Development, evaluation, and comparison of land use regression modeling methods to estimate residential exposure to nitrogen dioxide in a cohort study

Gillespie, J., Beverland, I. J., Hamilton, S. and Padmanabhan, S. (2016) Development, evaluation, and comparison of land use regression modeling methods to estimate residential exposure to nitrogen dioxide in a cohort study. Environmental Science and Technology, 50(20), pp. 11085-11093. (doi: 10.1021/acs.est.6b02089) (PMID:27618146)

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Abstract

We used a network of 135 NO2 passive diffusion tube sites to develop land use regression (LUR) models in a UK conurbation. Network sites were divided into four groups (32–35 sites per group) and models developed using combinations of 1–3 groups of “training” sites to evaluate how the number of training sites influenced model performance and residential NO2 exposure estimates for a cohort of 13 679 participants. All models explained moderate to high variance in training and independent “hold-out” data (Training adj. R2: 62–89%; Hold-out R2: 44–85%). Average hold-out R2 increased by 9.5%, while average training adj. R2 decreased by 7.2% when the number of training groups was increased from 1 to 3. Exposure estimate precision improved with increasing number of training sites (median intralocation relative standard deviations of 19.2, 10.3, and 7.7% for 1-group, 2-group and 3-group models respectively). Independent 1-group models gave highly variable exposure estimates suggesting that variations in LUR sampling networks with relatively low numbers of sites (≤35) may substantially alter exposure estimates. Collectively, our analyses suggest that use of more than 60 training sites has quantifiable benefits in epidemiological application of LUR models.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Padmanabhan, Professor Sandosh
Authors: Gillespie, J., Beverland, I. J., Hamilton, S., and Padmanabhan, S.
College/School:College of Medical Veterinary and Life Sciences > Institute of Cardiovascular and Medical Sciences
Journal Name:Environmental Science and Technology
Publisher:American Chemical Society
ISSN:0013-936X
ISSN (Online):1520-5851
Published Online:12 September 2016
Copyright Holders:Copyright © 2016 American Chemical Society
First Published:First published in Environmental Science & Technology 50(20):11085-11093
Publisher Policy:Reproduced under a Creative Commons License

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