Mobile phone use was evaluated with software modified mobile phones (SMPs) recording output power levels and minutes of talk time. Volunteers (n = 53, 2537 calls) from a New Jersey suburb, New York City, and San Francisco were provided an SMP phone for 5 days and asked to keep a log record of calls as well (total of 2537 calls). The data showed significant differences average output power (and SAR) for the different geographical areas. There was also a significant effect on output power that correlated with several behavioral and situational factors, including stationary vs. free moving, indoor vs. outdoor, etc. In addition, portable phantom heads were employed to better understand what factors influence energy distribution, signal, and ultimately power output control and SAR in the user. The authors report the type of technology (analog, CDMA, TDMA, or GSM) has a large influence on power output (and SAR) due to the different maximal limits and (presumably) network distribution. The authors also used billing records to evaluate the accuracy of questionnaire-based recall of mobile phone use, and reported that a large number of volunteers (n = 43) could not accurately estimate (to within 50%) the number and duration of daily, weekly, and monthly calls as well as differences between weekends and weekdays. Further, on average, volunteers underestimated their cumulative time on the mobile phone.
Authors' abstract: Kelsh et al. 2011 (#5076):
Epidemiologic studies of mobile phone users have relied on self reporting or billing records to assess exposure. Herein, we report quantitative
measurements of mobile-phone power output as a function of phone technology, environmental terrain, and handset design. Radiofrequency (RF) output data were collected using software-modified phones that recorded power control settings, coupled with a mobile system that recorded and analyzed RF fields measured in a phantom head placed in a vehicle. Data collected from three distinct routes (urban, suburban, and rural) were summarized as averages of peak levels and overall averages of RF power output, and were analyzed using analysis of variance methods. Technology was the strongest
predictor of RF power output. The older analog technology produced the highest RF levels, whereas CDMA had the lowest, with GSM and TDMA
showing similar intermediate levels. We observed generally higher RF power output in rural areas. There was good correlation between average power
control settings in the software-modified phones and power measurements in the phantoms. Our findings suggest that phone technology, and to a lesser extent, degree of urbanization, are the two stronger influences on RF power output. Software-modified phones should be useful for improving epidemiologic exposure assessment.