Acta Medica Mediterranea, 2016, 32: 1821
METABOLIC DISTURBANCES IN ABDOMINAL OBESITY
POP RALUCA*,**, ROMILA AURELIA***, ****, POP MARIAN*****, BACÂREA ANCA******
*
Medical Research Methodology Department, University of Medicine and Pharmacy Tirgu Mures - **Endocrinology Outpatient Clinic,
Emergency Mures County Hospital - 3Clinical Medical Department, Faculty of Medicine, University “Dunarea de Jos”, Galati, Romania
****
Clinical Geriatrics Department, Galati County Hospital Emergency - *****PhD student, University of Medicine and Pharmacy TirguMures - ******Pathophysiology Department, University of Medicine and Pharmacy Tirgu-Mures, Romania
ABSTRACT
Introduction: Increased waist circumference is an independent risk factor for cardio-vascular complications and mortality and
current studies focus on describing the factors involved in its etiology and pathogeny.
The objective of this study was to analyze all components of the metabolic syndrome in subjects with increased waist circumference, with the hypothesis that even in normal weighted apparently healthy subjects the metabolic profile is already modified.
Materials and methods: A cross-sectional study was conducted between February 2013 and April 2014. The sample consisted
of 266 consecutive patients presenting to the Endocrinology Outpatient Clinic of the Emergency Mures County Hospital for consultation who signed the informed consent. Inclusion criteria - waist circumference above 80cm for females and >94cm for males.
Exclusion criteria - secondary causes of increased abdominal circumference: pregnancy, generalized edema, endocrine causes:
untreated hypo- or hyperthyroidism, Cushing syndrome, medications that could lead to weight gain/loss, weight losing diet and refusal to participate. For all patients, height, weight, waist circumference and blood pressure were measured by the same person.
Venous blood samples were taken for determination of fasting blood glucose, triglycerides and HDL cholesterol. Microsoft Office
Excel was used for data collection and GraphPad Prism v. 5 for statistical analysis, with a level of significance α=0.05.
Results: Mean age of the sample was 51±12.7 years with a median of 53 years and a sex ratio F:M of 8.1:1. The normal weighted subjects had a high prevalence of associated disturbances (34.41% hypertriglyceridemia, 37.63% low HDL cholesterol,
29.03% increased blood glucose and 44.09% hypertension). Metabolically healthy obese represented 17.29% (n=46) of the sample.
When comparing the metabolically healthy subjects with abdominal obesity to the metabolically unhealthy subjects, the former are
younger (41.4 vs. 53.1 years, p<0.0001), thinner (BMI 28.7 vs. 32.5 kg/sqm, p<0.0001) and with significantly smaller differences of
the waist compared to the IDF cut-offs (11 vs. 20.2cm, p<0.0001).
Conclusions: Waist circumference is an important clinical parameter which correlates with all the elements of the metabolic
syndrome. Increased waist circumference should elicit metabolical evaluation and lifestyle modifications.
Keywords: waist circumference, metabolic disturbance, metabolically healthy obese.
DOI: 10.19193/0393-6384_2016_6_169
Received May 30, 2016; Accepted September 02, 2016
Introduction
Abdominal obesity, defined as increased waist
circumference according to the race, age and sex
specific references, leads to a higher cardio-vascular risk with better sensitivity than the general obesity(1). Various cut-offs have been used for defining
abdominal obesity, the most restrictive one being
that of the International Diabetes Federation
(IDF)(2).
Many factors are thought to be linked to
abdominal obesity, beginning with genetic factors(3),
lifestyle parameters, environment and level of education(4,5).
Studies have shown that abdominal obesity
alone is a risk factor for developing all other components of the metabolic syndrome (MetS), raising
the question whether it can be considered as an etiologic factor for the MetS(6). Various definitions are
available for the MetS, all of them having the
1822
increased waist circumference as a component(2,7-10).
The newest consensus on MetS definition recommends using population and country specific waist
circumference cut-offs(11).
Even in normal weighted subjects, increased
waist circumference is an independent risk factor,
leading to insulin resistance and all the other obesity related complications(12) (high blood glucose, low
high density lipoprotein (HDL) cholesterol, hypertriglyceridemia(13)). Moreover, the concept of “metabolically healthy obese”, defined as subjects with
obesity, who do not associate other metabolic disturbances has been the subject of recent studies,
aiming to define a genetic profile for this group(14).
The objective of this study was to analyze all
components of the metabolic syndrome in subjects
with increased waist circumference, with the
hypothesis that even in normal weighted apparently
healthy subjects, the metabolic profile is already
modified.
Materials and methods
A cross-sectional study was conducted in the
Endocrinology Outpatient Clinic of the Emergency
Mures County Hospital between February 2013 and
April 2014. The target population was represented
by subjects with abdominal obesity; the sample
consisted of 266 consecutive patients presenting to
the Endocrinology Outpatient Clinic for consultation who signed the informed consent. Inclusion
criteria - all consecutive subjects with abdominal
obesity according to the International Diabetes
Federation, above 80cm for females and >94 cm for
males. Exclusion criteria - pregnancy, generalized
edema, endocrine causes: untreated hypo or hyperthyroidism, Cushing syndrome, medications that
could lead to weight gain/loss, weight losing diet
and refusal to participate.
All patients were measured and weighted in
light clothes, with the same instruments by a single
person. Waist circumference was measured using a
measuring tape placed just above the upper margin
of the iliac crest. Blood pressure was measured
recumbent with a sphygmomanometer, and the
highest of three measurements was used. For subjects already diagnosed with hypertension, the maximum known blood pressure was recorded. Venous
blood samples were taken for determination of
metabolic parameters and were analyzed in the
same day using the automated analyzer COBAS
Integra 400 Plus.
Pop Raluca, Romila Aurelia et Al
The analyzed variables were: age (years), sex
(F/M), waist circumference (cm), the difference
between the measured waist circumference and the
corresponding cut-off (cm), body mass index (BMI,
kg/sqm), blood glucose (mg/dl), triglycerides
(mg/dl), HDL cholesterol (mg/dl) and blood pressure (mmHg). BMI was categorized according to
World Health Organization’s definitions in normal,
overweight and obesity grade I-III. Blood glucose
was considered normal at values below 100 mg/dl;
HDL cholesterol was considered normal at values
above 50 mg/dl for females and 40 mg/dl for
females; triglycerides were considered normal at
values below 150 mg/dl and systolic blood pressure
was considered normal at values below 140mmHg.
All subjects signed an informed consent and
the study was approved by the Hospital’s Ethics
Committee.
We used Microsoft Office Excel for the database and GraphPad Prism v. 5 for statistical analysis. Continuous categorical and binary variables
were used. We used Mann-Whitney, and KruskalWallis test for mean and median comparison,
Spearman coefficient for correlations, with a level
of significance α=0.05.
Results
The general characteristics of the sample are
presented in Table 1.
Sex (F:M)
249:36 (6.9:1)
Mean age (years)
48.3 ±16.1
Environment (U:R)
200:85 (2.3:1)
Normal BMI <25 kg/m2
n=33 (11.57%)
Overweight
n=98 (34.38%)
Grade I obesity
n=84 (29.47%)
Grade II obesity
n=43 (15.08%)
Grade III obesity
n=27 (9.47%)
Table 1: General characteristics of the study group.
When analyzing sex as a risk factor for metabolic dysfunctions, male subjects have higher probability of hypertriglyceridemia (RR=1.6, 95%CI
1.18-2.17, p=0.0164), impaired fasting glucose
(RR=1.8, 95%CI 1.32-2.47, p=0.0041) and hypertension (RR=1.43, 95%CI 1.17-1.74, p=0.0090),
but not low HDL cholesterol (RR=1.2, 95%CI 0.821.7, p=0.4301).
Metabolic disturbances in abdominal obesity
1823
The frequency of metabolic disturbances and
the percentage of subjects diagnosed and treated are
presented in Table 2, showing a high percentage of
newly diagnosed metabolic disturbances, the sole
exception being hypertension.
Metabolic disturbance
Frequency (n/%)
Percentage newly diagnosed
Hypertriglyceridemia
119 (41.7%)
47%
Low HDL cholesterol
150 (52.6%)
58%
High blood glucose
105 (36.8%)
55.20%
Hypertension
161 (56.5%)
21.10%
Figure 2: The metabolic disturbances’ frequency according to age, showing low, but non-negligible percentage
in the younger groups.
There is an increase in the frequency according to
age.
Waist circumference significantly correlates
with all the parameters analyzed (Table 4).
Table 2: Metabolic disturbances’ frequency in the sample.
Table 3 shows the metabolic disturbances’ frequency according to BMI, showing high percentages even for the subjects with normal BMI.
Subjects with abdominal obesity and normal
BMI had significantly better metabolic parameters.
Figure 1 shows the mean values of the metabolic
parameters according to BMI, showing a clear
ascending trendline.
Mean age
High TG % Low HDL (%) High glucose (%) HTA (%)
(years)
BMI
n
Normal
33
33.94
27.20%
45.40%
21.20%
21.20%
Overweight
98
46.53
33.60%
44.90%
27.50%
41.80%
Grade I obesity
84
51.51
41.60%
53.50%
38.10%
65.40%
Grade II obesity
43
51.56
55.80%
65.10%
44.20%
Grade III obesity
27
56.89
66.60%
66.60%
74.10%
Table 3: Metabolic disturbances according to BMI.
Parameter
Spearman coefficient
95% CI
p
Triglycerides
0.35
0.23-0.45
<0.001
HDL cholesterol
-0.27
-0.38 – (-0.15)
<0.001
Blood glucose
0.18
0.06 – 0.29
<0.001
Systolic blood
pressure
0.37
0.23 – 0.5
<0.001
BMI
0.82
0.78 – 0.85
<0.001
Table 4: Waist circumference correlation with the
metabolic parameters.
Metabolically healthy obese represented
17.29% (n=46) of the sample. When comparing
81.40%
the metabolically healthy subjects with abdomi85.20%
nal obesity to the metabolically unhealthy subjects, the former are younger (41.4 vs. 53.1
years, p<0.0001), thinner (BMI 28.7 vs. 32.5
kg/sqm, p<0.0001) and with significantly smaller
differences of the waist compared to the IDF cutoffs (11 vs. 20.2cm, p<0.0001).
Discussion
Figure 1: The mean values of the metabolic parameters
according to BMI, showing a clear ascending treadline.
We divided the sample in 6 age groups: under
30 years old (yo) (n=21), 31-40 yo (n=37), 41-50
yo (n=57), 51-60 yo (n=87), 61-70 yo (n=49) and
above 70 (n=15). Figure 2 shows the metabolic disturbances’ frequency according to age, showing
low, but non-negligible percentage in the younger
groups.
This study aimed to analyze the metabolic
parameters in subjects with abdominal obesity. The
results showed a high frequency of undiagnosed
metabolic disturbances in subjects with increased
waist circumference. The subjects included in the
study did not present for obesity as a chief complaint, therefore the metabolic dysfunctions were
newly diagnosed and elicited specific recommendations and treatment. This confirms the fact that
abdominal obesity should be considered as an individual risk factor and increased waist circumference should elicit metabolic evaluation even in the
absence of general obesity or other elements of the
1824
MetS, a fact recommended by a recent analysis of
Carmienke et al.(15). We chose the IDF criteria, given
the fact that is the most restrictive one and is recommended by the World Health Organization for
populational studies(16). We proved that waist circumference correlates well with all the metabolic
factors, confirming its central role in the definition
of the metabolic syndrome(2).
It is a well-established fact that metabolic syndrome’s prevalence increases with age(17,18), but the
important finding of this study was the high prevalence of metabolic disturbances in the young subjects. These results point to the need to increase
population awareness of the risk of abdominal obesity and its consequences and to focus on prevention methods, knowing this is one of the modifiable
risk factors(19).
Other studies have proved a higher frequency
of metabolic dysfunctions in females with increased
visceral fat(20), but we found that men have a higher
risk of metabolic dysfunction. The results might be
influenced by the small number of male subjects.
Another important issue analyzed is the profile
of the metabolically healthy obese. Extensive studies were conducted trying to describe the characteristics of this subgroup(14,21), which proved to have
lower risk of developing cardio-vascular complications and insulin resistance(22). Some studies proved
that these subjects develop the features of the metabolic syndrome in time, independently associated
with visceral fat accumulation, female sex, higher
fasting plasma insulin concentration, and lower
serum HDL associated cholesterol concentration(23).
Future longitudinal studies should be directed
towards identifying the factors involved in the progression from the metabolically healthy obese to
the unhealthy group(24).
Our study showed that subjects with isolated
abdominal obesity are younger, thinner and have a
smaller increase in the waist circumference.
The limitations of our study were the relative
small sample, the fact that subjects came from the
outpatient clinic and not the general population, and
the lack of evaluation of other factors involved in
abdominal obesity etiology (lifestyle parameters,
income, physical activity, etc.). Future directions
for research include a longitudinal study of the
metabolically healthy obese focused on the modifiable risk factors (sedentary lifestyle, diet, and exercise) in an attempt to postpone or even prevent the
progression towards metabolic syndrome.
Pop Raluca, Romila Aurelia et Al
Conclusions
Waist circumference is an important clinical
parameter which correlates with all the elements of
the metabolic syndrome. Increased waist circumference should elicit metabolic evaluation and lifestyle
modifications.
References
1)
2)
3)
4)
5)
6)
7)
8)
9)
10)
11)
Janssen I, Katzmarzyk PT, Ross R. Waist circumference
and not body mass index explains obesity-related
health risk. Am J Clin Nutr. 2004; 79(3): 379-84.
International
Diabetes
Federation.
http://www.idf.org/webdata/docs/IDF_Meta_def_final.
pdf. (Internet). 2006 (cited 2014 May 25). Available
from: http://www.idf.org/webdata/docs/
IDF_Meta_def_final.pdf.
Carey DG, Nguyen TV, Campbell LV, Chisholm DJ,
Kelly P. Genetic influences on central abdominal fat: a
twin study. Int J Obes Relat Metab Disord. 1996; 20(8):
722-6.
Roskam AJ, Kunst AE, Van Oyen H, Demarest S,
Klumbiene J, et al. Comparative appraisal of educational inequalities in overweight and obesity among
adults in 19 European countries. Int J Epidemiol. 2010;
39: 392-404.
Yu Y. Educational Differences in Obesity in the United
States: A Closer Look at the Trends. Obesity. 2011; 20:
904-8.
Grundy SM. Adipose tissue and metabolic syndrome:
too much, too little or neither. Eur J Clin Invest. 2015;
45(11): 1209-17.
Reaven GM. Banting lecture 1988. Role of insulin
resistance in human disease. Diabetes. 1988; 37(12):
1595-607.
Alberti KG, Zimmet PZ. Definition, diagnosis and
classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes
mellitus provisional report of a WHO consultation.
Diabet Med. 1998; 15(7): 539-53.
Balkau B, Charles MA. Comment on the provisional
report from the WHO consultation. European Group for
the Study of Insulin Resistance (EGIR). Diabet Med.
1999; 16(5): 442-3.
The National Cholesterol Education Program (NCEP)
Expert Panel. 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.
Alberti KG, Eckel RH, Grundy SM, Zimmet PZ,
Cleeman JI, Donato KA, Fruchart JC, James WP, Loria
CM, Smith SC. Harmonizing the metabolic syndrome:
a joint interim statement of the IDF Task Force on
Epidemiology and Prevention; NHLBI; AHA, World
Heart Federation; International Atherosclerosis
Society; and International Association for the Study of
Obesity. Circulation. 2009; 120: 1640-5.
Metabolic disturbances in abdominal obesity
12)
13)
14)
15)
16)
17)
18)
19)
20)
21)
22)
23)
24)
Phillips Catherine M., Christina Dillon, Janas M.
Harrington, Vera J. C. McCarthy, Patricia M. Kearney,
Anthony P. Fitzgerald, Ivan J. Perry. Defining
Metabolically Healthy Obesity: Role of Dietary and
Lifestyle Factors. PLoS One. 2013; 8(10): e76188.
Ruderman N, Chisholm D, Pi-Sunyer X, Schneider S.
The metabolically obese, normal-weight individual
revisited. Diabetes. 1998; 47(5): 699-713.
Berezina A, Belyaeva O, Berkovich O, et al.
Prevalence, Risk Factors, and Genetic Traits in
Metabolically Healthy and Unhealthy Obese
Individuals. BioMed Research International. 2015
548734.
Carmienke S., Freitag MH, Pischon T, Schlattmann P,
Fankhaenel T, Goebel H, Gensichen J. General and
abdominal obesity parameters and their combination in
relation to mortality: a systematic review and metaregression analysis. European Journal of Clinical
Nutrition. 2013; 67(10.1038/ejcn.2013.61): 573-585.
World Health Organization. Waist Circumference and
waist-hip ratio. Report of a WHO expert consultation.
Geneva 2011. 978 92 4 150149 1.
Rocha Fabiana Lucena, Nobre de Menezes Tarciana,
Lustosa Pimenteira de Melo Romulo, Figueroa Pedraza
Dixis. Correlation between indicators of abdominal
obesity and serum lipids in the elderly. Rev. Assoc.
Med. Bras. 2013; 59(1): 48-55.
Premanath M, H Basavanagowdappa, M Mahesh, M
Suresh. Correlation of abdominal adiposity with components of metabolic syndrome, anthropometric parameters and Insulin resistance, in obese and non obese,
diabetics and non diabetics: A cross sectional observational study. Indian Journal of Endocrinology and
Metabolism. 2014; 18(5): 676-682.
Zheng H, Tumin D, Qian Z. Obesity and mortality risk:
new findings from body mass index trajectories. Am J
Epidemiol. 2013; 178(11): 1591-9.
Berrin Demirbas, Gul Gursoy, Meltem Simsek, Remzi
Bahsi, Pinar Kosar, Behice Merve Usta. Visceral obesity may have different effects on metabolic syndrome
parameters in women and men. Acta Medica
Mediterranea. 2016; 32: 45.
Karelis A. D., Faraj M., Bastard J.-P., et al. The metabolically healthy but obese individual presents a favorable inflammation profile. The Journal of Clinical
Endocrinology and Metabolism. 2005; 90(7): 4145-50.
Hinnouho, G.M.; Czernichow, S.; Dugravot, A.; Nabi,
H.; Brunner, E.J.; Kivimaki, M.. Metabolically healthy
obesity and the risk of cardiovascular disease and type
2 diabetes: The Whitehall II cohort study. Eur. Heart J.
2015; 36: 551-9.
Hwang, Y.C.; Hayashi, T.; Fujimoto, W.Y.; Kahn, S.E.;
Leonetti, D.L.; McNeely, M.J. Visceral abdominal fat
accumulation predicts the conversion of metabolically
healthy obese subjects to an unhealthy phenotype. Int.
J. Obes. 2015; 39: 1365-70.
Munoz-Garach A, Cornejo-Pareja I, Tinahones F. Does
Metabolically Healthy Obesity Exist? Nutrients. 2016
E320.
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Acknowledgement
This project was supported in part by University of Medicine
and Pharmacy of Tirgu Mures through Internal Research Grant
5/23.12.2014
_______
Corresponding author
AURELIA ROMILA
Clinical Medical Department, Faculty of Medicine, University
“Dunarea de Jos”, Galati, Romania
Romani, Galati, no 1, Vadu Sacalelor Street, bl. Pescarus, ap. 8
(Romania)