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 Table of Contents 
Year : 2014  |  Volume : 21  |  Issue : 3  |  Page : 170-175  

Metabolic syndrome: Risk factors among adults in Kingdom of Saudi Arabia

Department of Medicine, College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Kingdom of Saudi Arabia

Date of Web Publication15-Oct-2014

Correspondence Address:
Naji J Aljohani
College of Medicine, King Fahad Medical City, Riyadh
Kingdom of Saudi Arabia
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2230-8229.142971

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Background: Metabolic syndrome (MetS) is a cluster of established cardiovascular risk factors that collectively increase predisposition to major chronic diseases, including heart diseases and diabetes mellitus. Citizens of developing countries such as Saudi Arabia are at risk for MetS as a result of industrialization and accessibility to fast foods. In this epidemiologic study, the kingdom-wide prevalence of MetS is determined. Materials and Methods: A total of 4578 Saudis aged 15-64 was randomly selected from 20 regions in Saudi Arabia. Anthropometrics were collected, and fasting blood samples collected to ascertain fasting blood glucose and lipid profile. Components of full MetS as defined by the International Diabetes Federation were used for screening. Results: The overall prevalence of MetS is 28.3%. Prevalence was significantly higher in males than in females (31.4 vs. 25.2%; P = 0.001). Prevalence of MetS was the highest in the northern and central region, and showed a parallel increase with age, and inversely with educational status. Region was also a significant contributor to MetS. Conclusion: Despite accumulating evidence of an epidemic, MetS remains largely unresolved in the kingdom. Aggressive public campaign should be launched, and policies implemented to control any future damage of MetS in the kingdom.

Keywords: Diabetes mellitus, metabolic syndrome, Saudi Arabia

How to cite this article:
Aljohani NJ. Metabolic syndrome: Risk factors among adults in Kingdom of Saudi Arabia. J Fam Community Med 2014;21:170-5

How to cite this URL:
Aljohani NJ. Metabolic syndrome: Risk factors among adults in Kingdom of Saudi Arabia. J Fam Community Med [serial online] 2014 [cited 2022 Jan 18];21:170-5. Available from:

   Introduction Top

Metabolic syndrome (MetS) is a cluster of cardiometabolic risk factors that include hyperglycemia, hypertension, obesity and dyslipidemia that increase the risk of diabetes mellitus type II and cardiovascular diseases (CVD). [1],[2] The prevalence of MetS in the of Kingdom of Saudi Arabia (KSA) and other countries in the region ranges from 18% to about 40% depending on the definition used, population studied and other sociodemographic characteristics. [3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13] In Saudi Arabia, economic and social transformations have brought about a change in a sedentary lifestyle resulting in increasing prevalence of obesity, and an estimated expected rise of MetS. There are serious implications of this trend on morbidity, mortality and health services expenditure. This study attempts to assess the prevalence of MetS in Saudi adults in the whole country and identify significant risk factors and predictors. The information thus generated will be helpful in making suggestions for the implementation of interventions to prevent, make an early diagnosis and control the problem.

   Materials and methods Top

This was a cross-sectional, community-based study that covered the entire population of KSA in 2005. The WHO STEP wise approach to surveillance (STEPS) of noncommunicable diseases (NCD) risk factors was the basis of the conduct of the survey and collection of the data. [14],[15] The STEPS approach focuses on obtaining core data on the established risk factors that determine the major disease burden. It is sufficiently flexible to allow each country to expand on the core variables and risk factors, and incorporate optional modules-related to local or regional interests. The STEPS instrument covers three different levels of "steps" of risk factor assessment. They are:

  • Questionnaire
  • Physical measurements
  • Biochemical measurements.

All Saudis aged 15-64 years from all the 20 health regions of the country made up the study population. A multistage stratified cluster random sampling technique was used to recruit the subjects. Stratification was based on age (five 10-year age groups) and gender (male/female, two groups). All health regions of the country (20 regions) were covered. Based upon the proposed methodology of the WHO STEP wise approach, a sample size of 196 was calculated for each of these categories. A list of all primary health care centers (PHCCs) in each region was prepared; 10% of these PHCCs were randomly chosen and allocated a regional sample proportionate to the size of their catchment population in the sampled PHCCs. To identify the households, a map of the health center coverage area was used to select the houses. Each house was assigned a number, and a simple random draw was made.

Data were collected using the WHO STEP wise approach, a tool used for epidemiologic studies to measure NCD in WHO-member countries. [14],[15] It covers three levels of risk factor assessment (steps) which include a questionnaire, physical (anthropometric) and biochemical measurements including fasting serum glucose, lipid profile (triglycerides [TGs], total, [high-density lipoprotein-cholesterol] HDL-C and [low-density lipoprotein-cholesterol] LDL-C), chronic diseases (noncommunicable e.g. hypertension, dyslipidemia, diabetes mellitus, etc.), and risk factors (e.g., obesity, smoking, physical activity, diet). The questionnaire was translated into Arabic by a team of physicians and then translated back to ensure its accuracy. The Arabic instrument was pretested and corrected before being tested on 51 eligible respondents to check the wording and the clarity of the questions. Necessary adjustments were made to the instrument in the light of the pretest. Data was collected by 54 male and 54 female data collectors working in teams. Each field team was made up of four persons: A male data collector, a female data collector, a driver, and a female assistant. The data collection teams were supervised by a hierarchy of a local supervisor, regional coordinators, and national coordinator.

All individuals involved in data collection attended a comprehensive training workshop of interview techniques, data collection tools, practical applications, and field guidelines.

Blood (5 ml) was collected, from the participants in the morning after an overnight fast. Sodium heparin was used as an anticoagulant, and the samples were centrifuged at 3,000 × g for 15 min at 20°C to separate plasma. Aliquots were prepared for storage (−20°C or − 80°C) until further analysis. Total cholesterol (TC), TGs, and glucose were measured with commercially available enzymatic colorimetric kits from QCA (Amposta, Spain). Seriscann normal (ref 994148) (QCA, Amposta, Spain) was used for quality control. Serum HDL-C levels were analyzed by an enzymatic method after precipitating serum reagents with phosphotungstic acid and magnesium. LDL-C was calculated according to the friedewald formula (LDL-C = TC − HDL − [TG/5]).

Height, weight, and waist and hip circumferences were measured using standard instruments, according to the STEP wise approach. [14],[15] Body weight and height were measured without shoes, using electronic measuring scale. Body mass index (BMI) was calculated as weight in kilogram divided by height in m 2 . Waist circumference (WC) was measured, in cm, midway between the lower costal margin and iliac crest during the end-expiratory phase.

For the definition of MetS, the International Diabetes Federation (IDF) for MetS was used in this study as follows: [16]

Central obesity (defined as WC ≥ 94 cm for Europid men and ≥ 80 cm for Europid women, with ethnicity specific values for other groups).

Plus any two of the following four factors:

  • Raised TG level: ≥150 mg/dL (1.7 mmol/L),
  • Reduced HDL-C: < 40 mg/dL (1.03 mmol/L*) in males and < 50 mg/dL (1.29 mmol/L*) in females
  • Raised blood pressure (BP): Systolic BP ≥ 130 or diastolic BP ≥85 mm Hg
  • Raised fasting plasma glucose ≥100 mg/dL (5.6 mmol/L).

The case definition of MetS was generated using statistical analysis system statistical package.

Questionnaires collected from the field were reviewed by the team leaders assigned to each team before submission to headquarters for data entry. A double entry of the questionnaires was done using  Epi-Info 2000 software and EpiData software developed by the Menzes center for validation. After entry, the data, was cleaned. New variables were defined by adopting the standard STEPS variables (STEPS data management manual, draft version v1.5, October 2003). The statistical analysis was done using SPSS for Windows, version 17.0 (Chicago, IL, USA). The data were given as mean and standard deviation for continuous variables and as frequencies (percentages) for categorical variables. Association between categorical variables was assessed using a Chi-square test. Univariate regression analysis was used with Mets as the dependent variable and the associated risk factors as independent variables. The level of significance was set at < 0.05 throughout the study. Total counts may vary because of missing data from certain variables.

The protocol and the survey instrument were approved by the ministry of health, center of biomedical ethics, and the appropriate authorities in KSA. Informed consent of all subjects was obtained. Participants were assured of confidentiality of data, and that they would be used only for the stated purpose of the survey. The survey was conducted in 2005 and the final report archived without any intension of publishing the results. At the beginning of 2013, however, the principal investigators (authors) of the study decided to have the results published to serve as baseline data for comparison with future studies. None of the contents of this 2005 survey had been published previously.

   Results Top

Of the 4758 subjects in the study, 4406 (92.6%) were included in the final statistical analysis as there were major deficiencies in the remaining records. Females constituted just above half (50.9%); about two-thirds of the subjects were in the age group 24-55 years, with less than secondary school education and an income of 3000 Saudi Riyals (SR) or more (1 SR = 3.75 US$). The prevalence of MetS was 28.3% (1245 cases out of 4406 subjects). [Table 1] shows the distribution of MetS cases according to subjects' sociodemographic characteristics. MetS was significantly higher in males, subjects of advancing age, the less educated, house-keepers and in northern and central regions of the country. MetS was significantly associated with those who had been smokers, had lower levels of physical activity at work, transport and recreation. It was more among subjects who consumed more fruits, but was not related to vegetable consumption.
Table 1: Distribution of MetS among participants according to their demographic characteristics

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[Table 2] shows the univariate regression analyses between certain habits and the risk of MetS. Those who were more physically active (answered "no" in sedentary activity) (odds ratio [OR] 0.77 (confidence interval (CI) 0.65-91)), did not use any means of transportation (OR 0.73 [CI 0.54-0.84]) did not engage in social (recreational) activities (OR 0.72 [0.58-0.90]) had decreased risk of MetS than those who were less active, used transportation and participated in social activities (P values 0.002, 0.001, and 0.002, respectively). Subjects who had never smoked were also at increased risk for MetS (OR 1.34 [1.11-1.962]). Consequently, subjects who consumed more than 5 servings of fruits/day had less risk for Mets than those who ate less (P = 0.002). This observation was not true for those subjects who consumed more than 5 servings of vegetables/day.
Table 2: Univariate regression analysis of selected habits in MetS risk

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[Table 3] shows selected demographic variables and risk for MetS. Being female, older, living in urban area, earning < SAR 7000 and being illiterate, were considered as significant risk factors for MetS.
Table 3: Univariate regression analysis for selected demographic characteristics and MetS risk

Click here to view

   Discussion Top

This study revealed that the prevalence of (MetS) in Saudi adults is more than 28% which is comparable to other national, regional and international studies. [3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13] This prevalence is lower than the previously adjusted prevalence reported by a community-based study of adults aged 18-55 years of age which using ATP III criteria gave a prevalence of 37%. The different age groups and definitions used may partly explain the differences in the prevalence. MetS affects approximately one-quarter of adults in many developed countries. [17],[18] It represents a group of risk factors that are linked to the accelerated development of atherosclerosis and CVD. Though the exact pathogenesis is not known many risk factors have been identified. [19] The significant risk factors identified by our study included males, increasing age, lower education, higher income, smokers and housekeepers. The prevalence of MetS was higher with age and male gender, which was consistent with other studies. [4],[20],[21],[22] Poor lifestyle practices were significantly associated with MetS in this study, which was again in accord with many studies. [23],[24],[25],[26],[27] Physical inactivity is strongly and inversely associated with MetS, which reduces with weight loss and regular physical activity. [23],[24] MetS Bhas has been significantly associated with smoking in some studies. In agreement with our study, exposure to tobacco has been implicated in the pathogenesis of insulin resistance, [25] as smoking acutely impairs the action of insulin and induces insulin resistance. [26],[27] Smoking was associated with MetS despite the fact that smokers had lower BMI than nonsmokers. [28] People at increased risk were those in households with lower levels of education. Education is a good indicator of social position in epidemiological studies and is often seen as the easy means of measuring present socioeconomic status because it precedes other indicators, such as income or occupation based on social position. It is comparable between women and men, does not usually change in adulthood, and shapes health behaviors through attitudes, values and knowledge. [29] Many studies have reported a higher prevalence of MetS among the less educated subjects, which is in agreement with our findings. [28],[29],[30],[31] In the results of studies in other countries the association of income with MetS was inconsistent. [30],[32],[33],[34] The accuracy of data on income is usually difficult to assess, which may explain inconsistencies of association of income with health problems. Occupation was significantly associated with MetS in this study in which prevalence rates among housekeepers and government employees were higher. Other studies reported significant association of MetS with the occupation, but there was no consistency with the nature of the occupations. The prevalence of MetS was higher in manual workers than in nonmanual workers. [33],[35],[36] Other studies reported a greater risk for MetS for food service workers, farm managers, machine operators and supervisors and transportation and material moving workers, and was lowest in writers, athletes, engineers, and scientists. [37] Other factors such as age, gender, education and income could have confounded the association of occupation with MetS.

The authors acknowledge some limitations. The study is cross-sectional in nature and hence causal relationships could not be ascertained. Some of the significant risk factors for MetS in bivariate analysis (smoking, physical activity, and occupation) were not detected as predictors in multivariate analysis. Self-reporting bias in lifestyle practices such as diet, smoking habits and physical activity may have affected the results. Genetic factors were not addressed in this study.

In summary, the prevalence of MetS in the kingdom is still alarmingly high. Major policies should be made and aggressive campaigns launched to control and/or minimize the potential economic burden of MetS and the predisposition of the Saudi people to disease.[39]

   References Top

1.Lorenzo C, Williams K, Hunt KJ, Haffner SM. Trend in the prevalence of the metabolic syndrome and its impact on cardiovascular disease incidence: The San Antonio Heart Study. Diabetes Care 2006;29:625-30.  Back to cited text no. 1
2.Wilson PW, D'Agostino RB, Parise H, Sullivan L, Meigs JB. Metabolic syndrome as a precursor of cardiovascular disease and type 2 diabetes mellitus. Circulation 2005;112:3066-72.  Back to cited text no. 2
3.Al-Nozha M, Al-Khadra A, Arafah MR, Al-Maatouq MA, Khalil MZ, Khan NB, et al. Metabolic syndrome in Saudi Arabia. Saudi Med J 2005;26:1918-25.  Back to cited text no. 3
4.Alzahrani A, Karawagh A, Alshahrani F, Naser T, Ahmed A, Emad H. Prevalence and predictors of metabolic syndrome among healthy Saudi adults. Br J Diabet Vasc Dis 2012;12:78.  Back to cited text no. 4
5.Al-Daghri NM. Extremely high prevalence of metabolic syndrome manifestations among Arab youth: A call for early intervention. Eur J Clin Invest 2010;40:1063-6.  Back to cited text no. 5
6.Harzallah F, Alberti H, Ben Khalifa F. The metabolic syndrome in an Arab population: A first look at the new International Diabetes Federation Criteria. Diabet Med 2006;23:441-4.  Back to cited text no. 6
7.Al-Shaibani H, El-Batish M, Sorkhou I, Al-Shamali N, Al-Namash H, Habiba S, et al. Prevalence of insulin resistance syndrome in a primary health care center in Kuwait. Fam Med 2004;36:540.  Back to cited text no. 7
8.Rguibi M, Belahsen R. Metabolic syndrome among Moroccan Sahraoui adult Women. Am J Hum Biol 2004;16:598-601.  Back to cited text no. 8
9.Khader Y, Bateiha A, El-Khateeb M, Al-Shaikh A, Ajlouni K. High prevalence of the metabolic syndrome among Northern Jordanians. J Diabetes Complications 2007;21:214-9.  Back to cited text no. 9
10.Kozan O, Oguz A, Abaci A, Erol C, Ongen Z, Temizhan A, et al. Prevalence of the metabolic syndrome among Turkish adults. Eur J Clin Nutr 2007;61:548-53.  Back to cited text no. 10
11.Malik M, Razig SA. The prevalence of the metabolic syndrome among the multiethnic population of the United Arab Emirates: A report of a national survey. Metab Syndr Relat Disord 2008;6:177-86.  Back to cited text no. 11
12.Zabetian A, Hadaegh F, Azizi F. Prevalence of metabolic syndrome in Iranian adult population, concordance between the IDF with the ATPIII and the WHO definitions. Diabetes Res Clin Pract 2007;77:251-7.  Back to cited text no. 12
13.Al-Lawati JA, Mohammed AJ, Al-Hinai HQ, Jousilahti P. Prevalence of the metabolic syndrome among Omani adults. Diabetes Care 2003;26:1781-5.  Back to cited text no. 13
14.Bonita R, de Courten M, Dwyer T. Surveillance of Risk Factors for Non Communicable Diseases. The WHO Stepwise Approach. Summary. Geneva, World Health Organization; 2001.  Back to cited text no. 14
15.Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: Findings from the third National Health and Nutrition Examination Survey. JAMA 2002;287:356-9.  Back to cited text no. 15
16.Kassi E, Pervanidou P, Kaltsas G, Chrousos G. Metabolic syndrome: Definitions and controversies. BMC Med 2011;9:48.  Back to cited text no. 16
17.Al-Daghri NM, Al-Attas OS, Alokail MS, Alkharfy KM, Sabico SL, Chrousos GP. Decreasing prevalence of the full metabolic syndrome but a persistently high prevalence of dyslipidemia among adult Arabs. PLoS One 2010;5:e12159.  Back to cited text no. 17
18.Prabhakaran D, Anand SS. The metabolic syndrome: An emerging risk state for cardiovascular disease. Vasc Med 2004;9:55-68.  Back to cited text no. 18
19.Barrimah IE, Mohaimeed AR, Midhat F, Al-Shobili HA. Prevalence of metabolic syndrome among qassim university personnel in Saudi Arabia. Int J Health Sci (Qassim) 2009;3:133-42.  Back to cited text no. 19
20.Meigs JB, Wilson PW, Nathan DM, D'Agostino RB Sr, Williams K, Haffner SM. Prevalence and characteristics of the metabolic syndrome in the San Antonio Heart and Framingham Offspring Studies. Diabetes 2003;52:2160-7.  Back to cited text no. 20
21.Villegas R, Perry IJ, Creagh D, Hinchion R, O'Halloran D. Prevalence of the metabolic syndrome in middle-aged men and women. Diabetes Care 2003;26:3198-9.  Back to cited text no. 21
22.Irwin ML, Ainsworth BE, Mayer-Davis EJ, Addy CL, Pate RR, Durstine JL. Physical activity and the metabolic syndrome in a tri-ethnic sample of women. Obes Res 2002;10:1030-7.  Back to cited text no. 22
23.Case CC, Jones PH, Nelson K, O'Brian Smith E, Ballantyne CM. Impact of weight loss on the metabolic syndrome. Diabetes Obes Metab 2002;4:407-14.  Back to cited text no. 23
24.Riediger ND, Clara I. Prevalence of metabolic syndrome in the Canadian adult population. CMAJ 2011;183:E1127-34.  Back to cited text no. 24
25.Bennet AM, Brismar K, Hallqvist J, Reuterwall C, De Faire U. The risk of myocardial infarction is enhanced by a synergistic interaction between serum insulin and smoking. Eur J Endocrinol 2002;147:641-7.  Back to cited text no. 25
26.Palaniappan L, Carnethon MR, Wang Y, Hanley AJ, Fortmann SP, Haffner SM, et al. Predictors of the incident metabolic syndrome in adults: The Insulin Resistance Atherosclerosis Study. Diabetes Care 2004;27:788-93.  Back to cited text no. 26
27.Berlin I, Lin S, Lima JA, Bertoni AG. Smoking Status and Metabolic Syndrome in the Multi-Ethnic Study of Atherosclerosis. A cross-sectional study. Tob Induc Dis 2012;10:9.  Back to cited text no. 27
28.Santos AC, Ebrahim S, Barros H. Gender, socio-economic status and metabolic syndrome in middle-aged and old adults. BMC Public Health 2008;8:62.  Back to cited text no. 28
29.Riediger ND, Clara I. Prevalence of metabolic syndrome in the Canadian adult population. CMAJ 2011;183:E1127-34.  Back to cited text no. 29
30.Zhen-Hai S, Yun L, Feng L, Yin-Bo F, Ling W, Yue-Qin L, et al. Association of education level with metabolic syndrome in Su-Xi-Chang area of Jiangsu province. Chin J Health Manage 2011;5:9-11.  Back to cited text no. 30
31.Kavanagh A, Bentley RJ, Turrell G, Shaw J, Dunstan D, Subramanian SV. Socioeconomic position, gender, health behaviours and biomarkers of cardiovascular disease and diabetes. Soc Sci Med 2010;71:1150-60.  Back to cited text no. 31
32.Loucks EB, Rehkopf DH, Thurston RC, Kawachi I. Socioeconomic disparities in metabolic syndrome differ by gender: Evidence from NHANES III. Ann Epidemiol 2007;17:19-26.  Back to cited text no. 32
33.Albert MA, Glynn RJ, Buring J, Ridker PM. Impact of traditional and novel risk factors on the relationship between socioeconomic status and incident cardiovascular events. Circulation 2006;114:2619-26.  Back to cited text no. 33
34.Myong JP, Kim HR, Jung-Choi K, Baker D, Choi B. Disparities of metabolic syndrome prevalence by age, gender and occupation among Korean adult workers. Ind Health 2012;50:115-22.  Back to cited text no. 34
35.Sánchez-Chaparro MA, Calvo-Bonacho E, González-Quintela A, Fernández-Labandera C, Cabrera M, Sáinz JC, et al. Occupation-related differences in the prevalence of metabolic syndrome. Diabetes Care 2008;31:1884-5.  Back to cited text no. 35
36.Davila EP, Florez H, Fleming LE, Lee DJ, Goodman E, LeBlanc WG, et al. Prevalence of the metabolic syndrome among U.S. workers. Diabetes Care 2010;33:2390-5.  Back to cited text no. 36
37.Yoo S, Nicklas T, Baranowski T, Zakeri IF, Yang SJ, Srinivasan SR, et al. Comparison of dietary intakes associated with metabolic syndrome risk factors in young adults: The Bogalusa Heart Study. Am J Clin Nutr 2004;80:841-8.  Back to cited text no. 37
38.Castanho GK, Marsola FC, Mclellan KC, Nicola M, Moreto F, Burini RC. Consumption of fruit and vegetables associated with the metabolic syndrome and its components in an adult population sample. Cien Saude Colet 2013;18:385-92.  Back to cited text no. 38
39.De Oliveira EP, McLellan KC, Vaz de Arruda Silveira L, Burini RC. Dietary factors associated with metabolic syndrome in Brazilian adults. Nutr J 2012;11:13.  Back to cited text no. 39


  [Table 1], [Table 2], [Table 3]

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