alexa Risk Factors Associated with Diabetes Mellitus in a Saudi Community: A Cross-Sectional Study | Open Access Journals
ISSN: 2167-1079
Primary Healthcare: Open Access
Make the best use of Scientific Research and information from our 700+ peer reviewed, Open Access Journals that operates with the help of 50,000+ Editorial Board Members and esteemed reviewers and 1000+ Scientific associations in Medical, Clinical, Pharmaceutical, Engineering, Technology and Management Fields.
Meet Inspiring Speakers and Experts at our 3000+ Global Conferenceseries Events with over 600+ Conferences, 1200+ Symposiums and 1200+ Workshops on
Medical, Pharma, Engineering, Science, Technology and Business

Risk Factors Associated with Diabetes Mellitus in a Saudi Community: A Cross-Sectional Study

Khlid Al A1, Abbas Al M2* and Nisha S

1Department of Respiratory therapy, Inaya Medical College, Riyadh, Saudi Arabia

2Department of Nursing, Inaya Medical College, Riyadh, Saudi Arabia.

Corresponding Author:
Dr. Abbas Al M
Department of Nursing
Inaya Medical College
Riyadh, Saudi Arabia
Tel: 0555877487
E-mail: aalmutair@inaya.edu.sa

Received date: May 13, 2017; Accepted date: June 22, 2017; Published date: June 29, 2017

Citation: Khlid Al A, Abbas Al M, Nisha S (2017) Risk Factors Associated with Diabetes Mellitus in a Saudi Community: A Cross-Sectional Study. Prim Health Care 7:270. doi:10.4172/2167-1079.1000270

Copyright: © 2017 Abbas Al M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Visit for more related articles at Primary Healthcare: Open Access

Abstract

Background: According to World Health Organization (WHO) statistics almost seven million of the Saudi population are diabetic and three million are pre-diabetic. The risk of developing diabetes increases with some risk factors including family history, age, obesity and lack of physical activity. It is highly significant to allocate resources to quantify the prevalence of diabetes through preforming an assessment of the blood glucose level of the target population. Therefore, we designed this study to determine the association between certain demographic and clinical variables and random blood sugar among Saudi population. Methods: Cross-sectional design using survey was used to recruit subjects from business location in the capital city of Riyadh. A total of 144 subjects were recruited using Simple random sampling technique. Information gathered included age, gender, family history, history of gestational diabetes, hypertension, level of physical activity, body mass index (BMI) and results of random blood sugar (RBS). Results: The study provided information about the association between certain demographic and clinical variables and Random Blood Sugar among Saudi population. The age and physical activity were significantly associated with high blood sugar level. Also, females who were diagnosed with Gestational Diabetes Mellitus (GDM) demonstrated a high score of RBS and therefore are at high risk for type 2 Diabetes Mellitus (DM). Conclusion: In conclusion, this study revealed that there is a significant association between certain demographic and clinical variables and Random Blood Sugar among Saudi population. A prevention program at the level of the community should be initiated targeting those risk factor groups to prevent diabetes mellitus. Also, further studies to modify the risk factors are highly recommended to control and reduce the DM prevalence in Saudi Arabian population.

Keywords

Diabetes mellitus; Gestational diabetes; Risk factors; Prevalence Saudi Arabia

Introduction

Diabetes mellitus is one of the largest global health emergencies of the 21st century and a major public health problem in Saudi Arabia in parallel with the worldwide diabetes pandemic. The adoption of a modern lifestyle is a predisposing factor to this emerging pandemic. The indigenous Saudi population seems to have a special genetic predisposition to develop type 2 DM, which is further amplified by a rise in obesity rates, and the presence of other variables of the insulin resistance syndrome. [1].

As per the statistics of World Health Organization (WHO) Saudi Arabia ranks seventh in the world for the diabetes rates. Approximately seven million of the population in Saudi Arabia is diabetic and around 3 million are pre-diabetic. Indeed, diabetes has approximately shown a ten-fold increase among Saudi population in the past three eras. [2]. DM is irreversible once established. Diabetes develops slowly but progresses from pre-diabetes to diabetes without proper treatment. [3]. As time progresses more and more people live with diabetes, which leads to serious life-changing complications. In addition to the 415 million adults who are estimated to currently have diabetes, there are 318 million adults with impaired glucose tolerance, which puts them at high risk of developing the disease in the future. It has been estimated that two out of five adults with diabetes are undiagnosed in the Middle East [4]. The risk of developing type 2 diabetes increases with family history, age, obesity and lack of physical activity. Besides members of certain racial/ethnic groups, women with prior GDM and individuals with impaired glucose tolerance (IGT) or impaired fasting glucose (IFG) are prone to develop diabetes as well.

Diabetes mellitus is known to affect quite a few body systems and thereby affect the individual’s health in different ways such as having coronary artery disease (CAD), renal failure, diabetic retinopathy, etc.

Therefore, many countries attempted to study the consequences of diabetes on the population. However, it is interesting to note that the prevalence of DM is extremely variable among different populations though it increases with aging. The urban areas of Saudi Arabia have high prevalence of DM, owing to changes in the lifestyles of people particularly over the past few decades. [5]. A study conducted in rural areas of Saudi Arabia showed that there was an escalation of prevalence with age and higher-income groups with an overall prevalence in women as twice as that for men. The blood glucose was significantly affected by the factors such as age, income and BMI [6]. An investigation on the prevalence and associated factors for glucose intolerance among Saudi populations in urban and rural communities revealed that the measurement of mean random plasma glucose (RPG) from the urban population was considerably higher than that of the rural population. The world’s highest age adjusted prevalence of DM was found in the urban population of Saudi Arabia [7].

In nutshell, the modernization and resultant shift in lifestyle to more sedentary activity with higher-fat diets and obesity are the causes of the increased prevalence of diabetes mellitus in the Saudi community. Rational planning and allocation of resources would be effective with the quantification of prevalence of DM among the Saudi population [8]. Type 2 DM is diagnosed by analyzing an elevated blood glucose concentration. Therefore, it is essential to perform an assessment with blood glucose determination in the target population in order to determine the prevalence of type 2 DM. Considering this, the main objective of our study was to determine the prevalence of type 2 DM in a representative sample among the visitors of a business location in Riyadh. Furthermore, we also intended to identify the risk factors associated with the development of diabetes mellitus.

Materials and Methods

Subjects were recruited from the visitors of a business location in Riyadh. A total of 144 subjects were selected using simple random sampling technique. Information gathered include demographic factors such as age, gender, family history, history of gestational diabetes, hypertension, level of physical activity, Body Mass Index (BMI) and results of Random Blood Sugar (Tables 1 and 2). The exclusion criteria included subjects with other chronic diseases such as hypertension, renal and liver diseases and infectious diseases. Visitors with chronic and infectious diseases were directed to visit a medical center to do further medical investigations. Incompletely filled questionnaires also were removed resulting in a total sample size to n=144.

Parameter Estimates
Parameter B Std. Error 95% Wald Confidence Interval Hypothesis Test
Lower Upper Wald Chi-Square df Sig
(Intercept) 243.682 115.8177 16.683 470.680 4.427 1 0.035
[Age=0] 0.705 106.6664 -208.358 209.767 0.000 1 0.995
[Age=1] 26.750 114.7790 -198.213 251.713 0.054 1 0.816
[Age=2] 265.773 119.8827 30.807 500.739 4.915 1 0.027
[Age=3] 0a            
[Physically Active=0] -158.682 53.6132 -263.762 -53.602 8.760 1 0.003
[Physically Active=1] 0a            
(Scale) 10539.366b 3042.4530 5985.408 18558.173      
Dependent Variable: RBS
Model: (Intercept), Age, Physically Active
a. Set to zero because this parameter is redundant
b. Maximum likelihood estimate

Table 1: Model 1.

Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 75.311 17.742   4.245 0.000
T_score 8.437 3.070 0.230 2.749 0.007
a. Dependent Variable: RBS

Table 2: Model 2.

SPSS software, version 23 (SPSS Inc., Chicago, Illinois, USA) was used for data entry and analysis. The data were presented as scores using a predefined scoring system for each variable. The main outcome was resting blood sugar level, which was calculated on a continuous scale. The Pearson correlation test was used to infer any significant correlation between demographic, clinical variables and main outcome. On the other hand, for analysis of the association between the studied variables and the outcome, generalized linear model (GLM) was used. All analyses were carried out at a significance level of 0.05.

Results

Two variables, specifically age of the participants and physical activity, were significantly associated with the outcome (P=0.027, P=0.03, respectively) (Table 3). Significant associations in the analysis were used in a generalized linear model to determine the independent factors associated with high RBS levels. The final model showed that being 50 years or older and with no physical activity will increase the risk of having a higher score of RBS, hence will be at high risk of type 2 diabetes. On the other hand, after adjusting for gender, female who were diagnosed with gestational diabetes increase the risk of higher score of RBS and therefore a higher risk of type 2 DM.

Variable Score Frequency (%)
Age (groups) Less than 40 years 95 (65.5)
  40-49 years 27 (18.6)
  50-59 years 18 (12.4)
  60 years older 4 (2.8)
     
Gender Male 31 (21.4)
  Female 113 (77.9)
     
Gestational Diabetes Yes 20 (13.8)
  No 11 (7.6)
     
Family History Yes 52 (35.9)
  No 92 (62.1)
     
Hypertension Diagnosis Yes 117 (80.7)
  No 19 (13.1)
     
Physically Active Yes 67 (46.2)
  No 70 (48.3)
     
BMI BMI less than 18.50 10 (6.9)
  BMI 18.50-24.99 33 (22.8)
  BMI 25:00-29.99 57 (39.3)
  BMI 30 or more 43 (29.7)

Table 3: Sociodemographic data.

After Combining the variable scores for each participant, a linear regression model was used to interpret any association between the total score and final resting blood sugar level (Table 4). Our model revealed a significant association between the total score and RBS (P=0.007). Moreover, using this model, we can conclude that that for each added one unit score unit and increase of 8.437 in resting blood sugar level was recorded (P=0.007). Therefore, increase in the total score of the submitted survey is associated with a higher risk of type 2 DM (Figures 1-3).

Mean 121.56
Std. Deviation 67.42

Table 4: RBS descriptive statistics.

primary-health-care-normally-distributed

Figure 1: From the histogram above, we can observe that the data is skewed to the left. As the RBS scores are not normally distributed as shown, we can explain this by the fact of our small sample size.

primary-health-care-physically-active

Figure 2: A boxplot representing the age and physically active variables in relation with RBS scores. It can be clearly noticed that older participants with no physical activity are at higher risk of increase in their RBS score, hence higher risk of type 2 DM (RBS 0-500 mg/dL).

primary-health-care-RBS-score

Figure 3: A line graph representing the increase in mean RBS score as the total score of the survey participants’ increase. A steep increase is noticed beyond the total score of 8, which is explained by our previous regression analysis. As most probably, participants who recorded more than 8 in their total scores are from older age groups.

Discussion

This cross-sectional survey provides information about the association between certain demographic and clinical variables and Random Blood Sugar among Saudi population. In the results, age of the participants and physical activity were significantly associated with the Random Blood Sugar level RBS (p=0.027, p=0.03, respectively). This confirms a study conducted in rural Saudi Arabia to assess the prevalence of diabetes mellitus. It is also in congruent with a study examining the longitudinal relation among physical activity, BMI and development of type 2 DM in a high risk population [9].

In fact, there were several studies which showed that a physically active lifestyle results in lower incidence of diabetes mellitus. A study conducted among 5990 male alumni of University of Pennsylvania revealed that the leisure time physical activity such as walking, stair climbing, sports etc. are inversely related to the development of type 2 DM. It is not only effective in preventing the type 2 DM but also provides a pronounced protective effect among persons who are at high risk for the disease [10]. A prospective cohort study including 5 years followup among US male physicians yielded similar results. Apparently, even after adjusting for BMI, the development of type 2 DM was reduced by exercise. It also identified the increased physical activity as a primary prevention strategy for type 2 DM [11]. Comparable findings were observed between regular vigorous exercise and incidence of type 2 DM in a prospective cohort study including 87253 US women aged between 34-59 years, even after doing multivariate adjustments for age, BMI, etc., the reduced risk for type 2 DM found with exercise was not altered [12]. A review of literature about physical inactivity among the population of Saudi Arabia exposed a high prevalence (43.3%-99.5%) of physical inactivity among Saudi children and adults. Additionally, the Saudi population is at high risk for coronary heart disease due to physical inactivity owing to major life style changes in recent years [13].

The results of the present study are very much consistent with the abovementioned prospective studies. However, diabetes was diagnosed by measuring Random Blood Glucose level in the present study, whereas subjective reporting was used in some of the previous studies. Precisely, the incidence of diabetes increases with decreased physical activity in higher age group.

1-3% of all pregnant women develop Gestational Diabetes Mellitus (GDM). Pregnancy induced insulin resistance coupled with decreased production of insulin are considered as the primary causes of GDM. A systematic review on patients with type 2 DM with a history of GDM, reported that once diagnosed with GDM, the progression to type 2 DM was at more similar rates, there was a marked rise of cumulative incidence in the first 5 years and followed by a slow rise after 10 years [14]. The prevalence of postpartum diabetes is found in women with the diagnosis of GDM at less than 24 weeks of gestation [15]. Even non obese glucose tolerant women with a history of GDM were showing a metabolic profile of type 2 DM [16].

The results of the current study are in congruent with the above findings. The females who were diagnosed with GDM, demonstrated a high score of RBS and therefore are at high risk for type 2 DM

A cross-sectional study conducted among adults in Bangladesh revealed that older age, higher socioeconomic status, hypertension and obesity are significantly correlated to the development of type 2 DM [17]. Likewise, a cross-sectional epidemiological study conducted in Greece showed that the prevalence of type 2 DM increased significantly with older age (p<0.001) [18]. Similarly, the prevalence of diabetes in the adult population of US between 40-74 years of age is increasing [19]. A household survey conducted in Saudi Arabia showed a significant increase in the prevalence of type 1 DM, type 2 DM and Impaired Glucose Tolerance in the age group >30 years and a slight decrease in the incidence of type 1 DM among those over the age of 60 years .It also shed light to the fact that Saudi Arabia is one among the countries that have a high prevalence for DM and a moderate risk for Impaired Glucose Tolerance [20].

The prevalence of diabetes mellitus was found to increase with age in the Al Kharj area of Saudi Arabia as 23% of the diabetic patients belonged to the age group more than 65 years whereas, only 0.3% remained in the age group below 24 years. [21].

Conclusion

The findings of the present study also showed that being 50 years or older with less physical activity will increase the risk of having high score of RBS, hence will be at high risk for type 2 DM.

In summary, the current study reemphasize the need for devising a nationwide awareness program about a lifestyle modification including increased physical activity (30-45 min/day), weight reduction, improved eating habits as well as early detection of diabetes. Being health care providers in Saudi Arabia, we have the responsibility for an immediate action to save the country from this alarming condition before it exceeds the capacity of adjustment. A large prospective study is recommended to assess the effectiveness of a lifestyle modification program on the reduction of prevalence of type 2 DM among Saudi population.

References

Select your language of interest to view the total content in your interested language
Post your comment

Share This Article

Recommended Conferences

Article Usage

  • Total views: 105
  • [From(publication date):
    June-2017 - Jul 20, 2017]
  • Breakdown by view type
  • HTML page views : 85
  • PDF downloads :20
 
 

Post your comment

captcha   Reload  Can't read the image? click here to refresh

Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

Agri, Food, Aqua and Veterinary Science Journals

Dr. Krish

agrifoodaquavet@omicsonline.com

1-702-714-7001 Extn: 9040

Clinical and Biochemistry Journals

Datta A

clinical_biochem@omicsonline.com

1-702-714-7001Extn: 9037

Business & Management Journals

Ronald

business@omicsonline.com

1-702-714-7001Extn: 9042

Chemical Engineering and Chemistry Journals

Gabriel Shaw

chemicaleng_chemistry@omicsonline.com

1-702-714-7001 Extn: 9040

Earth & Environmental Sciences

Katie Wilson

environmentalsci@omicsonline.com

1-702-714-7001Extn: 9042

Engineering Journals

James Franklin

engineering@omicsonline.com

1-702-714-7001Extn: 9042

General Science and Health care Journals

Andrea Jason

generalsci_healthcare@omicsonline.com

1-702-714-7001Extn: 9043

Genetics and Molecular Biology Journals

Anna Melissa

genetics_molbio@omicsonline.com

1-702-714-7001 Extn: 9006

Immunology & Microbiology Journals

David Gorantl

immuno_microbio@omicsonline.com

1-702-714-7001Extn: 9014

Informatics Journals

Stephanie Skinner

omics@omicsonline.com

1-702-714-7001Extn: 9039

Material Sciences Journals

Rachle Green

materialsci@omicsonline.com

1-702-714-7001Extn: 9039

Mathematics and Physics Journals

Jim Willison

mathematics_physics@omicsonline.com

1-702-714-7001 Extn: 9042

Medical Journals

Nimmi Anna

medical@omicsonline.com

1-702-714-7001 Extn: 9038

Neuroscience & Psychology Journals

Nathan T

neuro_psychology@omicsonline.com

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

John Behannon

pharma@omicsonline.com

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry

social_politicalsci@omicsonline.com

1-702-714-7001 Extn: 9042

 
© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version