Geospatial Distribution of Family Planning Services in Kira Municipality, Wakiso District, Uganda
Bibliographic record
Abstract
Introduction: Access to family planning (FP) services remains a challenge, particularly in informal urban settlements. The unmet need for FP in these settings is high, with a correspondingly high prevalence of unintended pregnancies that may lead to unsafe abortions. However, there is a paucity of quality data on the distribution of FP services in such settings in Uganda. This paper described the geospatial distribution of FP services in Kira Municipality, Wakiso District, Uganda. Methods: This was a cross-sectional study in which we determined the availability and distribution of FP services in Kira Municipality. Community mapping and analysis were conducted using ArcGIS (version 10.1) and ArcGIS Online. Stata version 13.1 was used for data analysis. Chi-square test was used to compare the contraceptive provision and availability among facilities from informal and formal settlements. Results: Of the 176 healthcare facilities surveyed, only 42% ( n = 74) offered contraceptives in informal settlements. The majority of the facilities were privately owned small clinics (95%). At least 80% of the facilities provided three or more modern contraceptive methods, with no difference ( p = 0.107) between facilities in informal and formal settlements. Only 30.7% ( p = 0.001) of the facilities provided at least one long-acting contraceptive. Similarly, 20 and 12% ( p = 0.001) of the facilities had implants and intrauterine devices (IUDs) on the day of the survey. Almost 25% of the facilities did not offer contraceptive services (counseling and commodities) to unmarried adolescents. Conclusions: Most facilities were small privately-owned clinics, offering at least three modern contraceptive methods. The unavailability of long-acting reversible methods in the informal settings may affect the quality of FP services due to limited choice. The inequity in service provision that disfavors the unmarried adolescent may increase unwanted/unintended pregnancies. We recommend that local governments and partners work toward filling the existing commodities gap and addressing the discrimination against unmarried adolescents in such 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".