Answer (a) — incorrect: Controls are subjects who were drawn from the high-income areas of Epiville (see areas circled by the orange lines). At the same time, cases came from all over Epiville. It is likely that those attending the weight-loss program do not represent the exposure distribution of the population giving rise to the cases obtained from the tertiary care facility since they are on average from higher income areas than the cases (and income is related to lawn/garden pesticide use). Thus, drawing cases and controls from different source populations per this sampling strategy may produce a biased estimate of effect.

Answer (b) — correct: Controls came from many different areas of Epiville, as did cases. In general, this is a more representative sampling method and it will be most likely to ensure that the cases and controls come from the same source population. Teitelbaum et al. (2007) attempted this type of sampling scheme by recruiting both cases and controls for the whole geographical area of Suffolk and Nassau counties. However, the Epiville sampling scheme is not perfect, as cases also came from outside of Epiville while controls did not. This highlights the difficulty of imagining a correct source population.

Answer (c) — incorrect: If this is a relatively rare disease it is not likely that the source population around the hospital will give rise to a sufficient number of cases which would be treated at the Hospital. As such, the majority of cases are from areas other than the areas surrounding the Hospital. Areas surrounding the Epiville General Hospital are marked on the map as areas of comparatively low income. Thus, controls from this area who attend the free clinic could be different from cases on many important factors related to lawn/garden pesticide use in addition to income, creating selection bias.