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Record W2620800036 · doi:10.5539/jfr.v6n4p6

Human Health Risk Assessment of Heavy Metals in Kampala (Uganda) Drinking Water

2017· article· en· W2620800036 on OpenAlexvenueno aff
Michael Bamuwamye, Patrick Ogwok, Vivian Tumuhairwe, Richard Eragu, Henriettah Nakisozi, Patrick Engeu Ogwang

Bibliographic record

VenueJournal of Food Research · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
Fundersnot available
KeywordsHazard quotientArsenicCadmiumTap waterEnvironmental chemistryMercury (programming language)Environmental scienceEnvironmental healthToxicologyChemistryEnvironmental engineeringMedicineHeavy metals

Abstract

fetched live from OpenAlex

Levels of aluminium, arsenic, cadmium, chromium, copper, iron, mercury, manganese, nickel, lead and zinc in tap water, groundwater-fed protected spring and bottled water were determined. The cancer and non-cancer risks associated with ingestion of heavy metals (HM) were also assessed for both children and adults. Forty seven water samples obtained from five divisions of Kampala city were analyzed using atomic absorption spectrophotometry. Cancer and non-cancer risks were determined using incremental lifetime cancer risk (ILCR) and non-carcinogenic hazard quotient (HQ), respectively. Lead content was higher than permissible limits (PL) according to East African Standard, World Health Organization, European Union and United States Environmental Protection Agency (USEPA). Arsenic showed minor exceedances above guideline values in tap water and groundwater-fed protected spring, whereas mercury, manganese and nickel were higher than PL. Levels of aluminium, cadmium, chromium, copper, iron, and zinc were below the PL. The lifetime risk of developing cancer through the oral route was greater than the USEPA acceptable level for both children and adults, revealing that exposure to HM in drinking water posed an unacceptable potential cancer risk. Arsenic contributed ca. 90% of the ILCR in tap water and groundwater-fed protected spring. The combined non-cancer risk of the HM expressed as hazard index (HI) was greater than one, with values for children being higher than those for adults. Lead contribution towards HI was in all cases above 90%. These results demonstrate the presence of alarming non-cancer risks for children.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.119
GPT teacher head0.451
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations84
Published2017
Admission routes1
Has abstractyes

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