The impact of population mobility on estimates of environmental exposure effects in a case‐control study

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 pop...

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Veröffentlicht in:Statistics in medicine Jg. 39; H. 11; S. 1610 - 1622
Hauptverfasser: Joseph, Anny‐Claude, Fuentes, Montserrat, Wheeler, David C.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Wiley Subscription Services, Inc 20.05.2020
Schlagworte:
Disease
environment
epidemiology
Pollutants
Population
residential mobility
epidemiology
environment
residential mobility
ISSN:0277-6715, 1097-0258, 1097-0258
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Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
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ISSN:0277-6715
1097-0258
1097-0258
DOI:10.1002/sim.8501