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Last updated: Sun, Jul 28, 2024
Some of the material presented in A Brief Epidemiology of Pain is the result of epidemiological research. The name suggests research into epidemics, and in a sense that's correct. It's concerned with diseases at the population level rather than at the physiological level. It looks at the occurrence and distribution of diseases within the population and at how they vary by age, sex, geography, time, and so forth. It also looks for clues to the etiology or causes of disease by looking for associations between the disease and factors that might promote or protect from it.
The statistics presented in A Brief Epidemiology of Pain about the frequency of different types of pain are one example of epidemiological results. Although the numbers seem straightforward, the slippery nature of pain has influenced them. Pain comes and goes, sometimes over years, before the patient consults a doctor about it, and so it is difficult to gather information on when pain started and how long it existed before the doctor heard about it. Researchers therefore tend to report the proportion who experienced pain during a time period, when the doctor was first consulted, or how many individuals experienced new pain during a period.
Epidemiologists also face the problem that pain is usually unremarkable. One four-year study found that only 20% of participants reported no pain in the past month each of three times that they were surveyed.1 Researchers try to distinguish significant pain in terms of its chronicity, the associated disability, or visits to a doctor. These limitations tend to veil that part of the pain picture that precedes the recognition that something serious has developed.
One way to look for clues to the etiology or causes of a condition is through what is called an ecological study. Groups with different ecologies (environments) are compared. For example, the occurrence of low back pain could be compared between lumberjacks and steeplejacks. A higher occurrence in either group might suggest some factor or factors in the environment that might be responsible for the higher occurrence. A drawback of such studies is that there are likely to be many confounding factors between the groups. Lumberjacks might be older or younger than steeplejacks, or they may be likely to stir their coffee with their thumbs2, either of which might be a risk factor for low back pain.
A case control study may provide more power by adding observations about individuals. The “cases” might be individuals with a defined lower back impairment. The “controls” would be others without such an impairment. The individuals might be matched with respect to known confounding variables, such as age or occupation. The cases and controls are studied for their prior history or experience or, as an epidemiologist might put it, their “exposures.” Factors that the impaired had but the controls didn't might then be considered as risk factors or possible causes for the later impairment.
The researcher has to ensure that the data concerning the two groups are in fact comparable. One study, in which the data reported by the subjects was checked against records, found that adults with widespread chronic pain were more likely to recall documented negative childhood events such as hospitalizations than were normal adults.3 If the self-reports hadn't been checked against the records, the researchers might have reported childhood hospitalizations as a potential risk factor for adult development of low back problems, or might have reported them as a stronger factor than in fact they were.
A cohort study can be used to ensure an accurate picture of subjects before onset of the disease that is being studied. In a cohort study, data is collected on a group (cohort) of healthy subjects, and the subjects are monitored to see which of them develop the disease of interest. This requires that the researchers identify in advance all factors of interest so that they can collect the necessary data.
It is expensive to check events reported by subjects in a case control study, and many events can't be checked for practical, legal, or economic reasons, or simply because no record exists for many events and factors that might influence a disease. A cohort study must not only identify and collect all the evidence that the researchers may later wish to analyze, but also must wait for events to develop. Relevant data may exist in the clinical records of certain healthcare systems, but using this resource limits the subjects who can be used.
Using clinical records has a further hidden risk or limitation. People who consult a doctor do so because they perceive their symptoms as serious. The perceptions that drive these decisions are probably idiosyncratic, and they are at least as occult as the pain itself is. How this self-selection affects results is therefore difficult to understand well.