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Using satellite derived land cover information for a multi-temporal study of self-reported recall of proximity to farmland

Abstract

Exposure misclassification is a major concern in epidemiologic studies. The potential for misclassification becomes even more problematic when participants are asked to recall historical information. Yet, historical information is important in cancer studies, where latency is long and causative exposures may have occurred years or even decades prior to diagnosis. Even though self-reported proximity to farmland is a commonly used exposure measure, the accuracy of recall is seldom, if ever validated. Geographic Information Systems (GISs) and land cover information derived from satellite imagery can allow researchers to assess the accuracy of this exposure measure, and to quantify the extent and importance of exposure misclassification. As part of a bladder cancer case–control study in Michigan, participants were asked whether they lived on a farm, or within a distance of 1/4, 1/4–1, 1–5, or >5 miles from farmland for each residence over their lifespan. Responses from 531 participants over two time periods — 1978 and 2001 — were investigated. Self reported proximity to farmland was compared to a “gold standard” derived from Michigan land cover files for the same time periods. Logistic regression and other statistical measures including sensitivity, specificity, and percentage matching were evaluated. In comparing self-reported and land cover-derived proximity to farmland, cases exhibited better agreement than controls in 2001 (adjusted OR=1.74; 95% CI=1.01, 2.99) and worse agreement in 1978, although not significantly (adjusted OR=0.74; 95% CI=0.47, 1.16). When comparing 2001 with 1978, both cases and controls showed better agreement in 2001, but only cases showed a significant difference (adjusted OR=2.36; 95% CI=1.33, 4.18). These differences in agreement may be influenced by differences in educational attainment between cases and controls, although adjustment for education did not diminish the association. Gender, age, number of years at residence, and geocoding accuracy did not influence agreement between the proximity approaches. This study suggests that proximity measures taken from satellite-derived land cover imagery may be useful for assessing proximity to farmland, and it raises some concerns about the use of self-reported proximity to farmland in exposure assessments.

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Acknowledgements

We thank the participants of this study for taking part in this research. We also thank Jerome Nriagu, principal investigator of the case–control study, for providing access to this data set, and Melissa Slotnick, Stacey Fedewa, Nicholas Mank, Caitlyn Meservey, and Taylor Builee for valuable assistance with data collection and data entry. We are grateful to the Michigan State Cancer Registry and the Michigan Public Health Institute for assisting with participant recruitment. This research was funded by the National Cancer Institute, Grant R01 CA96002-10.

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Correspondence to Gillian A Avruskin.

Appendices

Appendix 1

1978 Land use categories sorted by percentage of study area covered. Table A1

Table 7 Table A1

Appendix 2

2001 Land use categories sorted by percentage of study area covered. Table A2

Table 8 Table A2

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Avruskin, G., Meliker, J. & Jacquez, G. Using satellite derived land cover information for a multi-temporal study of self-reported recall of proximity to farmland. J Expo Sci Environ Epidemiol 18, 381–391 (2008). https://doi.org/10.1038/sj.jes.7500610

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