Research Article - Biomedical Research (2017) Volume 28, Issue 4
Effect of low glycemic index and food exchange system diets on metabolic syndrome components in Saudi medical studentsAbdulaziz A. Alodhayani1*, Adnan S. Bajaber2, Rasha Saleh Al-Hussan2
2Department of Food Science and Nutrition, King Saud University, Riyadh, Saudi Arabia
- *Corresponding Author:
- Abdulaziz A Al Odhayani
Family and Community Medicine
College of Medicine King Saud University, Saudi Arabia
Accepted on September 15, 2016
Metabolic Syndrome (MetS), a condition that manifests as a set of metabolic risk factors, is considered a global epidemic. The prevalence of MetS in Saudi Arabia has grown rapidly over the past decade. The aim of the present study was to determine the effect of Low Glycemic Index (LGI) and Food Exchange System (FES) diets on MetS components in patients with MetS in the Saudi population. We selected 69 subjects and divided them into 3 groups: LGI diet, FES diet, and control. Each group consisted of 23 subjects (12 women). Both treatment groups followed diet and physical activity regimens for 5 days per week for 6 weeks. Serum samples were taken pre- and post-treatment in all 3 groups and used for biochemical analyses. The results of study found significant difference in post-treatment values of hypertension i.e. SBP (p=0.007), DBP (p=0.01), Fasting Blood Glucose (FBG) (p=0.005), Triglycerides (TG) (p=0.0006) and Total Cholesterol (TC) (p=0.0006). There were no significant differences between groups in waist circumference (p=0.23) and high density lipoprotein (p=0.12). When the data from men and women were examined separately, we found significant differences between groups in the pretreatment values of TC (p=0.01) and the post-treatment values of FBG (p=0.65) and TG (p=0.99). We conclude that the LGI and FES diets are beneficial for patients with MetS, with a more potent impact produced by the LGI diet. We recommend implementing nutritional awareness and motivational counselling programs to help to improve the health of people with MetS in the Saudi population.
Metabolic Syndrome (MetS), Low Glycemic Index (LGI), Food Exchange System (FES), Glycemic Index (GI), Diet.
Metabolic Syndrome (MetS) is a multifactor disorder characterized by three or more abnormal metabolic risk factor traits including high Triglycerides (TG), Hypertension (HTN), high Fasting Blood Glucose (FBG), high Waist Circumference (WC), and low High Density Lipoprotein Cholesterol (HDL-C) . In Saudi Arabia and other countries, the prevalence of MetS has been estimated to be between 18% and 40%, depending on the specific population studied. Economic and social transformations have caused a shift to a sedentary lifestyle, resulting in an increasing prevalence of obesity, and an expected rise in the prevalence of MetS . The National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) documented that about 50 to 75 million people in the USA have MetS. In Europe, the prevalence rates of MetS among men and women are 15.7% and 14.2%, respectively. In Saudi Arabia, 66% of adult men and 71% of adult women are either overweight or obese . In the Gulf Cooperation Council (GCC) countries, Kuwait, Oman, Saudi Arabia, and the United Arab Emirates have the highest prevalence of diabetes . Limited information is available on the prevalence of MetS in Saudi Arabia, and most surveys in the population involve standard research targets other than MetS.
Diet patterns play a crucial role in controlling MetS, which often requires weight reduction as most people with MetS are overweight, obese, or morbidly obese. Because abdominal obesity in particular is a predisposing factor for MetS, specific nutritional influences on body fat distribution are important, although mechanisms are not yet exhaustively defined [5,6]. Earlier diet concept studies have suggested that MetS can be effectively controlled by regulating insulin resistance through Glycemic Index (GI). This theory focuses on how carbohydrate-rich foods can influence the physiological positions of the human body. The GI theory compares the ability of carbohydrate-rich foods to elevate blood glucose levels with that of a portion of a reference food (usually glucose or white bread) during the first 2 hours after consumption . This framework classifies carbohydratecontaining foods as having a high, medium, or low GI. For people with diabetes, LGI foods or carbohydrate-containing foods that result in a slight increase in blood glucose levels are considered more appropriate than High Glycemic Index (HGI) foods . There have been no studies on the effect of diet therapy on MetS in Saudi Arabia. Therefore, the aim of the present study was to investigate the effects of LGI and FES diets on MetS components in patients in the Saudi population.
Materials and Methodology
Enrolment of subjects
This study was carried out in King Khalid University Hospitals (KKUH), King Saud University, Riyadh, Saudi Arabia. Obese and morbidly obese subjects (n=69) with Body Mass Indices (BMIs) between 28.6 and 58.1 were recruited from the obesity center clinic. To be included, subjects had to be within the age range of 19-65 years and exhibit MetS per the International Diabetes Foundation (IDF) criteria . Subjects were excluded if they were following a weight reduction program or taking weight reduction supplements with or without an accompanying diet, affected by other metabolic disorders, had undergone bariatric surgery, were pregnant, or had adverse physical or psychological conditions. The selected 69 subjects were divided into 3 groups: LGI diet, FES diet, and control (Table 1). Each of the 3 groups consisted of 23 subjects (12 women). Selected subjects were examined in a designated room and anthropometric, clinical, demographic, and medical data were recorded and maintained confidentially. Ethical approval was obtained from KKUH and all the subjects signed the consent form prior to participating in the study.
|S. no||Characteristic features||Total (n=69)||Range (Minimum-Maximum)|
|1||Age (Years)||43.5 ± 12.7||(19-65)|
|2||Gender (M: F)*||(47.8%: 52.2%)||(1-69)|
|3||BMI (kg/m2)||41 ± 7.8||(28.6-58.1)|
|4||Weight (Kg)||112 ± 23.9||(69.5-167.3)|
|5||Height (cms)||164.4 ± 9.2||(128-193)|
|6||SBP (mmHg)||145 ± 16.9||(103-180)|
|7||DBP (mmHg)||88.8 ± 8.3||(69-110)|
|8||Waist (cms)||117.7 ± 12||(98-145)|
|9||FBG (mmol/l)||7.1 ± 2.5||(4.6-9.6)|
|10||TC (mmol/l)||5.0 ± 0.9||(3.5-7.9)|
|11||TG (mmol/l)||1.7 ± 0.8||(0.59-4.7)|
|12||HDL-C (mmol/l)||1.1 ± 0.3||(0.49-2.6)|
|13||LDL-C (mmol/l)||3.0 ± 0.8||(1.5-5.11)|
Table 1. Clinical characteristic features of subjects involved in this study.
Diet program and follow-up
.Subjects followed prescribed diets and physical activity regimens for 6 weeks. During the study period, both treatment groups were also presented with a training program that focused on commitment to long-term lifestyle improvements. Control group subjects were not provided with any information about the program and were evaluated as regular clinic patients. Prior to the start of the treatment period, subjects were surveyed on their lifestyles and eating habits, including questions about beverages consumed, including soft drinks, vegetable and fruit juices. The baseline values for all subjects are tabulated in Table 2. After the completion of study period, all subjects were asked to attend the KKUH clinic with a 12 hour overnight fast before having post-treatment anthropometric, biochemical, and clinical measurements taken. The post-treatment measurements are tabulated in Table 3. The training program included lectures, workshops, and written materials. Ten- to fifteen-minute motivational counselling sessions were conducted by telephone. Dietary compliance was monitored through regular telephone interviews. In addition, regular contact was maintained through mobile messages or emails. The intervention protocol, risks of participation, and study applications were explained to both treatment groups through lectures Treatment group subjects were instructed on their respective diet plans, while control subjects were asked to maintain their routine diet activities during the intervention.
|S. no||Characteristic features||Controls (n=23)||FES (n=23)||LGI (n=23)||P-value|
|1||Age (Years)||43.5 ± 12.7||43.7 ± 13.7||42.1 ± 11.6||0.89|
|2||Gender (Male: Female)||(11:12)||(11:12)||(11:12)||1|
|3||BMI (kg/m2)||40.9 ± 7.8||41.4 ± 8.6||41.1 ± 7.8||0.98|
|4||Weight (Kg)||112 ± 23.9||111 ± 23.9||113.3 ± 21.9||0.94|
|5||SBP (mmHg)||145 ± 16.9||144.5 ± 18.6||146.3 ± 15.3||0.93|
|6||DBP (mmHg)||88.8 ± 8.3||89.4 ± 9.8||87.6 ± 6.3||0.75|
|7||Waist (cms)||117.7 ± 12||115.1 ± 10.8||122.3 ± 14.3||0.41|
|8||FBG (mmol/l)||7.1 ± 2.5||6.9 ± 2.3||7.7 ± 2.3||0.49|
|9||TC (mmol/l)||4.8 ± 0.8||5.2 ± 1.0||4.9 ± 0.9||0.3|
|10||TG (mmol/l)||1.7 ± 0.8||1.8 ± 0.8||1.7 ± 0.9||0.89|
|11||HDL-C (mmol/l)||1.1 ± 0.3||1.1 ± 0.4||1.0 ± 0.2||0.45|
|12||LDL-C (mmol/l)||3.0 ± 0.8||3.1 ± 0.9||3.0 ± 0.8||0.89|
Table 2. Calculation of pre-values between the 3 subjects using ANOVA analysis.
Anthropometric measurement and sample collection
Anthropometric measurements including HTN, BMI, and WC were measured. HTN was based on Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP), measured using an electrosphygmomanometer (Datascope Accutorr plus NIBP with Trend Screen and Datascope SpO2 with the recorder module, Datascope Corporation, USA). Weight was measured without excess clothing, shoes, or socks, on electronic scales (InBody model 720, Germany). Height (cm) was measured using a freestanding stadiometer (Seca, Vogel and Halke, Hamburg, Germany). BMI was calculated as weight (kg) divided by height squared (m2) [10,11]. WC (cm) was measured midway between the lowest rib and iliac crest . Venous blood samples were collected after an overnight fast and 5 ml serum samples were separated for biochemical analyses. Serum was analysed for Fasting Blood Glucose (FBG) and lipid profile measurements, including TC, TG, HDL-C, and low Density Lipoprotein-Cholesterol (LDL-C) . HDL-C levels were measured using enzymatic/ cholesterol oxidase and TG levels were measured using enzymatic/lipase/glycerol kinase .
Data were expressed as mean ± SEM values. Statistical analyses were performed using the Statistical Package for Social Sciences (SPSS) version 19 software (SPSS Inc., Chicago, USA). The significance level used for all the tests was set at P ≤ 0.05. A t-test or 1-way Analysis of Variance (ANOVA) was performed to compare changes between groups.
Sixty-nine subjects were enrolled in our study (Table 1). The mean age was 43.5 ± 12.7 with an age range of 19-65 years. Of all subjects, 47.8% were male and 52.2% were female. The mean BMI and weight were 41 ± 7.8 and 112 ± 23.9 kg, respectively. Mean SBP was 145 ± 16.9 and mean DBP was 88.8 ± 8.3. SBP and DBP were used as indicators of hypertension. Mean FBG was 7.1 ± 2.5. Mean values of lipid profile measurements were as follows: 5.0 ± 0.9 for TC, 1.7 ± 0.8 for TG, 1.1 ± 0.3 for HDL-C, and 3.0 ± 0.8 for LDL-C.
ANOVA analysis of pre- and post-treatment values
ANOVA analysis was performed on the 3 study groups. There was no significant difference between groups with respect to age (p=0.89) or gender (p=1.0). We found no significant difference in SBP, DBP, FBG, TC, TG, HDL-C, or LDL-C between the 3 groups at baseline. However, we observed statistical differences between groups in the post-treatment measurements (p<0.05) of SBP (p=0.007), DBP (p=0.01), FBG (p=0.005), TC (p=0.0005), TG (p=0.0006), and LDL-C (p=0.009). We did not observe differences in BMI, weight, WC, or HDL-C (p>0.05) (Tables 2 and 3).
|S. no||Characteristic features||Controls (n=23)||FES (n=23)||LGI (n=23)||P-value|
|1||BMI (kg/m2)||41.2 ± 7.5||39.1 ± 9.0||38 ± 7.8||0.4|
|2||Weight (Kg)||112.8 ± 28.1||105.4 ± 24.1||104.9 ± 22.1||0.48|
|3||SBP (mmHg)||141.9 ± 14.2||132.9 ± 14.3||123.3 ± 11.8||0.007|
|4||DBP (mmHg)||80.5 ± 9.8||81.2 ± 8.6||74.8 ± 5.8||0.01|
|5||Waist (cms)||117.2 ± 10.1||111.2 ± 11.8||115.3 ± 13.9||0.23|
|6||FBG (mmol/l)||7.5 ± 3.4||6.5 ± 1.9||6.2 ± 1.9||0.005|
|7||TC (mmol/l)||4.8 ± 0.6||5.0 ± 0.9||4.1 ± 0.8||0.0005|
|8||TG (mmol/l)||1.6 ± 0.7||2.1 ± 0.8||1.3 ± 0.5||0.0006|
|9||HDL-C (mmol/l)||1.0 ± 0.3||1.0 ± 0.3||1.0 ± 0.2||0.12|
|10||LDL-C (mmol/l)||3.0 ± 0.6||3.0 ± 0.9||2.4 ± 0.7||0.009|
Table 3. Calculation of post-values between the 3 subjects using ANOVA analysis.
Gender association analysis of pre- and posttreatment values
We compared pre- and post-treatment values of anthropometric, biochemical, and clinical measurements by gender (Tables 4 and 5). The difference between mean ages of male (36.3 ± 12.1) and female (50.0 ± 9.3) subjects was not statistically significant (p<0.05). At baseline, there was a significant difference in TC (p=0.01) between the 3 groups and no significant difference in any of the other measures (p>0.05). Post treatment, FBG (p=0.01) and TC (p=0.04) were significantly different between the 3 groups (p<0.05). There were no significant differences in the other measures (p>0.05).
|S. no||Characteristic features||Males||Females||P value|
|1||Age (Years)||36.3 ± 12.1||50.0 ± 9.3||0.13|
|2||BMI (kg/m2)||40.6 ± 7.5||41.4 ± 8.1||0.66|
|3||Weight (Kg)||120.3 ± 23.2||104.5 ± 22.2||0.79|
|4||SBP (mmHg)||146.6 ± 18.3||143.4 ± 15.7||0.37|
|5||DBP (mmHg)||90.4 ± 8.4||87.4 ± 8.1||0.83|
|6||Waist (cms)||122.2 ± 11.1||113.5 ± 11.3||0.92|
|7||FBG (mmol/l)||6.7 ± 2.4||7.3 ± 2.6||0.65|
|8||TC (mmol/l)||5.0 ± 1.1||4.9 ± 0.7||0.01|
|9||TG (mmol/l)||1.9 ± 0.7||1.5 ± 0.7||0.99|
|10||HDL-C (mmol/l)||0.9 ± 0.3||1.2 ± 0.3||0.99|
|11||LDL-C (mmol/l)||3.1 ± 0.9||3.0 ± 0.8||0.49|
Table 4. Comparison of pre-values between males and female’s subjects.
|S. no||Characteristic features||Males||Females||P value|
|1||BMI (kg/m2)||39.1 ± 7.1||39.8 ± 8.5||0.3|
|2||Weight (Kg)||115.7 ± 24.6||100.4 ± 22.8||0.65|
|3||SBP (mmHg)||131.1 ± 16.4||134.25 ± 14.3||0.42|
|4||DBP (mmHg)||79.4 ± 8.1||78.4 ± 9.1||0.5|
|5||Waist (cms)||118.6 ± 11.7||110.9 ± 11.5||0.91|
|6||FBG (mmol/l)||6.0 ± 1.9||7.4 ± 2.9||0.01|
|7||TC (mmol/l)||4.6 ± 1.0||4.7 ± 0.7||0.04|
|8||TG (mmol/l)||1.9 ± 0.8||1.4 ± 0.6||0.09|
|9||HDL-C (mmol/L)||0.9 ± 0.3||1.2 ± 0.3||0.99|
|10||LDL-C (mmol/l)||2.8 ± 0.9||2.8 ± 0.7||0.14|
Table 5. Comparison of post-values between males and females’ subjects.
The aim of the present study was to investigate the effects of LGI and FES diets on MetS components in Saudi patients. The post value results of our current study suggested the LGI and FES diets are recommendable for the MetS patients. GI is the impact of carbohydrate containing foods on blood glucose. According to the literature, the LGI diet is associated with a decreased risk of MetS, type 2 diabetes, cardiovascular disease, stroke, chronic kidney disease, uterine fibroids, and several cancers, including breast, colon, and pancreas, and prostate cancer. In this study, we found a substantial change in MetS measures in the LGI diet group from pre-treatment to posttreatment. The FES diet theory dictates that approximately equivalent calories, proteins, fats, and carbohydrates may be exchanged or substitute without significant alteration to nutritional balance. The changes in MetS measures in the FES group were moderate. We observed that the 3 groups had significantly different HTN, FBG, and TG values posttreatment based on ANOVA analysis. There were significant changes in the metabolic parameters HTN, TG, and FBG from pre- to post-treatment, whereas there were no significant changes in WC and HDL-C. There were substantial changes in subject BMIs in both the LGI and FES groups, but they were not statistically significant. This may have been due to the short program duration.
Changing dietary habit represent a major challenge for many people . It has been showed that modifying dietary and physical activity habits through lifestyle interventions is an effective method of improving MetS components . One potential yet controversial mechanism for the effect of GI on obesity is that HGI foods induce the secretion of insulin and suppression of glucagon release . Insulin inhibits lipolysis and gluconeogenesis and stimulates lipogenesis and glycogenesis . The consequent rapid decrease in blood glucose stimulates hunger , which may result in greater energy intake and ultimately, obesity. Moreover, the long-term effect of insulin on the suppression of fatty acid oxidation may induce insulin resistance , which may be a risk factor for obesity. However, HGI foods may simultaneously induce insulin secretion and the release of leptin, a food intake suppressor. Leptin function depends on the presence of insulin . Therefore, there are two opposing theories about the role of the GI of foods in obesity. The strong relationship between MetS and dietary pattern, tobacco use, and physical inactivity has also been reported in the literature . In our study, we did not collect information on tobacco use, as this was not the focus of our study.
MetS is a constellation of risk factors associated with increased risk of diabetes and cardiovascular disease. It is a growing health problem in developed and developing countries. In GCC states, the current prevalence is estimated to be 20.7-37.2% [ATPIII] or 29.6-36.2% [IDF] for men, and 32.1-42.7% [ATPIII] or 36.1-45.9% [IDF] for women. However, the prevalence rates for women in GCC countries are almost 10-15% higher than in most developed countries. The cause is not clear, but socio-economic status may influence MetS and its components by affecting environmental and social factors [3,23]. Several studies on MetS have been carried out in Saudi Arabia. The overarching conclusion is that weight reduction owing to diet and physical exercise is significantly associated with an increase in HDL-C and a decrease in TG [3,24-31]. In this study, we did observe a significant change in TG values but not HDL-C values, which may be due to the low sample size of our study. Similar intervention program studies have been carried out in different parts of the globe in MetS subjects [32-36]. Fappa et al. concluded from his studies that telephonic counselling was an effective way to implement behavioural counselling to improve lifestyle habits in patients with MetS . Based on our study observations, we agree with the effectiveness of this strategy. The results of the Scicchitano et al. studies suggested the dyslipidaemia accelerates the atherosclerotic process and its morbid consequences; statins represent the evidence based treatment of choice for reducing low density lipoprotein cholesterol levels and decreasing cardiovascular events . The mechanisms underlying such actions are not fully understood but may be related to reducing 7a-hydroxylase, increasing faecal excretion of cholesterol, decreasing 3-hydroxy-3-methylglutaryl-CoA reductase mRNA levels or reducing the secretion of very low-density lipoprotein. This contribution provides an overview of the mechanism of action of nutraceuticals and functional food ingredients on lipids and their role in the management of lipid disorders Ciccone et al. studies conclude the healthy diet can improve cardiovascular risk profile of individuals .
The strength of our current study was designing the study with two different diet pattern groups along and control subjects with equal number of subjects in all the 3 groups. The current limitations of our study was (i) low sample size (ii) short intervention programme (6 weeks only) (iii) excluded diet pattern details. Based on the results of our current study, we conclude that LGI and FES diet patterns are recommendable for MetS patients. However, future studies are recommended for implementing the nutritional awareness motivational counselling programs in MetS in our population.
This study was supported by the College of Medicine Research Centre, Deanship of Scientific Research, King Saud University, Riyadh, Kingdom of Saudi Arabia.
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