Cell Phone Use and Crash Risk

To the Editor: In a recent report,1 Young argues that prior studies indicating harmful effects of cell phone use are confounded by driving time, and “corrects” his estimates to claim that no association exists. However, driving time does not confound the association—it is a requirement for the occurrence of the outcome, just as person-time with a uterus is necessary for uterine cancer. In both the density-sampled case-control and case-crossover designs, the exposure distribution in the controls is meant to estimate the exposure distribution in the person-time at risk for the outcome. In general, one samples directly from at-risk person-time. However, it is also possible to obtain valid estimates of the exposure distribution in the person-time at risk by sampling from nonrisk periods if the exposure distribution is unrelated to outcome risk.2 In a case-crossover study of cell phone use and collisions, cell phone use in the period immediately before the collision (hazard period) is compared with use during driving time earlier in the past (control period); cell phone use when the participant is not driving is irrelevant because one is not at risk for a collision. Furthermore, control persons/person-time must be selected independent of exposure opportunity; adjusting for the likelihood of cell phone use during the hazard or control period induces a bias by incorrectly controlling for exposure opportunity.3,4 Young1 reasons that if one underestimates driving time in the control period, one underestimates exposure (cell phone) time, resulting in an overestimate of the relative risk. However, this assumption implies that one talks on a cell phone only while driving and not during other times of the day. Although true with OnStar (OnStar, Detroit, MI) (a car-specific communications device), that is not necessarily true for cell phone use more generally; it is equally (if not more) likely that cell phone use is higher while not driving. In this case, exposure during nondriving control times would be an overestimate of exposure during the actual time at risk, and would lead to an underestimate of the relative risk. Instead of appropriately restricting control periods to driving time, Young multiplies his results by a “correction” factor based on the proportion of cases that did not drive during the control period; applying this estimate to all cases induces a downward bias by attempting to increase comparability between case and control periods with respect to “exposure opportunity”—a recognized fallacy.4 After commenting on this faulty logic previously,3,4 we are disappointed that researchers continue to propagate this erroneous method. Murray A. Mittleman Cardiovascular Epidemiology Research Unit Department of Medicine Beth Israel Deaconess Medical Center Harvard Medical School Boston, MA [email protected] Department of Epidemiology Harvard School of Public Health Boston, MA Malcolm Maclure Department of Epidemiology Harvard School of Public Health Boston, MA Department of Anesthesiology, Pharmacology and Therapeutics University of British Columbia British Columbia, Canada Elizabeth Mostofsky Cardiovascular Epidemiology Research Unit Department of Medicine Beth Israel Deaconess Medical Center Harvard Medical School Boston, MA Department of Epidemiology Harvard School of Public Health Boston, MA

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