Can you find the right people who you need to study?
The appropriate population, or "target population" is the group of people that a researcher wants to study.
For cohort studies in environmental epidemiology, the target population includes a group of people who were exposed to the contamination and a group of people who were not exposed to contamination.
There may be various difficulties in contacting the people who were exposed to the contamination. If a long time has passed since residents were exposed to a contaminant, many of them may have moved away.
For example, suppose the contamination happened in the in the 1970s, and the area has been re-developed since then with new housing and businesses. Suppose researchers conducting a health study send out a questionnaire to residents living in this redeveloped community. This questionnaire attempts to contact people who were exposed to the contamination in the 1970s. The researchers want to find out if these people had a higher occurrence of a specific health outcome related to the contaminant. It is likely that most current residents who receive the questionnaire were not actually exposed to the contamination. Most current residents had just recently moved to the new housing that was built long after the contamination occurred in the 1970s. Under these conditions, researchers will have a difficult time determining whether residents who were exposed to contamination had unusually high rates of the specific health outcome.
Another challenge to finding the target population is participation bias. In epidemiology, "bias" means a systematic error that affects the measurement process in a research study. Participation bias is when there are differences between the intended target population that you are trying to study and the group of people that actually participate in a study.
Suppose that researchers were able to find the updated address for most of the residents exposed to a hazardous chemical in the 1970s. Imagine if a person has moved away, and one day they receive a questionnaire about their health. A typical person might answer or not, depending on how busy they are, whether they want to help, or whether they are interested in some way. However, a person who is sick and might suspect that their illness could be related to the study may be more likely to participate. This can lead to more sick people answering the questionnaire, and so the group that participates is different than the entire "target population." In this case, because sick people are more likely to participate, the exposed group appears to be sicker than it really is. This example is one of many different ways that bias might occur.