Prevalence of metabolic syndrome in the Gulf Cooperation Council countries: meta-analysis of cross-sectional studies.

Metabolic syndrome is a collection of health-related conditions that lead to serious health condition. An individual with metabolic syndrome may acquire greater risk for adult-onset complications such as cardiovascular or neurological disorders. The aim of this study was to review and provide the prevalence of metabolic syndrome in Gulf Cooperation Council countries (GCC). Literature searches were performed on PubMed, Google scholar, and Web of Science Core Collection for English-language articles along with national studies. The following search terms were used during search: "prevalence of metabolic syndrome in GCC," "prevalence of metabolic syndrome in middle east," "prevalence of metabolic syndrome in Arab," and "prevalence of metabolic syndrome name of country." Thirty-seven studies were selected for final review out of 132 studies. The weighted pooled prevalence of metabolic syndrome was 27.3% with high heterogeneity (I 2=98.94%; Cochran Q-test P<0.01). The results showed comparatively high and rising rate of metabolic syndrome in the GCC area. Preventative strategy should be considered to reduce the risk of morbidity or mortality related to metabolic syndrome.

INTRODUCTION

The metabolic syndrome has been known to acquire by sedentary lifestyle and calorie rich eating habit. Various metabolic factors may lead to development of life strengthening diseases such as cardiovascular disease, type 2 diabetes, dyslipidemia, and hypertension (Ranasinghe et al., 2017). Although adult-onset diseases may solely occur without the metabolic factors, the risk for the co-occurrence has been known to increase by several folds with the existing metabolic factors (Mente et al., 2010). The most common definitions used to define metabolic syndrome were reported by the World Health Organization (WHO), European Group for Study of Insulin Resistance, National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III), International Diabetes Federation (IDF), and Joint Interim Societies (JIS). The metabolic syndrome was defined by basically similar components that included terms. For example, WHO used components such as impaired fasting glucose, impaired glucose tolerance, homeostatic model assessment for insulin resistance, obesity, dyslipidemia, hypertension, waist circumference, and blood pressure as criteria. The NCEP ATP III used components such as fasting triglyceride, fasting high-density lipoprotein, fasting blood glucose as criteria for prevalence of metabolic syndrome (Huang, 2009).

The member states of the Gulf Cooperation Council (GCC) include Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates. Recently, the prevalence of the type II diabetes mellitus and related adult-onset disorders have reported to be high in the GCC countries. Several publications reported that four out of six countries of the GCC countries are among the top 10 countries with the greatest prevalence rate for adult-onset type 2 diabetes and cardiovascular diseases (Al-Lawati et al., 2008; Kamran et al., 2007; Ranasinghe et al., 2017). The rapidly increasing rate of the adult-onset chronic complications such as type 2 diabetes and cardiovascular diseases have been related to the changes in the environment and lifestyle that lead to sedentary lifestyle and consumption of food high in calorie (Malik and Razig, 2008). Despite various studies on the prevalence of metabolic syndrome in the GCC countries, the overall report on the metabolic syndrome in the GCC countries is scarce. Therefore, this report was conducted to provide the evidence-based prevalence rate of metabolic syndrome in the GCC area through meta-analysis. Providing evidence- based prevalence rate of the metabolic syndrome in the GCC area could contribute fundamental foundation for developing scientifically supportive evidence for the metabolic syndrome prevention campaign.

MATERIALS AND METHODS

This study is a systemic review prepared by the meta-analysis based on the guidelines provided by the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis protocol) (Moher et al., 2010; Shamseer et al., 2015).

Data sources and search phrases

In order to obtain evidence-based study results on the prevalence rate for the metabolic syndrome, electronic literature searches were conducted on the web-based database sites such as the PubMed database, Google Scholar, and Web of Science collection. Only the English-language research articles with the nation-wide or population-based subjects were gathered for this study. The initial data collection was conducted without filtering for time. Specific search terms or phrases were used to find the articles. The search phrases included “prevalence of metabolic syndrome in middle east,” “prevalence of metabolic syndrome in Arab,” “prevalence of metabolic syndrome,” “name of country,” and “metabolic syndrome.”

Article selection procedure

After the initial gathering procedure, the selected articles were considered for inclusion based on the following inclusion and exclusion criteria. This study used broad inclusion criteria to provide comprehensive systemic reviews of the topic.

First, the articles were considered for inclusion if the articles were original research studies and reported on the prevalence rate for the metabolic syndrome. There were no restrictions on the study type unless the articles are review articles. Cohort and cross-sectional studies were also included. Geographic regions such as urban or rural regions were not excluding criteria. The studies on specific clinical complications such as diabetes, acute coronary syndrome, ovary syndrome, or hypertension were excluded from the study. In addition, the studies that did not deal with the prevalence of metabolic syndrome as the major factor were also not included in this study. In the initial selection phase, the studies were selected based on the key terms and phrases. During the second phase, the studies were reviewed for the title and abstract for exclusion. Finally, initially selected articles were screen and reviewed based on the full text for the final exclusion and inclusion process.

Data extraction

Information on the authors, year of publication, country of origin, sample size, gender and age of the subjects, and study design (case-control, cross-sectional or prospective cohort), metabolic syndrome identification criteria, prevalence of metabolic syndrome, and adjustment variables were obtained from the selected articles. Regarding the considerable factors and expected heterogeneity.

The random-effect model was applied for the analysis of data to obtain the expected heterogeneity and the considerable factors. The Cochran Q-test was utilized to estimate the heterogeneity between the selected studies.

Data synthesis and statistical analysis

The management and edition of data, estimation of standard error, and pooled mean effect size were estimated using Comprehensive Meta-Analysis Software (CMA) ver. 2.0 (Biostat, Englewood, NJ, USA). The pooled estimate of the prevalence rates was determined by the definitions on the metabolic syndrome provided by the ATP III, IDF, WHO, and JIS. Finally, the weighted average prevalence rates with 95% confidence interval (CI) for the selected studies were obtained by calculating the fixed effects and random effects of the meta-analysis.

RESULTS

One hundred thirty-two articles were retrieved on the prevalence or metabolic syndrome in the GCC countries through extensive search process online. After through inclusion and exclusion procedures, duplications and irrelevant articles were excluded. After reviewing the title and abstracts, 56 articles were selected for full-text screening. After the full article reviewing, seven articles were excluded due to chronic diseases, three articles were excluded since they were conducted on the subjects that were not of the GCC countries, and five were excluded for being review articles. Therefore, among 132 articles, 37 articles were selected as the final articles for the systematic review. The selection processes for the articles are shown in Fig. 1.

Fig. 1

PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis protocol) diagram for the systematic review of the metabolic syndrome prevalence rates in the Gulf Cooperation Council counties population.

Within 37 articles, 53 different studies were identified and included for the review. Among 53 studies, 19 were published before the year 2009 and 35 were published in the year 2010 or later. Different criteria were used to diagnose metabolic syndrome in the selected studies. Fifteen studies used the criteria proposed by the NCEP ATP III for diagnosing the metabolic syndrome. Eight studies used the criteria by the IDF and 13 studies used the criteria by both NCEP ATP III and IDF. One study used the criteria by NCEP ATP III and WHO and another study used the criteria by NCEP ATP III, IDF, and JIS (Table 1). The metabolic syndrome prevalence rate is also shown as a forest plot for in Fig. 2.

Table 1

Characteristics of the reviewed studies

Country	Study	Type of study	Published year	Sample size (person)	Metsdefinition	Mets prevalence rate (%)	Adjustments
Oman	Al-Lawati et al.	Cross-sectional	2003	1,419	ATP III	17.0 (crude)
						21.0 (adjust)	Age
	Al-Shafaee et al.	Cross-sectional	2008	281	ATP III	45.9
	El-Aty et al.	Cross-sectional	2014	3,137	ATP III	23.6	Age
	Al-barwani et al.	Cross-sectional	2008	392	IDF	28.0
					ATP III	21.0
UAE	Khthir and Espina	Cross-sectional	2014	575	ATP III	22.0
	Hajat and Shather	Cross-sectional	2012	760	IDF	48.7
					ATP III	50.3
	Malik and Razig	Cross-sectional	2008	4,097	IDF	40.5
					ATP III	39.6
Saudi	Al-Sarraj et al.	Cross-sectional	2008	309	ATP III	25.2
	Al-Sarraj et al.	Cross-sectional (obesity)	2010	227	ATP III	40.4
	Haroun et al.	Cross-sectional	2018	591	IDF	4.9
	Rouzi and Ardawi	Cross-sectional	2009	580	ATP III	33.4
	Bahijri et al.	Cross-sectional	2013	233	IDF	18.9
					ATP III	16.7
	Al-Qahtani and Imtiaz	Cross-sectional	2005	1,079	ATP III	20.0	Age
	Aljohani	Cross-sectional	2014	4,406	IDF	28.3
	Al-Nozha et al.	Cross-sectional	2005	17,293	ATP III	41.4 (crude)
						39.3 (adjust)	Age
	Al-Qahtani et al.	Cross-sectional	2006	2,577	IDF	16.1	Age
					ATP III	13.6	Age
	Barrimah et al.	Cross-sectional	2011	560	ATP III	31.4
	Taha et al.	Cross-sectional	2009	37	ATP III	29.7
	Alzahrani et al.	Cross-sectional	2012	600	ATP III	21.0
	Al-Agha et al.	Cross-sectional	2012	387	ATP III	14.3
	Al-Daghri et al.	Cross-sectional	2013	185	IDF	39.0
	AboGazalah and AlReshidi	Cross-sectional	2016	250	ATP III	36.0
					WHO	39.1
	Alswat et al.	Cross-sectional	2016	313	IDF	38.4
	Aljabri et al.	Cross-sectional (obesity)	2018a	1,526	IDF	69.5
	Al-Rubeaan et al.	Cross-sectional	2018	12,126	ATP III/IDF	39.8
	Aljabri et al.	Cross-sectional	2018b	2,810	IDF	64.6
	Saeed	Cross-sectional	2019	1,354a	IDF	12.0
Kuwait	Badr et al.	Cross-sectional	2007	434	ATP III	18.0
	Al-Isa et al.	Cross-sectional	2010	431	IDF	14.8
	Al Zenki et al.	Cross-sectional	2012	1,830	IDF/ATP III (WC>102/85 cm)	36.1
	Al-Isa	Cross-sectional	2013	303	IDF	11.7
					ATP III (modified)	9.8
	Roshdy	Cross-sectional	2011	153	JIS	28.1
					IDF	26.1
					ATP III	18.3
	Al Rashdan and Al Nesef	Cross-sectional	2010	2,280	ATP III	24.8
					IDF	36.2
	Boodai et al.	Cross-sectional	2014	80	ATP III	30.0
					IDF	21.3
Qatar	Bener et al.	Cross-sectional	2009	1,024	ATP II	26.5
					IDF	33.7
	Bener et al.	Cross-sectional	2014	1,552	ATP III	10.3
	Al-Thani et al.	Cross-sectional	2016	2,496	IDF/ATP III	37.0
	Hammoudeh et al.	Cross-sectional	2018	226	ATP III	27.4
					IDF	32.7

ATP III, Adult Treatment Panel III; IDF, International Diabetes Foundation; WHO, World Health Organization; JIS, Joint Interim Societies; WC, waist circumference.

Fig. 2

Forest plot for the metabolic syndrome prevalence rate of Gulf Cooperation Council counties.

Tables 2 and 3 show the pooled estimates for the prevalence rates of the metabolic syndrome in each country and the overall pooled estimated, respectively. The prevalence rates of the metabolic syndrome in Oman was 0.25 (95% CI, 0.19–0.31), UAE was 0.39 (95% CI, 0.34–0.42), Saudi was 0.28 (95% CI, 0.24–0.33), Kuwait was 0.22 (95% CI, 0.17–0.27), and Qatar was 0.26 (95% CI, 0.18–0.37). Moreover, the pooled prevalence rates of the metabolic syndrome were estimated for the subgroups of studies (Table 4). The random pooled samples of the studies reported before 2009 and after 2010 showed the metabolic syndrome prevalence rates of 0.28 (95% CI, 0.24–0.32) and 0.27 (95% CI, 0.23–0.32), respectively.

Table 2

Pooled estimations of the metabolic syndrome prevalence rate by country

Country	No. of studies	Sample size	Pooled prevalence	95% Confidence interval	P-value
Oman	6	7,040	0.25	0.19–0.31	<0.01*
UAE	5	10,289	0.39	0.34–0.45	<0.01*
Saudi	24	67,796	0.28	0.24–0.33	<0.01*
Kuwait	12	8,480	0.22	0.17–0.27	<0.01*
Qatar	7	5,994	0.29	0.25–0.34	<0.01*

P<0.05.

Table 3

Overall pooled estimation of the metabolic syndrome prevalence rate

Model	No. of studies	Sample size	Pooled prevalence	95% Confidence interval	P-value
Fixed	54	99,599	0.37	0.36–0.37	<0.01*
Random	54	99,599	0.28	0.25–0.31	<0.01*

P<0.05.

Table 4

Summary of the main results of the reviewed articles

Variable	No. of studies	Sample size	Effect sizes (95% CI)	Effect sizes (95% CI)	P-value
			Fixed pooled prevalence	Random pooled prevalence
Year of study
2003–2009	19	56,884	0.37 (0.36–0.37)	0.28 (0.24–0.32)	<0.01*
2009–2019	35	42,715	0.37 (0.36–0.37)	0.28 (0.24–0.32)	<0.01*
Diagnostic criteria
ATP III	29	56,815	0.36 (0.35–0.36)	0.25 (0.22–0.28)	<0.01*
IDF	20	25,929	0.37 (0.36–0.37)	0.30 (0.23 –0.38)	<0.01*
ATP III/IDF	3	16,452	0.39 (0.38–0.40)	0.38 (0.35–0.40)	<0.01*
JIS	1	153	0.28 (0.22–0.36)	0.28 (0.22–0.36)	<0.01*
WHO	1	250	0.39 (0.33–0.45)	0.39 (0.33–0.45)	<0.01*
Adjustment
Age and sex adjusted	6	31,409	0.33 (0.32–0.33)	0.23 (0.16–0.32)	<0.01*
Nonadjusted	48	36,997	0.38 (0.38–0.39)	0.28 (0.26–0.32)	<0.01*

CI, confidence interval; ATP III, Adult Treatment Panel III; IDF, International Diabetes Foundation; JIS, Joint Interim Societies; WHO, World Health Organization.

P<0.05.

Twenty-nine studies used the ATP III definition and the prevalence rate in the random pooled estimate was 0.25 (95% CI, 0.22–0.28). Ninety studies used the IDF definition and prevalence rate in the random pooled estimate was 0.28 (95% CI, 0.21–0.36). Three studies used both the ATP III and IDF and their prevalence rate in the random pooled estimate was 0.38 (95% CI, 0.35–0.40). One study used the JIS definition and its prevalence rate in the random pooled estimate was 0.28 (95% CI, 0.22–0.36). Finally, the last one study used the WHO definition and the prevalence rate in the random pooled estimate was 0.39 (95% CI, 0.39–0.45).

Regarding the effects of the adjustment on the random pooled estimates, six adjusted studies showed pooled for prevalence rate by the random effect of 0.28 (95% CI, 0.16–0.32). Forty-seven nonadjusted studies showed pooled prevalence by the random effect of 0.28 (95% CI, 0.25–0.31).

DISCUSSION

This study was conducted to observe the prevalence rate of metabolic syndrome in the GCC countries. In this meta-analysis review, 54 studies and 99,599 subjects were analyzed for the prevalence of metabolic syndrome. Overall, the pooled estimate of the metabolic syndrome prevalence rate in GCC was 0.28 (95% CI, 0.25–0.31). Such metabolic syndrome prevalence rate in the GCC region was greater than that of the other regions such as Latin American, Europe, Africa, and Asia. That is, the observed prevalence rate of the metabolic syndrome in the GCC countries such as was observably higher than other countries worldwide. For example, a systematic review of the countries in the Latin America region showed the metabolic syndrome prevalence rate of 24.9% with the ATP III’s metabolic syndrome definition (Márquez-Sandoval et al., 2011). A combined prospective cohort study on the prevalence rate of the metabolic syndrome reported of 15.0% in Europe with the WHO’s metabolic syndrome definition (Hu et al., 2004).

The prevalence rates of metabolic syndrome in the Sub-Saharan African regions range from 0% to 7.3% (Fezeu et al., 2007). A systematic review that reported the prevalence rates in the Asia-pacific region was 11.9% and 49.0% according to the definitions by ATP III and modified ATP III, respectively (Ranasinghe et al., 2017). On the other hand, the prevalence rates reported by the national survey in the United States were 35% and 39% according to the definitions by the ATP III and IDF, respectively (Ford, 2005). Therefore, the prevalence rate for the metabolic syndrome was high in comparison to some of the regions such as Africa or Asia while still lower than the regions such as the United States.

Over the past few decades, many of the GCC countries have experienced rapid wealth and corresponding urbanization. Such changes have led to a sedentary lifestyle by the general population due to rapid increase in the usage of motored vehicles for commuting. In addition, the working environment and facilities have changed to promote reduction in physical activity. The dietary patterns also changed in association with the environmental changes to promote inactivity and corresponding adult-onset diseases (Alzeidan et al., 2018). Conditions such as the infrastructure of the urban areas with scarce sidewalks or parks, hot arid climate, and conservative social culture restrict physical activity in the Gulf region (Alzeidan et al., 2018).

Although a vast amount of databases and articles were reviewed with detailed inclusion and exclusion criteria for the final selection limitations exist. Since a significant amount of regional reports were prepared in the native language, non-English articles could not be included in this study. The local studies that represent the regional information may provide more detailed input on the prevalence rate.

However, this is the first meta-analysis report on the prevalence ate of the metabolic syndrome in the GCC countries to our knowledge. This report may provide supportive information to prepare for the measures to intervene to prevent and control the onset of metabolic syndrome in the GCC region. It may assist to manage the morbidity and mortality rate related to adult-onset complications.