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. 2025 Sep 30;25:978. doi: 10.1186/s12884-025-07998-y

Magnitude and predictors of gestational trophoblastic disease in East Africa: a systematic review and meta-analysis

Gizachew Yilak 1,✉, Befkad Derese Tilahun 1, Amsalu Baylie Taye 1, Bogale Molla 1, Addisu Getie 2, Dejen Tsegaye 2,3, Mulat Ayele 4, Eyob Shitie Lake 4
PMCID: PMC12487570  PMID: 41029567

Abstract

Introduction

Gestational Trophoblastic Disease (GTD) encompasses a spectrum of placenta-related disorders with significant health risks. Despite the varying reported prevalence rates in East Africa, no comprehensive meta-analysis has been conducted to synthesize the overall burden and predictors of GTD in this region.

Methods

Following the PRISMA guidelines, we conducted a systematic review and meta-analysis of studies from PubMed, Cochrane Library, and Google Scholar (search period: 2000–2024). We assessed heterogeneity (I2 and Q tests), pooled estimates using a random-effects model, and evaluated publication bias using funnel plots and Egger’s test. A sensitivity analysis was performed to test the robustness of the findings.

Results

Eleven studies were included, revealing a pooled GTD magnitude of 10.5% (95% CI: 8.8–12.3; I2 = 100%, p < 0.001). Significant predictors included prior GTD history (AOR = 3.2, 95% CI: 0.6–5.7; I2 = 75.2%, p = 0.018) and grand multiparity (AOR = 8.9, 95% CI: 2.8–15.1; I2 = 76%, p = 0.041). Subgroup analysis showed that complete molar pregnancies (37.8%, 95% CI: 5.9–69.8) were more prevalent than partial molar pregnancies (11.8%, 95% CI: 9.7–13.9), both with high heterogeneity (I2 = 100%, p < 0.001).

Conclusion

Gestational trophoblastic disease remains a significant public health burden in East Africa, where delayed healthcare access contributes to worsened outcomes. Women with a history of gestational trophoblastic disease or high parity constitute high-risk populations that require targeted screening programs and early intervention strategies to improve their detection and management.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-025-07998-y.

Keywords: Gestational trophoblastic disease, Molar pregnancy, Hydatidiform mole, Choriocarcinoma, East Africa

Introduction

Gestational trophoblastic disease (GTD) represents a spectrum of pregnancy-related disorders originating from the abnormal proliferation of trophoblastic tissue, encompassing benign hydatidiform moles (complete and partial) and malignant gestational trophoblastic neoplasms. Characterized by elevated β-hCG secretion, GTD presents clinically with vaginal bleeding, uterine enlargement disproportionate to gestational age, and the absence of fetal heart tones [1–3]. While highly curable with proper management, particularly in developed nations, GTD remains a significant contributor to maternal morbidity and mortality in resource-limited settings, such as East Africa, where delayed diagnosis and limited access to specialized care are major challenges [4–6].

Gestational trophoblastic disease (GTD) is characterized by the secretion of a specific tumor marker, beta-human chorionic gonadotropin (β-hCG). This condition is highly treatable, even in cases of metastasis. Common clinical manifestations include amenorrhea, vaginal bleeding in the early trimester, spontaneous passage of grape-like vesicles, an enlarged uterus compared to the gestational age, and absence of fetal parts after 20 weeks of gestation. Ultrasonography is a reliable, noninvasive diagnostic tool for GTD in clinical practice [1, 2, 7].

The global epidemiology of GTD reveals striking geographical variations, with incidence rates in East Africa ranging from 2.8 to 11.4 cases per 1,000 deliveries, which is markedly higher than the 0.6–2.6 per 1,000 pregnancies reported in Western countries. This disparity likely reflects differences in the prevalence of risk factors, diagnostic capabilities and healthcare infrastructure [8–10].

Extensive research has identified several well-established predictors of GTD, including extremes of maternal age (< 15 or > 45 years), prior molar pregnancy (10–20 × increased risk), multiparity, and nutritional deficiencies (particularly carotene and folic acid deficiency). Emerging evidence also suggests the involvement of genetic factors and environmental exposure) [1, 2, 11].

Despite this growing understanding of GTD risk factors, critical gaps remain in the East African context. Existing studies from the region show concerning inconsistencies in reported prevalence estimates and risk factor associations in the region. For instance, hospital-based studies in Ethiopia report a prevalence ranging from 1.8 to 11.4 per 1,000 deliveries, whereas data from Tanzania and Kenya show similarly wide variations [12–15].

This systematic review and meta-analysis addressed crucial knowledge gaps in the burden of gestational trophoblastic disease in East Africa by providing the first comprehensive regional prevalence estimate while evaluating both established and local risk factors. As the most extensive study of its kind across 11 East African countries, our rigorous analysis cuts through conflicting data to reveal where diagnostic resources and screening programs are urgently needed. For healthcare providers, we offer clear clinical thresholds for early detection, and for policymakers, robust evidence to strengthen maternal health systems, from expanding ultrasound access in remote areas to ensuring the availability of chemotherapy. By transforming fragmented research into actionable insights, this study provides the missing link between GTD science and life-saving interventions, offering a roadmap for reducing preventable maternal deaths across the region.

Methods

Reporting

This systematic review rigorously followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [16], with the completed checklist available in the Supplementary Materials for full transparency.

Search strategy and information sources

We systematically searched PubMed, the Cochrane Library, and Google Scholar for studies reporting data on the magnitude and risk factors of GTD in East Africa. Our search strategy incorporated Medical Subject Headings (MeSH) terms, keyword combinations, and snowball searching through reference lists of identified articles. For studies with incomplete or ambiguous data, we contacted the corresponding author for clarification. Additionally, we retrieved unpublished studies and grey literature from the official websites of relevant international organizations, local institutions and university repositories.

Our comprehensive literature search employed Medical Subject Headings (MeSH) terms and keywords related to gestational trophoblastic diseases in East Africa, including “molar pregnancy,” “hydatidiform mole,” “gestational trophoblastic neoplasia,” and “placental site trophoblastic tumor.” We systematically combined these terms using Boolean operators (AND/OR) to develop optimized search strings, with the PubMed search strategy specifically structured as follows: (prevalence OR magnitude OR epidemiology) AND (risk factors OR determinants OR predictors) AND ("Hydatidiform mole"[MeSH] OR "gestational trophoblastic disease"[MeSH]) AND ("molar pregnancy"[MeSH]) AND ("East Africa"). This methodology enabled the sensitive retrieval of relevant publications while maintaining the search precision.

To ensure comprehensive coverage, we manually searched the reference lists of the included studies to identify additional relevant publications. All identified records were exported to EndNote version 8 (Clarivate Analytics), where duplicate removal and preliminary screenings were performed. Two independent investigators (GY and ESL) screened the titles and abstracts against the eligibility criteria prior to full-text retrieval. Following this initial assessment, the same reviewers evaluated the full-text articles using predefined inclusion and exclusion criteria. Any discrepancies in study selection were resolved through discussion with a panel of co-authors (MA, BDT, AG, DT, AW, and ABZ) during a consensus meeting to finalize the studies for inclusion in the systematic review and meta-analysis.

Inclusion and exclusion criteria

This meta-analysis incorporated observational (cross-sectional) studies published in English (2000–2024) examining either gestational trophoblastic disease (GTD) prevalence/magnitude or associated risk factors in East Africa, including relevant unpublished studies. The exclusion criteria comprised editorials, anonymous reports, qualitative studies, publications lacking abstracts/full texts, and studies with insufficient data on outcomes. Only studies involving confirmed GTD cases during active treatment or management were included.

Quality assessment

Following the database searches, duplicate articles were removed using EndNote X8 (Clarivate Analytics). Study quality was evaluated independently by four reviewers using the Joanna Briggs Institute (JBI) critical appraisal checklist [17, 18]. To ensure consistency, the reviewers conducted duplicate assessments of a subset of studies (10% random sample) through exchanged evaluation notes. Discrepancies in the quality ratings were resolved by calculating the mean scores. Based on the JBI criteria, studies scoring ≥ 5 (indicating low risk of bias/good quality) were included, while those scoring ≤ 4 (high risk/poor quality) were excluded from the meta-analysis.

Data extraction

We developed a standardized Excel-based extraction form to systematically collect key study characteristics, including author names, publication years, geographic regions, research designs, sample sizes, gestational trophoblastic disease (GTD) prevalence estimates and reported risk factor categories. Before full data extraction, we conducted a pilot test using four randomly selected studies to refine the extraction template. Two independent reviewers subsequently performed primary data extraction, which was verified by three other reviewers. Discrepancies between the reviewers were resolved by consensus. All extracted data were cross-verified against the original publications to ensure accuracy, and studies with incomplete data were excluded after two unsuccessful attempts to contact the corresponding authors of the studies.

Outcome measurement

Gestational trophoblastic disease (GTD) is characterized by abnormal placental trophoblast proliferation and can be diagnosed clinically (vaginal bleeding ± vesicles with molar ultrasound features), histologically, or incidentally via ultrasound [3].

Gestational Trophoblastic Neoplasia (GTN) is an umbrella term for malignant gestational trophoblastic diseases, including invasive moles, choriocarcinoma, and placental site trophoblastic tumors, characterized by abnormal post-gestational trophoblast proliferation, most commonly following molar pregnancy [19, 20].

Hydatidiform Mole (HM) is a benign form of gestational trophoblastic disease characterized by abnormal villous formation and distinct placental changes, classified histologically and genetically as either: complete hydatidiform mole (CHM) featuring diploid androgenetic conception, or partial hydatidiform mole (PHM) exhibiting triploid diandric fertilization [20].

Statistical analysis

After extracting the data in Microsoft Excel format, we imported them into STATA version 17.0 for further statistical analyses. The standard error for each study was computed using a binomial distribution formula. A random-effects meta-analysis was performed to estimate the pooled prevalence of gestational trophoblastic disease (GTD) [21]. Forest plots were generated to display the pooled prevalence with 95% confidence intervals (CIs) and odds ratios (ORs) with 95% CIs, illustrating the factors associated with GTD. Heterogeneity among studies was assessed using p-values, the inverse variance index (I2), and Cochran’s Q statistic (chi-square test) [18].

In this study, an I2 statistic value of zero indicated true homogeneity, whereas values of 25%, 50%, and 75% represented low, moderate, and high heterogeneity, respectively [21, 22]. A random-effects model was applied to the heterogeneous data set. Subgroup analyses were conducted based on sample size and publication year. When statistical pooling was not feasible, non-pooled data were summarized in tables. Sensitivity analysis was performed to evaluate the influence of individual studies on the overall estimates. Publication bias was assessed using funnel plots and validated using Egger’s regression test [23].

Results

Study selection

A total of 843 studies were identified through electronic database searches. After removing duplicates, 578 studies published between 2000 and 2024 were analyzed. Of these, 547 were excluded based on title screening. The remaining 31 studies underwent an abstract review, leading to the exclusion of 17 studies. Subsequently, 14 studies were assessed for full-text eligibility, and 11 articles (comprising 137,249 participants) met the inclusion criteria for the analysis of the prevalence of gestational trophoblastic disease (GTD) and its associated factors (Fig. 1).

Fig. 1.

Fig. 1

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PRISMA flow diagram of study selection for gestational trophoblastic disease research in East Africa

Characteristics of included studies

Table 1 presents the key characteristics of the 11 studies included in this systematic review and meta-analysis [1, 2, 4, 8, 9, 12–15, 24, 25]. Most studies (n = 6) were conducted in Ethiopia [2, 4, 8, 9, 12, 13], with single studies representing other East African nations: Eritrean [15], Uganda [14], Kenya [24], Rwanda [25], and Tanzania [1]. The publication dates of these studies predominantly fell between 2012 and 2021. The sample sizes exhibited considerable variation across studies, ranging from a modest cohort of 200 participants [1] to an extensive population of 33,438 participants [2] (Table 1).

Table 1.

Magnitude of gestational trophoblastic disease among pregnant women admitted to obstetric-gynecologic units in East Africa

Author/Reference Publication year Country Study design Sample size P Quality score
Biressew Wassihun et.al [4] 2020 Ethiopia Cross sectional 16,957 11 7/8
Admasu Taye et al. [8] 2019 Ethiopia Cross sectional 11,453 7.2 6/8
Yibrah Berhe et al. [9] 2019 Ethiopia Cross sectional 5185 8.6 7/8
Alemnew, Sara et al. [12] 2018 Ethiopia Cross sectional 16,247 6.3 6/8
Dereje Nigussie et.al [2] 2008 Ethiopia Cross sectional 33,438 2.8 7/8
Ahmed Barkadle et.al [13] 2022 Ethiopia Cross sectional 17,201 10.5 7/8
Dan K. Kaye [14] 2002 Uganda Cross sectional 27,485 3.42 7/8
Dawit Estifanos et.al [26] 2023 Eritrea Cross sectional 6845 6.6 5/8
Eunice Jeptoo [24] 2019 Kenya Cross sectional 454 23.6 6/8
D. Rwabizi et.al [25] 2016 Rwanda Cross sectional 1784 15 6/8
Mwajuma B. Et.al [1] 2022 Tanzania Cross sectional 200 21 7/8
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Meta-analysis of gestational trophoblastic disease magnitude and associated factors in East Africa

The included institution-based studies (n = 11) reported the magnitude of gestational trophoblastic disease (GTD). The observed magnitudes ranged from 2.8% [2] to 23.6% [24]. The random-effects meta-analysis yielded a pooled magnitude of 10.54% (95% CI: 8.84–12.24) across East African institutions, with significant heterogeneity (I2 = 100%, p < 0.001), as shown in (Fig. 2).

Fig. 2.

Fig. 2

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The pooled magnitude of gestational trophoblastic disease among all pregnant mothers admitted to obstetric and gynecologic unit in East Africa

Subgroup analysis of gestational trophoblastic disease magnitude

To explore the potential sources of heterogeneity, we conducted subgroup analyses stratified by sample size and year of publication. These stratifications were selected a priori because the sample size may influence detection rates in institutional studies, and the publication year may reflect temporal trends in diagnostic capabilities and disease patterns.

The overall pooled incidence of gestational trophoblastic disease (GTD) was 10.54% (95% CI: 8.84–12.24; I2 = 100%; p < 0.001) (Fig. 2). When stratified by sample size, studies with < 10,000 participants showed a higher GTD magnitude (10.54%; 95% CI: 8.84–50.40) than larger studies (6.87%; 95% CI: 4.57–9.17) (Fig. 3). Temporal analysis revealed that studies published since 2020 reported a significantly greater GTD magnitude (12.24%; 95% CI: 10.56–13.93) than those published before 2020 (9.55%; 95% CI: 8.41–10.70) (Fig. 4).

Fig. 3.

Fig. 3

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Subgroup analysis of gestational trophoblastic disease among all pregnant mothers admitted to obstetric and gynecologic units in East Africa by sample size

Fig. 4.

Fig. 4

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Subgroup analysis of gestational trophoblastic disease among all pregnant mothers admitted to obstetric and gynecologic units in East Africa by publication year

Sensitivity analysis

We employed a leave-one-out sensitivity analysis to assess the potential sources of heterogeneity in the estimated magnitude of gestational trophoblastic disease. Sensitivity analysis demonstrated that our findings were robust, and no study significantly influenced the results. The pooled magnitude estimates ranged from 40.85 (95% CI: 40.82–40.88) to 68.16 (95% CI: 68.10–68.21) after the sequential exclusion of individual studies (Table 2).

Table 2.

Sensitivity analysis of gestational trophoblastic disease among pregnant women in East Africa

Study omitted e۸ coef {95% conf. interval}
Biressew Wassihun 40.8380051 40.808769 40.867355
Admasu Taye et.al 49.506859 49.471592 49.542152
Yibrah Berhe et.al 52.726254 52.689087 52.763447
Alemnew Sara et.al 46.712925 46.679081 46.746796
Dereje Nigussie et.al 74.2235 74.01414 74.43306
Ahmed Barkadle et.al 40.856342 40.827003 40.8857
Dan K.Kaye 68.160477 68.103394 68.217598
Dawit Estifanos et.al 52.440571 52.403503 52.477661
Eunice Jeptoo 53.798862 53.761021 53.836727
D. Rwabizi et.al 53.62402 53.5863 53.66177
Mwajuma B. et.al 53.811565 53.773716 53.849438
Combined 53.814408 53.776559 53.852284
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Publication bias

We assessed publication bias using both visual inspection of funnel plots and Egger’s regression test. The funnel plot demonstrated a symmetrical distribution (Fig. 5), while Egger’s test showed significant small-study effects (p = 0.018), suggesting a potential publication bias. To address this, we performed a trim-and-fill analysis, which imputed six additional studies, bringing the total number to 17. The adjusted pooled prevalence of gestational trophoblastic disease was 2.03% (95% CI: 1.18–2.87), with no observed heterogeneity (I2 = 0.0%, p = 0.83) (Fig. 6).

Fig. 5.

Fig. 5

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Sensitivity analysis for gestational trophoblastic disease among pregnant women admitted to obstetric and gynecologic units in East Africa

Fig. 6.

Fig. 6

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Publication bias in studies of gestational trophoblastic disease among pregnant women admitted to obstetric and gynecologic units in East Africa

Type of molar pregnancy

Among the included studies, six (10, 12, 13, 25, 28, 29) examined the risk factors for complete molar pregnancy in East Africa, reporting a pooled prevalence of 37.84% (95% CI: 5.85–69.83) (Fig. 7). Five studies (8, 13, 15, 18, 19) investigated partial molar pregnancy, with a pooled prevalence of 11.78% (95% CI: 9.67–13.89) (Fig. 7).

Fig. 7.

Fig. 7

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Magnitude of molar pregnancy among pregnant women admitted to obstetric and gynaecologic units in East Africa

Predictors of gestational trophoblastic disease

Three of the included studies identified a significant association between gestational trophoblastic disease (GTD) and a history of GTD among pregnant women in East Africa. The strongest predictor was an adjusted odds ratio (AOR) of 5.2 (95% CI: 1.96–8.43), while the weakest association had an AOR of 1.4 (95% CI: 0.74–2.06). These risk estimates were compared with those of their respective reference groups (Fig. 8). Moreover, two of the included studies identified a significant association between gestational trophoblastic disease (GTD) and grand multiparity among pregnant women from East Africa. The strongest predictor was an adjusted odds ratio (AOR) of 12.3 (95% CI: 1.75–41.93), while the weakest association showed an AOR of 6.0 (95% CI: 5.2–63). These risk estimates were compared with those of the respective reference groups.

Fig. 8.

Fig. 8

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Predictors of gestational trophoblastic disease among pregnant women admitted to obstetric and gynecologic units in East Africa

Discussion

This systematic review and meta-analysis aimed to examine the magnitude of gestational trophoblastic disease and identify its predictors in East Africa. Eleven studies met the inclusion criteria. All studies provided data on the magnitude of gestational trophoblastic disease. The pooled analysis showed that the overall estimated incidence of gestational trophoblastic disease in East Africa was 10.54% (95% CI: 8.84–12.25).

This study found that the magnitude of gestational trophoblastic disease (GTD) in East Africa was 10.54% (95% CI: 8.84–12.25). This prevalence is substantially higher than the rates reported in other regions: 0.23% in a teaching hospital in Northern Nigeria, 0.47% in Port Harcourt, Nigeria, 0.72% at ABUTH Zaria, Nigeria, 0.14% in the Asian population of Northern England and North Wales, and 0.36% at the Institute of Sassari [27–31]. The higher incidence of gestational trophoblastic disease (GTD) in East Africa compared to developed nations likely stems from disparities in healthcare access, including limited preconception and antenatal care services, as well as fewer large-scale epidemiological studies in the region. To address this gap, targeted public health initiatives, such as community education in local languages on GTD symptoms and early care-seeking, along with strengthened healthcare infrastructure (expanded diagnostic facilities, trained medical personnel, and improved equipment availability), are urgently needed to enhance early detection and improve treatment outcomes.

The global epidemiology of gestational trophoblastic disease reveals profound disparities, with our East African cohort demonstrating the highest reported burden (10.54% prevalence rate). This markedly exceeds the magnitude in both Southeast Asia (1.2% in Indonesia) and the Middle East (1.7% in Turkey) [32, 33], while these regions themselves the rates are substantially higher than those documented in industrialized nations (0.14–0.72%). Such dramatic variations, spanning nearly two orders of magnitude across developmental contexts, likely reflect complex interactions between population genetic susceptibility, healthcare system capacity for early prenatal diagnosis, and regional differences in diagnostic standardization. The disparity between our high-risk East African population and low-magnitude settings highlights the need for context-specific public health strategies addressing the entire spectrum, from primary prevention to tertiary care management.

This systematic review identified several significant risk factors for gestational trophoblastic disease (GTD) in East Africa, including a history of GTD, multiparity (particularly ≥ 5 pregnancies), and spontaneous abortion. These findings are consistent with studies from distinct Nigerian tertiary centers, including a regional hospital in Southeast Nigeria and Nnewi Specialist Hospital [34–36]. The demonstrated recurrence risk among East African women with previous GTD underscores the need for enhanced postnatal surveillance. We recommend implementing routine postpartum monitoring for high-risk women (those with high parity, a history of pregnancy loss, or prior GTD), patient education programs emphasizing early symptom recognition, and integrated reproductive health services that combine family planning, genetic counseling, and risk-reduction strategies. Such multifaceted approaches could significantly improve early detection and reduce the disease burden.

This comprehensive review and meta-analysis found that 37.84% (range: 5.85–69.83%) of cases were complete hydatidiform moles, while 11.78% (range: 9.67–13.90%) were partial moles. Our findings are consistent with those of studies from Italy, Asia, a tertiary care center in Eastern Nepal, and Tokat Province, Turkey [37–39], demonstrate that complete moles are more prevalent than partial moles in these areas. However, a Canadian study by Altman and Ireland reported higher frequencies of partial moles. These geographical variations necessitate the implementation of region-specific diagnostic protocols by healthcare providers to ensure accurate mole classification and provide patient education about mole subtypes, their clinical implications, and associated risks. Such measures could improve the early detection of complete moles (which carry higher complication risks) and promote timely intervention through enhanced patient awareness of the importance of routine monitoring [40, 41].

Strength and limitations

This study had several strengths. First, we implemented a predefined methodology for both the search strategy and data extraction, ensuring rigorous and systematic review standards. We employed internationally validated tools to critically appraise the quality of the included studies. Furthermore, comprehensive subgroup and sensitivity analyses were conducted to evaluate potential small study effects and heterogeneity, accounting for key variables, including geographic location, sample size, and publication year. However, this study has certain limitations. The exclusion of grey literature and restriction to English-language publications may have introduced potential publication and language bias. These limitations should be carefully considered when interpreting the findings of this study.

Conclusion

The persistently high burden of GTD at the study facility underscores the urgent need for targeted interventions, such as enhanced early screening programs, particularly for multiparous women with prior GTD or multiple pregnancies, who face an elevated risk. The observed delays in healthcare access in East Africa highlight systemic gaps, advocating for community awareness campaigns and streamlined referral pathways to reduce diagnostic and treatment delays. These findings highlight the need for policy shifts to integrate GTD prevention and timely management into maternal health initiatives, ultimately improving outcomes in high-risk populations.

Supplementary Information

Supplementary Material 1. (1.1MB, pdf)

Acknowledgements

We extend our sincere gratitude to the authors of the primary studies included in this review for their valuable contributions to this field.

Abbreviations

AOR

Adjusted Odds Ratio

CI

Confidence Interval

EDHS

Ethiopian Demographic and Health Survey

GTD

Gestational Trophoblastic Disease

GTN

Gestational Trophoblastic Neoplasia

OR

Odds Ratio

PNC

Postnatal Care

SIPI

Short Interpregnancy Interval

SRMA

Systematic Review and Meta-analysis

WHO

World Health Organization

Authors’ contributions

GY spearheaded the study design, coordinated the implementation, and led the data analysis and manuscript drafting. BDT and AB contributed substantially to the study conception and design. GY, BDT, AB, BM, and AG conducted literature reviews, study selection, and quality assessments. GY, DT, and MA performed the data extraction and statistical analyses. GY and ESL interpreted the findings and prepared the manuscript drafts. All authors (GY, BDT, AB, BM, AG, DT, MA, and ESL) critically reviewed, revised, and approved the final manuscript, ensuring its scientific accuracy and integrity.

Funding

No funding.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

The original online version of this article was revised: "Following publication of the original article [1], the authors identified an error in the author name of Dejen Tsegaye. The incorrect author name is: Dejene Tsegaye. The correct author name is: Dejen Tsegaye.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Change history

10/29/2025

A Correction to this paper has been published: 10.1186/s12884-025-08384-4

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1. (1.1MB, pdf)

Data Availability Statement

No datasets were generated or analysed during the current study.

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