análise , Adulto JovemRESUMO
OBJECTIVES: We evaluated predictors of differences in published occupational lead concentrations for activities disturbing material painted with or containing lead in U.S. workplaces to aid historical exposure reconstruction. METHODS: For the aforementioned tasks, 221 air and 113 blood lead summary results (1960-2010) were extracted from a previously developed database. Differences in the natural log-transformed geometric mean (GM) for year, industry, job, and other ancillary variables were evaluated in meta-regression models that weighted each summary result by its inverse variance and sample size. RESULTS: Air and blood lead GMs declined 5%/year and 6%/year, respectively, in most industries. Exposure contrast in the GMs across the nine jobs and five industries was higher based on air versus blood concentrations. For welding activities, blood lead GMs were 1.7 times higher in worst-case versus non-worst case scenarios. CONCLUSIONS: Job, industry, and time-specific exposure differences were identified; other determinants were too sparse or collinear to characterize. Am. J. Ind. Med. 60:189-197, 2017. © 2017 Wiley Periodicals, Inc.
Assuntos
Chumbo/análise , Exposição Ocupacional/análise , Pintura , Poluentes Ocupacionais do Ar/análise , Bases de Dados Factuais , Humanos , Ocupações/estatística & dados numéricos , Estados UnidosRESUMO
PURPOSE: Tobacco smoking and occupational exposures are the leading risk factors for developing urothelial bladder carcinoma (UBC), yet little is known about the contribution of these two factors to risk of UBC recurrence. We evaluated whether smoking status and usual adult occupation are associated with time to UBC recurrence for 406 patients with muscle-invasive bladder cancer submitted to The Cancer Genome Atlas (TCGA) project. METHODS: Kaplan-Meier and Cox proportional hazard methods were used to assess the association between smoking status, employment in a high-risk occupation for bladder cancer, occupational diesel exhaust exposure, and 2010 Standard Occupational Classification group and time to UBC recurrence. RESULTS: Data on time to recurrence were available for 358 patients over a median follow-up time of 15 months. Of these, 133 (37.2%) experienced a recurrence. Current smokers who smoked for more than 40 pack-years had an increased risk of recurrence compared to never smokers (HR 2.1, 95% CI 1.1, 4.1). Additionally, employment in a high-risk occupation was associated with a shorter time to recurrence (log-rank p = 0.005). We found an increased risk of recurrence for those employed in occupations with probable diesel exhaust exposure (HR 1.8, 95% CI 1.1, 3.0) and for those employed in production occupations (HR 2.0, 95% CI 1.1, 3.6). CONCLUSIONS: These findings suggest smoking status impacts risk of UBC recurrence, although several previous studies provided equivocal evidence regarding this association. In addition to the known causal relationship between occupational exposure and bladder cancer risk, our study suggests that occupation may also be related to increased risk of recurrence.
Assuntos
Recidiva Local de Neoplasia/epidemiologia , Exposição Ocupacional/estatística & dados numéricos , Ocupações/estatística & dados numéricos , Fumar/epidemiologia , Neoplasias da Bexiga Urinária/epidemiologia , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Recidiva Local de Neoplasia/genética , Recidiva Local de Neoplasia/patologia , Fatores de Risco , Fumar/efeitos adversos , Fumar/genética , Fumar/patologia , Estados Unidos/epidemiologia , Neoplasias da Bexiga Urinária/genética , Neoplasias da Bexiga Urinária/patologiaRESUMO
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.
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Poluentes Ocupacionais do Ar/análise , Monitoramento Ambiental/métodos , Modelos Teóricos , Exposição Ocupacional/análise , Emissões de Veículos/análise , Estudos de Casos e Controles , Técnicas de Apoio para a Decisão , Humanos , Modelos Logísticos , Reprodutibilidade dos Testes , EspanhaRESUMO
OBJECTIVE: In community-based epidemiological studies, job- and industry-specific 'modules' are often used to systematically obtain details about the subject's work tasks. The module assignment is often made by the interviewer, who may have insufficient occupational hygiene knowledge to assign the correct module. We evaluated, in the context of a case-control study of lymphoid neoplasms in Asia ('AsiaLymph'), the performance of an algorithm that provided automatic, real-time module assignment during a computer-assisted personal interview. METHODS: AsiaLymph's occupational component began with a lifetime occupational history questionnaire with free-text responses and three solvent exposure screening questions. To assign each job to one of 23 study-specific modules, an algorithm automatically searched the free-text responses to the questions 'job title' and 'product made or services provided by employer' using a list of module-specific keywords, comprising over 5800 keywords in English, Traditional and Simplified Chinese. Hierarchical decision rules were used when the keyword match triggered multiple modules. If no keyword match was identified, a generic solvent module was assigned if the subject responded 'yes' to any of the three solvent screening questions. If these question responses were all 'no', a work location module was assigned, which redirected the subject to the farming, teaching, health professional, solvent, or industry solvent modules or ended the questions for that job, depending on the location response. We conducted a reliability assessment that compared the algorithm-assigned modules to consensus module assignments made by two industrial hygienists for a subset of 1251 (of 11409) jobs selected using a stratified random selection procedure using module-specific strata. Discordant assignments between the algorithm and consensus assignments (483 jobs) were qualitatively reviewed by the hygienists to evaluate the potential information lost from missed questions with using the algorithm-assigned module (none, low, medium, high). RESULTS: The most frequently assigned modules were the work location (33%), solvent (20%), farming and food industry (19%), and dry cleaning and textile industry (6.4%) modules. In the reliability subset, the algorithm assignment had an exact match to the expert consensus-assigned module for 722 (57.7%) of the 1251 jobs. Overall, adjusted for the proportion of jobs in each stratum, we estimated that 86% of the algorithm-assigned modules would result in no information loss, 2% would have low information loss, and 12% would have medium to high information loss. Medium to high information loss occurred for <10% of the jobs assigned the generic solvent module and for 21, 32, and 31% of the jobs assigned the work location module with location responses of 'someplace else', 'factory', and 'don't know', respectively. Other work location responses had ≤8% with medium to high information loss because of redirections to other modules. Medium to high information loss occurred more frequently when a job description matched with multiple keywords pointing to different modules (29-69%, depending on the triggered assignment rule). CONCLUSIONS: These evaluations demonstrated that automatically assigned modules can reliably reproduce an expert's module assignment without the direct involvement of an industrial hygienist or interviewer. The feasibility of adapting this framework to other studies will be language- and exposure-specific.
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Descrição de Cargo , Exposição Ocupacional/análise , Ocupações/classificação , Software , Algoritmos , Ásia , Estudos de Casos e Controles , Estudos Epidemiológicos , Humanos , Reprodutibilidade dos Testes , Fatores de Risco , Solventes/efeitos adversos , Inquéritos e QuestionáriosRESUMO
Assessment of retrospective exposures based on expert judgment in case-control studies is usually of unknown validity because of the difficulty in finding gold standards for comparison. We investigated the relationship between expert-assigned retrospective occupational polychlorinated biphenyl (PCB) exposure estimates and serum PCB concentrations. Analyses were conducted on a subset of cases (n = 94) and controls (n = 96) in the multi-center National Cancer Institute, Surveillance, Epidemiology, and End Results Case-Control Study of non-Hodgkin lymphoma. Based on the subjects' lifetime work histories, an industrial hygienist assigned each job a probability of PCB exposure [<5% (unexposed), 5-<50% (possibly exposed), ≥50% (probably exposed)]. Ordinary least squares regression was used to investigate associations between the probability rating and log-transformed lipid-adjusted serum levels of 14 PCB congeners and total PCBs (ΓPCBs). Compared to unexposed participants (n = 163), those with a probably exposed job (n = 7) had serum levels that were 87% higher for ΓPCBs (95% confidence interval: 1.33-2.62) and 38% of serum level variability was explained by the probability rating. Statistically significant associations between probability ratings and serum levels for 12 of 14 individual congeners were also observed. In summary, the observed contrast in PCB serum levels by probability rating provides support for the occupational PCB exposure assessment.
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Monitoramento Ambiental/métodos , Linfoma não Hodgkin/sangue , Exposição Ocupacional/análise , Bifenilos Policlorados/sangue , Adulto , Idoso , Estudos de Casos e Controles , Feminino , Humanos , Linfoma não Hodgkin/induzido quimicamente , Masculino , Pessoa de Meia-Idade , Exposição Ocupacional/efeitos adversos , Saúde Ocupacional , Bifenilos Policlorados/toxicidade , Estudos RetrospectivosRESUMO
PURPOSE: Trichloroethylene (TCE) is a carcinogen that has been linked to kidney cancer and possibly other cancer sites including non-Hodgkin lymphoma. Its use in China has increased since the early 1990s with China's growing metal, electronic, and telecommunications industries. We examined historical occupational TCE air concentration patterns in a database of TCE inspection measurements collected in Shanghai, China to identify temporal trends and broad contrasts among occupations and industries. METHODS: Using a database of 932 short-term, area TCE air inspection measurements collected in Shanghai worksites from 1968 through 2000 (median year 1986), we developed mixed-effects models to evaluate job-, industry-, and time-specific TCE air concentrations. RESULTS: Models of TCE air concentrations from Shanghai work sites predicted that exposures decreased 5-10% per year between 1968 and 2000. Measurements collected near launderers and dry cleaners had the highest predicted geometric means (GM for 1986 = 150-190 mg m(-3)). The majority (53%) of the measurements were collected in metal treatment jobs. In a model restricted to measurements in metal treatment jobs, predicted GMs for 1986 varied 35-fold across industries, from 11 mg m(-3) in 'other metal products/repair' industries to 390 mg m(-3) in 'ships/aircrafts' industries. CONCLUSIONS: TCE workplace air concentrations appeared to have dropped over time in Shanghai, China between 1968 and 2000. Understanding differences in TCE concentrations across time, occupations, and industries may assist future epidemiologic studies in China.
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Poluentes Ocupacionais do Ar/história , Tricloroetileno/história , Local de Trabalho/história , Poluentes Ocupacionais do Ar/análise , Carcinógenos/análise , Carcinógenos/história , China , Bases de Dados Factuais , Monitoramento Ambiental/história , Monitoramento Ambiental/métodos , História do Século XX , Humanos , Metais/análise , Metais/história , Modelos Estatísticos , Exposição Ocupacional , Solventes/análise , Solventes/história , Fatores de Tempo , Tricloroetileno/análiseRESUMO
BACKGROUND: Retrospective exposure assessment of occupational lead exposure in population-based studies requires historical exposure information from many occupations and industries. METHODS: We reviewed published US exposure monitoring studies to identify lead measurement data. We developed an occupational lead exposure database from the 175 identified papers containing 1,111 sets of lead concentration summary statistics (21% area air, 47% personal air, 32% blood). We also extracted ancillary exposure-related information, including job, industry, task/location, year collected, sampling strategy, control measures in place, and sampling and analytical methods. RESULTS: The measurements were published between 1940 and 2010 and represented 27 2-digit standardized industry classification codes. The majority of the measurements were related to lead-based paint work, joining or cutting metal using heat, primary and secondary metal manufacturing, and lead acid battery manufacturing. CONCLUSIONS: This database can be used in future statistical analyses to characterize differences in lead exposure across time, jobs, and industries.
Assuntos
Indústrias/estatística & dados numéricos , Chumbo/análise , Exposição Ocupacional/estatística & dados numéricos , Ocupações/estatística & dados numéricos , Local de Trabalho/estatística & dados numéricos , Bases de Dados Factuais , Humanos , Pintura/análise , Estudos Retrospectivos , Estados UnidosRESUMO
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 12â 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.
Assuntos
Indústrias , Exposição Ocupacional/análise , Ocupações , Fatores Sexuais , Trabalho , Adulto , Idoso , Estudos de Casos e Controles , Distribuição de Qui-Quadrado , Feminino , Identidade de Gênero , Setor de Assistência à Saúde , Zeladoria , Humanos , Masculino , Indústria Manufatureira , Pessoa de Meia-Idade , Estatísticas não Paramétricas , Inquéritos e Questionários , Adulto JovemRESUMO
OBJECTIVES: Lifetime occupational history (OH) questionnaires often use open-ended questions to capture detailed information about study participants' jobs. Exposure assessors use this information, along with responses to job- and industry-specific questionnaires, to assign exposure estimates on a job-by-job basis. An alternative approach is to use information from the OH responses and the job- and industry-specific questionnaires to develop programmable decision rules for assigning exposures. As a first step in this process, we developed a systematic approach to extract the free-text OH responses and convert them into standardized variables that represented exposure scenarios. METHODS: Our study population comprised 2408 subjects, reporting 11991 jobs, from a case-control study of renal cell carcinoma. Each subject completed a lifetime OH questionnaire that included verbatim responses, for each job, to open-ended questions including job title, main tasks and activities (task), tools and equipment used (tools), and chemicals and materials handled (chemicals). Based on a review of the literature, we identified exposure scenarios (occupations, industries, tasks/tools/chemicals) expected to involve possible exposure to chlorinated solvents, trichloroethylene (TCE) in particular, lead, and cadmium. We then used a SAS macro to review the information reported by study participants to identify jobs associated with each exposure scenario; this was done using previously coded standardized occupation and industry classification codes, and a priori lists of associated key words and phrases related to possibly exposed tasks, tools, and chemicals. Exposure variables representing the occupation, industry, and task/tool/chemicals exposure scenarios were added to the work history records of the study respondents. Our identification of possibly TCE-exposed scenarios in the OH responses was compared to an expert's independently assigned probability ratings to evaluate whether we missed identifying possibly exposed jobs. RESULTS: Our process added exposure variables for 52 occupation groups, 43 industry groups, and 46 task/tool/chemical scenarios to the data set of OH responses. Across all four agents, we identified possibly exposed task/tool/chemical exposure scenarios in 44-51% of the jobs in possibly exposed occupations. Possibly exposed task/tool/chemical exposure scenarios were found in a nontrivial 9-14% of the jobs not in possibly exposed occupations, suggesting that our process identified important information that would not be captured using occupation alone. Our extraction process was sensitive: for jobs where our extraction of OH responses identified no exposure scenarios and for which the sole source of information was the OH responses, only 0.1% were assessed as possibly exposed to TCE by the expert. CONCLUSIONS: Our systematic extraction of OH information found useful information in the task/chemicals/tools responses that was relatively easy to extract and that was not available from the occupational or industry information. The extracted variables can be used as inputs in the development of decision rules, especially for jobs where no additional information, such as job- and industry-specific questionnaires, is available.
Assuntos
Coleta de Dados/métodos , Indústrias/estatística & dados numéricos , Metais/toxicidade , Exposição Ocupacional/análise , Ocupações/estatística & dados numéricos , Solventes/toxicidade , Adolescente , Adulto , Carcinoma de Células Renais , Estudos de Casos e Controles , Feminino , Humanos , Neoplasias Renais , Masculino , Pessoa de Meia-Idade , Ocupações/classificação , Inquéritos e Questionários , Fatores de Tempo , Adulto JovemRESUMO
OBJECTIVES: The published literature provides useful exposure measurements that can aid retrospective exposure assessment efforts, but the analysis of this data is challenging as it is usually reported as means, ranges, and measures of variability. We used mixed-effects meta-analysis regression models, which are commonly used to summarize health risks from multiple studies, to predict temporal trends of blood and air lead concentrations in multiple US industries from the published data while accounting for within- and between-study variability in exposure. METHODS: We extracted the geometric mean (GM), geometric standard deviation (GSD), and number of measurements from journal articles reporting blood and personal air measurements from US worksites. When not reported, we derived the GM and GSD from other summary measures. Only industries with measurements in ≥2 time points and spanning ≥10 years were included in our analyses. Meta-regression models were developed separately for each industry and sample type. Each model used the log-transformed GM as the dependent variable and calendar year as the independent variable. It also incorporated a random intercept that weighted each study by a combination of the between- and within-study variances. The within-study variances were calculated as the squared log-transformed GSD divided by the number of measurements. Maximum likelihood estimation was used to obtain the regression parameters and between-study variances. RESULTS: The blood measurement models predicted statistically significant declining trends of 2-11% per year in 8 of the 13 industries. The air measurement models predicted a statistically significant declining trend (3% per year) in only one of the seven industries; an increasing trend (7% per year) was also observed for one industry. Of the five industries that met our inclusion criteria for both air and blood, the exposure declines per year tended to be slightly greater based on blood measurements than on air measurements. CONCLUSIONS: Meta-analysis provides a useful tool for synthesizing occupational exposure data to examine exposure trends that can aid future retrospective exposure assessment. Data remained too sparse to account for other exposure predictors, such as job category or sampling strategy, but this limitation may be overcome by using additional data sources.
Assuntos
Monitoramento Ambiental/métodos , Chumbo/análise , Exposição Ocupacional/análise , Poluentes Ocupacionais do Ar/análise , Humanos , Indústrias/estatística & dados numéricos , Indústrias/tendências , Chumbo/sangue , Funções Verossimilhança , Modelos Teóricos , Valor Preditivo dos Testes , Análise de RegressãoRESUMO
Polychlorinated biphenyls (PCBs), banned in the United Sates in the late 1970s, are still found in indoor and outdoor environments. Little is known about the determinants of PCB levels in homes. We measured concentrations of five PCB congeners (105, 138, 153, 170, and 180) in carpet dust collected between 1998 and 2000 from 1187 homes in four sites: Detroit, Iowa, Los Angeles, and Seattle. Home characteristics, occupational history, and demographic information were obtained by interview. We used a geographic information system to geocode addresses and determine distances to the nearest major road, freight route, and railroad; percentage of developed land; number of industrial facilities within 2 km of residences; and population density. Ordinal logistic regression was used to estimate the associations between the covariates of interest and the odds of PCB detection in each site separately. Total PCB levels [all congeners < maximum practical quantitation limit (MPQL) vs at least one congener ≥ MPQL to < median concentration vs at least one congener > median concentration] were positively associated with either percentage of developed land [odds ratio (OR) range 1.01-1.04 for each percentage increase] or population density (OR 1.08 for every 1000/mi(2)) in each site. The number of industrial facilities within 2 km of a home was associated with PCB concentrations; however, facility type and direction of the association varied by site. Our findings suggest that outdoor sources of PCBs may be significant determinants of indoor concentrations.
Assuntos
Poluição do Ar em Ambientes Fechados/análise , Poeira/análise , Poluentes Ambientais/análise , Pisos e Cobertura de Pisos , Bifenilos Policlorados/análise , Adulto , Idoso , Estudos de Casos e Controles , Monitoramento Ambiental , Feminino , Habitação , Humanos , Linfoma não Hodgkin/epidemiologia , Masculino , Pessoa de Meia-Idade , Exposição Ocupacional/análise , Estados Unidos/epidemiologia , Adulto JovemRESUMO
OBJECTIVES: Algorithm-based exposure assessments based on patterns in questionnaire responses and professional judgment can readily apply transparent exposure decision rules to thousands of jobs quickly. However, we need to better understand how algorithms compare to a one-by-one job review by an exposure assessor. We compared algorithm-based estimates of diesel exhaust exposure to those of three independent raters within the New England Bladder Cancer Study, a population-based case-control study, and identified conditions under which disparities occurred in the assessments of the algorithm and the raters. METHODS: Occupational diesel exhaust exposure was assessed previously using an algorithm and a single rater for all 14 983 jobs reported by 2631 study participants during personal interviews conducted from 2001 to 2004. Two additional raters independently assessed a random subset of 324 jobs that were selected based on strata defined by the cross-tabulations of the algorithm and the first rater's probability assessments for each job, oversampling their disagreements. The algorithm and each rater assessed the probability, intensity and frequency of occupational diesel exhaust exposure, as well as a confidence rating for each metric. Agreement among the raters, their aggregate rating (average of the three raters' ratings) and the algorithm were evaluated using proportion of agreement, kappa and weighted kappa (κw). Agreement analyses on the subset used inverse probability weighting to extrapolate the subset to estimate agreement for all jobs. Classification and Regression Tree (CART) models were used to identify patterns in questionnaire responses that predicted disparities in exposure status (i.e., unexposed versus exposed) between the first rater and the algorithm-based estimates. RESULTS: For the probability, intensity and frequency exposure metrics, moderate to moderately high agreement was observed among raters (κw = 0.50-0.76) and between the algorithm and the individual raters (κw = 0.58-0.81). For these metrics, the algorithm estimates had consistently higher agreement with the aggregate rating (κw = 0.82) than with the individual raters. For all metrics, the agreement between the algorithm and the aggregate ratings was highest for the unexposed category (90-93%) and was poor to moderate for the exposed categories (9-64%). Lower agreement was observed for jobs with a start year <1965 versus ≥1965. For the confidence metrics, the agreement was poor to moderate among raters (κw = 0.17-0.45) and between the algorithm and the individual raters (κw = 0.24-0.61). CART models identified patterns in the questionnaire responses that predicted a fair-to-moderate (33-89%) proportion of the disagreements between the raters' and the algorithm estimates. DISCUSSION: The agreement between any two raters was similar to the agreement between an algorithm-based approach and individual raters, providing additional support for using the more efficient and transparent algorithm-based approach. CART models identified some patterns in disagreements between the first rater and the algorithm. Given the absence of a gold standard for estimating exposure, these patterns can be reviewed by a team of exposure assessors to determine whether the algorithm should be revised for future studies.