Most health-conscious people are familiar with the concept of risk factors for disease. We’re too familiar, in fact. A risk factor is like the guest that nobody invited to the party, a spoiler. Though we might feel fine now, our individual risk for (fill in the blank) tells us that our wellbeing might not last. That vague and remote prospect of a stroke or a tumour has taken on a sharply numerical precision, thanks to screening tests that expose and quantify our risk factors.
The term stems from the Framingham Heart Study, which began in 1948. Ever since, researchers have measured the variables that contribute to cardiovascular disease in multiple generations of residents of the town of Framingham in Massachusetts. The participants did not have cardiovascular disease when they enrolled, but researchers routinely recorded factors suspected in disease onset, including blood pressure, cholesterol levels, and whether or not the person smoked.
Since no single factor was able to predict the heart attacks that occurred in Framingham, the study designers thought to combine half a dozen of them in what became the first numerical risk calculator, called the Framingham Risk Score. The researchers figured the relative importance of each risk factor after examining thousands of health histories. The combined risk score enabled doctors to make predictions that were borne out in future patients as the study proceeded.
Dozens of risk calculators are in service today, covering all medical specialties and organ systems. But since Framingham, risk factors have acquired an unwarranted power. Doctors try to manage them as if they’re the disease itself and, as a result, patients are subjected not only to undue worry but also to the harmful side effects of preventive medications and testing.
What’s more, in medicine’s version of mission-creep, the thresholds for many risk factors have been lowered so as to encompass ever larger pools of patients. People who believed they were normal in a particular health category abruptly learn that they are not – and that they probably need treatment. That they lack symptoms is misleading. Today’s patient is declared to be in good health not because she feels well, but because her latest scan or blood work indicates no abnormalities.
Robert Aronowitz, a historian of medicine and medical doctor at the University of Pennsylvania, points out that when drug companies are able to treat people who might become sick, as opposed to patients with symptoms, the market is a lot larger. Once put into the at-risk category, they might be taking medication for the rest of their lives. Aronowitz gives hypertension (high blood pressure) as an example: a risk factor for heart disease and stroke, it makes the arteries more prone to blockage and rupture. The first drugs developed for hypertension were used to treat people showing obvious signs of spiking pressure, such as shortness of breath and nosebleeds. Next, the medications were extended to people without symptoms who nonetheless had hypertension upon measurement – a systolic pressure (when the heart is pumping) of above 140, and a diastolic pressure (when the heart is at rest) of above 90. These patients, a much larger population, numbering in the tens of millions, had to be screened to be identified.
The threshold of what constituted a safe level of blood pressure ‘was gradually lowered’, writes Aronowitz. ‘And finally a new disorder, prehypertension, was defined and promoted, such that another segment of the population could be screened, labelled, and treated.’ ‘Prehypertension’ represents a systolic pressure of between 120 and 140, and a diastolic pressure of 80 to 90. Those ranges used to be considered normal, but not anymore.
Recently, the American Heart Association (AHA) recognised that things had gone too far. Since studies had shown that blood-pressure medication was of no benefit to those with prehypertension, the AHA raised the level at which people aged 60 and over should start taking drugs. Now the recommended trigger is a systolic pressure of 150 or higher. With the change, some 7 million Americans, more than half of whom were taking medication, were moved out of the at-risk column. It’s unlikely that 3‑4 million people will drop their medications, however. Once launched, a medical regimen of that magnitude is hard to turn around.
There’s a more fundamental issue. Risk factors and risk calculators are reminders that medical science does not completely understand the mechanisms of disease. Risk factors are associations; they don’t represent cause-and-effect relationships unless the connection to the disease is especially strong, like the link between cigarettes and lung cancer. Risk factors are based on averages taken from large groups, and consequently the individual patient can’t know his or her true probability of contracting the condition. For any population, the calculator could accurately forecast the number of, say, heart attacks over a 10-year period, but the algorithm can’t identify who will succumb and who will be spared.
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