Use of Intermittent Preventive Treatment among Pregnant Women in Sub-Saharan Africa: Evidence from Malaria Indicator Surveys
Bibliographic record
Abstract
Uptake of intermittent preventive therapy in pregnancy (IPTp) with sulfadoxine-pyrimethamine (IPTp-SP) is a clinically-proven method to prevent the adverse outcomes of malaria in pregnancy (MiP) for the mother, her foetus, and the neonates. The majority of countries in sub-Saharan Africa have introduced IPTp policies for pregnant women during the past decade. Nonetheless, progress towards improving IPTp coverage remains dismal, with widespread regional and socioeconomic disparities in the utilisation of this highly cost-effective service. In the present study, our main objective was to measure the prevalence of IPTp uptake in selected malaria-endemic countries in sub-Saharan Africa, and to investigate the patterns of IPTp uptake among different educational and wealth categories adjusted for relevant sociodemographic factors. For this study, cross-sectional data on 18,603 women aged between 15 and 49 years were collected from the Malaria Indicator Surveys (MIS) conducted in Burkina Faso, Ghana, Mali, Malawi, Kenya, Nigeria, Sierra Leone, and Uganda. The outcome variable was taking three doses of IPTp-SP in the last pregnancy, defined as adequate by the WHO. According to the analysis, the overall prevalence of taking three doses of IPTp-SP in the latest pregnancy was 29.5% (95% CI = 28.2⁻30.5), with the prevalence being highest for Ghana (60%, 95% CI = 57.1⁻62.8), followed by Kenya (37%, 95% CI = 35.3⁻39.2) and Sierra Leone (31%, 95% CI = 29.2⁻33.4). Women from non-poor households (richer-20.7%, middle-21.2%, richest-18.1%) had a slightly higher proportion of taking three doses of IPTp-SP compared with those from poorest (19.0%) and poorer (21.1%) households. Regression analysis revealed an inverse association between uptake of IPTp-SP and educational level. With regard to wealth status, compared with women living in the richest households, those in the poorest, poorer, middle, and richer households had significantly higher odds of not taking at least three doses of IPTp-SP during their last pregnancy. The present study concludes that the prevalence of IPTp-SP is still alarmingly low and is significantly associated with individual education and household wealth gradient. Apart from the key finding of socioeconomic disparities within countries, were the between-country variations that should be regarded as a marker of inadequate policy and healthcare system performance in the respective countries. More in-depth and longitudinal studies are required to understand the barriers to, and preferences of, using IPTp-SP among women from different socioeconomic backgrounds.
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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 | 0.000 |
| 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".