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. 2026 Aug 31;13:30502225261485776. doi: 10.1177/30502225261485776

Prevalence and Associated Factors of Developmental Delay Among Under-five Children in Sub-saharan African Countries: A Systematic Review and Meta-Analysis

Angefa Ayele 1,✉, Belayneh Jejaw Abate 2, Eliyas Addisu Taye 3, Endalew Minwuye Andargie 4, Halima Ayalew Kebede 5, Helen Brhan Alemaw 5, Sofiya Ayalew Kebede 6, Ashenafi Solomon Weldeyohanis 7, Adem Tsegaw Zegeye 3, Alo Edin 8
PMCID: PMC13530491  PMID: 42682745

Abstract

Background

Developmental delay (DD) is a major public health concern in Sub-Saharan Africa (SSA). This systematic review and meta-analysis estimated the pooled prevalence of DD and identified associated factors among children in SSA.

Methods

Observational studies were identified from PubMed, Google Scholar, CINAHL, Scopus, Cochrane Library, Web of Science, and African Journals Online. Data were analyzed using STATA version 16 with a random-effects model.

Results

Pooled prevalence was 33.00% (95% CI: 22.00–44.00). Subgroup analysis showed the highest prevalence in South Africa (37.00%; 95% CI: 10.00–73.00). Maternal education (AOR = 0.41; 95% CI: 0.24–0.72), child age (AOR = 0.43; 95% CI: 0.23–0.81), maternal age (AOR = 0.24; 95% CI: 0.10–0.57), and nutritional status (AOR = 3.59; 95% CI: 1.08–11.92) were significantly associated with DD.

Conclusion

The pooled prevalence of DD in Sub-Saharan Africa is high. Maternal education, child age, maternal age, and nutritional status were key factors associated with DD. Strengthening early screening, improving maternal education, and promoting optimal child nutrition are essential to reduce the burden of developmental delay.

Keywords: developmental delay, determinants, under-five children, Sub-Saharan Africa, meta-analysis

Introduction

Background

Early childhood is a crucial time for the development of the brain and the learning of basic language, motor, cognitive, and socioemotional skills. Children’s future academic success, efficiency, and health outcomes are determined by their development throughout the first five years of life. Developmental delay refers to a condition in which children fail to reach expected developmental milestones within a specified age range in one or more areas, such as motor, cognitive, language, or social development, within a specific age range. If not recognized early, developmental delay can lead to long-term impairment, decreased educational performance, and poor socioeconomic results later in life.1,2 Millions of children worldwide suffer from developmental delay, which is a serious public health issue, especially in low- and middle-income countries (LMICs). Due to poverty, malnourishment, and insufficient early stimulation, an estimated 250 million children under five in LMICs are at danger of not developing to their full potential. These children often experience multiple biological and environmental risk factors that hinder optimal development. As a result, developmental delays continue to play a significant role in both long-term socioeconomic inequality and childhood disability globally.3,4

In Sub-Saharan Africa (SSA), where children are often exposed to a variety of risk factors, including as undernutrition, infectious illnesses, poor maternal health, and restricted access to early childhood development programs, the burden of developmental delay is disproportionately higher. According to comprehensive evaluations, the prevalence of developmental delay among children in low- and middle-income nations is around 18.8%, with greater rates in African countries than other areas. These discrepancies are mostly driven by socioeconomic inequities and insufficient access to early childhood care and stimulation services. 5

The level of developmental delay varies greatly among Sub-Saharan African nations, according to various kinds of studies. For instance, prevalence among children aged 12 to 59 months has been reported to range from 15% to over 30% in community-based studies carried out in Ethiopia and other African contexts, indicating a significant burden in the area. These discrepancies could be the result of changes in population characteristics, study environments, and measurement instruments.5-7

Developmental delays are driven by multiple, interrelated factors, particularly in low-resource settings. Key risks include malnutrition, micronutrient deficiencies (such as iodine and iron deficiency anemia), and chronic childhood illnesses, all of which impair physical and cognitive development. Socioeconomic disadvantage especially poverty further heightens vulnerability by restricting access to adequate nutrition, healthcare, and safe living conditions. In addition, insufficient early stimulation, poor caregiver interaction, maternal depression, and children’s exposure to violence adversely affect cognitive and socio-emotional development. These factors frequently coexist and interact, amplifying the overall risk of developmental delays in early childhood.1,8,9

Furthermore, while some systematic reviews have looked into developmental delay in low- and middle-income countries, few studies have specifically synthesized evidence for Sub-Saharan Africa, where children face unique contextual risk factors such as high levels of poverty, malnutrition, and limited access to health and early childhood development services. As a result, the pooled burden and determinant factors of developmental delay among under-five children in Sub-Saharan Africa remain insufficiently summarized.1,5 Therefore, this systematic review and meta-analysis aimed to estimate the pooled burden of developmental delay and identify determinant factors among under-five children in Sub-Saharan African countries. Generating comprehensive evidence on the magnitude and determinants of developmental delay will help inform policymakers and health planners in designing targeted interventions to improve early childhood development outcomes in the region.

Research Questions

  • • What is the pooled magnitude of DD among under-five children in SSAs?

  • • What are the determinants of DD among under-five children in SSAs?

Methods

Our systematic review and meta-analysis were registered with the registration number CRD42023478148. Studies were selected based on predefined eligibility criteria using a Population Intervention Comparator Outcome (PICO) criteria to describe our research question. We included observational studies (cross-sectional, case–control, and cohort) conducted among children under five years in Sub-Saharan Africa that reported the prevalence and/or determinants of developmental delay. Eligible studies were those published in English between January 2016 and February 2026 and available as full-text articles at the time of the final literature search. Studies that did not report the outcome of interest or focused exclusively on highly specific clinical populations (e.g., severe malnutrition or congenital conditions) were excluded to maintain generalizability.

Information Source

PubMed, PsycINFO, Hinari, Science Direct, African Journal of Online (AJOL), Web of Science, Google Scholar databases, and Google were checked for primary articles conducted on developmental delay.

Search Strategy

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist was used to report the review. Endnote version X7.2 was used to maintain and manage citation and facilitate the review process. 10 On initial step of the search process, we checked for the presence of the existing systematic review and meta-analysis on similar topic by extensive search of literatures. All pertinent published studies in the following major databases; PubMed, Google scholar, CINAHL, Scopes, Cochrane library, the Web of Science and African Journals Online were involved in the review. The reference lists of identified studies were also reviewed to find additional articles. Pre-identified search terms were used to allow a comprehensive search strategy that included all the relevant studies.

We utilized “prevalence OR magnitude OR burden AND global developmental delay OR developmental delay OR neurodevelopmental delay AND children AND Sub-Saharan Countries” to search primary articles for objective one. “Determinants OR predictors OR associated factors OR risk factors AND developmental delay OR confirmed developmental delay AND children AND Sub-Saharan African Countries OR SSA”. Studies conducted from 2016 until present were incorporated to produce solid proof.

Quality Assessment and Data Extraction

To assess the quality of the data, the Ottawa–Newcastle Scale, adapted for the cross-sectional study, was used to evaluate the strengths of the included studies. 11 Two reviewers independently extracted the data using standardized data extraction checklist on Microsoft excel spread sheet. At the beginning, articles was downloaded and supplemented to Endnotes version 7.2 reference management. Duplicated articles were excluded by using Endnotes reference management. Then, the titles and abstracts of the studies were exhaustively assessed based on the relevance of the outcome. Full-text of the remaining articles was evaluated for eligibility based on prearranged inclusion and exclusion criteria. We used two data extraction formats. For the first outcome variable (prevalence of developmental delay), checklist for data extraction contains the title, author name, year of publication, country (the area where study was conducted), study design, outcome measurements, sample size, response rate and quality scores (Table 1). After two data extractors performed the review, any discrepancy was resolved by including the third reviewer for a possible consensus. When articles did not have adequate data, corresponding authors of the research articles were contacted though their email. Author name, publication year, and frequencies were assessed to identify associated factors.

Table 1.

Characteristics of the Included Studies to Assess the Prevalence of Developmental Delay and Its Associated Factors Among Children in SSAs, 2026 (n = 10)

Author Publication year Country Design Sample size Cases Tool Quality score Population
Ayele A et al. 2024 Ethiopia Cross-sectional 413 173 ASQ 8 < 5 years
E. Bonney et al. 2021 Uganda Cross-sectional 720 54 ECDI 8 3–4 years
K. Mitiku et al. 2023 Ethiopia Cross-sectional 417 68 CDI 7 < 5 years
A. C. Miller, et al. 2020 Madagascar Cross-sectional 432 173 ECDI 8 3-5 year
R. Shiferaw et al. 2024 Ethiopia Case-Control 332 83 Denver II 8 2 year
V. Tuyisenge et al. 2023 Rwandan Cross-sectional 358 88 ASQ-3 8 < 2 year
M. A. Mshimba, et al. 2024 Tanzania Cross-sectional 422 278 ECDI-2030 ​ 2-5 year
O. O. Olabumuyi, et al. 2024 Nigeria Cross-sectional 17,373 6532 ECDI 7 <5 year
Rodriguez, V. J. et al. 2023 South Africa Cohort 160 89 BINS 8 <2 year
C. C. de Beer et al. 2020 South Africa cohort 81 15 Vineland-3 9 <2 year
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Our review and meta-analysis included studies that scored at least 7 out of 10 on the Ottawa–Newcastle Scale.

Effect Measures

In this review and meta-analysis, we evaluated two objectives. The pooled prevalence of developmental delay among children was calculated by dividing the number of children with developmental delay by the total number of children included in this review and meta-analysis, multiplied by 100. The second objective was to assess the determinants of developmental delay among children in SSAs. In this review and meta-analysis, factors identified as determinants of Developmental delay in at least two studies were considered for meta-analysis. We used the odds ratio (OR) to express the pooled effect.

Synthesis Methods

In this study, heterogeneity was assessed using the I2 test and categorized as low, moderate, or high heterogeneity if it was 50%, 50–75%, or > 75%, respectively. 12 Analysis was performed using STATA version 16. Because of the high heterogeneity, a random effects model was selected for analysis. For each original article, the standard error was calculated using the binomial distribution formula. In order to identify the cause of heterogeneity, subgroup analysis was carried out. 13 To describe the results of this study, systematic review and meta-analysis texts, tables, and forest plots were used.

Reporting Bias Assessments

Potential biases included publication, language, and selection bias due to restriction to published English-language studies and database coverage. These were minimized through a comprehensive multi-database search, predefined eligibility criteria, and independent screening by two reviewers with consensus resolution. Publication bias was assessed using Eggers and Begg’s statistical tests 14 and funnel plots. 15 The presence of evidence for publication bias was declared when the p-value was less than 0.05. An odds ratio with a 95% confidence interval (CI) was used to express association.

Ethical Approval and Informed Consent

All studies included in this analysis were ethically approved by their respective universities’ scientific and institutional review boards. These studies had already been published in peer-reviewed international scientific publications; thus, no extra ethical approval was required for the current review.

Results

Study Search and Selection

We searched full-text publications and human studies published from 2016 until present. A total of 1,876 primary articles were scrutinized from PubMed, PsycINFO, Hinari, Science Direct, AJOL, Web of Science, Google Scholar, and Google databases. Among the total articles, 1,862 articles were excluded due to duplication and by title and abstract. Only 14 studies were selected for a full reading. However, an additional four studies were excluded due to them being conducted among vulnerable children (Malnutrition, Preterm and low-birth weight, and Congenital Heart Diseases) (Figure 1). Finally, a total of 10 articles that fulfill the inclusion criteria were selected for the meta-analysis.

Figure 1.

Figure 1.

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PRISMA flow diagram for the systematic review and meta-analysis of DD and determinant factors among under-five children in Sub-Saharan-Africa (2016-20206)

Characteristics of the Included Articles

This study was conducted on 20, 708 children. A total of 10 studies were included in this study. All of the included studies were cross sectional in design.16-25 Majority almost half of the studies used the Moreover, almost half of the studies used the Early Childhood Development Index (ECDI) to assess DD (Table 1).

Results of Syntheses and Reporting Bias

A forest plot was created, as observed in Figure 2, to display the outcomes of the included studies. This systematic review and meta-analysis comprised 10 primary studies to estimate the pooled prevalence of developmental delay. In the present systematic review and meta-analysis, the pooled prevalence of DD in SSAs was 33.00%, with a 95% CI of (22.00–44.00) (Figure 3).

Figure 2.

Figure 2.

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Forest plot of the included studies to assess the pooled prevalence of developmental delay among children in SSAs, 2026 (n = 10)

Figure 3.

Figure 3.

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Subgroup analysis (based on country) of the included studies to assess the source of heterogeneity among studies conducted in SSAs, 2023 (n = 10)

The heterogeneity between studies was high, I2 = 99.3%, with a p-value of <0.001. To assess the source of heterogeneity, a subgroup analysis was conducted based on country. Studies conducted in South Africa had a high prevalence of DD [37.00; 95% CI (10.00–73.00)] and heterogeneity (97.5% with p < 0.001) as compared to studies conducted Ethiopia (Figure 2). Subgroup analysis included all countries, but for countries represented by only one study, results were not interpreted separately, as a single study does not allow for reliable within-country comparisons or robust inference. Furthermore, in this study, there was publication bias, which was verified with an asymmetric funnel plot and Egger’s test <0.01 (Figure 4).

Figure 4.

Figure 4.

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Funnel plot of the included studies to assess publication bias among studies, 2026 (n = 10)

Factors Associated With Developmental Delay

In the present systematic review and meta-analysis, four associated factors-maternal age,16,18,22 age of child,18,22,23 nutritional status,16,22,23 and maternal education16,20 that were reported as associated factors in at least two primary studies were selected for meta-analysis. After we analyzed all four associated factors were remained significant determinant factors of DD.

Mothers who were educated had 59% lower odds for developmental delay compared to those who were not educated [0.41; 95% CI (0.24, 0.72)]. (Figure 4). A children in the higher age category had 57% lower odds of developmental delay compared to those in the younger age group [0.43; 95% CI (0.23, 0.81)]. (Figure 5). A children born to older mothers had 76% lower odds of developmental delay compared to those born to younger mothers [0.24; 95% CI (0.1, 0.57)].(Figure 6). A children with poor nutritional status had 3.59 times higher odds of developmental delay compared to those with normal nutritional status [3.59; 95% CI (1.08, 11.92)] (Figure 7).

Figure 5.

Figure 5.

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Maternal education and developmental delay among children in SSAs, 2026 (n = 2)

Figure 6.

Figure 6.

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Child age and developmental delay among children in SSAs, 2026 (n = 3)

Figure 7.

Figure 7.

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Maternal age and developmental delay among children in SSAs, 2026 (n = 3)

Discussion

This systematic review and meta-analysis aimed to assess the pooled prevalence of developmental delay among children in SSAs. In this review, the pooled prevalence of DD was 33.00%, with a 95% CI of (22.00–44.00). This result highlights a substantial burden among children in Sub-Saharan Africa (SSA). This estimate is broadly consistent with findings from previous systematic reviews and meta-analyses in low- and middle-income countries, which reported prevalence ranging from 25% to 43% among children under five4,5 (McCoy DC et al., 2016; Wondmagegn T et al., 2024). While some global estimates suggest slightly lower prevalence, the current pooled estimate aligns with the upper range of reported rates in low-resource settings, reflecting the substantial proportion of children experiencing developmental delay in SSA. The wide confidence interval (22–44%) may be attributed to heterogeneity in study settings, age groups, and assessment tools across the included studies (Figure 8).

Figure 8.

Figure 8.

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Nutritional status and developmental delay among children in SSAs, 2026 (n = 2)

Sub-group analysis by region revealed significant variations in the prevalence of DD with Southern Africa having the highest prevalence (37%.0), which followed by Ethiopia (28%.0). This study observed considerable heterogeneity among the included studies, along with indications of publication bias. These variations are likely due to differences in the measurement tools used to assess developmental delay, as well as the diverse characteristics of the study populations, including variations in age, lifestyle, and socioeconomic conditions.

Maternal and child factors were significantly associated with developmental delay (DD) in this review. Children of mothers with higher educational attainment were less likely to experience developmental delay, a pattern supported by longitudinal research showing that greater maternal education is consistently associated with better cognitive, language, and motor outcomes in early childhood. 26

Older child age was associated with lower likelihood of developmental delay, aligning with evidence that developmental progress accumulates with age as children acquire skills through interaction, stimulation, and maturation over time. 27 Children born to older mothers also demonstrated more favorable developmental outcomes, consistent with systematic reviews identifying maternal age and education among interpersonal factors that influence early childhood development. 28

Poor nutritional status was associated with a higher likelihood of developmental delay, in keeping with studies showing that undernutrition and suboptimal nutritional status adversely affect neurodevelopment in young children. 6

The findings of this review have important implications for policy and program implementation in Sub-Saharan Africa. The high prevalence of developmental delay emphasizes the need to strengthen early childhood development programs through routine developmental screening, early identification, and timely intervention at community and primary healthcare levels. Evidence shows that early interventions, adequate nutrition, and improved maternal education are key determinants of better child developmental outcomes.1,29 Integrating developmental monitoring into existing maternal and child health services, including nutrition and immunization programs, may improve early detection and support for at-risk children. 30

Despite being a systematic review and meta-analysis, this study has several limitations. First, there was substantial heterogeneity and evidence of publication bias among the included studies. Second, only studies published in English were considered, which may have excluded relevant research in other languages. Third, the included studies varied in assessment tools, geographic settings, and age groups, which could contribute to variability in the findings.

Conclusion

The pooled prevalence of developmental delay (DD) in Sub-Saharan Africa was high compared to other regions, indicating a substantial public health burden. Maternal education, child age, maternal age, and nutritional status were identified as key factors significantly associated with DD, underscoring the important role of both maternal and child characteristics in early childhood development. Based on these findings, we recommend that public health practice prioritize strengthening early childhood development programs through routine developmental screening and early identification at community and primary healthcare levels. Integrating developmental monitoring into existing maternal and child health services, particularly nutrition and immunization programs, is essential to improve early detection and intervention. In addition, interventions aimed at improving maternal education and child nutrition should be prioritized as part of broader child development strategies.

For future research, more longitudinal and standardized studies are needed to better establish causal relationships and reduce heterogeneity in assessment tools and study designs across Sub-Saharan Africa.

Acknowledgments

We would like to thank all authors of the studies included in this systematic review and meta-analysis.

Author Note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated

Author Contributions: AA and AE involved in developing proposal and statistical analysis. AA, BJA, EAT, EMA, HAK, HBA, SAK, ASW, ATZ, and AE involved in the design, selection of articles, and data extraction. AA, BJA and AE involved in developing the initial drafts of the manuscript. All authors participated in the final preparation of manuscript and they approved the final draft of the manuscript for submission.

Funding: The authors received no financial support for the research, authorship, and/or publication of this article.

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

ORCID iDs

Angefa Ayele https://orcid.org/0000-0002-5308-862X

Alo Edin https://orcid.org/0000-0001-6977-2672

Data Availability Statement

All data analyzed during this study are included in the manuscript.*

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Associated Data

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

Data Availability Statement

All data analyzed during this study are included in the manuscript.*

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