In many studies of environmental risk factors for disease, researchers use the location at diagnosis as a geographic reference for environmental exposures. However, many environmental pollutants change continuously over space and time. The dynamic characteristics of these pollutants coupled with population mobility in the United States suggest that for diseases with long latencies like cancer, historic exposures may be more relevant than exposure at the time of diagnosis. In this article, we evaluated to what extent the commonly used assumption of no population mobility results in increased bias in the estimates of the relationship between environmental exposures and long-latency health outcomes disease in a case-control study. We conducted a simulation study using the residential histories of a random sample from the National Institutes of Health-AARP (formerly American Association of Retired Persons) Diet and Health Study. We simulated case-control status based on subject exposure and true exposure effects that varied temporally. We compared estimates from models using only subject location at diagnosis to estimates where subjects were assumed to be mobile. Ignoring population mobility resulted in underestimates of subject exposure, with largest deviations observed at time points further away from study enrollment. In general, the effect of population mobility on the bias of the estimates of the relationship between the exposure and the outcome was more prominent with exposures that showed substantial spatial and temporal variability. Based on our results, we recommend using residential histories when environmental exposures and disease latencies span a long enough time period that mobility is important.
Keywords: environment; epidemiology; residential mobility.
© 2020 John Wiley & Sons, Ltd.