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Cell Phone Use and Crash Risk

Young, Richard A.

doi: 10.1097/EDE.0b013e31828abbea
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Department of Psychiatry and Behavioral NeurosciencesWayne State University School of MedicineDetroit, MIryoun@med.wayne.edu

The author responds:

Dr. Kidd1 agrees that previous epidemiological studies on the risk ratio of cell phone conversations while driving were biased because they did not take into account the proportion of time spent not driving during a control period (ie, part-time driving).2 Dr. Kidd’s first objection1 to the adjustment method is that the 2005–6 Seattle Global Positioning System (GPS) data2 are a different time and place than the epidemiological studies. An analysis3 of 2007–8 Chicago GPS data yielded similar results to Seattle,2 supporting the robustness of such data.

His second objection1 is that the two prevalence estimates4,5 of phone conversation while driving are inconsistent. This is a misreading. The prevalence of 6.7%4 is for a 24-hour prevalence period to match the 24-hour period in the GPS driving consistency analysis in my original article.2 The prevalence of 11%5 is for a daytime prevalence period in my subsequent analysis5 to match the daytime hours in the epidemiological studies.

Kidd’s third objection1 is that small differences (eg, in average call duration) might produce important changes in the adjusted risk ratio. Such variations make it preferable to use an adjustment method that is valid for any average call duration. The Table accomplishes this by calculating a rate ratio (RR) from the Toronto study6 raw caller counts and window durations.

TABLE. C

TABLE. C

The crude RR is 4.59, which incorrectly assumes that subjects were in their cars during an entire 10-minute control window (1700 total person-minutes). However, subjects were likely in their cars during only 20% of a prior-day control window.5 To avoid this part-time driving bias, control-window in-car person-minutes were adjusted to 340 (Table). Let ρ be the ratio of out-of-car to in-car control-window caller rates (ρ does not depend on call duration, window duration, or in-car time). The number of callers in the in-car control window is readily solved as 37/(4ρ + 1). For portable phones, ρ is estimated as 0.1,4 yielding 26.4 in-car control callers and adjusted RR 1.29.5 For embedded phones, ρ is 0, yielding 37 in-car control callers and adjusted RR 0.92, within the 95% confidence interval of the OnStar embedded phone with RR 0.62 (0.37–1.05).7

Future studies should report the number of people conversing on cell phones before crashes and in control periods only while driving. It is clear that previous epidemiological estimates of cell phone conversation producing a relative risk about 4 times greater than without cell phone conversation are wrong.

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ACKNOWLEDGMENTS

I thank Joshua Cohen, Charlene Hallett, Linda Angell, Katja Kircher, Greg Fitch, and Michael Posner for helpful comments and Sean Seaman for programming assistance in analyzing the GPS datasets.

Richard A. Young

Department of Psychiatry and Behavioral Neurosciences

Wayne State University School of Medicine

Detroit, MI

ryoun@med.wayne.edu

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REFERENCES

1. Kidd DG. , McCartt AT. Cell phone use and crash risk. Epidemiology. 2013;24:468–469
2. Young RA. Cell phone use and crash risk: evidence for positive bias. Epidemiology. 2012;23:116–118
3. Young RA. Driving consistency errors overestimate crash risk from cellular conversation in two case-crossover studies. In: Proceedings of the Sixth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design. 2011 Lake Tahoe, CA:298–305
4. Young RA. Cell phone use and crash risk [response]. Epidemiology. 2012;23:649–650
5. Young RA. More on cell phone use and crash risk [response]. Epidemiology. 2012;23:774–775
6. Redelmeier DA, Tibshirani RJ. Association between cellular-telephone calls and motor vehicle collisions. N Engl J Med. 1997;336:453–458
7. Young RA, Schreiner C. Real-world personal conversations using a hands-free embedded wireless device while driving: effect on airbag-deployment crash rates. Risk Anal. 2009;29:187–204
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