The University of Southampton
University of Southampton Institutional Repository

Applicability and feasibility of systematic review for performing evidence-based risk assessment in food and feed safety

Applicability and feasibility of systematic review for performing evidence-based risk assessment in food and feed safety
Applicability and feasibility of systematic review for performing evidence-based risk assessment in food and feed safety
Food and feed safety risk assessment uses multi-parameter models to evaluate the likelihood of adverse events associated with exposure to hazards in human health, plant health, animal health, animal welfare, and the environment. Systematic review and meta-analysis are established methods for answering questions in health care, and can be implemented to minimize biases in food and feed safety risk assessment. However, no methodological frameworks exist for refining risk assessment multi-parameter models into questions suitable for systematic review, and use of meta-analysis to estimate all parameters required by a risk model may not be always feasible. This paper describes novel approaches for determining question suitability and for prioritizing questions for systematic review in this area. Risk assessment questions that aim to estimate a parameter are likely to be suitable for systematic review. Such questions can be structured by their "key elements" [e.g., for intervention questions, the population(s), intervention(s), comparator(s), and outcome(s)]. Prioritization of questions to be addressed by systematic review relies on the likely impact and related uncertainty of individual parameters in the risk model. This approach to planning and prioritizing systematic review seems to have useful implications for producing evidence-based food and feed safety risk assessment.
evidence synthesis, meta-analysis, risk model, transparency, uncertainty
1040-8398
1026-1034
Aiassa, E.
fb392cd2-b86e-49a7-b5c2-3bae8e2205bd
Higgins, J.P.
087923c0-d3fe-4f0d-9b6d-9558ceb29512
Frampton, Geoff
26c6163c-3428-45b8-b8b9-92091ff6c69f
Greiner, M.
be534388-ca29-427b-8653-c267002cfad2
Alfonso, A.
e67527ef-2635-40ba-a91e-f44445e26107
Amzal, B.
390f8684-5583-46a5-90e1-53d31f4a16a0
Deeks, J.
d40b602a-d2c3-447a-a5b4-28ff6828a8f7
Dorne, J.L.
b8c3f762-57b5-4082-a290-a7ca22efaeb0
Glanville, J.
8f03bd66-069e-4e68-b4eb-b7549edce062
Lövei, G.L.
35044807-4294-47b1-9889-7b67e550be66
Nienstedt, K.
8c1e80f2-7ca4-4ae2-ba58-77b29ac7c14a
O'Connor, A.M.
9b5cec9f-857a-4cbb-8f94-923fdc538675
Pullin, A.S.
bad5219c-e419-41b2-8722-81bd98907668
Rajić, A.
653226f3-10df-495f-93a9-caa30483e1e8
Verloo, D.
ed7236fc-2dda-40f1-b361-4c5da955ff0a
Aiassa, E.
fb392cd2-b86e-49a7-b5c2-3bae8e2205bd
Higgins, J.P.
087923c0-d3fe-4f0d-9b6d-9558ceb29512
Frampton, Geoff
26c6163c-3428-45b8-b8b9-92091ff6c69f
Greiner, M.
be534388-ca29-427b-8653-c267002cfad2
Alfonso, A.
e67527ef-2635-40ba-a91e-f44445e26107
Amzal, B.
390f8684-5583-46a5-90e1-53d31f4a16a0
Deeks, J.
d40b602a-d2c3-447a-a5b4-28ff6828a8f7
Dorne, J.L.
b8c3f762-57b5-4082-a290-a7ca22efaeb0
Glanville, J.
8f03bd66-069e-4e68-b4eb-b7549edce062
Lövei, G.L.
35044807-4294-47b1-9889-7b67e550be66
Nienstedt, K.
8c1e80f2-7ca4-4ae2-ba58-77b29ac7c14a
O'Connor, A.M.
9b5cec9f-857a-4cbb-8f94-923fdc538675
Pullin, A.S.
bad5219c-e419-41b2-8722-81bd98907668
Rajić, A.
653226f3-10df-495f-93a9-caa30483e1e8
Verloo, D.
ed7236fc-2dda-40f1-b361-4c5da955ff0a

Aiassa, E., Higgins, J.P., Frampton, Geoff, Greiner, M., Alfonso, A., Amzal, B., Deeks, J., Dorne, J.L., Glanville, J., Lövei, G.L., Nienstedt, K., O'Connor, A.M., Pullin, A.S., Rajić, A. and Verloo, D. (2014) Applicability and feasibility of systematic review for performing evidence-based risk assessment in food and feed safety. Critical Reviews in Food Science and Nutrition, 55 (7), 1026-1034. (doi:10.1080/10408398.2013.769933). (PMID:25191830)

Record type: Article

Abstract

Food and feed safety risk assessment uses multi-parameter models to evaluate the likelihood of adverse events associated with exposure to hazards in human health, plant health, animal health, animal welfare, and the environment. Systematic review and meta-analysis are established methods for answering questions in health care, and can be implemented to minimize biases in food and feed safety risk assessment. However, no methodological frameworks exist for refining risk assessment multi-parameter models into questions suitable for systematic review, and use of meta-analysis to estimate all parameters required by a risk model may not be always feasible. This paper describes novel approaches for determining question suitability and for prioritizing questions for systematic review in this area. Risk assessment questions that aim to estimate a parameter are likely to be suitable for systematic review. Such questions can be structured by their "key elements" [e.g., for intervention questions, the population(s), intervention(s), comparator(s), and outcome(s)]. Prioritization of questions to be addressed by systematic review relies on the likely impact and related uncertainty of individual parameters in the risk model. This approach to planning and prioritizing systematic review seems to have useful implications for producing evidence-based food and feed safety risk assessment.

Text
__soton.ac.uk_ude_PersonalFiles_Users_gkf1_mydesktop_Aiassa 2014 Systematic Review Food Feed Safety.pdf - Accepted Manuscript
Download (426kB)

More information

e-pub ahead of print date: 5 August 2014
Keywords: evidence synthesis, meta-analysis, risk model, transparency, uncertainty
Organisations: Faculty of Medicine

Identifiers

Local EPrints ID: 383599
URI: http://eprints.soton.ac.uk/id/eprint/383599
ISSN: 1040-8398
PURE UUID: 86eb1a16-990a-477c-a7b3-70a747fd3b6f
ORCID for Geoff Frampton: ORCID iD orcid.org/0000-0003-2005-0497

Catalogue record

Date deposited: 24 Nov 2015 11:33
Last modified: 18 Feb 2021 16:41

Export record

Altmetrics

Contributors

Author: E. Aiassa
Author: J.P. Higgins
Author: Geoff Frampton ORCID iD
Author: M. Greiner
Author: A. Alfonso
Author: B. Amzal
Author: J. Deeks
Author: J.L. Dorne
Author: J. Glanville
Author: G.L. Lövei
Author: K. Nienstedt
Author: A.M. O'Connor
Author: A.S. Pullin
Author: A. Rajić
Author: D. Verloo

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×