Recent advances in research on radiofrequency fields and health

Since the Royal Society of Canada report on potential health risks of radiofrequency (RF) fields from wireless telecommunications in the spring of 1999, there have been several newly published reports on risks associated with the use of mobile phones. This article provides a summary of scientific research on the potential health effects of radiofrequency fields that has been reported since the original Royal Society report was published. This update also discusses several earlier results not included in the original report.

Characterization of uncertainty and variability in residential radon cancer risks

Radon, a naturally occurring gas found at some level in most homes, is an established risk factor for human lung cancer. The U.S. National Research Council has recently completed a comprehensive evaluation of the health risks of residential exposure to radon and developed models for projecting radon lung cancer risks to the general population. This analysis suggests that radon may play a role in the etiology of 10-15% of all lung cancer cases in the United States, although these estimates are subject to considerable uncertainty. In this article, we present a detailed analysis of uncertainty and variability in estimates of lung cancer risk due to residential exposure to radon. We use a general framework for the analysis of uncertainty and variability that we developed previously. Specifically, we focus on estimates of the age-specific excess relative risk (ERR) and lifetime relative risk (LRR), both of which vary substantially among individuals. We also consider estimates of the population attributable risk (PAR), which reflects the proportion of the lung cancer burden attributable to radon. Variability in the ERR and LRR is largely determined by variability in residential exposure levels and in the dosimetric K-factor used to extrapolate from occupational to environmental settings. Uncertainty in the ERR and LRR is due to uncertainty in the model parameters, notably those reflecting the carcinogenic potency of radon and the modifying effect of attained age. Uncertainty in the PAR is determined by uncertainty about the values of the parameters in the risk models used to estimate the PAR. Uncertainty in radon levels in homes and the dosimetric K-factor contribute comparatively little to uncertainty in the PAR. These results suggest that reduction in uncertainty about the PAR for radon induced lung cancer can only be achieved if more reliable risk projection models can be developed.

Estimates of the proportions of carcinogens and anticarcinogens in bioassays conducted by the U.S. National Toxicology Program. Application of a new meta-analytic approach

A meta-analysis was performed in order to estimate the proportion of liver carcinogens, the proportion of chemicals carcinogenic at any site, and the corresponding proportion of anticarcinogens among chemicals tested in 397 long-term cancer bioassays conducted by the U.S. National Toxicology Program (NTP). Although the estimator used was negatively biased, the study provided persuasive evidence for a larger proportion of liver carcinogens (0.43, 90% CI: 0.35, 0.51) than was identified by the NTP (0.28). A larger proportion of chemicals carcinogenic at any site was also estimated (0.59, 90% CI: 0.49, 0.69) than was identified by the NTP (0.51), although this excess was not statistically significant. A larger proportion of anticarcinogens (0.66) was estimated than carcinogens (0.59). Despite the negative bias, it was estimated that 85% of the chemicals were either carcinogenic or anticarcinogenic at some site in some sex-species group. This suggests that most chemicals tested at high enough doses will cause some sort of perturbation in tumor rates.

Evaluation of regression calibration and SIMEX methods in logistic regression when one of the predictors is subject to additive measurement error

BACKGROUND

This paper presents an evaluation of two methods of measurement error adjustment based on recently-developed computer routines (RCAL and SIMEX) under logistic regression models, when one of the two predictors is subject to additive measurement error or Berkson error.

METHODS

Computer simulations were used to generate data under a variety of conditions and the methods compared in terms of bias, mean squared error and confidence interval coverage of the regression estimates.

RESULTS

Based on our investigations, RCAL was shown to perform very well in all situations considered, except in the presence of Berkson error when the predictor variables were highly correlated.

CONCLUSIONS

Since measurement error can lead to misleading inference, it is important to adjust for measurement error in the application of logistic regression. Until better measurement error adjustment methods become available, we recommend RCAL on the basis of our simulation results.

Increased effects of smoking and obesity on asthma among female Canadians: the National Population Health Survey, 1994-1995

To assess smoking, obesity, and other risk factors for asthma, the authors examined 17,605 subjects aged 12 years or more who participated in the National Population Health Survey in 1994-1995. Asthma was considered present if an affirmative response was given to the question, "Do you have asthma diagnosed by a health professional?" The authors used analytic weights incorporating a design effect to take the complex survey design into account. The prevalence of asthma was 10.4% for males and 11.2% for females aged 12-24 years. Among the subjects aged 25 years or more, the prevalence varied from 4.1% to 5.8% for men and from 4.9% to 6.4% for women. Female smokers demonstrated a 1.7-fold increase in the prevalence of asthma compared with female nonsmokers, with the smoking effect more pronounced among female children and young adults. In contrast, there was no significant relation between smoking and asthma in males. The prevalence of asthma increased with increasing body mass index in females, but not in males. Immigrant status, history of allergy, and household income were significant predictors for both genders. Low household income was associated with a higher prevalence of asthma in men and women.

Methods for detecting and estimating population threshold concentrations for air pollution-related mortality with exposure measurement error

The association between daily fluctuations in ambient particulate matter and daily variations in nonaccidental mortality have been extensively investigated. Although it is now widely recognized that such an association exists, the form of the concentration-response model is still in question. Linear, no threshold and linear threshold models have been most commonly examined. In this paper we considered methods to detect and estimate threshold concentrations using time series data of daily mortality rates and air pollution concentrations. Because exposure is measured with error, we also considered the influence of measurement error in distinguishing between these two completing model specifications. The methods were illustrated on a 15-year daily time series of nonaccidental mortality and particulate air pollution data in Toronto, Canada. Nonparametric smoothed representations of the association between mortality and air pollution were adequate to graphically distinguish between these two forms. Weighted nonlinear regression methods for relative risk models were adequate to give nearly unbiased estimates of threshold concentrations even under conditions of extreme exposure measurement error. The uncertainty in the threshold estimates increased with the degree of exposure error. Regression models incorporating threshold concentrations could be clearly distinguished from linear relative risk models in the presence of exposure measurement error. The assumption of a linear model given that a threshold model was the correct form usually resulted in overestimates in the number of averted premature deaths, except for low threshold concentrations and large measurement error.

A unified approach to risk assessment for cancer and noncancer endpoints based on benchmark doses and uncertainty/safety factors

A fundamental goal of toxicology is to determine safe levels of human exposure to toxic substances. In the absence of information to establish dose-response relationships at low exposure levels generally experienced by humans, high-dose to low-dose linear extrapolation is generally used for estimating carcinogenic risks and the no-observed-adverse-effect-level divided by uncertainty (safety) factors is widely used for establishing human exposure guidelines for noncancer effects. The basis and impact of this dichotomy is examined and questioned. It is proposed that a unified approach be adopted for establishing human exposure guidelines for both cancer and noncancer endpoints. It is suggested that a lower confidence limit on the dose estimated to produce an excess incidence of adverse health effects in 10% of the individuals in a human study or 10% of the animals in laboratory experiments be used as a point-of-departure. This dose would be divided by appropriate uncertainty factors to establish human exposure guidelines. For severe irreversible adverse health effects we suggest a total default uncertainty factor (divisor) for animal data on the order of 10,000, which is comparable to current guidelines. For reversible biological effects a smaller default uncertainty factor on the order of 1000 may be employed. This is comparable to the divisor often used currently when the point-of-departure is the lowest-observed-adverse-effect-level. It is asserted that the toxicological information generally available does not warrant numerical estimates of risk at low levels of human exposure. Rather, we support a unified approach for all adverse health effects of dividing a benchmark dose by appropriate uncertainty factors to establish guidelines for human exposures to toxic substances.

Estimates of the proportion of chemicals that were carcinogenic or anticarcinogenic in bioassays conducted by the National Toxicology Program

Estimates were made of the proportion of chemicals that were carcinogenic, anticarcinogenic, or either in 397 long-term bioassays conducted by the National Toxicology Program (NTP). The estimates were obtained from the global pattern of p-values obtained from statistical tests applied to individual experiments. These tests accounted for multiple comparisons using a randomization procedure and were found to operate at the correct level of significance. Representative estimates of the proportion of carcinogens [with 90% confidence intervals (CI)] compared to the NTP estimates were as follows: male mice, 0.32 (CI, 0.19-0.44), NTP = 0.29; female mice, 0. 28 (CI, 0.15-0.41), NTP = 0.34; male rats, 0.35 (CI, 0.23-0.47), NTP = 0.36; female rats, 0.34 (CI, 0.21-0.46), NTP = 0.28; all sexes and species, 0.59 (CI, 0.49-0.69), NTP = 0.51. Representative estimates of the proportion of anticarcinogens were as follows: male mice, 0. 34; female mice, 0.27; male rats, 0.40; female rats, 0.44; all sexes and species, 0.66. Thus, there was as much or more evidence in this study for anticarcinogenesis as carcinogenesis. Even though the estimators used were negatively biased, it was estimated that 85% of the chemicals were either carcinogenic or anticarcinogenic at some site in some sex-species group. This suggests that most chemicals given at high enough doses will cause some sort of perturbation in tumor rates.

Two stage model for carcinogenesis: number and size distributions of premalignant clones in longitudinal studies

The two stage clonal expansion model of carcinogenesis provides a convenient biologically based framework for the description of toxicologic and epidemiologic data on carcinogenesis. Under this model, a cancer cell is generated following the occurrence of two critical mutations in a single stem cell. Initiated cells that have sustained the first mutation undergo a stochastic birth-death process resulting in clonal expansion of the initiated cell population. In this article, we consider the analysis of longitudinal data on the number and size of premalignant clones, formed by clonal expansion of initiated cells. In particular, the joint distribution of the number of premalignant clones observed at different points in time in the same subject is derived. The application of these results in the statistical analysis of longitudinal data on the number and size of premalignant clones observed in initiation-promotion experiments is indicated.

Procedures for calculating benchmark doses for health risk assessment

Safety assessment for noncancer health effects generally has been based upon dividing a no observed adverse effect (NOAEL) by uncertainty (safety) factors to provide an acceptable daily intake (ADI) or reference dose (RfD). Since the NOAEL does not utilize all of the available dose-response data, allows higher ADI from poorer experiments, and may have an unknown, unacceptable level of risk, the benchmark dose (BD) with a specified, controlled low level of risk has become popular as an adjunct to the NOAEL or the low observed adverse effect level (LOAEL) in the safety assessment process. The purpose of this paper is to summarize statistical procedures available for calculating BDs and their confidence limits for noncancer endpoints. Procedures are presented and illustrated for quantal (binary), quasicontinuous (proportion), and continuous data. Quasicontinuous data arise in developmental studies where the measure of an effect for a fetus is quantal (normal or abnormal) but the experimental unit is the mother (litter) so that results can be expressed as the proportion of abnormal fetuses per litter. However, the correlation of effects among fetuses within a litter poses some additional statistical problems. Also, developmental studies usually include some continuous measures, such as fetal body weight or length. With continuous data there generally is not a clear demarcation between normal and adverse measurements. In such cases, extremely high and/or low measurements at some designated percentile(s) can be considered abnormal. Then the probability (risk) of abnormal individuals can be estimated as a function of dose. The procedure for estimating a BD with continuous data is illustrated using neurotoxicity data. When multiple measures of adverse effects are available, a BD can be estimated based on a selected endpoint or the appearance of any combination of endpoints. Multivariate procedures are illustrated using developmental and reproductive toxicity data.

First analysis of mortality and occupational radiation exposure based on the National Dose Registry of Canada

A cohort mortality study of occupational radiation exposure was conducted using the records of the National Dose Registry of Canada. The cohort consisted of 206,620 individuals monitored for radiation exposure between 1951 and 1983 with mortality follow-up through December 31, 1987. A total of 5,426 deaths were identified by computerized record linkage with the Canadian Mortality Data Base. The standardized mortality ratio for all causes of death was 0.61 for both sexes combined. However, trends of increasing mortality with cumulative exposure to whole body radiation were noted for all causes of death in both males and females. In males, cancer mortality appeared to increase with cumulative exposure to radiation, without any clear relation to specific cancers. Unexplained trends of increasing mortality due to cardiovascular diseases (males and females) and accidents (males only) were also noted. The excess relative risk for both sexes, estimated to be 3.0% per 10 mSv (90% confidence interval 1.1-4.8) for all cancers combined, is within the range of risk estimates previously reported in the literature.