A practical approach to estimating the true effect of exposure despite imprecise exposure classification

Incorporating individual-level distributions of exposure error in epidemiologic analyses: an example using arsenic in drinking water and bladder cancer

PURPOSE

Epidemiologic analyses traditionally rely on point estimates of exposure for assessing risk despite exposure error. We present a strategy that produces a range of risk estimates reflecting distributions of individual-level exposure.

METHODS

Quantitative estimates of exposure and its associated error are used to create for each individual a normal distribution of exposure estimates which is then sampled using Monte Carlo simulation. After the exposure estimate is sampled, the relationship between exposure and disease is evaluated; this process is repeated 99 times generating a distribution of risk estimates and confidence intervals. This is demonstrated in a bladder cancer case-control study using individual-level distributions of exposure to arsenic in drinking water.

RESULTS

Sensitivity analyses indicate similar performance for categorical or continuous exposure estimates, and that increases in exposure error translate into a wider range of risk estimates. Bladder cancer analyses yield a wide range of possible risk estimates, allowing quantification of exposure error in the association between arsenic and bladder cancer, typically ignored in conventional analyses.

CONCLUSIONS

Incorporating distributions of individual-level exposure error results in a more nuanced depiction of epidemiologic findings. This approach can be readily adopted by epidemiologists assuming distributions of individual-level exposure.

Case-control assessment of the association between non-Hodgkin's lymphoma and occupational radiation with doses assessed using a job exposure matrix

BACKGROUND

Epidemiologic data for an association between radiation exposure and non-Hodgkin's lymphoma (NHL) have been inconclusive though the strongest evidence has been provided by studies of patients treated with radiotherapy.

METHODS

We evaluated the association between occupational radiation exposure and non-Hodgkin's lymphoma in men using a population-based case-control study with 1,056 case and 1,860 control subjects sampled from eight geographic areas in the United States. Because dosimetry data were not available, doses were estimated for individuals who reported occupational radiation exposure using a radiation job exposure matrix developed for this purpose. Conditional logistic regression was used to model the association between reported occupational radiation exposure and NHL incidence.

RESULTS

We found that most men (> 90%) did not report exposure to occupational sources of radiation. Among those who reported exposure, estimated cumulative doses were low, with an estimated mean of less than 0.02 Gray and a maximum of 0.12 Gray. The risk for NHL was not associated with ever having reported an occupational radiation exposure (OR = 0.90, 95% CI = 0.74-1.10) nor was there evidence of a dose-response relationship between risk and either the estimated cumulative doses or duration of exposure.

CONCLUSIONS

The findings in this study are consistent with results from most current research on occupational radiation and NHL risk that have found no increased risk of NHL at low levels of occupational radiation exposure. While it should be noted that exposure misclassification likely biased our results toward the null, this large population-based case-control study adds to existing evidence which suggests that there is little to no increased risk for NHL associated with exposure to low levels of radiation such as that commonly found in many occupational settings.

Mortality from respiratory cancers (including lung cancer) among workers employed in formaldehyde industries

A joint study on effects of formaldehyde exposure in industrial populations by the National Cancer Institute and the Formaldehyde Institute, Inc. (Blair et al. [1986]: J Natl Cancer Inst 76: 1071-1084; Blair and Stewart [1989]: J Occup Med 31: 881, Blair et al. [1990]: Am J Ind Med 17:683-700) reported no significant elevation in risk ratios standardized to the general population. Using the same data as Blair et al., we compared more exposed to less exposed workers to compute relative risk for respiratory and lung cancers using a multivariate, log-linear model incorporating factors for job type (hourly vs. salaried), cumulative exposure (0.1-0.5, 0.5-2, 2+ vs. < 0.1 ppm/years), length of exposure (1-5, 5-10, 10+ vs. < 1 years), and age. Models were fit for all workers, all males, all workers less than 65 years of age, and for all males less than 65 years of age. Hourly workers have a significantly elevated relative risk when compared to salaried workers. While only high levels of cumulative exposure show a significant elevation in relative lung cancer risk, trend analyses of the coefficients of a log-linear model show a significant trend of increasing risk with increasing formaldehyde exposure. The significantly elevated respiratory and lung cancer risk for workers younger than 65 may indicate a shift of respiratory cancer mortality towards younger ages among those occupationally exposed to formaldehyde.(ABSTRACT TRUNCATED AT 250 WORDS)

Comments on the Health Effects Institute-Asbestos Research (HEI-AR) report: "Asbestos in public and commercial buildings," with emphasis on risk assessment methods used

A Health Effects Institute--Asbestos Research Report calculates the risk of exposure to environmental asbestos fibers (EAF) by downward extrapolation from the mortality of workers exposed for 20 years. This extrapolation is improper because 1) relative risks of asbestos exposure very likely are not linearly progressive; 2) the composition of EAF may not be equivalent to that in mining or fabricating; 3) the same environmental asbestos concentration probably represents different exposure doses for different populations; and 4) health effects of asbestos exposure on children, seniors, patients, the institutionalized, the handicapped, and the chronically ill may not be the same as those of healthy workers. Evidence of asbestos-related disease among family members of exposed workers demonstrates that the risk observed for EAF is substantially larger than that estimated from downward extrapolation and suggests a basis for an alternative approach to estimating asbestos-related health risks. Such epidemiologic procedures are well established and ought to form the basis for detecting the health effects of EAF. It is also unclear which industry supports HEI-AR.