A study from South India - European Journal of Biotechnology and

European Journal of Biotechnology and Bioscience 2014; 2 (4): 59-62
University, Karnataka, India.
ISSN: 2321-9122
www.biosciencejournals.com
EJBB 2014; 2 (4): 59-62
Received: 23-09-2014
Accepted: 05-10-2014
Priyanka N Pawaskar
Department of Physiology,
Center for Basic Sciences,
Kasturba Medical College,
Bejai, Mangalore, Manipal
University, Karnataka, India.
Arun. S
Department of General
Medicine, Kasturba Medical
College, Mangalore, Manipal
University, Karnataka, India.
Kavana G.V
Department of Physiology,
AJIMS, Mangalore,
Karnataka, India.
Nayanatara Ak
Department of Physiology,
Center for Basic Sciences,
Kasturba Medical College,
Bejai, Mangalore, Manipal
University, Karnataka, India.
Anupama N
Department of Physiology,
Center for Basic Sciences,
Kasturba Medical College,
Bejai, Mangalore, Manipal
University, Karnataka, India.
Ramesh Bhat
Department of Physiology,
Center for Basic Sciences,
Kasturba Medical College,
Bejai, Mangalore, Manipal
University, Karnataka, India.
Correspondence:
Arun. S
Department of General
Medicine, Kasturba Medical
College, Mangalore, Manipal
2. Materials and Method
Association of anthropometric indices of obesity with
dyslipidemia: A study from South India
Priyanka N Pawaskar, Arun. S, Kavana G.V, Nayanatara Ak, Anupama
N, Ramesh Bhat
Abstract
Anthropometry is a simple reliable method for quantifying body size and proportions. The present
study was aimed to study the association of selected established anthropometric indices of obesity such
as waist circumference (WC), waist-hip ratio (WHR) and body mass index (BMI) with dyslipidemia in
the population residing in south India. Hundred healthy subjects within the age group of 25 and 60
years were selected from out-patients setting in a teaching hospital. Anthropometric data and serum
lipid profile were analysed. Based on anthropometric parameters and the lipid profile the subjects were
grouped into obese and non-obese groups. Data obtained was statistically analysed. The raised values
of WC, WHR and BMI were highly significant (p<0.001) in obese group compared to non-obese
group. Based on the present results we conclude that WC was more sensitive for predicting altered lipid
profile and WHR is a prime factor to predict occurrence of dyslipidaemia. Routine health examination
will enhance obesity related evaluation of cardio vascular risk factors.
Keywords: serum lipid profile, waist circumference, waist-hip ratio, Body mass index, dyslipidemia
1. Introduction
In the modern era, obesity has emerged as a ‘global epidemic’. It has affected both developed
and developing nations with same intensity, India being no exception. National family health
survey reports shows that 14.8% women and 12.1% men are obese in India [1]. Today, in the
presence of limited physical exertion and improper regulation of food intake, humans have
increased adipose energy stores resulting in susceptibility to various diseases [2 , 3]
Obesity is a complex, multi-factorial, chronic condition that is associated with mortality and
significant morbidity and is prevalent worldwide [4, 5]. Imbalance of body fat in terms of its
quantity and distribution is observed in obesity. Dyslipidemias are disorders of lipoprotein
metabolism, including lipoprotein overproduction and deficiency [6]. In many communities
there is a general increasing trend in dyslipidemia with increasing obesity [7, 8, 9]. Obesity and
dyslipidemia appear to develop from an interaction which involves the integration of social,
behavioral, cultural, physiological, metabolic, and genetic factors [10, 11]. BMI has been
extensively used in clinical practice to screen obesity [12]. Pattern of body fat distribution is
an important determinant of disease risk [13]. Multicompartment models and dual-energy Xray absorptiometry are all reliable methods to obtain accurate measurement of total body fat
[14]
. However, due to the inferior cost effectiveness of such modalities compared to time honored anthropometric techniques, the former methods are not practical for routine clinical
use. Using simple, noninvasive, anthropometric methods, diagnosing obesity as a possible
predictor of dyslipidemia is expected to be helpful in efforts to prevent, diagnose early, and
control both mortality and morbidity. Further, identifying the best anthropometric index in
any population is essential to predict chronic disease risk factor and to facilitate enhanced
screening for disease risk factors. There is lack of representative data regarding the
anthropometric profile of south Indians and their association with, dyslipidemia. Hence, the
present study intends to compare the ability of simple, non–invasive techniques applicable in
field practices in predicting approximately the lipid levels in the body, thus, preventing the
future health hazards.
This study was a hospital-based cross sectional analytical
~ 59 ~ European Journal of Biotechnology and Bioscience
study conducted in a study population comprising of healthy
individuals aged between 25 years and 60 years attending the
out-patient department at a teaching, tertiary care Hospital in
south India. Informed written consent was obtained from all
participants, and the experiment protocol was approved by
Ethics committee of the college. Subjects were then enrolled
considering the exclusion criteria of presence of history of
dyslipidemia, hypertension, diabetes mellitus, malignancy or
any other major chronic illness, use of lipid lowering agents,
and / or other drug delivery system , family history of lipid
related disorders as well as critically ill patients presenting
with medical emergencies like myocardial infarction,
hyperglycemia, ascites or pregnancy were excluded from the
study to avoid bias due to distorted anthropometric indices.
Thus, this study included a total of 100 cardio –metabolically
healthy males & females with the help of self - structured
questionnaire. WC was measured, in cm, midway between
the lower costal margin and iliac crest during the endexpiratory phase, with a non- elastic tape. Hip circumference
was measured, in cm, at the level of the greater trochanters,
with the person standing and relaxed muscles. WHR was
defined as the WC divided by the hip circumference. Body
weight and height were measured without shoes, using an
electronic measuring scale. BMI was calculated as weight in
kg divided by height in m2 (Quetlet’s Index) [15]. 5 ml venous
blood was collected from each subject after an overnight fast
of 12-14 hours. Serum was separated within one hour of the
blood collection and stored at -200C until analyzed for lipid
profile. Serum samples were analyzed for lipid profile
estimations, using Roche/ Hitachi auto analyzer [16, 17, 18]. The
cutoff levels for obesity were as follows WC > 80 cm and 90
cm for males and females, respectively, WHR > 0.9 for
males and 0.8 for females, respectively, and BMI > 23
kg/m2, according to WHO standards for South Asian
population. Subjects were then classified into obese and nonobese groups. Based on the ATP III classification,
dyslipidaemia was defined as TC > 200 mg/dl, TG > 150
mg/dl, HDL < 40 mg/dl, and LDL > 100 mg/dl, and the
subjects were categorized as obese and non – obese
depending on their respective lipid values. Individuals with 2
or more deranged lipid values were considered obese.
the self - structured questionnaire our cross - sectional study
included a total of randomly selected apparently healthy 58
males and 42 females. Mean age of all 100 subjects was
43.11 ± 9.98 years. In present study, based on WC 68% of
study population were categorized in obese group and 32%
as non obese group. On basis of WHR 61% of subjects were
grouped as obese and 39% as non - obese. Further, 54% of
subjects were grouped under obese category and 46% as non
- obese based on BMI values (Fig 1). Anthropometric indices
and serum lipid profile values showed a significant (p<0.001)
increase in obese group when compared to non-obese group
(Table 2). Of all the 68 obese subjects, WC has correctly
identified 59 subjects as obese with abnormal serum lipid
profile (table 3). Further, based on percent sensitivity and
specificity of anthropometric parameters in predicting
dyslipidaemia WC was more sensitive in terms of diagnostic
accuracy, i.e. correctly identified the obese with
dyslipidaemia, (65.5% ) and WHR showed higher positive
predictive value considering the diagnostic power, i.e. ability
to correctly predict occurrence of dyslipidaemia (PPV % 88.5%) in healthy study subjects (table 4).
Fig 1: Percentage distribution of obese and Non –obese group based
on waist circumference, waist hip ratio and body mass index.
Table 1: Anthropometric indices and serum lipid profile in obese
and non - obese group; values expressed as Mean ±SD.
Parameters
Waist circumference (cm)
Waist Hip Ratio
BMI (kg/ m2)
Total Cholesterol
Triglycerides
HDL
LDL
2.1 statistical Analysis
All statistical tests were conducted using SPSS version 16.
Significance value was taken as ‘p’ < 0.001 or ‘p’ < 0.05.
Sensitivities and specificities of anthropometric indices were
compared.
3. Results
Considering all inclusion and exclusion criteria and based on
Obese group
94.71 ± 7.24
0.94 ± 0.07
27.71 ± 2.1
248.36 ±28.65
255.91 ± 32.22
33.19 ± 6.23
134.55 ± 12.61
* - p<0.001; obese versus non obese group
Table 2: Anthropometric Indices and serum Lipid Values; n - number of subjects
N
WC
WHR
BMI
68
61
54
Obese
Abnormal
Normal
Lipid profile
Lipid profile
59
9
53
7
46
8
n
32
39
46
Non – obese
Abnormal
Normal
Lipid profile
Lipid profile
28
4
34
6
41
5
Table 3: Percent Sensitivity and specificity of anthropometric parameters in predicting dyslipidaemia
~ 60 ~ Non – Obese
79.29 ± 8.21*
0.80 ± 0.05*
22.50 ± 2.3*
174.33 ± 24.00*
104.00 ± 28.42*
44.05 ± 3.06*
81.8 ± 9.11*
European Journal of Biotechnology and Bioscience
WC (cm)
65.5
40.77
82.4
13.7
Sensitivity
Specificity
Positive predictive value %
Negative predictive value %
4. Discussion
Dyslipidemia is an independent and modifiable risk factor
for cardiovascular diseases [19]. Prevalence of dyslipidaemia
in recent years might be probably due to westernization of
diet and transitions in wealth and lifestyle. Obesity poses a
significant health threat to individuals and places a major
burden on health care system. Obesity is associated with
endothelial dysfunction, greater arterial stiffness [20] and
insulin tolerance. Early detection of obesity by simple and
reliable methods can help reverse or reduce these untoward
effects. Anthropometric measurements are surrogate
measures of body fat and are better predictors of
dyslipidemia. They require no sophisticated equipment,
lengthy procedures and are cost-effective. Literature survey
shows that anthropometric index varies according to study
design, geographic area and characteristics of the study
population [21, 22].
WC, WHR and BMI are good indicators for body fatness and
central fat distribution. In our study, anthropometric
measures of obesity were significantly correlated with
prevalence of dyslipidemia. The association of dyslipidemia
with obesity observed in this study is in accordance with
previous research reports [21, 22]. Further, WC more accurately
predicted deranged lipid profile and WHR has rightly
projected obese subjects with dyslipidaemia. Studies with
computed tomography sections have disclosed the fact of
nearer relationship between dyslipidemia and WC [22, 23, 24].
An increased WC is most likely associated with elevated risk
factors because of its relation with visceral fat accumulation,
mechanism may involve excess exposure of the liver to fatty
acids [25].
Waist circumference (WC) has been recommended as a
better indicator of abnormal fat content in the body than
BMI. This has also been validated by the Quebec Health
Survey done by Lemeui et al. [26]. The inability of BMI to
correctly predict deranged lipid profile is in agreement with
another broad based study done by Shamai et al. [27]. BMI
does not take into account proportion of weight related to
increased muscle mass, bone weight or visceral organ mass.
Individuals with a similar BMI can vary considerably in their
abdominal fat mass by virtue of these factors. And hence,
with same BMI can have varied range of serum lipid profile.
Our study observed that compared with BMI, WC and WHR
are good indicators for body fatness in adults at the
population level and as well provide additional information
about central fat distribution. This is in agreement with the
studies of Xu C et al. and the fieldwork done by Feldstein et
al. in the Chinese and Argentine populations, respectively
and thus validates that WC is a better predictor of
dyslipidaemia than WHR, WHtR and BMI [28, 29]. Identifying
early dyslipidaemia can help in instituting corrective
measures to reduce disease burden. Raised values of WC
and WHR might be useful as relatively in - expensive firststage screening tools to detect dyslipidaemia. Routine health
examination will enhance obesity related evaluation of
WHR
60.1
46.15
88.5
14.4
BMI (kg/ m 2)
52.9
38.15
83.8
12.19
cardiovascular risk factors and thus, in prevention of future
health hazards. Present study concluded that WC is a more
sensitive and a reliable predictor while WHR is a more
specific anthropometric index in predicting dyslipidaemia
among healthy individuals. Incorporating these into routine
health examination will enhance obesity related evaluation of
cardio vascular risk factors and thus, in prevention of future
untoward health hazards. We suggest using preferably WC as
an inexpensive and easy method in clinical and
epidemiological fields. The main limitation of this study is
that we were not able to adjust for the physical activity level,
dietary food intake and socioeconomic status of participants:
Further studies therefore need to be conducted on a large
population.
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