HERisk and statistical clustering integrated for health risk modelling of PTEs in natural water resources for drinking and sanitary uses

  • Johnson C. Agbasi
  • , Daniel A. Ayejoto
  • , Johnbosco C. Egbueri*
  • , Nazia Khan
  • , Sani I. Abba
  • , Varish Ahmad
  • , Mohammed F. Abuzinadah
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

Potentially toxic elements (PTEs) are well-known for exposing living organisms and humans to different levels of risk. The present study aimed to evaluate the extent of exposure to health risks sustained by the inhabitants of different suburbs across Southeastern Nigeria as a result of contaminated water sources. There are existing literatures on human health risk assessment in the study region. However, this is the first study to report a detailed breakdown of the risks faced by nine age groups in the study area. This was achieved by integrating a novel code (HERisk), statistical clustering, and water quality data. Laboratory analysis showed that the levels of PTEs (Fe2+, Ni2+, Cr3+, and Pb2+) in 53.6%, 17.8%, 3.5%, and 46% of the samples were found to be above the recommended limits. Aggregated human health risk scores for ingestion and dermal routes revealed that children aged 1 to 2 years are the most vulnerable to health hazards. According to cumulative carcinogenic health risk values (0.00E+00 to 2.41E-04), samples proximal to regions with significant human activities expose the locals to a high risk of developing cancer via ingestion. Q-mode hierarchical cluster analysis successfully validated the classification schemes used for the interpretation of the HERisk code values, captured the patterns in the dataset, and brought forth new perspectives. The comprehensive approach detailed in this study can be adopted as a framework for ongoing monitoring and assessment of water quality.

Original languageEnglish
Pages (from-to)513-539
Number of pages27
JournalToxin Reviews
Volume43
Issue number4
DOIs
StatePublished - 2024

Bibliographical note

Publisher Copyright:
© 2024 Informa UK Limited, trading as Taylor & Francis Group.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation

Keywords

  • Cancer
  • Nigeria
  • Q-mode hierarchical clustering
  • water quality

ASJC Scopus subject areas

  • Toxicology

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