The burden of congenital heart disease in Malaysia: a comprehensive review and meta-analytic synthesis, 1970–2024

Abstract

Background

Congenital heart disease (CHD) remains a leading contributor to congenital anomalies globally. In Malaysia, available data on CHD are limited, with birth prevalence estimates varying widely across studies, suggesting potential underestimation and gaps in understanding CHD prevalence. This systematic review and meta-analysis aimed to assess the reported prevalence and subtypes of CHD in Malaysia.

Methods

This study was conducted according to PRISMA guidelines and registered with PROSPERO (CRD42024500619). Studies from the Malaysian population published from inception till October 2024 were searched in Google Scholar, PubMed, EMBASE, and Web of Science.

Results

A total of 303 were identified and 7 studies met the inclusion criteria. Data on total CHD prevalence and 36 specific subtypes were collected and pooled using an inverse variance random-effect model. Among the 7 eligible studies, encompassing 1,474,172 live births, the pooled CHD prevalence was 4.21 per 1,000 live births (95% confidence interval [CI] [2.21–6.22]; P < 0.0001), with significant heterogeneity (I² = 99%). The reported prevalence exhibited markedly variation, declining from 6.80 per live births (95%CI [5.19–8.41]) in 1963 to 1.35 per 1,000 live births (95%CI [0.96–1.74]) in 1999, before rising again to 6.80 per 1,000 live births (95%CI [6.63–6.97]) in 2020. Among CHD subtypes, ventricular septal defects were the most prevalent (36.23%), followed by patent ductus arteriosus (18.16%). Subgroup analyses by geographic location (states of Malaysia), publication year, and study design highlighted further variability in prevalence rates.

Conclusions

The observed fluctuations in CHD prevalence underscore the necessity for robust surveillance systems and investigation into the factors driving these trends in Malaysia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-025-23800-2.

Background

Congenital heart defect (CHD) is the leading cause of major congenital anomalies, posing a significant global health concern [1, 2]. CHDs are the primary cause of death within the first year of life, contribute substantially to morbidity and hospitalization in children, and often necessitate lifelong follow-up [3]. Developing countries have experienced notable increases in birth rates and the incidence of CHD [4–6]. Advances in congenital heart surgery, catheter interventions, and research have improved survival rates for children with CHD into adolescence and adulthood. However, in Malaysia, limited awareness and resources for CHD pose additional barriers for affected individuals [7].

The reported birth prevalence of CHD varies widely among studies worldwide, with the estimate of 8 per 1,000 live births generally accepted as the best approximation [2, 4, 5]. In Malaysia, approximately 500,000 live births occur annually, and an estimated 4,000 to 5,000 children are born with significant CHD requiring expert cardiological care [8]. Despite the availability of scattered data, pooled data on CHD prevalence in Malaysia still needs to be included. Reliable information on CHD birth prevalence is crucial for understanding its aetiology and improving care planning. Therefore, this systematic review and meta-analysis aim to estimate the pooled prevalence of total CHD and 36 subtypes of CHD in Malaysia.

Methodology

This study used Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines for study design, search strategy, screening, and reporting [9]. (PROSPERO CRD42024500619) (18 January 2024).

Research question and search strategy

The research question was developed using PC; “P” stands for Population, and “C” for Condition [10]. PC components were as follows: “P”; Malaysian baby residing in Malaysia, “C”; CHDs. A systematic search was conducted using Medical Subject Heading terms and free keywords for “Malaysian baby”, “Congenital heart defect” and “Prevalence”. Employing these key terms, the search map included: (prevalence OR epidemiology OR magnitude OR pattern) AND (infant OR newborn OR baby OR children OR premature) AND (congenital heart defect OR congenital heart disease OR birth defect OR congenital anomaly) AND “each state and federal territory within Malaysia''. All the literature accessible from inception till October 2024 was included in the systematic review. Relevant studies were identified through a comprehensive literature search encompassing Medline (PubMed) (accessed on 19th October 2024), EMBASE (accessed on 19th October 2024), Web of Science (accessed on 19th October 2024), and Google Scholar (accessed on 19th October 2024) (Supplementary Table 1).

Study selection and screening

The retrieved studies were exported to Covidence software (https://www.covidence.org/) to remove duplicate studies. All three stages of review (titles, abstracts, and full-text reviews) were conducted by AKSY and SM. Pre-specified inclusion criteria were used to screen the full-text articles further. Disagreements were discussed during a consensus meeting for the final selection of studies to be included in the systematic review.

Inclusion and exclusion criteria

Cross-sectional and cohort studies of populations residing in any state within Malaysia reporting at least the prevalence of CHD subtypes with enough data to compute the estimates, regardless of stillbirth, were included. The inclusion criteria encompassed studies published in English from inception till October 2024. Citations without abstract and/or full-text, anonymous reports, editorials, letters, commentaries, reviews, and qualitative studies were excluded from the analyses. Studies conducted among populations of Malaysian origin residing outside Malaysia and studies without confirmed CHD (e.g. suspected but non-confirmed CHD) were also excluded from this review.

Quality assessment

The methodological quality of the included studies was assessed using the Joanna Briggs Institute (JBI) critical appraisal checklist for prevalence studies [11]. This tool evaluates the reliability, relevance, and validity of prevalence data through a structured set of criteria aimed at identifying potential sources of bias in study design, conduct and analysis. Detailed descriptions and justifications for each appraisal item are available in the JBI methodological guidance [12]. AKSY and SM independently conducted the quality assessments. Any discrepancies were discussed and resolved through consensus. Based on the proportion of criteria met, studies were classified as high quality (> 70%), moderate quality (50–70%), or low quality (< 50%).

Data extraction

Data from the selected studies were extracted, with variables including the year of publication, study period, location, racial distribution, age distribution, gender distribution, diagnosis method, study design, number of live births, number of CHD patients, birth prevalence of total CHD, reported cases for each CHD subtypes, and family history. Data was extracted into an Excel® spreadsheet, and its format was refined after a pilot test involving four randomly selected papers. Two authors (AKSY and SM) extracted the data using the extraction form in collaboration.

Synthesis of results

Data analysis was conducted using Excel® spreadsheet, while statistical analyses were conducted using IBM SPSS Statistics (v29) and Cochrane Review Manager (RevMan). Meta-analytical estimates of the birth prevalence of CHD were calculated in RevMan using a random-effects model based on the DerSimonian and Laird method with inverse variance weighting. Subgroup analyses were performed in SPSS using a random-effects framework. Heterogeneity among effect sizes was assessed via I² and τ² statistics, where τ² indicated between-group variation and I² represented the proportion of total variation attributed to heterogeneity. I² values were interpreted as follows: 25% (low heterogeneity), 50% (moderate heterogeneity), and 75% (high heterogeneity) [13]. Potential sex-specific differences in CHD populations were assessed by stratifying the patient populations by gender. Subgroup analyses were conducted based on geographic location (states of Malaysia), publication year, and study design. Sensitivity analyses evaluated the impact of individual studies on the overall estimates. Publication bias was assessed visually using a funnel plot and quantitatively via Egger’s regression test.

Results

Search results

A total of 303 eligible studies were identified across multiple databases; 238 from Google Scholar, 33 from PubMed, 16 from Embase, 14 from Web of Science, and 2 through citation searching. After the removal of 28 duplicates, 273 articles remained. Title and abstract screening led to the exclusion of 238 studies based on criteria outlined in the Methods section. Full-text assessments resulted in further exclusions due to inappropriate settings, patient populations, review papers, study designs, outcomes, or redundant data from the same authors. In instances where multiple publications by the same author appeared to analyse overlapping cohorts, the version with the most comprehensive dataset was retained for quantitative analysis. Redundant studies were excluded from meta-analysis to prevent duplication of data but are discussed qualitatively to acknowledge their relevance and findings. Ultimately, 7 studies met the inclusion criteria for this systematic review and meta-analysis [14–20] (Fig. 1; Supplementary Fig. 1).

Fig. 1.

PRISMA flow chart of study selection

Study characteristics

The seven studies included in this analysis exhibited various methodologies: six employed a cross-sectional design [14–17, 19, 20], while one adopted a retrospective cohort approach [18]. Of these, 28.57% (2/7) were published before 1997, with the remaining 71.43% (5/7) published between 1998 and 2024. The studies collectively encompassed a total population of 1,474,172 live births, among which 10,491 cases of CHD were identified (Supplementary Table 2). Diagnostic methods varied across studies, incorporating multiple modalities such as echocardiography, clinical diagnosis, cardiac catheterization, electrocardiography, chest X-rays, cardiac computed tomography/magnetic resonance imaging, phonocardiography, haemoglobin assessment, arterial blood-gas analysis, surgical findings, portable Cambridge Transrite evaluations, and ultrasound imaging. Table 1 presents the detailed characteristics of each included study, which include study period, number of CHD cases, total sample size, racial distribution, age distribution, gender distribution, geographic location (Malaysian states), study design, and diagnostic modalities used in each study.

Table 1.

Detailed characteristics of the included studies, including study period, number of CHD cases, total sample size, racial distribution, age distribution, gender distribution, geographic location (Malaysian states), study design, and diagnostic modalities used in each study

Author	Study period	Number of CHD cases	Racial distribution	Age distribution	Gender distribution	Geographic location (States of Malaysia)	Study design	Diagnostic modalities used	Reference
		Total sample size
Balasundaram, 1970	1963—1965	68	39 Chinese 12 Malay 17 Indian	Majority in the 15–24 age group	37 Male 31 Female	Perak	Cross-sectional	Clinical signs, Chest X-ray, Electrocardiogram, and Portable Cambridge Transrite	[14]
		10,000
Noraihan et al., 2005	January 1999 – June 2000	46	N/A	N/A	N/A	Kuala Lumpur	Cross-sectional	Verification from pediatricians, and further investigation to confirm the clinical findings	[15]
		34,109
Johnson et al., 1978	November 1975 – April 1978	1021	N/A	N/A	N/A	Kuala Lumpur	Cross-sectional	Clinical diagnosis, Chest radiographs, Electrocardiograph, Cardiac catherization with cardiac angiography, Haemoglobin determination, Arterial blood-gas studies, Phonocardiography, and Echocardiography	[16]
		N/A
Mat Bah et al., 2018	2006–2015	3557	2476 Malay 687 Chinese 227 Indian 167 Other	106 (Antenatal) 1657 (0-28 days) 1383 (1-12 months) 331 (1-4 years) 80 (5-10 years)	1709 Male 1848 Female	Johor	Cross-sectional	2D echocardiogram, Surgical data, Clinical consultation, Cardiac catheterization, and Cardiac CT scan or MRI	[17]
		531,904
Bah et al., 2024	2006—2020	5728	N/A	4774 term infants	2798 Male 2930 Female	Johor	Cohort	2D echocardiogram or other imaging modalities, and postnatal diagnosis	[18]
		860,670
Thong et al., 2005	14-month period	35	N/A	N/A	124 Male 122 Female 7 Indeterminate	Perak	Cross-sectional	Clinical findings, Imaging studies, and Post-mortem reports	[19]
		17,720
Peng & Chuan, 1988	April 1984 – March 1987	36	Predominant Malay population	N/A	N/A	Kedah	Cross-sectional	Verification by paediatricians, Radiological and cardiological investigations, Laboratory investigations, and Ultrasound examinations	[20]
		19,769

“N/A” means data not available

Quality assessment

Based on the JBI quality assessment tool, six studies were rated as high quality, while one study was classified as medium quality. A summary of the risk of bias is provided in the Supplementary Table 3.

Total CHD birth prevalence

Figure 2 illustrates the temporal fluctuation in total CHD birth prevalence rates over the study period. The prevalence initially registered a high of 6.8 per 1,000 live births (95% confidence interval [CI]:5.19–8.41) in 1963, followed by a marked decline to 1.35 per 1,000 live births (95% CI: 0.96–1.74) in 1999. By 2020, the prevalence rate returned to 6.8 per 1,000 live births (95% CI: 6.63–6.97), suggesting a resurgence or improved reporting practices. The pooled prevalence of CHDs across all studies was 4.21 per 1,000 live births (95% CI: 2.21–6.22; P < 0.0001), with considerable heterogeneity (I² = 99%) (Fig. 3).

Fig. 2.

Temporal trend of total CHD birth prevalence in Malaysia from 1963 to 2020. The blue line represents the trajectory of CHD birth prevalence over time, with individual data points indicating the calculated prevalence for each study period

Fig. 3.

Forest plot depicting the pooled CHD birth prevalence in Malaysia across studies conducted between 1963 and 2020

Birth prevalence of 36 CHD subtypes

The distribution of CHD subtypes is depicted in Supplementary Fig. 2, categorised into acyanotic and cyanotic forms. Table 2 displays a detailed breakdown of the prevalence across 36 CHD subtypes. Acyanotic CHDs were predominant, comprising 75.13% of all cases, whereas cyanotic CHDs accounted for 13.77%. Ventricular septal defects (VSD) emerged as the most common subtype, representing 36.23% of cases, followed by patent ductus arteriosus (PDA) at 18.16% and pulmonary stenosis at 9.25%. Tetralogy of Fallot (TOF) was the most common cyanotic CHD, ranking fourth overall at 6.13%, followed by atrial septal defect (ASD) at 5.97%, D-transposition of the great arteries (TGA) at 2.33%, and atrioventricular septal defect (AVSD) at 2.21%. All remaining subtypes individually accounted for less than 2% of total CHD burden. Percentages were calculated by summing the number of cases reported for each subtype across all included studies and dividing this by the total number of CHD cases. The distribution of subtypes is presented visually as a pie chart in Fig. 4.

Table 2.

Prevalence distribution of CHD subtypes

CHD Subtypes	Prevalence of CHD subtypes/1000 (95% CIs)	References
Ventricular septal defect	2.402 (1.410, 3.394)	[14, 16–18]
Patent ductus arteriosus	1.243 (0.529, 1.957)	[14, 17, 18]
Pulmonary stenosis	0.694 (0.159, 1.230)	[17, 18]
Atrial septal defect	0.407 (0.000, 0.816)	[14, 17, 18]
Tetralogy of Fallot	0.354 (0.000, 0.737)	[17, 18]
Atrioventricular septal defect	0.166 (0.000, 0.428)	[17, 18]
D-Transposition of the Great Arteries	0.163 (0.000, 0.423)	[17, 18]
Pulmonary atresia with ventricular septal defect	0.134 (0.000, 0.369)	[17, 18]
Coarctation of aorta	0.129 (0.000, 0.361)	[17, 18]
Heterotaxy syndrome	0.108 (0.000, 0.319)	[17, 18]
Double outlet right ventricle	0.101 (0.000, 0.000)	[17, 18]
Hypoplastic left heart syndrome	0.09 (0.000, 0.284)	[17, 18]
Tricuspid atresia	0.079 (0.000, 0.260)	[17, 18]
Combined lesions	0.078 (0.000, 0.000)	[18]
Pulmonary atresia with intact ventricular septum	0.074 (0.000, 0.249)	[17, 18]
Aortic stenosis	0.070 (0.000, 0.241)	[17, 18]
Total anomalous pulmonary venous drainage	0.060 (0.000, 0.218)	[17, 18]
Ebstein's anomaly	0.054 (0.000, 0.205)	[17, 18]
Truncus arteriosus	0.054 (0.000, 0.203)	[17, 18]
Dextrocardia	0.051 (0.000, 0.002)	[14]
Others	0.051 (0.000, 0.000)	[17, 18]
Mitral atresia	0.045 (0.000, 0.180)	[17, 18]
Double inlet left ventricle	0.040 (0.000, 0.000)	[17, 18]
Congenitally corrected D-Transposition of the Great Arteries	0.036 (0.000, 0.158)	[17, 18]
Interrupted aortic arch	0.030 (0.000, 0.142)	[17, 18]
Coronary artery fistula	0.017 (0.000, 0.000)	[17, 18]
Cor triatriatum	0.013 (0.000, 0.000)	[17, 18]
Aortopulmonary window	0.012 (0.000, 0.000)	[17, 18]
Anomalous left coronary artery from pulmonary artery	0.011 (0.000, 0.000)	[17, 18]
Mitral stenosis	0.002 (0.000, 0.000)	[18]

Fig. 4.

Percentage of CHD subtypes, % (95% CIs). ALCAPA, Anomalous left coronary artery from pulmonary artery; AS, Aortic Stenosis; ASD, Atrial Septal Defect; AVSD, Atrioventricular septal defect; CAF, Coronary artery fistula; CAVF, Coronary arteriovenous fistula; ccTGA, Congenitally corrected D-Transposition of the Great Arteries; CI, Confidence interval; CoA, Coarctation of the Aorta; DORV, Double outlet right ventricle; EA, Ebstein's anomaly; ECD, Endocardial cushion defect; HLHS, Hypoplastic Left Heart Syndrome; IAA, Interrupted Aortic Arch; PAIVS, Pulmonary atresia with intact ventricular septum; PAVSD, Pulmonary atresia with ventricular septal defect; PDA, Patent Ductus Arteriosus; PS, Pulmonary Stenosis; SOVF, Sinus of Valsalva fistula; TA, Truncus Arteriosus; TA/TS, Tricuspid Atresia or Stenosis; TAPVD, Total anomalous pulmonary venous drainage; TGA, D-Transposition of the Great Arteries; TOF, Tetralogy of Fallot; VSD, Ventricular Septal Defect

Sex-specific CHD case distribution

A random-effects model meta-analysis assessed the sex distribution among CHD cases, revealing that males constituted 49% (95% CI: 0.48–0.50) (Supplementary Fig. 3) and females 51%. Heterogeneity among the population proportions was low (I² = 0%, τ² = 0.00).

Subgroup analysis of total CHD birth prevalence

Subgroup analyses stratified by geographic location (states of Malaysia), publication year, and study design revealed notable variation in CHD birth prevalence. By state, the prevalence was highest in Johor at 6.76 per 1,000 live births (95% CI: 6.63–6.90), followed by Perak at 4.33 per 1,000 live births (95% CI: 0.00–9.05), Kedah at 1.82 per 1,000 live births (95% CI: 1.23–2.41), and Kuala Lumpur at 1.35 per 1,000 live births (95% CI: 0.96–1.74) (Fig. 5).

Fig. 5.

Subgroup analysis of total CHD birth prevalence stratified by geographic location (states of Malaysia)

When stratified by publication year, CHD birth prevalence was 4.25 per 1,000 live births (95% CI: 0.00–9.13) for studies published between 1970 and 1997, compared to 4.22 per 1,000 live births (95% CI: 1.33–7.11) for studies published between 1998 and 2024 (Fig. 6).

Fig. 6.

Subgroup analysis of total CHD birth prevalence stratified by publication year

In terms of study design, cross-sectional studies reported a CHD birth prevalence of 3.69 per 1,000 live births (95% CI: 1.28–6.10), whereas the single cohort study reported a higher prevalence of 6.80 per 1,000 live births (95% CI: 6.63–6.97) (Fig. 7).

Fig. 7.

Subgroup analysis of total CHD birth prevalence stratified by study design

Heterogeneity

A leave-one-out sensitivity analysis was conducted to assess the influence of individual studies on the overall CHD birth prevalence in Malaysia. The results indicated that the findings were robust and not influenced by any single study. After sequential removal of individual studies, the total CHD birth prevalence ranged from 3.69 to 4.80 per 1,000 live births (Supplementary Table 4).

Publication bias

Publication bias was assessed using a funnel plot, which demonstrated a symmetrical distribution. Egger’s regression test yielded a P value of 0.131, indicating no significant evidence of publication bias (Supplementary Figs. 4 and 5).

Discussions

This systematic review and meta-analysis represents the first comprehensive synthesis of published evidence on CHD birth prevalence in Malaysia from inception to October 2024. The reported prevalence has fluctuated over time, with a pooled estimate of 4.21 per 1,000 live births, significantly lower than the global average of 8 per 1,000 live births [2, 4, 5]. This discrepancy may stem from the absence of fully representative national data and the limited number of studies focusing on CHD prevalence in Malaysia. A decline in reported CHD prevalence during the 1990 s may be attributed to incomplete diagnosis due to restricted access to structured prenatal diagnostic facilities [21]. Conversely, the rising prevalence observed after the 2000 s coincides with demographic shifts, particularly the increasing maternal age associated with delayed childbearing due to higher levels of female education and workforce participation [22]. Advanced maternal age is a well-established risk factor for congenital anomalies, including CHDs [23]. Additional maternal factors such as pre-gestational diabetes mellitus, phenylketonuria, febrile illness, infections, therapeutic drug exposures, vitamin A usage, marijuana use, and exposure to organic solvents have also been implicated in elevated CHD risk [24]. Furthermore, inadequate health literacy and high-risk behaviors during pregnancy, as highlighted by Narknok and Sakboonyarat (2023) may have contributed to the increasing CHD prevalence [25]. Further research is required to delineate the relative contributions of these factors to the observed prevalence trends.

In addition to the studies included in the meta-analysis, one article was identified as relevant but excluded from quantitative synthesis due to a high likelihood of cohort overlap. The study by Mat Bah, M. N. et al. (2018) reported on CHD cases drawn from the same institution and time frame as a larger study by the same author group already included in this review [26]. While it focused specifically on critical CHD and involved a smaller sample size, it reported demographic distributions that was consistent with those in the included dataset.

The demarcation of studies into pre- and post-1997 groups reflect a pivotal shift in Malaysia’s healthcare priorities and diagnostic capabilities related to congenital abnormalities. By the mid-1990s, congenital abnormalities had emerged as a leading cause of infant and perinatal mortality [27]. This period also saw the implementation of a rapid reporting system for perinatal deaths, enhancing the recognition and classification of congenital disorders [27]. Thus, the year 1997 marks an inflection point indicative of increased national focus and surveillance for CHD, justifying its use as a temporal threshold in this review. Advancements in diagnostic methodologies, particularly the widespread adoption of echocardiography, further contributed to changes in CHD detection [28]. Prior to this, diagnosis relied heavily on post-mortem findings, physical examination, radiography, catheterization, and surgical reports, limiting identification primarily to severe cases [2]. Echocardiography facilitated the detection of asymptomatic and mild cases, contributing to an apparent rise in reported prevalence [29]. Although limitations remain, such as the underestimation of VSD size in cases complicated by aortic valve prolapse [30], echocardiography remains the most widely used diagnostic tool for CHD. Improvements in diagnostic access, intraoperative assessment, and data recording post-2000 further support this observed trend [31], as reflected by the subgroup analysis showing more studies published after 1998.

Over the past century, significant advancements in CHD treatment have markedly improved survival rates, driven by innovations in cardiothoracic surgery and anaesthesia [32]. Historically, Malaysia’s capacity for complex paediatric cardiothoracic surgeries was constrained to the National Heart Institute and two private hospitals, resulting in prolonged waiting times [8]. This challenge was exacerbated by a shortage of paediatric cardiothoracic surgeons. The high cost of private-sector surgeries further restricted access for many families, leading to preventable mortality among children awaiting surgery [8, 33].

In line with previous studies, the current findings reveal that acyanotic CHDs account for the majority of cases. This observation is consistent with the study by Chia et al. (1988), which reported that all 143 heart disease cases identified among 19,151 deliveries were acyanotic, reflecting an incidence rate of 0.7% [34].

This meta-analysis identified VSD as the most prevalent CHD subtype in Malaysia, with a pooled prevalence of 36.23% (95% CI: 35.31–37.15%). PDA followed, with a prevalence of 18.16% (95%CI: 17.44–18.90%). These rates are higher than global estimates reported in systematic reviews and meta-analyses covering 1970 to 2017, which found VSD and PDA prevalences of 35.57% (95%CI: 33.88–37.28%) and 10.17% (95%CI: 8.52–11.95%), respectively [4]. The elevated prevalence of VSD and PDA in Malaysia may reflect previously discussed gaps in prenatal diagnostic capabilities, particularly during earlier periods. Unlike developed countries with well-established diagnostic infrastructure, Malaysia’s historical limitations in prenatal and postnatal screening likely contributed to underdiagnosis and delayed detection.

Gender is a multifaceted construct shaped by complex social, cultural, and biological influences that evolve over time and across environments [35]. These gender-related factors, which begin shaping individuals from early life, may interact with biological sex to influence cardiovascular development and disease susceptibility [35]. Investigating gender differences in CHD prevalence is essential for advancing precision medicine, informing risk stratification, and developing tailored prevention and treatment strategies. Previous review has reported notable gender-related differences in specific CHD subgroups, underscoring the need for such analysis [36]. In the present study, females accounted for 51% of CHD cases, an observation consistent with earlier findings that report a slightly higher cumulative prevalence of CHD in females across the lifespan [37–39]. Although this difference did not reach statistical significance, it may reflect underlying biological mechanisms, including sex-linked genetic and hormonal factors, that contribute to differential CHD risk [36].

Subgroup analysis by state revealed that Johor exhibited the highest CHD birth prevalence compared to other regions. This may be attributed to the use of the Pediatric Cardiology Clinical Information System in Johor, which facilitated the collection of more comprehensive and accurate data [17, 18]. In contrast, studies conducted in other states relied primarily on data from single hospitals. Analysis by publication period indicated comparable CHD birth prevalence rates for studies published between 1970–1997 and 1998–2024, underscoring the persistent burden of CHD in Malaysia. Stratification by study design showed a CHD birth prevalence of 3.69 per 1,000 live births (95% CI: 1.28–6.10) in cross-sectional studies and 6.80 per 1,000 live births (95% CI: 6.63–6.97) in cohort study. This disparity may reflect the rigorous patient follow-up inherent to a cohort study, which enables more reliable reporting of patient characteristics and outcomes.

The reported birth prevalence of CHD represents a reasonable estimate of its true burden. However, substantial heterogeneity was observed across studies. This variation is likely attributed to differences in study design, population demographics, sampling locations, sample sizes, and diagnostic methodologies. CHD prevalence also fluctuates with age and gestational age, as exemplified by PDA, which is considered a transient functional anomaly in preterm infants but a pathological condition in term infants [40, 41]. A key limitation of this study is the inability to conduct subgroup analyses based on gestational age due to insufficient data within the included studies. Additionally, the lack of comprehensive local epidemiological data, as reflected in the National Medical Research Register, constrains the accuracy of prevalence estimates. From a clinical standpoint, these findings highlight the need for standardized screening protocols and improved diagnostic precision, particularly in distinguishing transient from pathological anomalies. Expanding the use of echocardiographic screening in neonatal care, coupled with enhanced training for healthcare providers, may facilitate early detection and reduce missed diagnoses. Strengthening nationwide CHD surveillance systems is also essential. Implementing standardized diagnostic criteria and ensuring systematic data collection across healthcare facilities, including rural and underserved regions such as East Malaysia, will improve the accuracy of CHD prevalence estimates. At the public health level, targeted awareness campaigns on maternal health, early detection, and risk factor mitigation by focusing on diabetes management, infection prevention, and environmental exposure reduction, could contribute to primary prevention efforts. From a policy perspective, establishing a national CHD registry is essential for long-term surveillance, optimized resource allocation, and evidence-based decision-making. Investing in prospective, multicentre studies with longitudinal follow-up will not only refine prevalence estimates but also identify population-specific risk factors, ultimately informing targeted prevention and intervention strategies to alleviate the burden of CHD in Malaysia.

Conclusion

The reported total CHD birth prevalence in Malaysia has fluctuated considerably over time, with an estimated prevalence of 4.21 per 1,000 live births. The high proportion of VSD and PDA subtypes is particular concerning, underscoring the need for targeted interventions at the community level to alleviate the CHD burden. Early detection remains crucial for preventing severe complications and improving patient outcomes across all CHD subtypes. Strengthening data-sharing initiatives, particularly through National Medical Research Register, could facilitate a more comprehensive understanding of CHD epidemiology, ultimately informing more effective management strategies and public health policies.

Authors’ contributions

Authors’ contributions: A.S.Y.K. carried out data curation, formal analysis, methodology, data interpretation, and drafting of the original manuscript. S.M. contributed to the study conception, funding acquisition, data interpretation, supervision, and manuscript review and editing. K.Y.K. was involved in funding acquisition and provided revisions to the manuscript. M.C.M.; M.A.K.; Q.A. contributed to manuscript review and editing. All authors read and approved the final manuscript.

Funding

This research was funded by the Ministry of Higher Education, Malaysia under the fundamental research grant scheme [grant numbers FRGS/1/2022/SKK06/MUSM/03/2].

Data availability

All data generated or analysed during this study are included in this published article and its online supplementary file.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.