Effects of Recall and Selection Biases on Modeling Cancer Risk From Mobile Phone Use: Results From a Case-Control Simulation Study.

BACKGROUND: The largest case-control study (Interphone study) investigating glioma risk related to mobile phone use showed a J-shaped relationship with reduced relative risks for moderate use and a 40% increased relative risk among the 10% heaviest regular mobile phone users, using a categorical risk model based on deciles of lifetime duration of use among ever regular users. METHODS: We conducted Monte Carlo simulations examining whether the reported estimates are compatible with an assumption of no effect of mobile phone use on glioma risk when the various forms of biases present in the Interphone study are accounted for. Four scenarios of sources of error in self-reported mobile phone use were considered, along with selection bias. Input parameters used for simulations were those obtained from Interphone validation studies on reporting accuracy and from using a nonresponse questionnaire. RESULTS: We found that the scenario simultaneously modeling systematic and random reporting errors produced a J-shaped relationship perfectly compatible with the observed relationship from the main Interphone study with a simulated spurious increased relative risk among heaviest users (odds ratio = 1.91) compared with never regular users. The main determinant for producing this J shape was higher reporting error variance in cases compared with controls, as observed in the validation studies. Selection bias contributed to the reduced risks as well. CONCLUSIONS: Some uncertainty remains, but the evidence from the present simulation study shifts the overall assessment to making it less likely that heavy mobile phone use is causally related to an increased glioma risk.

Association between long-term occupational noise exposure and obesity.

Noise exposure has been linked to several health outcomes including obesity. This cross-sectional study examined the association between occupational noise exposure and body mass index as a measure of general obesity in 913 textile workers (totally from nine factories) in Yazd city, Iran, from winter to summer of 2018. The sound pressure level (dBA) at each working station was measured by a calibrated sound level meter. The long-term noise exposure score of each worker (as dBA.year) was calculated by multiplying the working history in each unit to its corresponding noise level. Models were adjusted for personal, behavioral, environmental, and family history factors. In total, 81.05% (n = 740) of the participants were exposed to noise levels higher than 85 dBA. The direct association was found for the fully adjusted model (ß = 0.002; 95% CI: 0.001: 0.004). For the model with past year noise exposure, a 10.6% increase in odds was observed for each 5 dBA increase in noise exposure (95% CI: 1.005: 1.216). We found a 0.1% increase in the odds of being overweight in mixed-gender analysis (95% CI: 1.001:1.002) for each 5 dBA.year in the fully adjusted model. Occupational noise exposure should be regarded as a risk factor for cardiometabolic outcomes in industrial workers.