Deprivation and Its Association with Child Health and Nutrition in the Greater Kampala Metropolitan Area of Uganda
Bibliographic record
Abstract
African cities are experiencing increasing living standard disparities with limited evidence of intra-urban health disparities. Using data from the 2006-2016 Uganda Demographic and Health Surveys, we employed the UN-Habitat definition to examine slum-like household conditions in the Greater Kampala Metropolitan Area (GKMA). Subsequently, we developed a slum-like severity index and assessed its association with under-5 common morbidities and healthcare access. We also assessed the characteristics of people in slum-like household conditions. We identified five slum-like conditions: substandard housing conditions, limited water access, overcrowding, unclean cooking fuel, and limited toilet access. By 2016, 67% of GKMA households were classified as slum-like conditions, including 31% in severe conditions. Limited toilet access, overcrowding, and limited water access were the main forms of deprivation.Living in slum-like household conditions correlated with lower education levels, youth status, unprofessional jobs, and marriage. Compared to neighboring Kampala city urban outskirts, Kampala city households had lower slum-like prevalence. Children in GKMA living in slum-like household conditions were more likely to experience diarrhea (moderate: OR = 1.21[95% CI: 1.05-1.39], severe: OR = 1.47 [95% CI: 1.27-1.7]); fever (moderate: OR = 2.67 [95% CI: 1.23-5.8], severe: OR = 3.09 [95% CI: 1.63-5.85]); anemia (moderate: OR = 1.18 [95% CI: 0.88-1.58], severe: OR = 1.44 [95% CI: 1.11-1.86]); and stunting (moderate: OR = 1.23 [95% CI: 1.23-1.25], severe: OR = 1.40 [95% CI: 1.41-1.47]) compared to those living in less slum-like conditions. However, seeking treatment for fever was less likely in slum-like household conditions, and the association of slum-like household conditions with diarrhea was insignificant. These findings underscore the precarious urban living conditions and the need for targeted health interventions addressing the social determinants of health in urban settings.
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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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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".