Prevalence of type-2 diabetes and prediabetes in Malaysia: A systematic review and meta-analysis.

OBJECTIVE: The main purpose of this study was to investigate the pooled prevalence of prediabetes and type-2 diabetes in the general population of Malaysia.
METHOD: We systematically searched Medline (PubMed), Embase, Web of Science, Google Scholar and Malaysian Journals Online to identify relevant studies published between January 1, 1995, and November 30, 2021, on the prevalence of type-2 diabetes in Malaysia. Random-effects meta-analyses were used to obtain the pooled prevalence of diabetes and prediabetes. Subgroup analyses also used to analyze to the potential sources of heterogeneity. Meta- regression was carried to assess associations between study characteristics and diabetes prevalence. Three independent authors selected studies and conducted the quality assessment. The quality of the final evidence was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.
RESULTS: Of 2689 potentially relevant studies, 786 titles and abstract were screened. Fifteen studies with 103063 individuals were eligible to be included in the meta-analyses. The pooled prevalence of diabetes was 14.39% (95% CI, 12.51%-16.38%; I2 = 98.4%, 103063 participants from 15 studies). The pooled prevalence of prediabetes was 11.62% (95% CI, 7.17%-16.97%; I2 = 99.8, 88702 participants from 9 studies). The subgroup analysis showed statistically significant differences in diabetes prevalence by the ethical sub-populations with highest in Indians (25.10%; 95% CI, 20.19%-30.35%), followed by Malays (15.25%; 95% CI, 11.59%-19.29%), Chinese (12.87%; 95% CI, 9.73%-16.37%), Bumiputeras (8.62%; 95% CI, 5.41%-12.47%) and others (6.91%; 95% CI, 5.71%-8.19%). There was no evidence of publication bias, although heterogeneity was high (I2 ranged from 0.00% to 99·8%). The quality of evidence based on GRADE was low.
CONCLUSIONS: Results of this study suggest that a high prevalence of prediabetes and diabetes in Malaysia. The diabetes prevalence is associated with time period and increasing age. The Malaysian government should develop a comprehensive approach and strategy to enhance diabetes awareness, control, prevention, and treatment. TRIAL REGISTRATION: Trial registration no. PROSPERO CRD42021255894; https://clinicaltrials.gov/.

Introduction

Diabetes mellitus is one of the most serious worldwide public health issues, posing a significant global burden on both public health and socioeconomic development. Although the incidence of diabetes has begun to decline in some nations, diabetes prevalence has climbed in most other developing and developed countries in recent decades [1-6]. According to the International Diabetes Federation (IDF), 9.3 percent (463 million) of adults worldwide have diabetes in 2019. The number is expected to rise to 10.2% (578 million) by 2030 and 10.9% (700 million) by 2045 if effective prevention methods are not implemented [7,8]. Furthermore, in 2017, nearly half of all people with diabetes (50.1%) were undiagnosed, approximately 374 million individuals (18–99 years) [8]. Similarly, prediabetes is estimated to affect 374 million (7.5%) of the global population in 2019 and is expected to increase to 8.0 percent (454 million) by 2030 and 548 million (8.6%) by 2045, with 48.1% of individual with prediabetes are under the age of 50 [8]. Type-2 diabetes reduces the average lifespan by around ten years [9].

Malaysia has the highest rate of diabetes in Western Pacific region and one of the highest in the world and costing around 600 million US dollars per year [10,11]. The prevalence of diabetes raised from 11.2% in 2011 to 18.3% in 2019, with a 68.3% increase [12]. According to a national survey report, in Malaysia in 2019, 3.6 million adults (18 and above years) had diabetes, 49% (3.7 million) cases were undiagnosed [13]. Diabetes is expected to affect 7 million Malaysian adults aged 18 and older by 2025, posing a major public health risk with a diabetes prevalence of 31.3% [12]. The prevalence of diabetes in Malaysia, based on published articles, ranges from 7.3% to 23.8% [14,15]. The increasing trend is a result of a variety of causes, including population expansion, population ageing, urbanization, and rising rates of obesity and physical inactivity [16]. The alarming prevalence of diabetes and its complications in Malaysia prompted this study to systematically identify, summarize available evidence on the prevalence of diabetes and prediabetes, and to estimate the pooled prevalence of diabetes and prediabetes in Malaysia. To our knowledge, no prior effort has been made to combine existing data on the prevalence of diabetes and prediabetes in Malaysian populations.

Methods

Design and registration

Our systematic review and meta-analysis protocol was registered with PROSPERO in March 2021 (registration number CRD42021255894). We conducted this study in accordance with the PRISMA guidelines [17], and the PRISMA 2009 checklist is attached in supplementary file (S1 File).

Literature search

Similar to our previous systematic reviews [18-20], we systematically searched Medline (PubMed), Web of Science, Google scholar, Embase and Malaysian Journals Online to identify relevant studies published between January 1, 1995, and November 30, 2021, on the prevalence of prediabetes and diabetes in Malaysia. The following keywords were combined to design the search strategy: “diabetes”, “type-II diabetes”, “type 2 diabetes”, “prediabetes”, “T2D”, “non-communicable diseases”, “prevalence”, “impaired fasting glucose”, “impaired glucose tolerance”, “risk factor”, “risk factors”, “epidemiology”, “glucose abnormalities”, “glucose intolerance”, “Malaysia”, “Malaysian” and “Malays”, as well as variations thereof. To identify potential additional studies and reports, we also scrutinized the reference list of all selected articles. The results of search strategy are provided in the supplementary file (S1 Table).

Inclusion and exclusion criteria

For this study, studies were included if they provided enough data to calculate prevalence of diabetes and prediabetes; included a community-or population-based survey and published in English between January 1995 to September 2021; participants residing in Malaysia. The following studies were excluded: were review articles, case studies, qualitative studies, case series, abstracts, and intervention studies; was irrelevant to type-2 diabetes; reported on gestational or type-1 diabetes; based on Malaysian community living outside of Malaysia; and based on duplicated information (data); and based on data that was published in more than one study (the latest data version was considered).

Data extraction

Three investigators (JAN, AA, and RM) independently conducted data extraction using a preconceived and standardized data extraction form. The collected information was: surname name of the author, year of publication, year of investigation, study design, state where study was conducted, mean or median age of participants, total sample size, percentage of male participants, percentage of hypertensive participants, sampling strategy, percentage of smoker participants, area (rural vs urban), diagnostic criteria and percentage of overweight or obese participants. Disagreements and uncertainties were addressed by mutually consensus or consultation with the 4th investigator (SA).

Methodological quality assessment

Three of investigators (JAN, AA, and RM) independently evaluated the quality of each study by using the JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data [21]. Any discrepancies were discussed between the investigators, and another investigator (SA) made a final judgment if no mutual consensus could be reached. Each study received a score ranging from 0 to 9. We classified each study as high risk (for scores <50%), moderate risk (for quality scores above 50–69%), or low risk of bias based on its score (for quality scores ≥70%).

Statistical analysis

Statistical software R (version 4.1.0) was used to generate meta-analysis for diabetes and prediabetes prevalence. Because of the significant expected heterogeneity among studies, random-effects meta-analyses were used. Prior to pooling prevalence estimates, the Freeman-Tukey double arc-sine transformation was applied to stabilise the variance of the raw prevalence estimates from each included study. The I2 index was considered to evaluate heterogeneity between studies, with I2 values between 25% or below indicate mild degree of heterogeneity, between 26%-50% indicate moderate degree of heterogeneity, and greater than 50% indicate the presence of substantial heterogeneity [22-24]. Forest plots were created to visually assess the results of pooling.

We used subgroup meta-analysis to explore causes of substantial heterogeneity. For this purpose, we stratified meta-analyses by area of residence (urban vs rural), participant age group, gender, time period, and ethical subgroup. We investigated sources of heterogeneity with a meta-regression. The covariates in the meta-regression considered were state where study was conducted, study year, area of residence (rural vs urban), sample size, baseline year of data collection, mean age of participants, methodological quality, and gender. Visual inspection of the funnel plots was performed to evaluate publication bias in the meta-analyses. Egger’s test and Begg’s test method were also considered for quantitative estimate of the publication bias. Cohen’s coefficient was used to determine inter-rater agreement among the authors who were engaged in data extraction and study selection [25]. The quality of this systematic review and meta-analysis was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach [26].

Results

The PRISMA diagram with the flow of articles through this study is described in Fig 1. Our initial electronic search identified 2682 potentially relevant articles, and an additional 7 articles were identified by checking reference lists. After excluding of duplicates (n = 1903), we screened 786 articles by title and abstract and excluded 733 irrelevant articles. Inter-rater agreement among the investigators on abstract selection was very high (κ = 0.846, p<0.001). We scrutinized the eligibility of potentially relevant studies (n = 53) in full text against the inclusion and exclusion criteria. The articles were removed as 12 studies did not mention the results of diabetic patients, duplication of dataset (n = 10), only assessed patients with type-1 diabetes (n = 11), did not include enough information to compute prevalence (n = 5). Thus, 15 studies were identified as the eligible studies in the meta-analysis (Fig 1).

Fig 1

Study and data inclusion, using PRISMA 2009 guideline [17].

Table 1 summarizes the general characteristics of 15 selected studies [11,14,15,27-38]. In total, 103063 individuals were included. A cross-sectional study design was utilised in 11 of the 15 investigations, and 4 studies did not explicitly describe a study strategy, it can be inferred as a cross-sectional study design. Sample sizes ranged from 119 to 34539 individuals, with a median of 1489 individuals. The age of participants enrolled ranged from 15 to 85 years overall in 15 studies. The studies were published between 1996 and 2020, while the participants were enrolled between November 1993 and June 2019. In 14 studies, the proportion of male participants in the study sample was recorded. Male participation ranged from 0 to 54.8%, and the percentage of overweight participants ranged from 11 percent to 49.1 percent. Following an evaluation of the studies’ quality, 11 were found to be of low-risk bias, 5 to be of moderate level, and none to be of high-risk bias. The authors had a high level of agreement on the extracted data (k = 0.86, p = 0.001).

Table 1

Summary of the general characteristics selected studies.

Author	Year	Data collection Year	Sample Size	Positive for type-2 diabetes	Positive for prediabetes	Prevalence of diabetes	Avg. Age of participant	Research Design	Setting	Male (%)	State	Sampling strategy	Diagnostic method And criteria	% of hypertension	% of Over-weight/Obese	% of smoker	Risk Bias
NHMS-2019 [11]	2019	2019	10464	1915	NA	18.3	NA	NA	Both	49.9	National	Two Stage Stratified Random	FBG≥7 mmol/l, 2hBG>11.1 mmol/l	32.7	NA	11.5	High
Harris et al. [14]	2019	February to May 2015	330	24	NA	7.3	43.7	CS	Rural	40.3	Eastern Sabah	Stratified Random Sampling	FBG≥7 mmol/l	26.79	NA	18.45	Medium
Samsudin et al. [15]	2016	September 2012 to February 2013	1414	337	NA	23.8	69.31	CS	Urban	NA	Northern Areas	Stratified, Multistage, and Snowball	NA	42.4	NA	NA	Medium
Khebir et al. [27]	1996	November 1993 to January 1994	260	38	30	14.6	46.5	CS	Rural	43.1	Kuala Selangor	Simple Random sampling	2hPG>11.1 mmol/l	NA	11	NA	High
NHMS-2006 [28]	2006	2006	34539	4007	1451	11.6	NA	CS	Both	44.8	National	Two Stage Stratified Random	FPG≥7 mmol/l, 2hPG≥11.1 mmol/l	NA	NA	NA	High
Nazri at al. [29]	2008	September 2005	348	27	NA	7.8	40.7	CS	Rural	47.3	Pulau Kundur	Simple Random Sampling	NA	12.6	49.1	55.8	Medium
Rampal at al. [30]	2009	2004	7683	1168	1321	15.2	46.8	CS	Urban	39.6	National	Stratified Two Stage Cluster Sampling	FBG≥7 mmol/l	NA	NA	NA	High
Mohamud et al. [31]	2010	NA	119	10	20	8.5	35.83	NA	Rural	0	Peninsular	NA	FPG≥7 mmol/l	NA	NA	NA	High
NHMS-2011 [32]	2011	2011	17783	2703	871	15.2	NA	NA	Both	46.7	National	NA	FBG≥6.1 mmol/l, 2hBG>11 mmol/l	32.7	NA	NA	High
Mustafa et al. [33]	2011	April to August 2008	3879	489	857	12.6	50.93	CS	Both	34	National	NA	FPG≥7 mmol/l, 2hPG≥11.1 mmol/l	76.5	NA	10.8	High
Nazaimoon et al. [34]	2013	NA	4336	993	939	22.9	48.02	CS	Both	35.1	National	Two Stage Stratified Random	FPG≥7 mmol/l, 2hPG≥11.1 mmol/l,6.3≤HbA1C≤6.5 mmol/l	NA	NA	NA	High
NHMS-2015 [35]	2015	2015	19935	3489	937	17.5	NA	NA	Both	47.6	National	NA	FBG≥6.1 mmol/l, 2hBG>11 mmol/l	30.3	NA	NA	High
Aniza et al. [36]	2016	March to November 2011	1489	162	NA	10.9	44.9	CS	Rural	38.7	Tanjung Karang	Convenient Sampling	NA	20.6	NA	21.8	High
Naggar et al. [37]	2017	March 2016	316	34	NA	10.8	NA	CS	NA	53.5	Selangor	Simple Random Sampling	NA	30	19.7	21.3	Medium
Rahim et al. [38]	2020	August to November 2017	168	33	17	19.6	52.63	CS	Rural	54.8	Penang	Simple Random Sampling, Convenience Sampling	NA	39.5	23.7	25.2	Medium

Abbreviations; HbA1C, glycated hemoglobin; FBG, fasting blood glucose, FBG, fasting blood glucose, FPG, fasting plasma glucose CS, cross-sectional; 2hBG, 2-hour blood oral glucose; mmol/l, millimoles per liter, NA, not available.

Quantitative synthesis

The findings of the overall and subgroup meta-analyses are shown in Table 2. The diabetes prevalence was reported in 15 studies, with a total of 103063 individuals. The prevalence of diabetes ranged from 7.8% to 23.8%. The overall pooled estimated prevalence of diabetes was 14.39% (95% CI, 12.51%–16.38%; prediction interval: 7.37–23.23). Fig 2 shows diabetes prevalence estimates derived from meta-analysis. The analysis revealed a significant heterogeneity. The level of heterogeneity in the meta-analysis was high (I2 = 98.4%; P < 0.001) (Fig 2). The Egger’s and Begg’s tests did not find any publication bias in the meta-analysis (p = 0.7296 and p = 0.5862, respectively). The visual inspection of funnel plot also showed no evidence of the presence of publication bias (Fig 3). The sensitivity analysis revealed that the pooled prevalence of diabetes varied from 13.76% (95% CI, 11.90%–15.72%) to 14.91% (95% CI, 12.96%–16.98%) after removing a one study at one time (Supplement file, S1 Fig), but no single study had a significant influence on the pooled prevalence.

Table 2

Summary of overall and subgroup meta-analyses.

Variable	Studies	Sample size	Positive cases	Prevalence, % (95% CI)	I2	95%, Prediction interval	p-Heterogeneity	p Egger	P-Difference
Prediabetes	9	88702	6443	11.62 (7.17–16.97)	0.998	(0.29–35.23)	< 0.001	0.1209	0.8978
Male prediabetes	7	39241	2796	10.98 (6.95–15.79)	0.994	(0.58–31.47)	< 0.001
Female prediabetes	8	49201	3565	11.40 (6.55–17.40)	0.997	(0.01–37.55)	< 0.001
Diabetes	15	103063	15429	14.39 (12.51–16.38)	0.984	(7.37–23.23)	< 0.001	0.7296
Undiagnosed	8	91526	6798	8.60 (6.48–10.99)	0.992	(2.25–18.48)	< 0.001	0.2363
By Gender								0.7555	0.6063
Male	12	45580	6697	13.80 (11.94–15.77)	0.961	(7.53–21.56)	< 0.001
Female	13	55678	7992	14.54 (12.50–16.70)	0.973	(7.49–23.40)	< 0.001
By Setting								0.8733	0.0594
Rural	11	37307	5060	12.72 (10.63–14.97)	0.966	(5.84–21.73)	< 0.001
Urban	7	61561	9285	15.89 (13.59–18.34)	0.984	(8.23–25.48)	< 0.001
By Age								0.3720	0.0001
20 to 29	5	2078	110	3.16 (3.62–6.94)	0.493	(1.35–11.05)	0.0915
30 to 45	4	5935	815	13.71 (12.85–14.60)	0.000	(11.84–15.69)	< 0.001
46 to 59	4	11165	2517	25.66 (20.60–31.07)	0.966	(5.70–53.57)	< 0.001
60+	6	10191	3489	33.45 (28.45–38.64)	0.955	(17.14–52.08)	< 0.001
Time period								0.7296	0.0210
1995–2010	5	42949	5250	11.82 (9.44–14.43)	0.951	(4.56–21.81)	< 0.001
2011–2020	10	64615	11003	15.77 (13.75–17.89)	0.974	(8.98–24.00)	< 0.001
Ethnicity								0.1269	<0.0001
Malay	10	56435	7718	15.25 (11.59–19.29)	0.993	(3.70–32.67)	0.0001
Chinese	9	18057	1949	12.87 (9.73–16.37)	0.974	(3.29–27.38)	0.0233
Indian	9	7909	1724	25.10 (20.19–30.35)	0.959	(9.14–45.65)	0.0001
Bumiputeras	9	9699	704	8.62 (5.41–12.47)	0.968	(0.37–25.27)	0.3535
Others	6	1710	122	6.91(5.71–8.19)	0.000	(5.25–8.76)	0.8290

Fig 2

Pooled prevalence of type-2 diabetes in Malaysia.

Fig 3

Funnel plot of the prevalence of type-2 diabetes in Malaysia.

The prevalence of prediabetes was reported in 9 studies, with a total of 88702 individuals. The overall pooled estimated prevalence of prediabetes was 11.62% (95% CI, 7.17%–16.97%, prediction interval: 0.25–35.23) by random-effects meta-analysis. The meta-analysis had a high level of heterogeneity (I2 = 99.8%; P <0.001) (Fig 4). The visual inspection of the funnel plot (Fig 5) suggested no evidence of the presence of publication bias in the analysis. This was also not found to be statistically significant by the Egger’s test of bias. The sensitivity analysis revealed that the pooled prevalence of diabetes varied from 10.43% (95% CI, 6.56%–15.07%) to 12.84% (95% CI, 7.40%–19.49%) after removing a one study at one time (Supplement file S2 Fig), but no single study had a significant influence on the pooled prevalence of prediabetes. According to GRADE approach (Table 3), the quality of evidence on the pooled prevalence of diabetes was found to be of low certainty because of inconsistency (the presence of high heterogeneity).

Fig 4

Pooled prevalence of prediabetes in Malaysia.

Fig 5

Funnel plot of the prevalence of prediabetes in Malaysia.

Table 3

GRADE assessment for the studies included in the synthesis with meta-analysis.

Quality assessment
№ of studies	Study design	Participants	Risk of Bias	Inconsistency	Indirectness	Imprecision	Publication Bias	Estimated effect (95% CI)	Quality of Evidence
15	Observational studies	103063	Serious1	Very Serious2	Serious3	Serious4	Not Serious5	14.39% (12.51–16.38)	⨁⨁ LOW

1 Study quality (assessed by the JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data) ranged from high to low risk of bias. More than 50% of studies included in this analysis were of low risk of bias.

2Based on substantial heterogeneity (I2 ranged from 0.00% to 99·8%) and differing estimates of the effect across studies.

3Downgrade for serious indirectness due age and ethnical variation, therefore affecting the generalizability to the general population.

4The spread of the 95% CI exceeded 10% (±5%); and Only 2 studies had large 95% CIs.

5Visual inspection of funnel plot found no evidence of publication bias. The Egger’s and Begg’s tests also did not find any publication bias in the meta-analysis (p = 0.7296 and p = 0.5862, respectively).

Table 2 also demonstrates the prevalence of diabetes according to gender, setting (rural or urban), ethical sub-groups, time period and age of participants. The prevalence of prediabetes and diabetes did not differ significantly when stratified by sex. The pooled prevalence of diabetes by gender was 13.80% (95% CI, 11.94%–15.77%; I2 = 96.1%) for men and 14.54% (95% CI, 12.50%–16.70%; I2 = 97.3%) for women in the population-based studies while pooled prevalence of prediabetes was 11.40% (95% CI, 6.55%–17.40%; I2 = 99.7%) for women and 10.98% (95% CI, 6.95%–15.79%; I2 = 99.4%) for men. The prevalence of diabetes for each ethical subpopulation was highest in the Indians sub-population (25.10%; 95% CI, 20.19%–30.35%), followed by Malays (15.25%; 95% CI, 11.59%–19.29%), Chinese (12.87%; 95% CI, 9.73%–16.37%), Bumiputeras (8.62%; 95% CI, 5.41%–12.47%) and others (6.91%; 95% CI, 5.71%–8.19%). There was a significant (p<0.001) increasing trend in diabetes prevalence with increasing age, from 3.16% (95% CI: 3.62%–6.94%) in the 20–29 years age group, 13.71% (95% CI, 12.85%–14.60%) in the 30–45 years age group, 25.66% (95% CI, 20.60%–31.07%) in the 46–59 years of age group, and 33.45% (95% CI, 28.45%–38.64%) in the 60 and above years age groups.

Diabetes prevalence stratified by publication period: 1995–2010, and 2011–2020. Diabetes prevalence was 11.82% (95% CI, 9.44%–14.43%) and 15.77% (95% CI, 13.75%–17.89%) for the publication periods, respectively. Over a 26-year period (1995–2020), the pooled prevalence of diabetes raised from 11.82% to 15.77%. Furthermore, there was no significant difference in the prevalence of diabetes based on diagnostic method (FBG/2hBG, 14.95%; FBG, 10.32%, with p = 0.2058). For all subgroup analyses, there was no publication bias.

Random-effects univariable meta-regression models (Table 4) revealed a stronger association with prevalence of diabetes and increasing age year (β = 0.0073; 95% CI: 0.0021–0.0125, p = 0.0059; R2 = 12.45%), study year (β = 0.0039; 95% CI: 0.0007–0.0071, p = 0.0173; R2 = 53.13%), and study setting (β = -0.1141; 95% CI: -0.2250–-0.0032, p = 0.0438; R2 = 12.63%). The diabetes prevalence was not statistically associated with gender, overweight, smoking status, and quality of studies.

Table 4

Summary of findings univariate meta-regression analyses.

Variable	Beta (β)	p-value	95%CI	R2%
Publication year	0.0025	0.1975	(-0.0013–0.0063)	44.27
Study year	0.0039	0.0173	(0.0007–0.0071)	53.13
Age	0.0073	0.0059	(0.0021–0.0125)	12.45
Hypertension	0.0004	0.5777	(-0.0011–0.0020)	4.60
Methodology	-0.0387	0.1325	(-0.0898–0.0123	14.89
Overweight	-0.0042	0.1484	(-0.0100–0.0015)	40.69
Gender (male)	0.0014	0.3164	(-0.0013–0.0040)	0.00
Setting	-0.1141	0.0438	(-0.2250–-0.0032)	12.63
Smoking	-0.0015	0.4588	(-0.0056–0.0025)	0.00

Discussion

The primary goal of this systematic review and meta-analysis was to collect all available data on the prevalence of diabetes and prediabetes, as well as the risk factors associated with them, among adults in Malaysia between 1995 and 2021. The findings of this study will aid in the development of public health strategies to reduce the prevalence of prediabetes and diabetes. This analysis included 15 studies with a total of 103063 participants. The pooled prevalence of diabetes was 14.39%–approximately one out of every 7 people living in Malaysia is suffering from diabetes. Our results are consistent with a meta-analysis examining the prevalence of diabetes in another Asian country (Pakistan 14.62%) [20]. However, the prevalence of diabetes in Malaysia is significantly higher than the neighboring countries, like Singapore (5.5%) [39] and Indonesia (6.2%) [40].

When age groups were compared, the prevalence of diabetes in the 20–29 year age group was the lowest (3.16%), while the highest prevalence was reported in the 60 and older age group (33.46%). People aged 60 and more are more than 10 times as likely as those aged 20–29 to have type-2 diabetes. This is because that Malaysians is a fast-ageing population in world with average age is 74.4 years in 2017 [41,42]. At the population level, the increasing ageing population and low death rates will increase the proportion of people living with diabetes, putting a large number of people at risk of acquiring sequelae [43].

By stratifying ethically, subgroup analysis revealed that there is a strong association between pooled diabetes prevalence and major ethnic groups. The prevalence of diabetes was most common in the Indian’s subpopulation (25.10%), followed by the Malays (15.25%), Chinese (12.87%), Bumiputera (8.62%) and others (6.91%). The results also suggest that the prevalence of diabetes is not influenced by year of publication, sex distribution, gender ratio, methodological quality of studies, setting and smoking.

This study has certain limitations. As expected, we found significant heterogeneity in the included studies, suggesting that about 97% of the variability in the measure of the prevalence of diabetes is due to heterogeneity between studies rather than chance. Subgroup analysis and meta-regression models were used to address the issue of high heterogeneity, with factors added to the univariate model. The findings of this meta-analysis should be interpreted with caution due to the high degree of heterogeneity. Another shortcoming of this review is that the articles chosen did not differentiate between type 1 and type 2 diabetes. As a result, we hypothesized that all cases of diabetes reported were type-2 which accounts for 90 to 95 percent of all diabetes cases. Furthermore, this study is based on only a few publications (only 15). Because of the small number of studies included in this review, only univariate meta-regression (instead of multivariable meta-regression) analysis is used to analyze the importance of each covariate.

Despite these limitations, this is the first systematic review and meta-analysis to provide pooled prevalence of diabetes and prediabetes in Malaysia. Before beginning the study, we published a protocol outlining our methodology, and we employed scientific and statistical procedures to collect and pool data. Subgroup studies and random effect meta-regression analyses were performed to evaluate the numerous factors that could affect our estimate.

Conclusion

This study comprehensively describes the prevalence of prediabetes and diabetes in adult population from Malaysia from 1995 to 2021. This study suggests that the pooled diabetes prevalence in Malaysia was 14.39%, but varied significantly by ethical subpopulations with the highest in Indians and lowest in Bumiputeras. The prevalence of diabetes is higher than in neighbouring countries such as Indonesia and Singapore.

Because diabetes and prediabetes are on the increase in Malaysia, the Malaysian government should establish diabetes control programmes throughout the country. To minimize the prevalence of diabetes in Malaysia, the Malaysian government should develop a comprehensive approach and strategy to enhance diabetes awareness, control, prevention, and treatment.

Forest plot of the sensitivity analysis for prevalence of type-2 diabetes in Malaysia.

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Forest plot of the sensitivity analysis for prevalence of prediabetes in Malaysia.

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Search strategies for electronic databases.

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PRISMA checklist.

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15 Nov 2021

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you for giving me the opportunity to review this manuscript. The authors conducted a systematic review and meta-analysis to investigate the pooled prevalence of prediabetes and diabetes in the general population of Malaysia. I have few comments that I feel authors should address before the manuscript is considered for publication.

1.The introduction part is not sufficiently described on the problem statement of diabetes in Malaysia. It lacks motivation to conduct the current study. I believe authors have not elaborated the burden of diabetes and that the studies conducted in Malaysia could apprehend the true “burden” of diabetes and pre-diabetes based on established works till date. The following literature that was conducted from the Malaysian perspective needs to be critically appraised, elaborated and cited in the current paper:

- Ganasegeran K, Hor CP, Jamil MFA, Loh HC, Noor JM, Hamid NA, Suppiah PD, Abdul Manaf MR, Ch’ng ASH, Looi I. A Systematic Review of the Economic Burden of Type 2 Diabetes in Malaysia. International Journal of Environmental Research and Public Health. 2020; 17(16):5723. https://doi.org/10.3390/ijerph17165723

- Ganasegeran K, Hor CP, Jamil MFA, Suppiah PD, Noor JM, Hamid NA, Chuan DR, Manaf MRA, Ch’ng ASH, Looi I. Mapping the Scientific Landscape of Diabetes Research in Malaysia (2000–2018): A Systematic Scientometrics Study. International Journal of Environmental Research and Public Health. 2021; 18(1):318. https://doi.org/10.3390/ijerph18010318

2. In addition, the authors could highlight the burden of diabetes of neighboring countries, especially within the Western Pacific region, in comparison to Malaysia.

3. In the PRISMA chart, what do the authors meant by “additional records identified through other sources?” What are the sources were used? This needs to be clarified.

4. In the PRISMA chart again, I could not capture authors intention of excluding up to 307 full text articles with reason. What reasons?

5. Please attach the results of your search strategies for each database used as your supplementary file.

6. Classifying studies as high risks bias, moderate risk bias and low risks from the methodological quality assessment seems a little awkward. Cross-sectional studies are often not powered to establish causality or temporality, instead mere associations and they can be self-reported. Were these taken into consideration?

7. Is the tool for methodological assessment appropriate? Authors mentioned four studies did not explicitly mention study design. Then why was it included and how could it be interpreted to extract prevalence rates?

8. Most studies are single-centered. Will they be sufficiently be powered to be pooled for a country level estimate?

9. Authors included the NHMS surveys as well. Kindly note that NHMS is the nation’s five year survey of exploring health of the Malaysian people. It is a report published and not those studies published as reported in the methods part (extracted from databases) as claimed by the authors.

10. Inclusion criteria is not clear on the type pf diabetes – type 1, type 2, gestational or all?

Authors need to undertake the revisions as suggested above, to be further considered for publication.

Reviewer #2: In this paper “Prevalence of diabetes and prediabetes in Malaysia: a systematic review and meta-analysis”, the authors (Sohail Akhtar and et al) estimated the prevalence of diabetes and pre-diabetes in Malaysia population. To do so, they reviewed published articles until September 30, 2021 and then pooled all values of prevalence. Unfortunately, the manuscript contained many flaws, some were serious:

Title & Introduction section

- Type of diabetes must be specified.

- References (e.g. number 27, 29, 31, and … must be written in Vancouver reference style.

- Introduction should be short, summary, and comprehensive.

Method section

- Search strategy is not well-defined. Authors must apply some key words such as ‘prediabetes’ , ‘gestational diabetes’

- Please describe about reasons of excluding 307 studies.

- Exclusion and inclusion criteria should be reported for 307 excluded studies.

- Gestational diabetes cases must be categorized separately.

Results

- In results section, first paragraph must describe first diagram (e.g. relevant studies=54).

- In second paragraph, description about gender frequency has been repeated.

- Please report number of studies by type of diabetes(type I and type II)

- Please report prevalence by diagnostic method

- In table 1, please specify positives for diabetes, pre-diabetes, …

- In table 1, it seems that some subjects are wrong. E.g. the prevalence for Smsudin et al (14) study in original study is 69 but in present study reported 65. Also, in original full text, snowball sampling (non-random) is method of sampling but authors reported ‘Random’ in Table 1.

- In Table1, citing of studies is incorrect. Please check it.

- In section of ‘quantitative synthesis’, prevalence for men reported 14.63 but it is 16.15 in table 2.

- Table 2 has some typing errors.

- In table 3, please specify type of gender.

- The authors must check all extracted data.

- The statistical analysis is not good and not representing the results properly.

- Non-significant variables in univariate analysis did not discuss in discussion section.

- Authors did not carry out Sensitivity analysis.

Reviewer #3: 1. GRADE scoring was not used to assess the quality of meta-analysis evidence. Evaluate your meta-analysis using the GRADE score.

2. Diabetes diagnosis criteria were not stated for studies, as it was changed over the years.

3. Studies reporting prevalence may not be published or can be published in local databases. Your search must be amended by searching for these publications and gray literature.

4. Article screening process was well described, but the numbers stated are wrong.

5. In the abstract of the article and the results, two different population sizes are mentioned. It should be corrected.

6. In the result section “Male participation ranged from 0 to 61.8%, and the number of overweight participants ranged from 11 percent to 49.1 percent". The "number" should be changed to "percentage".

7. In the result section “table 1 summarize……”. The study is not a longitudinal study. Thus using baseline characteristics is inappropriate, it should be changed to general characteristics.

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10 Dec 2021

PONE-D-21-32696

Prevalence of diabetes and prediabetes in Malaysia: a systematic review and meta-analysis

PLOS ONE

Dear Dr. Akhtar,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Reply: Thanks a lot for your response and comments. All the comments of the reviews have been carefully considered and incorporated in the revised version. The point-by-point response is given below here and mentioned in the revised version in highlighted color, as given below.

Response to Reviewer 1: All changes have been mentioned in Yellow Colour

Response to Reviewer 2: All changes have been mentioned in Green Colour

Response to Reviewer 3: All changes have been mentioned in Pink Colour

Please note that:

a) Please clarify the sources of funding (financial or material support) for your study. List the grants or organizations that supported your study, including funding received from your institution.

Answer: We don’t have any sources of funding for this study.

b) b) State what role the funders took in the study. If the funders had no role in your study, please state: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.”

Answer: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

c) If any authors received a salary from any of your funders, please state which authors and which funders.

Answer: No author received any salary form any funder.

d) If you did not receive any funding for this study,

Answer:The authors received no specific funding for this work

Reviewer #1:

Reviewer #1: Thank you for giving me the opportunity to review this manuscript. The authors conducted a systematic review and meta-analysis to investigate the pooled prevalence of prediabetes and diabetes in the general population of Malaysia. I have few comments that I feel authors should address before the manuscript is considered for publication.

1.The introduction part is not sufficiently described on the problem statement of diabetes in Malaysia. It lacks motivation to conduct the current study. I believe authors have not elaborated the burden of diabetes and that the studies conducted in Malaysia could apprehend the true “burden” of diabetes and pre-diabetes based on established works till date. The following literature that was conducted from the Malaysian perspective needs to be critically appraised, elaborated and cited in the current paper:

- Ganasegeran K, Hor CP, Jamil MFA, Loh HC, Noor JM, Hamid NA, Suppiah PD, Abdul Manaf MR, Ch’ng ASH, Looi I. A Systematic Review of the Economic Burden of Type 2 Diabetes in Malaysia. International Journal of Environmental Research and Public Health. 2020; 17(16):5723. https://doi.org/10.3390/ijerph17165723

- Ganasegeran K, Hor CP, Jamil MFA, Suppiah PD, Noor JM, Hamid NA, Chuan DR, Manaf MRA, Ch’ng ASH, Looi I. Mapping the Scientific Landscape of Diabetes Research in Malaysia (2000–2018): A Systematic Scientometrics Study. International Journal of Environmental Research and Public Health. 2021; 18(1):318. https://doi.org/10.3390/ijerph18010318

Answer: Thanks a lot for your comments. Both the references have been added in the introduction section (see the yellow highlighted section, page1 (2nd paragraph).

2. In addition, the authors could highlight the burden of diabetes of neighboring countries, especially within the Western Pacific region, in comparison to Malaysia.

Answer: A comparison has been added. See highlighted in yellow in introduction section, page 1

3. In the PRISMA chart, what do the authors meant by “additional records identified through other sources?” What are the sources were used? This needs to be clarified.

Answer: Additional records identified through hand searching of reference list of selected articles. Corrected accordingly on page 12 and already mentioned in search strategy.

4. In the PRISMA chart again, I could not capture authors intention of excluding up to 307 full text articles with reason. What reasons?

Answer: Irrelevant articles were excluded on the basis of title and abstract review. Corrected accordingly in the PRISMA chart on page 12 (highlighted in yellow)

5. Please attach the results of your search strategies for each database used as your supplementary file.

Answer: Thanks a lot for your comment. Added on supplementary life.

6. Classifying studies as high risks bias, moderate risk bias and low risks from the methodological quality assessment seems a little awkward. Cross-sectional studies are often not powered to establish causality or temporality, instead mere associations and they can be self-reported. Were these taken into consideration?

Answer: Critical appraisal is a systematic process used to identify the strengths and weaknesses of a research article to assess the usefulness and validity of research findings. The most important components of a critical appraisal are an evaluation of the appropriateness of the study design for the research question and a careful assessment of the key methodological features of this design.

We have now considered another appraisal for prevalence study“JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data”. The purpose of this appraisal is to evaluate the methodological quality of a study and to determine the extent to which a study has addressed the possibility of bias in its design, conduct and analysis

7. Is the tool for methodological assessment appropriate? Authors mentioned four studies did not explicitly mention study design. Then why was it included and how could it be interpreted to extract prevalence rates?

Answer: Thanks a lot for your comment. The four studies which did not explicitly mention study design but can be inferred as a cross-section study design (as mentioned now result section. However, we have changed the critical appraisal from “Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies” to “JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data” to check the methodological quality of included articles.

8. Most studies are single-centered. Will they sufficiently be powered to be pooled for a country level estimate?

Asnwer: Meta-analysis is a research process used to systematically synthesise or merge the findings of single (single or multi-centered), independent studies, using statistical methods to calculate an overall or ‘absolute’ effect.

9. Authors included the NHMS surveys as well. Kindly note that NHMS is the nation’s five-year survey of exploring health of the Malaysian people. It is a report published and not those studies published as reported in the methods part (extracted from databases) as claimed by the authors.

Answer: We also scrutinized the reference list for additional studies and reports, as mentioned in the literature search section. The NHMS surveys were found in reference lists from different articles.

10. Inclusion criteria is not clear on the type of diabetes – type 1, type 2, gestational or all?

Answer: Articles only on type-2 diabetes were considered for this systematic review and meta-analysis. The title and inclusion exclusion criteria have been updated accordingly.

Authors need to undertake the revisions as suggested above, to be further considered for publication.

**********************************************************************************

Reviewer #2:

In this paper “Prevalence of diabetes and prediabetes in Malaysia: a systematic review and meta-analysis”, the authors (Sohail Akhtar and et al) estimated the prevalence of diabetes and pre-diabetes in Malaysia population. To do so, they reviewed published articles until September 30, 2021 and then pooled all values of prevalence. Unfortunately, the manuscript contained many flaws, some were serious:

Title & Introduction section

- Type of diabetes must be specified.

Answer: Thanks a lot for your comment. Title and paper are modified accordingly.

- References (e.g., number 27, 29, 31, and … must be written in Vancouver reference style.

Answer: Checked and changed to Vancouver reference style accordingly.

- Introduction should be short, summary, and comprehensive.

Answer: Introduction section is reduced now in comprehensive way.

Method section

- Search strategy is not well-defined. Authors must apply some key words such as ‘prediabetes’, ‘gestational diabetes’

Answer: The term ‘prediabetes’ is added now search strategy, and “gestational diabetes” is added in the exclusion criteria. We only added articles on type-2 diabetes.

- Please describe about reasons of excluding 307 studies.

Answer: Irrelevant articles excluded based on title and abstract review (n = 733). Corrected accordingly on page 12 (PRISMA Chart).

- Exclusion and inclusion criteria should be reported for 307 excluded studies

Answer: The following exclusion criteria is present, section “Inclusion and exclusion criteria” on page 3 (highlighted in green). “The following studies were excluded: were review articles, case studies, qualitative studies, case series, abstracts, and intervention studies; was irrelevant to type-2 diabetes; reported on gestational or type-1 diabetes”.

- Gestational diabetes cases must be categorized separately.

Answer: We have only considered type-2 diabetes in this systematic review and meta-analysis. Therefore, gestational diabetes is added in exclusion criteria and type-2 diabetes is mentioned in the title now. See, page 3 (highlighted in green)

Results

- In results section, first paragraph must describe first diagram (e.g. relevant studies=54).

Answer: First diagram is described now, page 5.

- In second paragraph, description about gender frequency has been repeated.

Answer: Gender repetition has been deleted now.

- Please report number of studies by type of diabetes (type I and type II)

Answer: We have only considered type-2 diabetes in this systematic review and meta-analysis.

- Please report prevalence by diagnostic method

Answer: Most of the studies did not report the prevalence of diabetes by diagnostic methods. The prevalence of diagnostic method is presented on page number 8 (highlighted in green).

- In table 1, please specify positives for diabetes, pre-diabetes, …

Answer: The positive of diabetes and prediabetes are now described in table 1 (highlighted in green)

- In table 1, it seems that some subjects are wrong. E.g. the prevalence for Smsudin et al (14) study in original study is 69 but in present study reported 65. Also, in original full text, snowball sampling (non-random) is method of sampling, but authors reported ‘Random’ in Table 1.

Answer: Thanks a lot for your comment. Firstly, age value is corrected now in the table 1. Secondly, stratified sampling was applied for the selection of sub-areas and later they used snowball sample to choose the housing estates. Therefore, both (Stratified random and Snowball sampling are mentioned in table 1)

- In Table1, citing of studies is incorrect. Please check it.

Answer Checked and corrected accordingly.

- In section of ‘quantitative synthesis’, prevalence for men reported 14.63 but it is 16.15 in table 2.

Answer Checked and corrected accordingly.

- Table 2 has some typing errors.

Answer Re-checked and corrected accordingly.

- In table 3, please specify type of gender.

Answer Done accordingly.

- The authors must check all extracted data.

Answer The extracted data is rechecked and corrected accordingly.

- The statistical analysis is not good and not representing the results properly.

Answer Statistical analysis has significantly improved by adding Sensitive Analysis, Grade approach, Begg’s test, etc (highlighted in green)

- Non-significant variables in univariate analysis did not discuss in discussion section.

Answer Added in the discussion section.

- Authors did not carry out Sensitivity analysis.

Answer Sensitivity analysis has been added now.

**********************************************************************************

Reviewer #3:

1. GRADE scoring was not used to assess the quality of meta-analysis evidence. Evaluate your meta-analysis using the GRADE score.

Answer: Thanks a lot for your suggestion. GRADE scoring has been added accordingly. Mentioned in result section on page 9.

2. Diabetes diagnosis criteria were not stated for studies, as it was changed over the years.

Answer: Mentioned now accordingly in table 1.

3. Studies reporting prevalence may not be published or can be published in local databases. Your search must be amended by searching for these publications and gray literature.

Answer: Thanks a lot for your comment. Malaysia online journals are searched too now. We have founded one more relevant through local journals.

4. Article screening process was well described, but the numbers stated are wrong.

Answer: Corrected accordingly

5. In the abstract of the article and the results, two different population sizes are mentioned. It should be corrected.

Answer: Thanks a lot for your comment. Corrected accordingly

6. In the result section “Male participation ranged from 0 to 61.8%, and the number of overweight participants ranged from 11 percent to 49.1 percent". The "number" should be changed to "percentage".

Answer: Thanks a lot for your correction. Changed it accordingly

7. In the result section “table 1 summarize……”. The study is not a longitudinal study. Thus using baseline characteristics is inappropriate, it should be changed to general characteristics.

Answer: Changed it accordingly

13 Jan 2022

Prevalence of type-2 diabetes and prediabetes in Malaysia: a systematic review and meta-analysis

PONE-D-21-32696R1

Dear Dr. Akhtar,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Giulio Francesco Romiti

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you for addressing my previous comments. The responses to my previous comments have been addressed and justified appropriately. The revisions are satisfactory.

Reviewer #3: Significant changes have been made from the original submission. I believe the article should be considered for acceptance.

17 Jan 2022

PONE-D-21-32696R1

Prevalence of type-2 diabetes and prediabetes in Malaysia: a systematic review and meta-analysis

Dear Dr. Akhtar:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Giulio Francesco Romiti

Academic Editor

PLOS ONE