Human Health Risk Assessment of Heavy Metals in Kampala (Uganda) Drinking Water
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".