Estimating the Impact of Medication on Diabetics' Diet and Lifestyle Choices

individual may choose to remain sedentary, slightly overweight and eat too much of the wrong
foods, knowing that such choices compromise health and longevity.

The various theories about the benefits of risk regulation provide a framework for evaluating
behavioral responses to a diabetes finding. Dickie and Gerking (1997) identified four hypotheses
about how people respond to changes in risk policies. Technologists might extrapolate from
laboratory experiments to forecast that the benefits of a new and imposed technology would be
fully realized. Namely, no one would change behavior and everyone would thus exact all
possible health benefits of the new technology. Alternatively, people adapt to risk reducing
innovations by becoming less vigilant about safety. They listed three variations of this notion.
Peltzman (1975) argued that a risk reducing technology lowers the cost of risky behavior and
induces an increase in risky behavior. The outcome of more risk taking could at least partially
offset the benefits of the regulation. Wilde (1982) postulated a target risk level so that
behavioral change would exactly offset benefits of regulation, leaving no net change in health
outcomes. Viscusi (1992) suggested that people may overestimate the risk-reducing capability
of required technologies. This lulling effect could lead people to take more risks than before the
risk-reducing technology was required. Health outcomes could be worse.

If a person were surprised by being told he is diabetic, then clearly he was overestimating his
health status. Usually such information is not given in isolation. Doctors would likely issue a
stern lecture about the importance of managing diet (making big changes) and taking more
exercise. The importance of medication would also be part of the lecture. In effect, the newly-

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