Most studies of mobile phone use are case-control studies that rely on participants' reports of past phone use for their exposure assessment. Differential errors in recalled phone use are a major concern in such studies. INTERPHONE, a multinational case-control study of brain tumour risk and mobile phone use, included validation studies to quantify such errors and evaluate the potential for recall bias. Mobile phone records of 212 cases and 296 controls were collected from network operators in three INTERPHONE countries over an average of 2 years, and compared with mobile phone use reported at interview. The ratio of reported to recorded phone use was analysed as measure of agreement. Mean ratios were virtually the same for cases and controls: both underestimated number of calls by a factor of 0.81 and overestimated call duration by a factor of 1.4. For cases, but not controls, ratios increased with increasing time before the interview; however, these trends were based on few subjects with long-term data. Ratios increased by level of use. Random recall errors were large. In conclusion, there was little evidence for differential recall errors overall or in recent time periods. However, apparent overestimation by cases in more distant time periods could cause positive bias in estimates of disease risk associated with mobile phone use.
Background: Energy intake determined from self-reported dietary assessment methods may be underreported. Therefore, it is important that such methods be validated against another with known validity for energy intake or energy expenditure. Methods: We investigated potential underestimation of energy intake obtained from our semi-quantitative food-frequency questionnaire (FFQ) administered between 2000 and 2001 in the metropolitan area of Montreal, Canada. The study population included 246 adults aged 18 to 82 years. The ratio of energy intake to estimated basal metabolic rate (EI/BMR) was used to assess underreporting and physical activity was determined from self-administered questions. Comparison of the EI/BMR ratio with the Goldberg statistical cut-off allowed us to detect individuals who were low energy reporters (LERs). LERs and non-LERs were compared to determine if they differed on sociodemographic, anthropometric and lifestyle variables. Results: The EI/BMR ratio was 1.26 for men and 1.32 for women. LERs represented 43% of the sample of individuals. Male LERs accounted for 54% compared with 35% among females. Underreporting of energy intake was highest in men and individuals who were older, heavier, with higher body mass index and lower education level. A higher proportion of male LERs perceived their financial situation as adequate while a greater proportion of female LERs considered themselves poor. Conclusion: Our data suggest that underreporting of energy intake from the FFQ was considerable and may bias dietary interpretation. As this was uneven across the sample, it is crucial to recognise the characteristics of LERs in order to increase the validity of reported energy intake.
Average power levels are substantially higher than the minimum levels theoretically achievable in GSM networks. Exposure indices could be improved by accounting for average power levels of different telecommunications systems. There appears to be little value in gathering information on circumstances of phone use other than use in very sparsely populated regions.
In women with gestational diabetes mellitus, the routine induction of labor at 38 or 39 weeks is associated with a lower risk of cesarean delivery compared with expectant management but may increase the risk of neonatal intensive care unit admission when done at <39 weeks of gestation.
We undertook a re-analysis of the Canadian data from the 13-country case-control Interphone Study (2001-2004), in which researchers evaluated the associations of mobile phone use with the risks of brain, acoustic neuroma, and parotid gland tumors. In the main publication of the multinational Interphone Study, investigators concluded that biases and errors prevented a causal interpretation. We applied a probabilistic multiple-bias model to address possible biases simultaneously, using validation data from billing records and nonparticipant questionnaires as information on recall error and selective participation. In our modeling, we sought to adjust for these sources of uncertainty and to facilitate interpretation. For glioma, when comparing those in the highest quartile of use (>558 lifetime hours) to those who were not regular users, the odds ratio was 2.0 (95% confidence interval: 1.2, 3.4). After adjustment for selection and recall biases, the odds ratio was 2.2 (95% limits: 1.3, 4.1). There was little evidence of an increase in the risk of meningioma, acoustic neuroma, or parotid gland tumors in relation to mobile phone use. Adjustments for selection and recall biases did not materially affect interpretation in our results from Canadian data.
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