Effects of measurement errors on estimates of exposure-response relationships

Individual exposure to particulate air pollution and its relevance to thresholds for health effects: a study of traffic wardens

OBJECTIVE

To investigate the differences between measurements of personal exposure to particulate air pollution and static area measurements in a group of people working close to traffic and to determine whether such differences might obscure any threshold for health effects in epidemiological studies.

METHODS

Personal air sampling was carried out on two groups of eight traffic wardens for four days on two consecutive weeks in November 1994. These measurements were compared with standard environmental static sampling data that were obtained for the same period. A simulation with log normal distributions of personal exposures was produced, and an arbitrary risk calculated for each exposure, assuming a threshold of 50 micrograms/m3, and an exposure-response curve was calculated.

RESULTS

The median concentration for personal samplers in week 1 was 123 micrograms/m3 and 41 micrograms/m3 in week 2. Corresponding area concentrations were 10 micrograms/m3 and 7.5 micrograms/m3. The differences between the personal and area results were significant, as were the differences for personal sampling between weeks 1 and 2. The simulation showed that the variation in individual exposures around an area sampler obscured the threshold.

CONCLUSIONS

Area sampling data may be of limited value in the investigation of the biological effects of exposure to pollution and their use may result in real thresholds being obscured. Personal exposure assessment may be crucial in determination of the health effects attributable to different concentrations of air pollutants.

Epidemiology and quantitative risk assessment: a bridge from science to policy

Quantitative risk assessment provides formalized scientific input to regulatory agencies that set occupational and environmental standards for potentially toxic exposures. Current practice relies heavily on statistical extrapolation from high-dose animal studies. Human data obviate the need for interspecies extrapolation and reduce the range of high-to-low dose extrapolation. This paper proposes a framework for classifying individual epidemiologic studies as to their adequacy for use in dose-response extrapolation. The framework considers five criteria: (1) a stable positive association with an adverse health outcome; (2) high overall study quality; (3) no substantial confounding; (4) quantitative exposure assessment for individuals; (5) evidence of a dose-response relationship. With these criteria, studies can be categorized as (1) suitable to serve as a basis for extrapolation; (2) inadequate to be the basis for direct extrapolation but appropriate to use for evaluating the plausibility of animal-derived risk estimates; or (3) useful only for hazard identification, not for dose-response assessment. Methods for using studies in the first two categories are briefly described. The emphasis is not on establishing rigid rules, but rather on ensuring a consistent, reliable process that makes optimum use of available data.

Use of human data in quantitative risk assessment of carcinogens: impact on epidemiologic practice and the regulatory process

Epidemiologic data are increasingly being used to assess cancer risk from chemicals as their value is recognized and as more and better studies become available. Weight-of-evidence approaches are now available for classifying the experimental and epidemiological evidence regarding human carcinogenicity. When the human data are extensive and of good quality, they should be given substantial weight in assessing risk. Both the positive and the negative epidemiologic data should be used in a quantitative risk assessment (QRA), because only then can an unbiased risk assessment be derived. Good-quality epidemiological studies are those with sound methodology, lack of bias, long enough follow-up times to observe a carcinogenic response, adequate exposure information, and dose-response information. Before a lack of carcinogenicity can be inferred, it is essential that the exposures be of substantial duration and intensity, and that the number of exposed persons be reasonably large. Epidemiologists need to give more attention to exposure assessment, because lack of quantitative exposure information is often the limiting factor that prevents the use of epidemiologic data in QRA. Development of methods to estimate historical workplace exposure intensities from surrogate industrial hygiene variables should receive high research priority, since they have the potential to increase the usefulness in QRA of many epidemiologic studies that have limited exposure information. Several frequently used surrogates for exposure measurements have limitations or pitfalls in their use. In particular, the use of "ever/never" exposed has a large potential to produce falsely negative results by means of a "dilution" effect, especially in the common case where the exposure distribution is skewed. Duration of exposure (rather than duration x intensity) may also give misleading results. There is little information to suggest that synergistic exposures to multiple toxicants in an industrial environment are likely to invalidate QRAs, probably because few studies have identified a group of workers with major workplace exposures to multiple carcinogens that cause the same type of cancer. Most of the interactive effects which have been identified to date are between smoking and some occupational carcinogen, so this possibility needs careful evaluation for smoking-related diseases. It is important to evaluate dose-response gradients in a QRA to obtain maximum precision and accuracy in the resulting risk coefficient. The analysis should take into account an appropriate cancer induction period. Various methods to account for cancer induction times are compared; those that incorporate a lag period or model the induction-time distribution are superior to other methods.(ABSTRACT TRUNCATED AT 400 WORDS)