Prevalence and risk factors for asthma in East Africa: a systematic review and meta-analysis

Abstract

Background

The prevalence of childhood asthma is increasing in developing countries, accompanied by numerous risk factors. This leads to substantial asthma related morbidity, mortality and economic consequences. The systematic review and meta-analysis aimed to determine prevalence and risk factors associated with asthma in East Africa, thereby elucidating the asthma burden among children and adolescents in the region.

Methods

Relevant articles were identified through searches of five databases ( PubMed, Embase (Ovid), CINAHL (EBSCO), Scopus, and Web of Science), with the PRISMA guideline used for data extraction. Random effects meta-analyses were performed to calculate pooled estimates and associated 95% confidence intervals [CIs]. Heterogeneity between the studies was assessed using Cochrane Q-test and the I² statistic.

Results

This meta-analysis encompassed 11 studies involving 20,258 children with asthma across six East African countries. The pooled prevalence of asthma was 15.2% (95% CI: 11.9%,18.5%), with notable variation across countries, ranging from 5.2% (95% CI: 3.3%, 7.1%) in Tanzania to 20.8% (95% CI: 17.6%, 24.0%) in Uganda. Risk factors for asthma included family history of asthma (pooled odds ratio [POR] = 3.1, 95% CI: 1.7, 4.5), environmental exposure(POR = 10.1, 95% CI: 1.3, 19.8), allergy exposure (POR = 3.1, 95% CI: 2.3, 4.0), and exposure to smoking (POR = 2.9, 95% CI: 1.4, 4.3).

Conclusion

The prevalence of asthma among children in East Africa was high, and multiple risk factors were associated with it.It appears that strategies and targeted interventions to address specific modifiable factors (e.g., environmental exposure, allergy exposure, and exposure to smoking) should be emphasized.

Clinical trail number

CRD42024545007.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-026-06550-x.

Background

Asthma is a chronic respiratory disease characterized by repeated episodes of breathing difficulties [1]. It is caused by inflammation and the narrowing of the airways, leading to symptoms such as wheezing [2].

Many children with asthma have pertinent symptoms including cough, wheezing, chest tightness, feeling lightheaded, trouble sleeping, and shortness of breath [3]. Numerous factors, such as exposure to allergens, indoor and outdoor air pollution, climatic change, and upper respiratory tract infections, can trigger asthma in children [1, 4]. While there is currently no cure for asthma [5], can significantly improve outcomes for individuals by preventing both the development and triggering of asthma symptoms [6].

Asthma, the most prevalent non-communicable disease in children, poses a significant global health burden, affecting 10–15% of children worldwide [7, 8]. In Europe, prevalence increased by about 1% per decade, while in Africa and the Middle East, it rapidly increased by over 2%. Conversely, the Asia–Pacific region found a 1% decrease, and there was no change in the Americas [7]. In high-income countries such as Germany and England, the prevalence of asthma at age 4 varies between 1.72% and 13.48%, respectively [9].

The prevalence of asthma in children in Africa over the past two decades is rising including in East Africa [10], According to the International Study of Asthma in Children conducted in Africa, such as Addis Ababa asthma symptom rates was (9.1%), Nairobi (18.0%), and Cape Town (20.3%) were comparable to those in Western Europe [11].

Moreover, across Africa, including East Africa, childhood asthma affects about 13.9% [12], a rate exceeding global rates, and is linked to several risk factors contributing to the onset and exacerbation of asthma symptoms [4]. Furthermore, asthma prevalence in regions of Africa such as Ethiopia (16.3%), Tanzania (12.3%), and South Africa (53%) has at different times matched rates seen in high-income countries [10].

Access to medications for childhood asthma in Africa is frequently constrained compared to developed nations, a discrepancy driven by factors like healthcare infrastructure, financial resources, and availability of essential drugs. This disparity results in significant morbidity, mortality, and economic implications associated with asthma in the region [13, 14].

Childhood asthma impacts children, families, and communities. Beyond the immediate challenges such as breathing difficulties and compromised quality of life, it leads to frequent hospital visits, school absenteeism, and limitations in activities [1, 15]. Moreover, the emotional burden on both the child and caregivers is considerable due to the ongoing symptom management and concerns about potential worsening condition [16]. Furthermore, the significant financial consequences encompass medical expenses, decreased productivity from caregiver absences, and costs linked to medications and treatments [17, 18]. Addressing childhood asthma comprehensively involves not only medical interventions but also family assistance, caregiver education, and public health strategies to mitigate its effects on individuals and societies.

In East Africa, various studies have explored childhood asthma prevalence and risk factors, highlighting its critical significance and the numerous challenges it poses for children and families [19–21]. Findings in the region have been inconsistent; this may arise from varying methodologies, sample sizes, geographical locations, and study durations. Therefore, conducting a systematic review and meta-analysis to evaluate the prevalence of childhood asthma and associated risk factors in East Africa is crucial for various reasons. This review will consolidate existing research findings, providing a comprehensive overview of the status of childhood asthma in the region. In addition, it will provide updated data to aid decisions for healthcare providers, policymakers, and researchers.

Methods

Research question

This review was guided by two research questions: (i) What is the prevalence of asthma among children aged ≤17 years in East Africa and (ii) What are the risk factors associated with asthma in this population ?

Search strategy

The review protocol was registered in the PROSPERO database (CRD42024545007). The systematic review and meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines[22] (Supplementary File Table 1). We conducted comprehensive extensive searches across five databases: PubMed, Embase Ovid, CINAHL (EBSCO), Scopus, and Web of Science. The search covered all studies irrespective of publication year using four key concepts based on the Population, Exposure, Comparison, and Outcomes (PECO) framework (Supplementary File Table 2). The search period was from March 2024 to May 2024. The search strategy incorporated terms using Boolean operators "AND" and "OR" such as ((((Asthma OR Hyperreactivity* OR Bronchial OR Hypersensitivity* OR Allerg* OR Childhood Asthma OR Pediatric* Asthma* OR Paediatric Asthma*) AND (Factor* OR Interlink* OR Associate* factor* OR Determinant* OR Contributors* OR Correlate* OR Interaction* OR Effect* OR Relationship* OR Influence*) AND (Child* OR Infant* OR Adolescent* OR Young Adult* OR Neonat* OR Pediatric*) AND (Burundi OR Comoros OR Djibouti OR Eritrea OR Ethiopia OR Kenya OR Madagascar OR Malawi OR Mauritius OR Mozambique OR Rwanda OR Seychelles OR Somalia OR South Sudan OR Tanzania OR Uganda OR Zambia OR Zimbabwe))))(Supplementary File Table 3).

Inclusion and exclusion criteria

We included all observational studies reporting the prevalence of asthma and/or risk factors among children aged≤17 years in East Africa. Articles that could not be fully accessed were excluded due to the inability to assess article quality without complete text availability and to estimate the outcome variable were excluded in the study. Moreover, systematic review, clinical trials, qualitative articles, case reports, case series, and studies that did not differentiate asthma in children from other respiratory disorders were excluded from the analysis. Due to limited data, we included all studies regardless of publication date or sample size and conducted subgroup analyses to assess their effects. A total of eleven articles met the inclusion criteria and were selected for analysis.

Articles reported only asthma case without prevalence or defining the outcome. We estimated asthma prevalence by calculating the ratio of reported cases to the total study population and applying a standardized asthma definition (Children with either physician diagnosed, or self-reported asthma were considered to have asthma. Diagnostic assessments involved inquiries about symptoms such as wheezing, breathing difficulties, and the evaluation of all potential risk factors [19, 21]). We also contacted authors to clarify missing information where possible.

The outcome of interest was the prevalence of asthma and the risk factors among children aged ≤ 17 old in East Africa. To determine prevalence, we extracted the number of children with asthma, divided it by the total number of children, and subsequently multiplied by 100 in each study.

Data regarding potential risk factors linked to asthma in children, including family history of asthma, exposure to allergens such as pets and pollen, environmental factors like changes in climate, indoor pollution from sources such as cook stoves and dust, secondhand smoke exposure were extracted from eligible studies. Where available, the adjusted odds ratio (AOR) corresponding to all these potential risk factors were extracted from each study,

Study selection and quality assessment

ESC reviewed the titles and abstracts of identified studies from the literature searches and retrieved full-text articles for those considered relevant for further assessment against eligibility criteria. Any uncertainties for inclusion were resolved through discussions. Furthermore, the reliability, relevance, and outcomes of the selected publications were assessed using The Joanna Briggs Institute appraisal (JBI) tool was applied to rate as high (> 70%), moderate (50–70%), or low quality (< 50%) based on assessment scores [23] (Supplementary File Table 4).

Data extraction

Data from selected studies were extracted into a pre-designed Excel spreadsheet, including author names, study year, country, study design, sample size, age range, prevalence estimates and risk factors data. The database format was collaboratively designed and approved by all authors.

Statistical analysis

We calculated the pooled prevalence estimates with 95% confidence interval [CI] using the DerSimonian and Laird random-effects model to account for observed variability. We computed the pooled odds ratio (POR) with a 95% CI for the risk factors associated with asthma, based on AORs reported in individual studies. Furthermore, subgroup analyses were conducted by age groups (> 8 years and ≤ 8 years as the mean age of children in the studies was 8 years), study country, data collection period, and sample size. This technique assists in identifying patterns, inconsistencies, and potential sources of variation within the data, thereby improving the understanding of the research conclusions and their implications across diverse subpopulations or situations over time. The weighted inverse variance random-effects model of Der Simonian and Laird method to adjust for the observed variability. Heterogeneity between studies was assessed using the Cochrane Q-test and I² statistics, and publication bias was assessed using the Egger test. Sensitivity analyses were performed to determine whether the pooled estimates were influenced by any single study. Data analysis was performed using STATA (version 17).

Results

Selection process and characteristics of studies

The initial database search resulted in 1214 articles, of which 429 remained after duplicate removal. Following title and abstract screening, 83 full-text articles were evaluated for eligibility, and 72 were excluded not meeting inclusion criteria . Ultimately, 11 studies were eligible for inclusion in the systematic review and meta-analyses, encompassing 20,258 children from six East African countries. (Fig. 1). Of these, three were conducted in Mozambique and Ethiopia, two in Kenya , and one each in Tanzania, Uganda, and Sudan . The age range of participant across the studies was 1- 15 years. , Sample sizes varied from100 (Mozambique) and 3365 (Ethiopia) (Table 1).

Fig. 1.

PRISMA flow diagram of searching process

Table 1.

The characteristics of included studies

First Author/year	Country	Study Design	Age in year	Sample size	Prevalence %	Environmental exposure: AOR	Allergic exposure: AOR	Family history of asthma: AOR	Exposure to smoking: AOR
Esamai etal (2001) [20]	Kenya	cross-sectional	13 −14	3258	23.6	-	-	-	-
Halay etal (2018) [24]	Sudan	cross-sectional	1–6	3352	20.4	-	-	-	-
Hailu et al. (2002) [25]	Ethiopia	cross-sectional	13–14	3365	16.2	-	-	-	-
Mavale et al. (2007) [26]	Mozambique	cross-sectional	13–14	1614	11.9	-	-	-	-
Maval et al. (2007) [27]	Mozambique	cross-sectional	6–7	2630	13.3	-	-	-	-
Maval et al. (2004) [21]	Mozambique	case–control	2–8	100	-	26.8	4.0	3.8	2.4
Melaku (1991) [28]	Ethiopia	cross-sectional	13 −14	2951	18.2	-	-	-	-
Mugusi et al. (2004) [19]	Tanzania	cross-sectional	5–15	511	5.2	-	-	-	-
Nantanda et al. (2013) [4]	Uganda	cross-sectional	< 5	614	20.8	3.8	2.6	2.4	-
Odhiambo etal (1998) [29]	Kenya	cross-sectional	8–15	604	9.5	7.46	3.36	-	4.0
Woldetsadik et al. (2018) [30]	Ethiopia	cross-sectional	6–7	1259	13.1	2.2	2.3	-	-

The pooled prevalence of asthma and risk factors among children in East Africa

The pooled prevalence of childhood asthma 10 studieswas 15.2% (95% CI: 11.9%, 18.5%) (Fig. 2). Subgroup analyses revealed higher asthma prevalence in children aged ≤ 8 years (16.8%,95% CI: 12.5%, 21.1%)compared to those > 8 years(14.1% ,95% CI: 9.2%, 19.0%). Moreover, asthma prevalence was highest inUganda (20.8% ,95% CI: 17.6%, 24.0%)and lowest in Tanzania (5.2% ,95% CI: 3.3%, 7.1%). Additionally, studies with relative large sample sizes (>700 participants) reported asthma prevalence of 16.7% (95% CI 13.6-19.8), whereas relatively smaller studies (≤700 participants) reported 11.7% (95% CI 3.6-19.9). Asthma prevalence also differed by study period, increasing from 14.0% (95% CI 10.0-18.1) before 2010 to 18.0% (95% CI 12.8-23.3) after 2010 (Figs. 3, 4, 5 and 6).

Fig. 2.

Forest plot to test for Asthma among children in East Africa

Fig. 3.

Asthma among children in East Africa by country categories

Fig. 4.

Asthma among children in East Africa by age of the children in year categories

Fig. 5.

Asthma among children in East Africa by study period categories

Fig. 6.

Asthma among children in East Africa by sample size categories

Meta-analysis of four studies revealed that family history of asthma, environmental exposure (changes in climate, indoor pollution and dust) allergy exposure(exposure to pets and pollen) and exposure to indoor smoking were risk factors for childhood asthma in the East Africa region (Table 2).

Table 2.

The risk factors of asthma among children in East Africa

Risk factors	POR	95% CI
Family history of asthma	3.1	1.7, 4.5
Environmental exposure	10.1	1.3, 19.8
Allergy exposure	3.1	2.3, 4.0
Exposure to smoking	2.9	1.4, 4.3

Publication bias

Regarding publication bias, Egger's test indicated no bias (p = 0.415) in the prevalence of childhood asthma across East Africa (Table 3). Likewise, Egger's test results suggested no bias (p = 0.822) in the risk factors of childhood asthma in the region. Furthermore, sensitivity analysis showed that no single study significantly influenced the overall estimation of asthma prevalence (Fig. 7).

Table 3.

Egger's test in prevalence of childhood asthma in East Africa

Standardized effect coefficient		Standard error	T	p > t	95% CI
Slope	21.6	6.8	3.15	0.014	5.8	37.3
Bias	−7.3	8.4	−0.86	0.415	−26.8	12.2

Fig. 7.

Sensitivity test for Asthma among children in East Africa

Discussion

Our systematic review and meta-analysis demonstrate that childhood asthma prevalence in East African countries is high, with significant associations identified for family history of asthma, environmental exposures, allergic exposure , and smoking exposure . Subgroup analyses revealed that prevalence varying by population and study characteristics country, as well as region.

The pooled prevalence of childhood asthma in r East Africa is higher than in many high- and middle-income countries, including Tunisia (6.5%) [31], Iran (4.4%) [32], the Middle East (7.5%) [33], India (7.9%) [34], China (11.2%) [35], Israel (10.0%) [36], Australia (6.3%) [37], Germany (1.7%) [38], USA (7.9%) [39], Korea (2.1%) [40]. Likewise, a recent systematic review and meta-analysis reported global prevalence 10.2%, with regional prevalences of Asia (10%), Europe (9%), Latin America (14%), North America (13%), and Africa (11%) [41]. Moreover, our finding lower than the study conducted in Egypt (26.5%) [10], and New South Wales, Australia (22%) [42].

High heterogeneity (I² = 97.5%) across studies prompted to improve the accuracy . In our study, asthma prevalence was higher in studies with sample sizes (> 700), at 16.7%, compared to 11.7% in studies with samples (≤ 700).This difference may reflect sample size bias or regional variation. The 700-participant threshold was chosen based on the sample size distribution. These findings suggest that asthma may be more prevalent than previously estimated, highlighting the need for larger studies to inform policy, guide interventions, and strengthen international collaboration.

Observed disparities may be associated with inadequate access to healthcare resources contributing to underdiagnosis or delayed treatment, combined with genetic predisposition, poor housing conditions, elevated pollution , and increased allergen exposure among children in East Africa [43, 44]. Methodological differences may also contribute to high heterogeneity s particularly varying diagnostic criteria for asthma in young children . Symptoms such as cough and wheeze are common but not always indicative of asthma , and lung function tests are rarely performed in children under five this age group45, 46]. Moreover, the criteria used to diagnose asthma vary across studies, with some definitions requiring two or more wheezing episodes, while others consider three or more within a year. Such inconsistencies in diagnostic standards and data collection methods may contribute to underestimating childhood asthma burden [47, 48].

Asthma is a chronic disease caused by complex interactions between genetic and environmental risk factors, both of which play a key role in its development [49], and the high incidence of asthma has been linked to those factors in children [50]. Many children in Africa, including the East, have a genetic Background associated with black ancestry [51, 52], which may influence their susceptibility to asthma, making it higher than white children [53, 54]. This disparity may represent a double burden of asthma, potentially worsened by environmental changes and increasing urbanization in the future.

Children with a familial background of asthma face an increased risk of inheriting genetic susceptibility to respiratory conditions, potentially manifesting as early-onset or more severe asthma symptoms [55]. Moreover, exposure to environmental tobacco smoke further exacerbates this vulnerability, leading to heightened respiratory issues and exacerbations in affected children [56]. The combination of genetic predisposition and exposure to smoking underscores the importance of preventive measures, such as smoking cessation in households with asthmatic children, to mitigate the risk of asthma.

Environmental exposure were strongly associated with asthma in our analysis ;, although the wide confidence interval reflects limited data, inconsistence exposure and measured. Even though , this finding aligns with other research [57, 58]. Changes in the environment, such as heightened pollution levels and increased allergen exposure due to climate shifts, can serve as asthma triggers, affecting both the emergence and worsening of the disease [59]. Those with allergic histories are especially vulnerable, as sensitization and inflammatory reactions can increase their sensitivity to allergens, resulting in more frequent and severe asthma manifestations [60].

Therefore, recognizing and addressing these factors are essential for managing, preventing, and delaying asthma exacerbations in children. Similarly, our findings highlight the significant impact of these factors on childhood asthma in East Africa. Hence, minimizing exposure to these risk factors and implementing targeted interventions are crucial for reducing the prevalence and severity of asthma among children in the region.

Limitation of the study

This review has some important limitations that should be considered when interpreting the findings. First medication availability and and treatment access in East Africa were not assessed due to a lack of data, which may underestimateasthma burden. Second, inclusion of studies regardless of diagnostic criteria may affect prevalence accuracy, particularly in children under five where distinguishing asthma from other respiratory conditions is challenging. Third, restricting the review to English-language publications and excluding studies that did not clearly differentiate asthma may have led to underreporting. Fourth, the limited number of studies for particular risk factors resulted in wide confidence intervals, warranting cautious interpretation.

Conclusion

Childhood asthma in East Africa was found to have notably high prevalence. This review also identified key risk factors, including environmental exposure, allergic predisposition, and exposure to smoke , emphasizing the need for targeted interventions to address specific modifiable factors . Further research is important to better quantify the burden and clarify contributing factors to inform effective prevention strategies.

Abbreviations

AOR

Adjusted Odds Ratio

POR

Pooled Odds Ratio

JBI

Joanna Briggs Institute

Authors’ contributions

ESC, JK, AJ and NH conceptualized and designed the study. ESC developed the protocol was conducted data extraction, analysis and drafted and manuscript. All authors provided feedback on developing the manuscript.

Funding

Not applicable.

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.