Drivers of anemia reduction among women of reproductive age in Senegal: a country case study
Bibliographic record
Abstract
BACKGROUND: In Senegal, anemia prevalence among women of reproductive age (WRA) decreased from 59% in 2005 to 54% in 2017. However, determinants of reduction in disease burden under challenging public health conditions have not been studied. OBJECTIVES: We aimed to conduct a systematic in-depth assessment of the quantitative and qualitative determinants of anemia reduction among WRA in Senegal between 2005 and 2017. METHODS: Standard Exemplars in Global Health methodology was used for quantitative analyses using Senegal's Demographic and Health Surveys. Qualitative analyses included a systematic literature review, program/policy analysis, and interviews with key stakeholders. A final Oaxaca-Blinder decomposition analysis (OBDA) evaluated the relative contribution of direct and indirect factors. RESULTS: Among non-pregnant women, mean hemoglobin (Hb) increased from 11.4 g/dL in 2005 to 11.7 g/dL in 2017 (P < 0.0001), corresponding to a 5%-point decrease in anemia prevalence (58% to 53%). However, inequities by geographical region, household wealth, women's educational attainment, urban compared to rural residence, and antenatal care during last pregnancy continue to persist. During this time period, several indirect nutrition programs were implemented, with stakeholders acknowledging the importance of these programs but agreeing there needs to be more consistency, evaluation, and oversight for them to be effective. Our OBDA explained 59% of the observed change in mean Hb, with family planning (25%), malaria prevention programs (17%), use of iron and folic acid (IFA) during last pregnancy (17%), and improvement in women's empowerment (12%) emerging as drivers of anemia decline, corroborating our qualitative and policy analyses. CONCLUSIONS: Despite a reduction in anemia prevalence, anemia remains a severe public health problem in Senegal. To protect the gains achieved to date, as well as accelerate reduction in WRA anemia burden, focused efforts to reduce gender and social disparities and improve coverage of health services, such as family planning, IFA, and antimalarial programs, are needed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".