Differences in physical and mental health symptoms among residents living near municipal solid waste sites: a cross sectional study in the Ashanti Region, Ghana
Bibliographic record
Abstract
OBJECTIVE: Physical and mental health concerns and symptoms, including sleep problems, low mood, extreme tiredness, and appetite loss are prevalent among people living near waste sites. This research examines differences in health symptoms among residents living near municipal solid waste sites in the Ashanti Region, Ghana. METHODS: The study used cross-sectional data from 827 residents living near three municipal waste sites, including Besease, Asokore, and Dompoase sites in the Ashanti Region, Ghana. Descriptive statistics, Pearson's chi-square, and binary logistic regressions were performed to examine the differences and associations between the variables. RESULTS: Health symptoms, including sleep problems/insomnia, frequent extreme tiredness, low mood, loss of appetite, stress, anxiety, and depression, were reported by the majority of the participants. Residents near open dumpsites (Besease and Asokore) exhibit significantly higher likelihoods of experiencing various health symptoms such as extreme fatigue, depression, psychological disorders, thinking and concentration problems, low mood, loss of appetite, and anxiety compared to those near the engineered Oti landfill in Dompoase. CONCLUSION: While emphasizing the importance of proper landfill design and management in Ghana, this study underscores the need for further longitudinal and clinical investigations. Clinically establishing the link between dumpsites and health symptoms is imperative for informed public health interventions and policy decisions aimed at mitigating the potential adverse health effects of landfills on residents' well-being.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".