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Comparison between Generalized Linear Modelling and Additive Bayesian Network; Identification of Factors associated with the Incidence of Antibodies against Leptospira interrogans sv Pomona in Meat Workers in New Zealand


Pittavino, M; Dreyfus, A; Heuer, C; Benschop, J; Wilson, P; Collins-Emerson, J; Torgerson, P R; Furrer, R (2017). Comparison between Generalized Linear Modelling and Additive Bayesian Network; Identification of Factors associated with the Incidence of Antibodies against Leptospira interrogans sv Pomona in Meat Workers in New Zealand. Acta Tropica, 173:191-199.

Abstract

Background Additive Bayesian Network (ABN) is a graphical model which extends Generalized Linear Modelling (GLM) to multiple dependent variables. The present study compares results from GLM with those from ABN analysis used to identify factors associated with Leptospira interrogans sv Pomona (Pomona) infection by exploring the advantages and disadvantages of these two methodologies, to corroborate inferences informing health and safety measures at abattoirs in New Zealand (NZ). Methodology and Findings in a cohort study in four sheep slaughtering abattoirs in NZ, sera were collected twice a year from 384 meat workers and tested by Microscopic Agglutination with a 91% sensitivity and 94% specificity for Pomona. The study primarily addressed the effect of work position, personal protective equipment (PPE) and non-work related exposures such as hunting on a new infection with Pomona. Significantly associated with Pomona were “Work position” and two “Abattoirs” (GLM), and “Work position” (ABN). The odds of Pomona infection (OR, [95% CI]) was highest at stunning and hide removal (ABN 41.0, [6.9-1044.2]; GLM 57.0, [6.9-473.3]), followed by removal of intestines, bladder, and kidneys (ABN 30.7, [4.9-788.4]; GLM 33.8, [4.2-271.1]). Wearing a facemask, glasses or gloves (PPE) did not result as a protective factor in GLM or ABN. Conclusions/Significance The odds of Pomona infection was highest at stunning and hide removal. PPE did not show any indication of being protective in GLM or ABN. In ABN all relationships between variables are modelled; hence it has an advantage over GLM due to its capacity to capture the natural complexity of data more effectively.

Abstract

Background Additive Bayesian Network (ABN) is a graphical model which extends Generalized Linear Modelling (GLM) to multiple dependent variables. The present study compares results from GLM with those from ABN analysis used to identify factors associated with Leptospira interrogans sv Pomona (Pomona) infection by exploring the advantages and disadvantages of these two methodologies, to corroborate inferences informing health and safety measures at abattoirs in New Zealand (NZ). Methodology and Findings in a cohort study in four sheep slaughtering abattoirs in NZ, sera were collected twice a year from 384 meat workers and tested by Microscopic Agglutination with a 91% sensitivity and 94% specificity for Pomona. The study primarily addressed the effect of work position, personal protective equipment (PPE) and non-work related exposures such as hunting on a new infection with Pomona. Significantly associated with Pomona were “Work position” and two “Abattoirs” (GLM), and “Work position” (ABN). The odds of Pomona infection (OR, [95% CI]) was highest at stunning and hide removal (ABN 41.0, [6.9-1044.2]; GLM 57.0, [6.9-473.3]), followed by removal of intestines, bladder, and kidneys (ABN 30.7, [4.9-788.4]; GLM 33.8, [4.2-271.1]). Wearing a facemask, glasses or gloves (PPE) did not result as a protective factor in GLM or ABN. Conclusions/Significance The odds of Pomona infection was highest at stunning and hide removal. PPE did not show any indication of being protective in GLM or ABN. In ABN all relationships between variables are modelled; hence it has an advantage over GLM due to its capacity to capture the natural complexity of data more effectively.

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Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Mathematics
07 Faculty of Science > Institute for Computational Science
05 Vetsuisse Faculty > Chair in Veterinary Epidemiology
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Language:English
Date:2017
Deposited On:09 May 2017 13:21
Last Modified:07 May 2018 00:01
Publisher:Elsevier
ISSN:0001-706X
Funders:Swiss National Science Foundation (PBBEBS-124186, SNF138562 and SNF144973), Rural Woman New Zealand, and commissioned by the Tertiary Education Commission (TEC) via the Institute of Veterinary, Animal and Biomedical Sciences, Massey University (TEC #RM12703 (2008)),
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.actatropica.2017.04.034
Project Information:
  • : FunderSNSF
  • : Grant ID
  • : Project TitleSwiss National Science Foundation (PBBEBS-124186, SNF138562 and SNF144973)
  • : Funder
  • : Grant ID
  • : Project TitleRural Woman New Zealand, and commissioned by the Tertiary Education Commission (TEC) via the Institute of Veterinary, Animal and Biomedical Sciences, Massey University (TEC #RM12703 (2008)),

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