Berrie, L, Ellison, GTH orcid.org/0000-0001-8914-6812, Norman, PD orcid.org/0000-0002-6211-1625 et al. (4 more authors) (2019) The Association Between Childhood Leukemia and Population Mixing An Artifact of Focusing on Clusters? Epidemiology, 30 (1). pp. 75-82. ISSN 1044-3983
Abstract
Background: Studies investigating the population-mixing hypothesis in childhood leukemia principally use two analytical approaches: (i) non-random selection of areas according to specific characteristics, followed by comparisons of their incidence of childhood leukemia with that expected based on the national average; and (ii) regression analyses of region-wide data to identify characteristics associated with the incidence of childhood leukemia. These approaches have generated contradictory results. We compare these approaches using observed and simulated data.
Methods: We generated 10,000 simulated regions using the correlation structure and distributions from a United Kingdom dataset. We simulated cases using a Poisson distribution with the incidence rate set to the national average assuming the null hypothesis that only population size drives the number of cases. Selection of areas within each simulated region was based on characteristics considered responsible for elevated infection rates (population density and inward-migration) and/or elevated leukemia rates. We calculated effect estimates for 10,000 simulations and compared results to corresponding observed data analyses.
Results: When the selection of areas for analysis is based on apparent clusters of childhood leukemia biased assessments occur; the estimated 5-year incidence of childhood leukemia ranged between 0 and 8 per 10,000 children in contrast to the simulated 2 cases per 10,000 children, similar to the observed data. Performing analyses on region-wide data avoids these biases.
Conclusions: Studies using non-random selection to investigate the association between childhood leukemia and population mixing are likely to have generated biased findings. Future studies can avoid such bias using a region-wide analytical strategy.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 Wolters Kluwer Health, Inc. All rights reserved. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
Keywords: | population mixing; childhood leukaemia; simulation |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Healthcare (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Clinical & Population Science Dept (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Specialist Science Education Dept (Leeds) |
Funding Information: | Funder Grant number Candlelighters No Ext Ref Given |
Depositing User: | Symplectic Publications |
Date Deposited: | 18 Jul 2018 14:35 |
Last Modified: | 25 Jun 2023 21:26 |
Status: | Published |
Publisher: | Wolters Kluwer Health |
Identification Number: | 10.1097/EDE.0000000000000921 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:133454 |
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