Uncertainty in the relation between exposure to magnetic fields and brain cancer due to assessment and assignment of exposure and analytical methods in dose-response modeling

Self-reported and urinary biomarker-based measures of exposure to glyphosate and mancozeb and sleep problems among smallholder farmers in Uganda

OBJECTIVE

We aim to showcase the impact of applying eight different self-reported and urinary biomarker-based exposure measures for glyphosate and mancozeb on the association with sleep problems in a study among 253 smallholder farmers in Uganda.

METHODS

The questionnaire-based exposure measures included: (1) the number of application days of any pesticide in the last 7 days (never, 1-2; >2 days) and six glyphosate and mancozeb-specific measures: (2) application status over the last 12 months (yes/no), (3) recent application status (never, last 7 days and last 12 months), (4) the number of application days last 12 months, (5) average exposure-intensity scores (EIS) and (6) EIS-weighted number of application days in last 12 months. Based on 384 repeated urinary biomarker concentrations of ethylene thiourea (ETU) and glyphosate from 84 farmers, we also estimated (7) average biomarker concentrations for all 253 farmers. Also in the 84 farmers the measured pre-work and post-work biomarker concentrations were used (8). Multivariable logistic regression models were used to assess the association between the exposure measures and selected Medical Outcomes Study Sleep Scale (MOS-SS) indices (6-item, sleep inadequacy and snoring).

RESULTS

We observed positive associations between (1) any pesticide application in the last 7 days with all three MOS-SS indices. Glyphosate application in the last 7 days (3) and mancozeb application in the last 12 months (3) were associated with the 6-item sleep problem index. The estimated average urinary glyphosate concentrations showed an exposure-response association with the 6-item sleep problem index and sleep inadequacy in the same direction as based on self-reported glyphosate application in the last 7 days. In the analysis with the subset of 84 farmers, both measured and modelled post-work urinary glyphosate concentration showed an association with snoring.

CONCLUSIONS

Self-reported, estimated average biomarker concentrations and measured urinary biomarker exposure measures of glyphosate and mancozeb showed similar exposure-response associations with sleep outcomes.

Evaluating Exposure-Response Associations for Non-Hodgkin Lymphoma with Varying Methods of Assigning Cumulative Benzene Exposure in the Shanghai Women's Health Study

Objectives

To provide insight into the contributions of exposure measurements to job exposure matrices (JEMs), we examined the robustness of an association between occupational benzene exposure and non-Hodgkin lymphoma (NHL) to varying exposure assessment methods.

Methods

NHL risk was examined in a prospective population-based cohort of 73087 women in Shanghai. A mixed-effects model that combined a benzene JEM with >60000 short-term, area benzene inspection measurements was used to derive two sets of measurement-based benzene estimates: 'job/industry-specific' estimates (our presumed best approach) were derived from the model's fixed effects (year, JEM intensity rating) and random effects (occupation, industry); 'calibrated JEM' estimates were derived using only the fixed effects. 'Uncalibrated JEM' (using the ordinal JEM ratings) and exposure duration estimates were also calculated. Cumulative exposure for each subject was calculated for each approach based on varying exposure definitions defined using the JEM's probability ratings. We examined the agreement between the cumulative metrics and evaluated changes in the benzene-NHL associations.

Results

For our primary exposure definition, the job/industry-specific estimates were moderately to highly correlated with all other approaches (Pearson correlation 0.61-0.89; Spearman correlation > 0.99). All these metrics resulted in statistically significant exposure-response associations for NHL, with negligible gain in model fit from using measurement-based estimates. Using more sensitive or specific exposure definitions resulted in elevated but non-significant associations.

Conclusions

The robust associations observed here with varying benzene assessment methods provide support for a benzene-NHL association. While incorporating exposure measurements did not improve model fit, the measurements allowed us to derive quantitative exposure-response curves.

Bias in the estimation of exposure effects with individual- or group-based exposure assessment

In this paper, we develop models of bias in estimates of exposure-disease associations for epidemiological studies that use group- and individual-based exposure assessments. In a study that uses a group-based exposure assessment, individuals are grouped according to shared attributes, such as job title or work area, and assigned an exposure score, usually the mean of some concentration measurements made on samples drawn from the group. We considered bias in the estimation of exposure effects in the context of both linear and logistic regression disease models, and the classical measurement error in the exposure model. To understand group-based exposure assessment, we introduced a quasi-Berkson error structure that can be justified with a moderate number of exposure measurements from each group. In the quasi-Berkson error structure, the true value is equal to the observed one plus error, and the error is not independent of the observed value. The bias in estimates with individual-based assessment depends on all variance components in the exposure model and is smaller when the between-group and between-subject variances are large. In group-based exposure assessment, group means can be assumed to be either fixed or random effects. Regardless of this assumption, the behavior of estimates is similar: the estimates of regression coefficients were less attenuated with a large sample size used to estimate group means, when between-subject variability was small and the spread between group means was large. However, if groups are considered to be random effects, bias is present, even with large number of measurements from each group. This does not occur when group effects are treated as fixed. We illustrate these models in analyses of the associations between exposure to magnetic fields and cancer mortality among electric utility workers and respiratory symptoms due to carbon black.

The effect of uncertainty in exposure estimation on the exposure-response relation between 1,3-butadiene and leukemia

In a follow-up study of mortality among North American synthetic rubber industry workers, cumulative exposure to 1,3-butadiene was positively associated with leukemia. Problems with historical exposure estimation, however, may have distorted the association. To evaluate the impact of potential inaccuracies in exposure estimation, we conducted uncertainty analyses of the relation between cumulative exposure to butadiene and leukemia. We created the 1,000 sets of butadiene estimates using job-exposure matrices consisting of exposure values that corresponded to randomly selected percentiles of the approximate probability distribution of plant-, work area/job group-, and year specific butadiene ppm. We then analyzed the relation between cumulative exposure to butadiene and leukemia for each of the 1,000 sets of butadiene estimates. In the uncertainty analysis, the point estimate of the RR for the first non zero exposure category (>0-<37.5 ppm-years) was most likely to be about 1.5. The rate ratio for the second exposure category (37.5-<184.7 ppm-years) was most likely to range from 1.5 to 1.8. The RR for category 3 of exposure (184.7-<425.0 ppm-years) was most likely between 2.1 and 3.0. The RR for the highest exposure category (425.0+ ppm-years) was likely to be between 2.9 and 3.7. This range off RR point estimates can best be interpreted as a probability distribution that describes our uncertainty in RR point estimates due to uncertainty in exposure estimation. After considering the complete probability distributions of butadiene exposure estimates, the exposure-response association of butadiene and leukemia was maintained. This exercise was a unique example of how uncertainty analyses can be used to investigate and support an observed measure of effect when occupational exposure estimates are employed in the absence of direct exposure measurements.

Guidelines to evaluate human observational studies for quantitative risk assessment

BACKGROUND

Careful evaluation of the quality of human observational studies (HOS) is required to assess the suitability of HOS for quantitative risk assessment (QRA). In particular, the quality of quantitative exposure assessment is a crucial aspect of HOS to be considered for QRA.

OBJECTIVE

We aimed to develop guidelines for the evaluation of HOS for QRA and to apply these guidelines to case-control and cohort studies on the relation between exposure to benzene and acute myeloid leukemia (AML).

METHODS

We developed a three-tiered framework specific for the evaluation of HOS for QRA and used it to evaluate HOS on the relation between exposure to benzene and AML.

RESULTS

The developed framework consists of 20 evaluation criteria. A specific focus of the framework was on the quality of exposure assessment applied in HOS. Seven HOS on the relation of benzene and AML were eligible for evaluation. Of these studies, five were suitable for QRA and were ranked based on the quality of the study design, conduct, and reporting on the study.

CONCLUSION

The developed guidelines facilitate a structured evaluation that is transparent in its application and harmonizes the evaluation of HOS for QRA. With the application of the guidelines, it was possible to identify studies suitable for QRA of benzene and AML and rank these studies based on their quality. Application of the guidelines in QRA will be a valuable addition to the assessment of the weight of evidence of HOS for QRA.

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 > or =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.

Occupational noise exposure and ischaemic heart disease mortality

AIMS

To investigate the hypothesis that long term exposure to excessive noise can increase the risk of ischaemic heart disease.

METHODS

A case-control design, nested within a cohort of nuclear power workers employed at two sites in England over the period 1950-98, was used. Cases were men who died from ischaemic heart disease (ICD-9: 410-414) aged 75 or under; each was matched to a surviving control of the nearest age who joined the same site at the same time. Personal noise exposure was assessed retrospectively for each man by hygienists using (1) company work histories, (2) noise survey records from 1965-98, and (3) judgements about likely use of hearing protection devices. Men were classified into four groups according to their cumulative exposure to noise, with men whose exposure at the company never exceeded 85dB(A) for at least one year being considered "unexposed". Risks were compared via odds ratios (ORs) using conditional logistic regression and adjusted for systolic and diastolic blood pressure, height, BMI, and smoking, as measured at recruitment to the company.

RESULTS

Analysis was based on 1101 case-control pairs. There was little difference between the exposure groups at recruitment. There was no evidence of increased risk at site A: the ORs for ischaemic heart disease mortality among low, medium, and high exposure categories, compared to unexposed men, being 1.04, 1.00, and 0.77. The corresponding ORs (95% CIs) at site B were 1.15 (0.81-1.65) 1.45 (1.02-2.06), and 1.37 (0.96-1.96). When the comparison was confined to men with at least five years of employment, these dropped to 1.07 (0.64-1.77), 1.33 (0.88-2.01), and 1.21 (0.82-1.79) respectively.

CONCLUSIONS

The authors did not find statistically robust evidence of increased risk but the estimates at site B are consistent with those in a major cohort study. A strength of the present study is that the validity of noise estimation at site B has been demonstrated elsewhere.

Risk estimation for carcinogens based on epidemiological data: A structured approach, illustrated by an example on chromium

It is generally recognized that human, epidemiological data, if available, are preferred as the starting point for quantitative risk analysis above the use of data from animal studies. Although methods to obtain proper risk estimates from epidemiological data are available, several impediments prevent their widespread application. These impediments include unfamiliarity with epidemiological methods and the lack of a structured and transparent approach. We described a framework to conduct quantitative cancer risk assessment based on epidemiological studies in a structured, transparent, and reproducible manner. Important features of the process include a weight-of-the-evidence approach, estimation of the optimal exposure-risk function by fitting a regression model to the epidemiological data, estimation of uncertainty introduced by potential biases and missing information in the epidemiological studies, and calculation of excess lifetime risk through a life table to take into account competing risks. Sensitivity analyses are a useful tool to obtain insight into the impact of assumptions made and the variability of the underlying data. The framework is sufficiently flexible to allow many types of data, ranging from published, sometimes incomplete data to detailed individual data, while maintaining an optimal result, i.e., a state-of-the-art risk estimate with confidence intervals, based on all available evidence of sufficient quality.

Performance of different exposure assessment approaches in a study of bitumen fume exposure and lung cancer mortality

BACKGROUND

We compared performance of different exposure assessment approaches in a cohort study of cancer risk among European asphalt workers.

METHODS

Three bitumen fume exposure indices (duration of exposure (years), average exposure (mg/m3) and cumulative exposure (mg/m3*years)) and two latency models (with and without a 15 year lag) were considered for an association between lung cancer mortality and bitumen fume.

RESULTS

There was no association between lung cancer risk and either duration or cumulative exposure. However, there was the suggestion of an increase in lung cancer risk accompanying rise in average exposure. Only models with average bitumen fume exposure (with or without lag) improved model fit, albeit to the same extent.

CONCLUSIONS

Constructing quantitative indices of exposure intensity was justified because they produced the greatest improvement in fit of models that explored possible relationship between bitumen fume exposure and lung cancer risk. The identified associations require further investigation.

Validity of empirical models of exposure in asphalt paving

AIMS

To investigate the validity of empirical models of exposure to bitumen fume and benzo(a)pyrene, developed for a historical cohort study of asphalt paving in Western Europe.

METHODS

Validity was evaluated using data from the USA, Italy, and Germany not used to develop the original models. Correlation between observed and predicted exposures was examined. Bias and precision were estimated.

RESULTS

Models were imprecise. Furthermore, predicted bitumen fume exposures tended to be lower (-70%) than concentrations found during paving in the USA. This apparent bias might be attributed to differences between Western European and USA paving practices. Evaluation of the validity of the benzo(a)pyrene exposure model revealed a similar to expected effect of re-paving and a larger than expected effect of tar use. Overall, benzo(a)pyrene models underestimated exposures by 51%.

CONCLUSIONS

Possible bias as a result of underestimation of the impact of coal tar on benzo(a)pyrene exposure levels must be explored in sensitivity analysis of the exposure-response relation. Validation of the models, albeit limited, increased our confidence in their applicability to exposure assessment in the historical cohort study of cancer risk among asphalt workers.