Adolescent sexual and reproductive health in sub-Saharan Africa: who is left behind?
Bibliographic record
Abstract
Adolescent sexual and reproductive health (ASRH) continues to be a major public health challenge in sub-Saharan Africa where child marriage, adolescent childbearing, HIV transmission and low coverage of modern contraceptives are common in many countries. The evidence is still limited on inequalities in ASRH by gender, education, urban-rural residence and household wealth for many critical areas of sexual initiation, fertility, marriage, HIV, condom use and use of modern contraceptives for family planning. We conducted a review of published literature, a synthesis of national representative Demographic and Health Surveys data for 33 countries in sub-Saharan Africa, and analyses of recent trends of 10 countries with surveys in around 2004, 2010 and 2015. Our analysis demonstrates major inequalities and uneven progress in many key ASRH indicators within sub-Saharan Africa. Gender gaps are large with little evidence of change in gaps in age at sexual debut and first marriage, resulting in adolescent girls remaining particularly vulnerable to poor sexual health outcomes. There are also major and persistent inequalities in ASRH indicators by education, urban-rural residence and economic status of the household which need to be addressed to make progress towards the goal of equity as part of the sustainable development goals and universal health coverage. These persistent inequalities suggest the need for multisectoral approaches, which address the structural issues underlying poor ASRH, such as education, poverty, gender-based violence and lack of economic opportunity.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".