Literature DB >> 32497888

Do food and stress biomarkers work for wastewater-based epidemiology? A critical evaluation.

P M Choi1, D A Bowes2, J W O'Brien3, J Li4, R U Halden2, G Jiang5, K V Thomas3, J F Mueller3.   

Abstract

Dietary characteristics and oxidative stress are closely linked to the wellbeing of individuals. In recent years, various urinary biomarkers of food and oxidative stress have been proposed for use in wastewater-based epidemiology (WBE), in efforts to objectively monitor the food consumed and the oxidative stress experienced by individuals in a wastewater catchment. However, it is not clear whether such biomarkers are suitable for wastewater-based epidemiology. This study presents a suite of 30 urinary food and oxidative stress biomarkers and evaluates their applicability for WBE studies. This includes 22 biomarkers which were not previously considered for WBE studies. Daily per capita loads of biomarkers were measured from 57 wastewater influent samples from nine Australian catchments. Stability of biomarkers were assessed using laboratory scale sewer reactors. Biomarkers of consumption of vitamin B2, vitamin B3 and fibre, as well as a component of citrus had per capita loads in line with reported literature values despite susceptibility of degradation in sewer reactors. Consumption biomarkers of red meat, fish, fruit, other vitamins and biomarkers of stress had per capita values inconsistent with literature findings, and/or degraded rapidly in sewer reactors, indicating that they are unsuitable for use as WBE biomarkers in the traditional quantitative sense. This study serves to communicate the suitability of food and oxidative stress biomarkers for future WBE research.
Copyright © 2020. Published by Elsevier B.V.

Entities:  

Keywords:  Biomarkers; Diet; Food; Stress; Wastewater; Wastewater-based epidemiology

Year:  2020        PMID: 32497888     DOI: 10.1016/j.scitotenv.2020.139654

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  2 in total

1.  Artificial neural network-based estimation of COVID-19 case numbers and effective reproduction rate using wastewater-based epidemiology.

Authors:  Guangming Jiang; Jiangping Wu; Jennifer Weidhaas; Xuan Li; Yan Chen; Jochen Mueller; Jiaying Li; Manish Kumar; Xu Zhou; Sudipti Arora; Eiji Haramoto; Samendra Sherchan; Gorka Orive; Unax Lertxundi; Ryo Honda; Masaaki Kitajima; Greg Jackson
Journal:  Water Res       Date:  2022-04-13       Impact factor: 13.400

2.  Wastewater-based epidemiology in hazard forecasting and early-warning systems for global health risks.

Authors:  B Kasprzyk-Hordern; B Adams; I D Adewale; F O Agunbiade; M I Akinyemi; E Archer; F A Badru; J Barnett; I J Bishop; M Di Lorenzo; P Estrela; J Faraway; M J Fasona; S A Fayomi; E J Feil; L J Hyatt; A T Irewale; T Kjeldsen; A K S Lasisi; S Loiselle; T M Louw; B Metcalfe; S A Nmormah; T O Oluseyi; T R Smith; M C Snyman; T O Sogbanmu; D Stanton-Fraser; S Surujlal-Naicker; P R Wilson; G Wolfaardt; C O Yinka-Banjo
Journal:  Environ Int       Date:  2022-02-14       Impact factor: 9.621

  2 in total

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