



































Effect of an aqueous extract of Dichrostachys glomerata on anthropometric, lipid and inflammatory parameters of obese patients with metabolic syndrome


Functional Foods in Health and Disease 2013; 3(11):416-427                                                          Page 416 of 427 

Research Article                Open Access 

 

Anti-inflammatory, anthropometric and lipomodulatory effects 

Dyglomera® (aqueous extract of Dichrostachys glomerata) in obese patients 

with metabolic syndrome 

 

Dieudonne Kuate
abd

, Blanche C. Etoundi
ac

, Judith L. Ngondi,
a 

Wan Abdul Manan 

Bin Wan Muda
d
 and Julius E. Oben

a
* 

 

a
Laboratory of Nutrition and Nutritional Biochemistry, Department of Biochemistry, Faculty of 

Science, University of Yaounde 1, Yaounde, Cameroon; 
b
Department of biochemistry, Faculty 

of science , University of Dschang; 
c
Department of biochemistry, Faculty of science , University 

of Douala; 
d
Program in Nutrition, School of  Health Sciences Universiti Sains Malaysia, 16150 

Kubang Kerian Kelantan, Malaysia  

 

*Corresponding author:
 
Julius E. Oben: Laboratory of Nutrition and Nutritional Biochemistry, 

Department of Biochemistry, Faculty of Science, University of Yaounde 1, PO Box 812 

Yaounde, Cameroon. 

 

Submission date: October 8, 2013; Acceptance date: November 11, 2013; Publication date: 

November 18, 2013  

 

Running Title: Anti metabolic syndrome effects of Dyglomera® 

 

 

ABSTRACT 

Background: Increased visceral fat, dyslipidemia and increased markers of inflammation and 

coagulation are cardiovascular risk factors commonly encountered in obese people with 

metabolic syndrome. Previous studies have shown that ground Dichrostachys glomerata (DG), a 

spice used in Western Cameroon, can have beneficial effects on inflammation and various other 

cardiovascular disease risk factors. The purpose of the present study was to evaluate the effects 

of Dyglomera®, an aqueous extract of DG (standardized to NLT 10% polyphenols)   on certain 

anthropometric, biochemical (including pro-inflammatory and pro-thrombotic states) and 

hemodynamic parameters in obese patients with metabolic syndrome.  

 

Methods: The study was an 8-week randomized, double-blind, placebo-controlled trial involving 

116 males and 202 females aged between 24 and 58 years. Participants were randomly divided 

into two groups: treatment and placebo. Capsules containing the active treatment (200 mg 

Dyglomera®) or placebo (200 mg maize powder) were administered 30–60 minutes before lunch 

and dinner throughout the study period. Various biochemical (namely, blood glucose, lipid 

profile, pro-inflammatory and pro-thrombotic markers), anthropometric and hemodynamic 

parameters were measured at baseline and after 4 and 8 weeks of treatment.   



Functional Foods in Health and Disease 2013; 3(11):416-427                                                          Page 417 of 427 

 

Results: At the end of the study, the Dyglomera® group showed statistically significant 

differences in all 16 parameters compared to baseline values. Changes in BMI and waist 

circumference were accompanied by changes in biochemical parameters, with the exception of 

adiponectin levels which were not correlated to waist circumference and PAI-1 values. The 

results confirm the hypothesis that Dyglomera®, the aqueous extract of DG, has anti-

inflammatory properties, and is effective in reducing cardiovascular disease risk factors 

associated with metabolic syndrome in obese human subjects. 

 

Key words: Dichrostachys glomerata extract, inflammation, obesity, metabolic syndrome  

 

 

1. INTRODUCTION 

Obesity and its related complications are generally referred to as metabolic syndrome (MetS) and 

its prevalence is increasing worldwide, with some countries experiencing as much as a three-fold 

increase in the last three decades [1]. Due to the fact that MetS is a multifactorial disorder 

involving genetic and environmental factors, its management remains a challenge to scientists 

worldwide. Even though obesity-related complications appear to be secondary to the condition 

itself, some of the accompanying changes are life-threatening, requiring a combination of 

management strategies for appropriate control. This is the case in type 2 diabetes mellitus, 

dyslipidemia, atherosclerosis, hypertension, oxidative stress, and inflammation. MetS comprises 

a clustering of atherosclerotic factors, including visceral obesity, dyslipidemia, and disturbed 

carbohydrate metabolism [2]. It is associated with pro-inflammatory and pro-thrombotic states, 

in which the role of increased visceral fat deposits is thought to be central. Abdominal obesity 

leads to alteration of the normal physiological balance of adipokines, insulin resistance, 

endothelial dysfunction and a pro-atherogenic state [3,4]. In association with this, the presence of 

conventional cardiovascular risk factors such as hypertension results in a significantly elevated 

cardiometabolic risk. The pathway leading to MetS involves the abnormal production of 

hormones and cytokines from the adipose tissue [3], namely, excessive production of IL-6, TNF-

α and the prothrombotic agent plasminogen activator inhibitor type 1 (PAI-1).  This is 

accompanied by low secretion of the protective adipocytokine adiponectin, a molecule that 

exerts anti-inflammatory, anti-atherogenic, and anti-diabetic effects, and whose production is 

down-regulated in obese individuals with metabolic syndrome [3,5]. On the other hand, 

overproduction of IL-6 by the adipose tissue in obesity induces hepatic (C-reactive protein) CRP 

synthesis, which promotes the onset of cardiovascular complications [6].  

The management of disorders clustered in this syndrome and the elucidation of the 

mechanisms involved in its development are of great interest for the benefit of health. While 

lifestyle modification through dietary intervention and exercise have had limited success in 

treating these disorders, they have not stopped the increasing prevalence of MetS and may have 

low long-term sustainability.  Pharmacological therapy has therefore been proposed as an adjunct 

to diet and lifestyle changes to improve long-term weight loss [7]. The numerous synthetic drugs 

developed to combat obesity and metabolic syndrome have had only marginal success, due in 



Functional Foods in Health and Disease 2013; 3(11):416-427                                                          Page 418 of 427 

part to their accompanying adverse effects [8,9]. This has turned the focus of some researchers 

towards nutraceuticals, compounds derived from foods or other natural products that are 

considered to be safer. Medicinal foods and herbal drugs are therefore widely prescribed, even 

when their biologically active compounds are unknown [10,11].
 

Dichrostachys glomerata (DG) (Forssk.). Chiov. is a deciduous tree found in Cameroon 

and other tropical countries. DG produces edible fruits and seeds, and the dried fruits are 

commonly used as a spice in a traditional soup of the Western provinces of Cameroon called 

“Nah poh”[12]. The hypotensive property of the plant was first reported more than four decades 

ago [13]. This plant has been shown to have antiviral, anti-infectious, [14] anti-inflammatory, 

and analgesic effects in rats [15] and cicatrizing effects [16]. A study from our laboratory 

showed that DG fruits also exhibit in vitro and in vivo antioxidant activity and can inhibit 

oxidation of low-density lipoproteins (LDL) [17]. A study of diabetic rats showed the ability of 

DG to reduce fasting blood glucose and glycosylated hemoglobin levels [18]. A recent study 

indicated that whole, ground  DG had a positive effect on cardiovascular risk factors associated 

with obesity and type 2 diabetes [19]. While these reports suggest that DG can have beneficial 

effects on health, the bioactive components of DG have not been well characterized. Toward this 

end the current study was undertaken to evaluate the effects of an aqueous extract of 

standardized DG on MetS markers in obese humans.   

 

2. METHODS AND MATERIALS   

2.1. Test material: Dyglomera®, an aqueous extract of DG (standardized to NLT 10% 

polyphenols), was supplied by Gateway Health Alliances, Fairfield, California, USA.  They were 

supplied as 200 mg capsules.  Identical-looking placebo capsules were also manufactured 

containing 200 mg of maize-based powder.  

 

2.2. Study population and intervention 

The study was a double-blind, placebo-controlled trial lasting 8 weeks. A total of 318 

participants (202 females and 116 males) were randomly selected from a pool of 1,360 obese 

subjects previously recruited from the city of Yaounde and its environs. The participants 

included males and non-pregnant/non-lactating females aged 24–58 years, with a BMI between 

30-40 kg/m
2
. The NCEP ATP III criteria were used for the diagnosis of MetS, such that if any 

three of the following conditions were present in the same patient they were considered to have 

MetS: waist circumference > 102 cm in men and > 88 cm in women; triglycerides (TAG) ≥ 150 

mg/dL; high-density lipoprotein (HDL) < 40 mg/dL in men and < 50 mg/dL in women; fasting 

glucose ≥ 110 mg/dL and blood pressure ≥ 130/85 mm Hg (or use of antihypertensive agents) 

[20]. A physician examined participants to ascertain their eligibility for inclusion in the study. 

Participants were randomly divided into two groups, and were instructed to take 200 mg of either 

Dyglomera® or placebo 30-60 min before lunch or dinner throughout the study period.  They 

were asked to report any lapses in taking the pills.  Since the capsules were identical in size, 

shape, and appearance, neither the researchers nor participants knew which treatment was given. 

Participants were encouraged to maintain their prior lifestyle and dietary habits throughout the 

study. 



Functional Foods in Health and Disease 2013; 3(11):416-427                                                          Page 419 of 427 

 

2.3. Exclusion criteria  

Exclusion criteria included impaired kidney function, cardiac problems, serious hypertension 

(systolic and diastolic blood pressure above 180 mm Hg, and 110 mm Hg, respectively), need for 

daily insulin management, and enrollment in another clinical study within the past 6 months. 

Also excluded were volunteers with a history of drug or alcohol abuse, those on cholesterol-

lowering, inflammation-reducing and/or other medications (e.g., steroids) that interfere with 

blood clotting and wound repair, as well as participants with infections including HIV/AIDS or 

cancer. 

 

2.4. Approval and informed consent  

The study was approved by the local ethical committee (Approval No. 006/CNE/MP/07). The 

purpose, nature, and potential risks of the study were explained to all participants, who gave their 

written informed consent before participation. The study was done in full accordance with the 

ethical provisions of the World Medical Association Declaration of Helsinki (as amended by the 

52nd General Assembly, Edinburgh, Scotland, October 2000). 

 

2.5. Anthropometric measurements 

Various anthropometric parameters were measured at baseline and at biweekly follow-up visits 

for the 8 weeks of treatment. Height was measured with a Harpenden™ stadiometer (Cranlea & 

Company, Birmingham, UK), which measures height to the nearest 0.5 cm. Body weight and 

percentage body fat were assessed using a Tanita
TM

 BC-418 Segmental Body Composition 

Analyzer/Scale (Arlington Heights, Illinois, USA) that uses bioelectrical impedance analysis to 

compute body composition. BMI was calculated as the ratio of weight (kg) to height squared 

(m
2
). Waist (average of narrowest and the widest parts of the trunk) and hip (widest point) 

circumferences were measured to the nearest 0.1 cm. The participants were asked to fast for 12 

hours and to wear light clothing for visits when measurements were taken. The participants were 

measured at approximately the same time of day and by the same technician across visits. 

 

2.6. Blood pressure 

As with the anthropometric measurements, blood pressure was recorded at baseline and at 

biweekly follow-up visits. Blood pressure was measured on the left arm after a 10-minute rest. 

Triplicate readings were taken over 5-minute intervals and the average was recorded. 

 

2.7. Sample collection 

At Week 4 and Week 8, blood samples (5 ml of blood) were collected after a 12-hour overnight 

fast. The plasma or serum obtained from each blood sample were split into multiple 500 µl 

aliquots and stored at -20 °C until needed.   

 

2.8. Analytical methods  

This study used the Trinder glucose activity test [21], which determines glucose in the blood 

using glucose oxidase with an alternative oxygen receptor. Plasma total cholesterol was assayed 



Functional Foods in Health and Disease 2013; 3(11):416-427                                                          Page 420 of 427 

by the cholesterol oxidase method [22], while triglycerides were assayed following the method 

described by Bucolo and David [23]. HDL cholesterol was determined using a heparin 

manganese precipitation of Apo B-containing lipoproteins [24], and LDL cholesterol was 

calculated using the Friedewald formula [25].  C-reactive protein was measured using an ELISA 

method (BioCheck™ hsC Reactive Protein ELISA kit, Foster City, CA USA). . Fasting insulin 

(mIU/l) was determined using the Medgenic immunoenzymetric assay by Biosource-Europe SA 

(Nivelles, Belgium). Insulin sensitivity was assessed by the homeostasis assessment model 

(HOMA-IR [mmol/L × mU/L] = (fasting glucose [mmol/L] × fasting insulin [mU/L]/22.5). 

Fasting serum adiponectin was measured using the Linco RIA, and PAI-1 concentrations were 

assessed by using an enzyme-linked immunosorbent assay (Diagnostica Stago, Asnières-sur-

Seine, France). 

 

2.9. Statistical analysis 

The data were summarized (mean and standard error) for Week 0 (baseline), Week 4, and Week 

8 (final), and the intra-group variation and the data were analyzed using SPSS 16.0 for Windows 

(SPSS Inc., Chicago, IL, USA). Because the repeated measurements on each participant were 

correlated in nature (covariance), a mixedmodel approach was used to characterize variation 

between patients and within patients because it is a flexible tool for analyzing repeated, 

longitudinal treatments. The interaction between time and intervention was tested at the 0.05 

level of significance. If the interaction was significant, comparisons were made between the 

treatment and placebo groups for each month. Between-treatment changes were tested using one-

way analysis of covariance (ANCOVA), adjusted for baseline values, with the initial value as a 

covariate. Bilateral correlations between variables were examined using Pearson’s correlation 

coefficients. P values less than 0.05 were considered to be statistically significant. 

 

3. RESULTS  

3.1. Baseline characteristics A total of 297 individuals (154 in the Dyglomera® treatment group 

and 143 in the placebo group) out of 318 initial participants completed the study (21 participants 

dropped out of the study). The number of premature withdrawals was higher in the placebo 

group than in the Dyglomera® group (16 vs 5). The baseline (T0) anthropometric, 

hemodynamic, and metabolic characteristics of the two study groups are listed in Tables 1–4. 

Plasma TAG, total cholesterol, plasma glucose, insulin resistance (HOMA-IR), CRP, and 

circulating PAI-1 were slightly higher at T0, whereas HDL cholesterol and adiponectin were 

lower at T0 than normal values, which is reflective of the obese status of the patients in the 

study. The baseline characteristics across the two experimental groups were not significantly 

different.  

 

3.2. Anthropomorphic characteristics and blood pressure.  Table 1 shows the changes in the 

various anthropometric variables (body weight, BMI, waist and hip circumference, and percent 

body fat) over the 8-week trial period.  

 

 



Functional Foods in Health and Disease 2013; 3(11):416-427                                                          Page 421 of 427 

Table 1. Anthropometric effects of DG in obese subjects with metabolic syndrome 
 

Variable Group T0 T4 T8 Change from baseline      

(T8 - T0) (%) 

Weight (kg) DG 99.26± 1.12 93.73± 1.07
a 

88.12± 1.05
b 

-11.15± 0.18 (-11.33)
†
 

Placebo 98.69± 1.15 98.72± 1.12
 

98.17± 1.11
 

-0.53± 0.11 (-0.49)
 

BMI (kg/m
2
) DG 36.63± 0.25 34.59± 0.25

a
 32.51±0.26

b
 -4.13± 0.06 (-11.33)

†
 

Placebo 36.02± 0.26 36.04± 0.26 35.84± 0.26 -0.18± 0.04 (-0.49) 

Waist (cm) DG 106.20± 0.88 99.79± 0.98
b 

95.48± 0.99
b 

-10.72± 0.28
† 
(-10.23)

†
 

Placebo 105.43± 1.00 105.49± 0.97
 

104.65± 0.97
 

-0.77± 0.08 (-0.70)
 

Hip (cm) DG 127.37± 0.73 122.92± 0.75
a 

118.34± 0.73
b 

-9.03± 0.22 (-7.10)
†
 

Placebo 126.52± 0.82 126.34± 0.85
 

125.88± 0.84
 

-0.64± 0.21 (-0.51)
 

Body fat (%) DG 44.88± 0.58 42.32± 0.56
a 

40.15± 0.55
b 

-4.73± 0.11 (-10.68)
†
 

Placebo 44.28± 0.61 44.37± 0.60
 

44.08± 0.59
 

-0.20± 0.10 (-0.37)
 

 

a
p < 0.05 compared with placebo, adjusted for baseline 

b
p < 0.001 compared with placebo, adjusted for baseline 

†
p < 0.05 compared with baseline, intra-group analysis 

 

Compared to the placebo group, the Dyglomera® treatment group showed a significant average 

weight reduction of 11.15 kg (-11.33% of total body weight) (p < 0.001) after 8 weeks of 

treatment with Dyglomera®. The amount of weight loss achieved in the current study using 

Dyglomera® was higher than that obtained with whole, ground DG in a previous study[19]. This 

reduction in weight was accompanied by a loss of visceral fat as measured by waist 

circumference (-10.23%). In general, changes to BMI, waist and hip circumferences, and body 

fat paralleled the loss in weight. Similarly, blood pressure also decreased significantly in the 

Dyglomera® treatment group compared with the placebo group (p < 0.001)  (Table 2).   

 

Table 2. Effects of DG on blood pressure in obese subjects with metabolic syndrome 
 

Variable Group T0 T4 T8 Change from baseline     

(T8 - T0) (%) 

SBP (mm Hg) 
DG 143.93± 0.48 122.51± 1.07

b  
119.75± 0.92

b 
-24.18± 1.00 (-16.69)

†
 

Placebo 142.60± 0.54 142.92± 0.83
 

144.29± 0.95
 

1.69±0.83 (+1.22)
 

DBP (mm Hg) 
DG 93.43± 0.52 85.62± 0.6

b  
82.25± 0.69

b  
-11.18± 0.66 (-11.81)

†
 

Placebo 93.29± 0.54 94.77± 0.61
 

95.27± 0.68
 

1.99± 0.47 (2.19)
 

 

a
p < 0.05 compared with placebo, adjusted  for baseline 

b
p < 0.001 compared with placebo, adjusted for baseline  

†
p < 0.05 compared with baseline, intra-group analysis 

 

3.3. Blood parameters: As shown in Table 3, there were significant variations in the lipid profile 

from baseline to Week 8 of Dyglomera® treatment in TAG, TC, HDL and LDL concentrations.  

 



Functional Foods in Health and Disease 2013; 3(11):416-427                                                          Page 422 of 427 

Table 3. Effects of DG on blood glucose and lipid parameters in obese subjects with metabolic 

syndrome 
 

Variable Group T0 T4 T8 Change from baseline      

(T8 - T0) (%) 

Glucose 

(mg/dL) 

DG 110.25± 0.48 85.82± 0.82
a 

79.55± 0.51
b 

-30.70± 0.66 (-27.67)
 †
 

Placebo 108.99± 0.74 110.54± 0.68
 

111.75± 0.77
 

2.76± 0.59 (+2.72) 

TAG 

(mg/dL) 

DG 151.92± 3.01 46.80± 2.48
a 

44.01± 1.86
b
 -105.12± 3.54(-69.49)

 †
 

Placebo 150.79± 1.78
 
 156.11± 3.04

 
151.77± 2.39

 
0.98± 2.91 (+4.33)

 

TC 

(mg/dL) 

DG 219.57± 1.82 137.84± 2.73
b 

122.76± 3.36
b 

-96.82± 3.65 (-43.67)
 † 

Placebo 216.47± 3.26 217.91± 2.98
 

216.35± 3.16
 

-0.12± 1.88 (+0.63)
 

HDL 

(mg/dL) 

DG 37.68± 0.54 50.39± 1.58
a 

58.23± 1.07
b 

20.55± 0.84 (+55.52)
 † 

Placebo 27.24± 0.99 19.87± 1.09
 

24.92± 1.13
 

-2.32± 1.05 (+0.41)
 

LDL 

(mg/dL) 

DG 151.51± 1.96
 
 78.09± 3.02

a 
76.27± 3.44

b 
-75.23± 3.60 (-49.18)

 † 

Placebo 159.07± 3.26
 
 166.82± 3.12

  
161.07±3.39

  
2.00± 2.26

 
 (+1.61)

 

 

a
p < 0.05 compared with placebo, adjusted for baseline 

b
p < 0.001 compared with placebo, adjusted for baseline 

†
p < 0.05 compared with baseline, intra-group analysis 

 

These variations were significant compared with the placebo group (p < 0.001). There was also a 

significant reduction of blood glucose by 27.67% in the Dyglomera® group from baseline to 

Week 8 (p < 0.001) (Table 3). As shown in Table 4, the Dyglomera® group demonstrated 

significant reductions in insulin and insulin resistance (HOMA-IR) respectively by 10.38% and 

35.11%, CRP by 17.16%, PAI-1 by 39.61 % in response to the weight loss during the 

Dyglomera® supplementation from baseline to Week 8 (p < 0.001). Inverse to the change in 

body weight, adiponectin levels increased by 21.86% in the Dyglomera® group from baseline to 

Week 8. 
 

Table 4. Effects of DG on insulin resistance and circulating markers of inflammation and blood 

coagulation in obese subjects with metabolic syndrome 
 

Variable Group T0  T4 T8 Change from baseline (T8 

- T0) (%) 

Insulin (mIU/L) DG 13.01± 0.15 12.27± 0.13
a 

11.67± 0.15
a 

-1.34± 0.10 (-10.38)
 †
 

Placebo 13.80± 0.74 13.71± 0.17
 

13.66± 0.19
 

-0.15± 0.11 (-1.05) 

HOMA-IR 

(mmol/L×mU/L) 

DG 3.55± 0.04 2.60± 0.04
a 

2.30± 0.03
a
 -1.25± 0.03 (-35.11)

 †
 

Placebo 3.71± 0.05 3.74± 0.05
 

3.77± 0.06
 

0.06± 0.04 (+1.65)
 

Adiponectin 

(µg/mL) 

DG 5.80± 0.11 6.51± 0.14
 a 

7.08± 0.17
b 

1.28± 0.10 (21.86)
 † 

Placebo 5.48± 0.15 5.51± 0.19
 

5.54± 0.19
 

0.05± 0.11 (+0.40)
 

CRP (mg/L) DG 6.43± 0.14 5.80± 0.07
a 

5.10± 0.11
b 

-1.32± 0.14 (-17.16)
 † 

Placebo 6.12± 0.99 6.25± 0.21
 

6.07± 0.21
 

-0.05± 0.14 (-1.73)
 

PAI-1 (ng/L) DG 32.58± 0.22 26.25± 0.34
a 

19.81± 0.37
b 

-12.77± 0.26 (-39.61)
 † 

Placebo 33.14± 0.26 32.39± 0.28
 

32.31±0.28
 

-0.83± 0.09 (-2.52)
 

 

a
p < 0.05 compared with placebo, adjusted for baseline 

b
p < 0.001 compared with placebo, adjusted for baseline 

†
p < 0.05 compared with baseline, intra-group analysis 



Functional Foods in Health and Disease 2013; 3(11):416-427                                                          Page 423 of 427 

With regard to lipid profiles, this study confirms the strong hypolipidemic effects of 

Dyglomera® and suggests it could protect against MetS through reduced TC (mean = 96.82 

mg/dL (-43.67%)), reduced LDL (mean = 75.23 mg/dL (-49.18%)), reduced TAG (mean = 

105.12 mg/dL (-69.49%)) and increased HDL (mean = 20.55 mg/dL (+55.52%)).  

  

3.4. Correlation of select anthropometric changes with metabolic parameters and adipocytokines 

before and after weight loss.   

Pearson correlations between outcome variables are presented in Table 5 and they reveal that the 

change in BMI was significantly associated with changes in insulin, HDL, LDL, CRP, 

adiponectin, insulin and  PAI-1 levels (p <0.01). Similarly, waist circumference reduction was 

significantly associated with the all the above mentioned parameters except adiponectin. While 

there was no significant correlation between the adipocytokines adiponectin and PAI-1, 

increased HDL was positively correlated with adiponectin levels and was negatively correlated 

with other anthropometric and biochemical parameters. 

 

Table 5. Correlation between BMI, waist circumference, cholesterol and circulating markers of 

inflammation and coagulation in obese subjects with metabolic syndrome 
 

Correlations 

Parameters  BMI Waist HDL LDL CRP Adiponectin Insulin PAI-1 

BMI Pearson 

Correlation 
1 0.474

**
 -0.260

**
 0.351

**
 0.221

**
 -0.180

**
 0.160

**
 0.365

**
 

Sig. (2-tailed)  0.000 0.000 0.000 0.000 0.000 0.001 0.000 

Waist Pearson 

Correlation 
0.474

**
 1 -0.128

**
 0.092

*
 0.176

**
 -0.041 0.159

**
 0.307

**
 

Sig. (2-tailed) 0.000  0.006 0.048 0.000 0.378 0.001 0.000 

HDL-C Pearson 

Correlation 
-0.260

**
 -0.128

**
 1 -0.475

**
 -0.188

**
 0.184

**
 -0.135

**
 -0.402

**
 

Sig. (2-tailed) 0.000 0.006  0.000 0.000 0.000 0.004 0.000 

LDL-C Pearson 

Correlation 
0.351

**
 0.092

*
 -0.475

**
 1 0.246

**
 -0.225

**
 0.161

**
 0.501

**
 

Sig. (2-tailed) 0.000 0.048 0.000  0.000 0.000 0.000 0.000 

CRP Pearson 

Correlation 
0.221

**
 0.176

**
 -0.188

**
 0.246

**
 1 0.308

**
 0.552

**
 0.495

**
 

Sig. (2-tailed) 0.000 0.000 0.000 0.000  0.000 0.000 0.000 

Adiponectin Pearson 

Correlation 
-0.180

**
 -0.041 0.184

**
 -0.225

**
 0.308

**
 1 0.557

**
 0.001 

Sig. (2-tailed) 0.000 0.378 0.000 0.000 0.000  0.000 0.988 

Insulin Pearson 

Correlation 
0.160

**
 0.159

**
 -0.135

**
 0.161

**
 0.552

**
 0.557

**
 1 0.471

**
 

Sig. (2-tailed) 0.001 0.001 0.004 0.000 0.000 0.000  0.000 



Functional Foods in Health and Disease 2013; 3(11):416-427                                                          Page 424 of 427 

PAI-1 Pearson 

Correlation 
0.365

**
 0.307

**
 -0.402

**
 0.501

**
 0.495

**
 0.001 0.471

**
 1 

Sig. (2-tailed) 0.000 0.000 0.000 0.000 0.000 0.988 0.000  

 

** Correlation is significant at p < 0.01 (2-tailed). 

* Correlation is significant at p < 0.05 (2-tailed) 

 

4. DISCUSSION 

The purpose of this study was to evaluate the effects of an extract of DG (Dyglomera®) on 

anthropometric parameters, blood lipids, and other variables in obese patients with MetS. 

Because obesity results in increased visceral fat deposits that promote insulin resistance and 

inflammation through alteration of adipokine secretion, even modest reductions to weight and 

waist circumference are associated with favorable changes in serum adipocytokines [6].   

Compared to whole, ground powder [19], the extract (Dyglomera®)  induced a greater 

reduction in weight (11.15 kg vs. 7.67kg), BMI (4.13 kg/m
2
 vs. 3.00 kg/m

2
), abdominal 

circumference (10.72 cm vs. 7.17 cm), body fat (4.43 % vs. 3.20 %), systolic blood pressure 

(24.8 mm Hg vs. 13.09 mm Hg), and  fasting blood glucose (30.7 mg/dL vs. 28.91 mg/dL). 

Weight loss in overweight and obese individuals reduces mortality and morbidity, and is 

important in the treatment of obese patients. The current data suggest that weight loss per se 

leads to significant improvement in numerous cardiometabolic risk factors. In particular the 

Dyglomera®-treated subjects exhibited significant decreases in PAI-1, CRP, and fasting insulin 

levels. In addition, they showed a significant increase in adiponectin concentrations, an 

adipokine whose plasma concentrations correlate positively with insulin sensitivity, and levels of 

which are lower both in obese and type 2 diabetic patients than in lean, healthy individuals [26].  

Hypoadiponectinemia is independently associated with the development of obesity-related MetS, 

as well as insulin-resistant diabetes and atherosclerosis [27], and this relationship is stronger than 

that of any other inflammatory marker [28]. Mechanisms of action of Dyglomera® may include 

antioxidant activity and inhibition of LDL oxidation [17] as well as modulation of blood glucose 

and HbA1c levels [19], all of which may have contributed to the effects conferred by 

Dyglomera® treatment in the present study. 

Dyslipidemia is a component of MetS, which has an  underlying cause of altered 

metabolism of triglyceride-rich lipoproteins such as VLDL and IDL remnants [29,30].  Elevated 

TAG levels are also very common in both MetS and the general population [31].  The use of 

Dyglomera® by the general population could therefore have a preventive effect on dyslipidemia 

and MetS. Reducing LDL levels is generally considered a key factor in the management of 

cardiovascular risk because LDL particles are the main carriers of circulating cholesterol and 

play a key role in cholesterol transfer and metabolism [32]. The guidelines in the  Third Report 

of the National Cholesterol Education Program (Adult Treatment Panel III) (NCEP ATP III) 

focus on LDL levels as the primary target of cholesterol-lowering therapy [20].  Supplementation 

with Dyglomera® could therefore be a useful strategy to lower LDL levels.      

In summary, Dyglomera® reduces the weight and improves the atherogenic risk factors 

associated with MetS after 8 weeks of treatment. The effects in the current study, which focused 

on the extract of DG (Dyglomera®), appears to be stronger than those observed in previous 



Functional Foods in Health and Disease 2013; 3(11):416-427                                                          Page 425 of 427 

studies using whole, ground DG, thus conferring a superior anti-atherogenic capacity on 

Dyglomera®. 

 

Competing interests  

The authors declare that they have no competing interests. 

 

Authors’ Contributions 

Julius Oben conceived and coordinated the study, and prepared the manuscript. Ngondi Judith 

Laure co-designed and worked on the initial draft of the manuscript. Dieudonne Kuate carried 

out anthropometric measurements, analytical work, statistical analyses and prepared the draft of 

the manuscript. Blanche CO Etoundi  carried out anthropometric measurements, analytical work 

and processed results. All authors read and approved the final manuscript. 

 

REFERENCES: 

 

1. Centers for Disease Control and Prevention (CDC). Behavioral Risk Factor 

Surveillance System Survey Data. Atlanta, Georgia: U.S. Department of Health and 

Human Services, Centers for Disease Control and Prevention, 2010. 

2. Eckel RH, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet 2005; 365: 

1415–28. 

3. Ritchie SA, Connell JMC. The link between abdominal obesity, metabolic syndrome 

and  cardiovascular disease. Nutr Metabol Cardiovasc Dis 2007; 17:319-26. 

4. Kadowaki T, Yamauchi T, Kubota N, Hara K, Ueki K, Tobe K. Adiponectin and 

adiponectin receptors in insulin resistance, diabetes, and the metabolic syndrome. J 

Clin Invest 2006; 116:1784–92. 

5. Galiste M, Duarte J, Zarzuel A. Effects of dietary fibers on disturbances clustered in 

the metabolic syndrome. J Nutr Biochem 2008; 19:71–84. 

6. Valsamakis G, McTernan P, Chetty R, Al Daghri N, Field A, Hanif W, Barnett A, and 

Kumar S.  Modest weight loss and reduction in waist circumference after medical 

treatment are associated with favorable changes in serum adipocytokines. Metabolism 

2004; 53:430-34. 

7. National Task Force on the Prevention and Treatment of Obesity. Long term 

pharmacotherapy in the management of obesity.  JAMA 1996; 276:1907–15. 

8. Bray  GA, Blackburn  GL, Ferguson JM, Greenway FL, Jain AK, Mendel CM, 

Mendels J, Ryan DH, Schwartz SL, Scheinbaum ML, Seaton TB.  Sibutramine 

produces dose-related weight loss.  Obes Res Relat Metab Disord 1999 ; 7 :189–98. 

9. Sjöström L, Rissanen A, Andersen T, Boldrin M, Golay A, Koppeschaar HP, Krempf 

M.  for The European Multicentre Orlistat Study Group. Randomised placebo-

controlled trial of orlistat for weight loss and prevention of weight regain in obese 

patients   Lancet 1998 ; 352:167–72. 

10. Pari L, Umamaheswari J.  Antihyperglycaemic activity of Musa sapientum flowers: 

effect on lipid peroxidation in alloxan diabetic rats. Phytother Res 2000 ; 14:1-3. 

http://www.ncbi.nlm.nih.gov/pubmed?term=%22Bray%20GA%22%5BAuthor%5D
http://www.ncbi.nlm.nih.gov/pubmed?term=%22Blackburn%20GL%22%5BAuthor%5D


Functional Foods in Health and Disease 2013; 3(11):416-427                                                          Page 426 of 427 

11. Valiathan MS, Healing plants.  Current Science 1998 ; 75:1122–27. 

12. Tchiégang C, Mbougueng PD. Chemical composition of spices used in the cooking of 

nah poh and nkui of western Cameroon. Tropicultura  2005 ; 23:193–200. 

13. Roth LW, Keller F, U.S. Patent 3,089,817, 1963.  

14. Fankam AG, Kuete V, Voukeng IK, Kuiate JR, Pages JM. Antibacterial activities of 

selected Cameroonian spices and their synergistic effects with antibiotics against 

multidrug-resistant phenotypes. BMC Complementary and Alternative Medicine 2011; 

11:104. doi:10.1186 /1472-6882-11- 104.  

15. Atsang AKG, Dzeufiet DPD, Foyet HS, Nana P, Sokeng DS, Dimo T, Kamtchouing P. 

Analgesic and Anti-Inflammatory Activities of Dichrostachys glomerata (Forssk.) 

Hutch. Fruits Methanolic Extract in Rats. J Phys Pharm Adv 2012; 2(8): 269-276  

16. Kudi AC, Umoh JU, Eduvie LO, Gefu J. Screening of some Nigerian Medicinal plants 

for antibacterial activity. J Ethnopharm 1999; 67(2): 225-228. 

17. Kuate D, Etoundi BCO, Soukontoua YB, Ngondi JL, Oben JE.  Antioxidant 

characteristics of Dichrostachys glomerata spice extracts. CYTA-Journal of Food 

2010; 8:23–37. 

18. Kuate, D. Effects of some spices on glucose and lipid metabolism and oxidative stress. 

Ph.D. Thesis, University of Yaounde, Yaounde, Cameroon. 2010.  

19. Kuate D, Etoundi BC, Ngondi JL, Oben JE. Effects of Dichrostachys glomerata spice 

on cardiovascular diseases risk factors in normoglycemic and type 2 diabetic obese 

volunteers. Food Res Int 2011; 44:1197-02. 

20. Executive summary of the Third Report of the National Cholesterol Education 

Program (NCEP). Expert Panel on Detection, Evaluation, and Treatment of High 

Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA. 2001; 285:2486-97.  

21. Trinder P. determination of blood glucose using 4-amino- phenazone as oxygen 

acceptor. J Clin Pathol 1969; 22: 158-61. 

22. Richmond W. Preparation and properties of a cholesterol oxidase from Nocardia sp. 

and its application to the enzymatic assay of total cholesterol in serum Clin Chem 1973; 

19:1350–56.  

23. Bucolo G, David H. Quantitative determination of serum triglycerides by the use of 

enzymes.  Clin Chem 1973; 19:476–82. 

24. Bachorik PS, Wood PD, Albers JJ, Steiner P, Dempsey M, Kuba K, Karlsson L. 

Plasma high-density lipoprotein cholesterol concentrations determined after removal 

of other lipoproteins by heparin/manganese precipitation or by ultracentrifugation.  

Clin Chem 1976; 22: 1928–34. 

25. Friedewald WT, Levy RI, Fredrickson DS.  Estimation of the concentration of low-

density lipoprotein cholesterol in plasma, without use of the preparative 

ultracentrifuge. Clin Chem 1972; 18:499-02.  

26. Chandran M, Phillips SA, Ciaraldi T, Henry RR. Adiponectin: more than just another 

fat cell hormone?  Diabetes Care 2003; 26:2442–50. 



Functional Foods in Health and Disease 2013; 3(11):416-427                                                          Page 427 of 427 

27. Ouchi N, Kihara S, Arita Y,  Nishida M, Matsuyama A. Adipocyte-derived plasma 

protein, adiponectin, suppresses lipid accumulation and class A scavenger receptor 

expression in human monocyte-derived macrophages  Circulation 2001;103:1057-63. 

28. Matsushita K,  Ishikawa T, Sumita S, Kobayashi T, Ogawa H, Inoue N, Katsumi 

Matsumoto K.  Comparison of circulating adiponectin and proinflammatory markers 

regarding their association with metabolic syndrome in Japanese men.  Arterioscler 

Thromb Vasc Biol 2006 ; 26:871–6.  

29. Gazi I, Liberopoulos EN, Mikhailidis DP, Elisaf M. Metabolic Syndrome: Clinical 

Features Leading to Therapeutic Strategies. Vasc Dis Prev 2004; 1:243-53. 

30. Brunzell JD, Hokanson JE. Dyslipidemia of central obesity and insulin resistance. 

Diabetes Care 1999; 22:C10-C13. 

31. Liberopoulos EN, Daskalopoulou SS, Mikhailidis DP. Management of high 

triglycerides: What non specialists in lipids need to know.  Hell J Cardiol 2005; 

46:268-72. 

32. Bairaktari ET, Seferiadis KI, Elisaf  M. Evaluation of methods for the measurement of 

low-density lipoprotein cholesterol.  J Cardiovasc Pharmacol Therapeut 2005; 10:45-

54. 

 


