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Record W4414530931 · doi:10.1186/s12302-025-01193-8

Public health burden of polycyclic aromatic hydrocarbons in the East African environment: a systematic review

2025· article· en· W4414530931 on OpenAlex
Godswill J. Udom, Nicodemus Niwamanya, Omoirri Moses Aziakpono, Nita-wills G. Udom, H. Malathi, Harshit Gupta, Shirin Shomurotova, Ilemobayo Victor Fasogbon, Hope Onohuean, Patrick Maduabuchi Aja, Orish Ebere Orisakwe, Fatima Razaki, Jerome O. Nriagu, Khursheed Muzammil

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnvironmental Sciences Europe · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsnot available
FundersKing Khalid University
KeywordsPublic healthAir quality indexPsychological interventionEnforcementSocioeconomic statusGlobal healthSustainable developmentEnvironmental justice

Abstract

fetched live from OpenAlex

Polycyclic aromatic hydrocarbons (PAHs) are toxic substances formed during the incomplete burning of organic matter, and they pose major threats to human health and the environment. This systematic review assesses the public health burden of PAH exposure in East Africa, focusing on sources, health effects, and mitigation strategies. East Africa is experiencing rapid urbanization, industrial growth, and increasing reliance on biomass fuels, all of which contribute to elevated environmental PAH levels. Despite these developments, the region remains underrepresented in global PAH risk assessments, with limited localized data guiding policy and public health responses. This geographic focus is thus critical to identify context-specific exposure sources, assess the unique vulnerabilities of East African populations, and support targeted mitigation strategies aligned with regional socioeconomic and environmental realities. Using the PRISMA framework, studies were screened for quality and bias via the Newcastle–Ottawa Scale and JBI checklists, with 20 out of 183 articles meeting the inclusion criteria. Key exposure sources include biomass and fossil fuel combustion, urban air pollution, industrial emissions, occupational hazards, and dietary intake. Vulnerable groups, particularly women, children, and low-income urban dwellers, face heightened risks, including the risk of respiratory diseases, cardiovascular disorders, cancer, adverse birth outcomes, and neurodevelopmental impairments. Despite growing concerns, policy gaps, weak enforcement of air quality standards, and limited public awareness hinder effective mitigation. Therefore, urgent interventions are needed, including clean energy adoption, urban air pollution control, industrial regulations, and stronger public health policies. To address PAH exposure in East Africa, a multi-sectoral approach integrating policy reforms, community engagement, and sustainable environmental practices to protect public health is imperative.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.895

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.028
GPT teacher head0.233
Teacher spread0.206 · 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