ArticlePLOS global public health2025
Pregnancy loss and its predictors among ever-pregnant women in Sub-Saharan Africa: Multilevel mixed effect negative binomial regression.
Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Geospatial Variation and Determinants of Time to Pregnancy Loss Among Reproductive-Aged Women in East Africa: Bayesian Spatial Frailty Model.BioMed research international · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPregnancy loss is a significant maternal health issue in Sub-Saharan Africa. Africa has the highest rates of stillbirths globally, with an estimated 2.7 million stillbirths occurring each year on the continent. The pregnancy loss data are underreported and inconsistently recorded in Sub-Saharan Africa. Therefore, this study aimed to determine the number of pregnancy loss and its predictors among ever-pregnant women in Sub-Saharan Africa using a recent round of demographic and health survey (DHS) data.
methodA secondary data analysis was conducted among 235,086 weighted ever-pregnant women in Sub-Saharan Africa using a recent round of DHS data from 2015-2023. Multilevel mixed effect negative binomial regression was conducted. An adjusted incidence rate ratio (AIRR) with a 95% confidence interval (CI) was reported.
resultThe median number of pregnancy loss in Sub-Saharan Africa is 2.67, 95%CI (2.64, 2.69). A one-year increase in maternal age [AIRR= 1.05, 95%CI (1.06, 1.07)], primary educational status of the mother [AIRR = 1.10, 95% CI (1.01, 1.22)], women with a partner who has higher education [AIRR= 1.18, 95% CI (1.04, 1.39)], a higher number of under-five children [AIRR =0.95, 95% CI (0.91,0.99)], women have ever pregnant in Cote'divore [AIRR 1.76, 95% CI (1.6, 2)] are associated with the number of pregnancy loss.
conclusionThe findings indicate that there are three pregnancy losses among ever-pregnant women in Sub-Saharan Africa. Notably, a one-year increase in maternal age and higher education levels for both mothers and their partners are linked to an increased risk of pregnancy loss. In contrast, mothers with multiple children generally experience lower rates of loss. Therefore, policy interventions should address the heightened risk of pregnancy loss linked to advancing maternal age and higher education levels for both mothers and their partners. This can be achieved by supporting programs that educate prospective parents about the effects of maternal age on pregnancy outcomes. Furthermore, promoting flexible educational pathways and providing career support can encourage healthier timing for pregnancies. Additionally, initiatives that support families and promote larger family sizes may help reduce pregnancy loss rates in Sub-Saharan Africa.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.