Linda S. Erdreich

Factors that Influence the Radiofrequency Power Output of GSM Mobile Phones

Abstract Erdreich, L. S., Van Kerkhove, M. D., Scrafford, C. G., Barraj, L., McNeely, M., Shum, M., Sheppard, A. R. and Kelsh, M. Factors that Influence the Radiofrequency Power Output of GSM Mobile Phones. Radiat. Res. 168, 253–261 (2007). Epidemiological studies of mobile phone use and risk of brain cancer have relied on self-reported use, years as a subscriber, and billing records as exposure surrogates without addressing the level of radiofrequency (RF) power output. The objective of this study was to measure environmental, behavioral and engineering factors affecting the RF power output of GSM mobile phones during operation. We estimated the RF-field exposure of volunteer subjects who made mobile phone calls using software-modified phones (SMPs) that recorded output power settings. Subjects recruited from three geographic areas in the U.S. were instructed to log information (place, time, etc.) for each call made and received during a 5-day period. The largest factor affecting energy output was study area, followed by user movement and location (inside or outside), use of a hands-free device, and urbanicity, although the two latter factors accounted for trivial parts of overall variance. Although some highly statistically significant differences were identified, the effects on average energy output rate were usually less than 50% and were generally comparable to the standard deviation. These results provide information applicable to improving the precision of exposure metrics for epidemiological studies of GSM mobile phones and may have broader application for other mobile phone systems and geographic locations.

Improving the Use of Epidemiologic Data in Health Risk Assessment

Epidemiologic data with quantitative exposure measures is infrequently available for specific environmental agents. This lack of exposure measures creates confusion in interpreting epidemiologic data and therefore has impeded its efficient use in health risk analysis. This paper discusses screening and evaluating epidemiologic studies for use in assessing health risk. It also describes the larger role of epidemiology in reducing uncertainties in risk analysis. The approach recognizes that the various designs used to increase statistical power and to control for covariables have different functions in contemporary risk assessment as practiced by regulatory agencies. Each of these study designs is categorized for its role in risk analysis as useful for hazard identification or for dose-response assessment. Studies presenting geographic correlations are construed to be not directly useful in health risk assessment. The numerical level of the exposure data is a deciding factor in using valid epidemiologic studies. However, data measured on an ordinal scale can be used in qualitative assessments and can demonstrate the strength of the relationship. The application of this procedure is illustrated using epidemiologic studies on the carcinogenicity of chemicals contaminated with dioxins.

Epidemiologic methods in analysis of scientific issues

Studies of human populations provide much of the information that is used to evaluate compensation cases for hearing loss, including rates of hearing loss by age, and dose–response relationships. The reference data used to make decisions regarding workman’s compensation is based on epidemiologic studies of cohorts of workers exposed to various noise levels. Epidemiology and its methods can be used in other ways in the courtroom; to assess the merits of a complaint, to support Daubert criteria, and to explain scientific issues to the trier of fact, generally a layperson. Using examples other than occupational noise induced hearing loss, these methods will be applied to respond to a complaint that hearing loss followed exposure to a sudden noise, a medication, or an occupational chemical, and thus was caused by said exposure. The standard criteria for assessing the weight of the evidence, and epidemiologic criteria for causality show the limits of such anecdotal data and incorporate quantitative and tempora...

Human vibration standards–Do we ask the right questions?

Standards for vibration exposure promulgate different limits for hand–arm vibration (HAV) and for whole‐body vibration (WBV). The discrepancy between the two should be explainable on some rational basis [Griffin, Handbook of Human Vibration (1990)], but there is no obvious difference in the mechanism of pathogenesis to the skin at each of the sites. The difference may arise because the endpoints chosen as the basis of each of the standards are different. One approach to estimating dose response [Jarabek, Toxicol. Lett. 79, 171–184 (1995)], characterizes the steps in developing a model as proceeding from a protective to a predictive paradigm as data progress from qualitative to quantitative. To develop vibration standards along this continuum, certain data must be developed: Among these are identification of performance effects of HAV, identification of long‐term effects of WBV, and clarification of the impedance of the affected biological structures. Some of these areas have been addressed in recent revis...

Using hearing conservation data to study the epidemiology of noise‐induced hearing loss

Annual audiometric testing mandated by Federal Regulations is creating an enormous, fragmented database. Epidemiologic studies, based on this information, can potentially elucidate important parameters related to the development of noise‐induced hearing loss. This paper illustrates the application of survival data analysis to the audiometric data of approximately 2500 people taken over as many as ten successive years. Survival analysis includes both the number of people who fail during a study (develop a standard threshold shift in this instance) as well as those who survive or are lost to follow‐up. In this case, we found that the survival function (the probability of surviving past a time interval) and the hazard function (the probability of surviving through a time interval given that the worker has survived to the beginning of the interval) are insensitive to the exposures at the facility. However, when these functions are stratified on age at first test, older workers are at higher risk than younger ...

Risk assessment for noise induced hearing loss

Nationally mandated hearing conservation programs provide the protocol for the design of epidemiologically sound “natural experiments” through which we may refine the risk assessment of hearing loss from noise exposure. Although a variety of appropriate data is being collected, contemporary epidemiologic methods for analyzing them are at present not widely employed. The life table technique for dealing with people entering and leaving the program at different times and people lost to follow‐up, introduced in an earlier paper [J. Erdreich and L. S. Erdreich, “Epidemiologic Strategies to Understanding NIHL,” in New Perspectives in NIHL (Raven, New York, 1980)] will be illustrated. The bias introduced by unappropriate control group will be demonstrated. Various methods for summarizing risk for dichotomous and continuous data are discussed in the context of the intended public health goal.

Risk assessment for noise exposure

In this paper we propose that full use is not made of available noise‐exposed threshold data. Specifically, data from noise‐exposed populations can be analyzed to assess impact of exposure in two ways: (1) to provide estimates of the number of cases of hearing loss attributable to noise in the population or, (2) to provide estimates of increased risk of hearing loss in an exposed individual relative to the unexposed person. Previous studies have neglected prediction of risk to the individual, emphasizing instead the impact on the population. To more fully understand the effect of noise exposure, the approaches must be combined. We will present two statistics which may be calculated from population threshold data: Percent risk is the statistic commonly computed from hearing conservation data. Percent risk is an estimate of the number or of the proportion of cases of hearing loss attributable to noise exposure. Rate ratio is the second statistic we will discuss. The rate ratio estimates the increased risk o...

Intermodulation products fh + f1 and 2fh + f1: Masking and growth with variable low‐frequency primary

Masked threshold for a phase incremented pulsed tone at fh + f1 or at 2fh + f1 was measured in the presence of phase‐synchronized maskers fh and f1. The frequency of f1 was either 250, 500, or 1000 Hz and the ratio fh/f1 was fixed at 1.2. The amplitude of the menaural phase effect varied with the level of the primaries, being smaller at the high and low extremes of the range of primary amplitudes. Growth of masking is frequency dependent. Combination tone estimates were calculated based on the assumption that the menaural phase effect is the result of interaction between an aural combination tone and the maskee. Analysis of the growth rates does not permit rejection of a frequency‐independent nonlinear mechanism for their generation.