Factors associated with motherhood among urban refugee adolescent girls and young women in informal settlements in Kampala, Uganda
Bibliographic record
Abstract
Adolescent girls and young women (AGYW) in sub-Saharan Africa face a high risk of unintended pregnancy. This risk is compounded in informal settlements, where resources are scarce and access to sexual and reproductive health services is limited. Being a young mother in informal settlements could exacerbate existing experiences of resource scarcity and poor access to sexual and reproductive health services. To explore this, we analyzed the factors associated with motherhood among refugee AGYW in Kampala, Uganda. Between January and March 2018, peer researchers recruited refugee youth aged 15-24 and living in five informal settlements in Kampala to participate in this study. We used a backwards generalized linear model with a log binomial regression to determine if mental health, resource insecurity and sexual and reproductive health variables were associated with motherhood among study participants. Our analysis included 333 AGYW with a mean age of 19.3 years (standard deviation: 2.6). Nearly one-quarter (23 percent; n = 76) of AGYW had children. Having children was associated with greater likelihood of reporting food insecurity (adjusted prevalence ratio [aPR]: 1.96, 95 percent confidence interval [CI]: 1.07-3.61), depressive symptoms (aPR: 2.03, 95 percent CI: 1.09-3.80), and contraception uptake (aPR: 2.37, 95 percent CI: 1.58-3.56) compared to not having children. Mental health and resource insecurity interventions are required for refugee AGYW with children in informal settlements. Sexual and reproductive health services should be promoted to refugee AGYW regardless of motherhood status to prevent unplanned pregnancy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 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".