170
INDIAN J MED RES, APRIL 2003
Indian J Med Res 117, April 2003, pp 170-179
Receiver operating characteristics curve analysis of body fat
& body mass index in dyslipidaemic Asian Indians
A. Misra, R.M. Pandey*, S. Sinha, R. Guleria, V. Sridhar & V. Dudeja
Departments of Medicine & *Biostatistics, All India Institute of Medical Sciences, New Delhi, India
Received November 12, 2002
Background & objectives: Optimal limit of body mass index (BMI) for Asian Indians remains to be
defined. In this study, we describe the anthropometric and lipid profiles and determine the appropriate
cut-offs of BMI for defining obesity in dyslipidaemic patients.
Methods: Correlations were carried out between lipid profile and anthropometric variables in 217
dyslipidaemic Asian Indians and the data were compared to those of 123 healthy historical controls.
Receiver operating characteristics (ROC) curve analysis was carried out to determine the appropriate
cut-offs of BMI for defining obesity taking the percentage of body fat (% BF) as the standard.
Results: Dyslipidaemic patients had high waist-hip ratio (W-HR) and percentage of BF. The prevalence
of obesity as measured by percentage of BF was significantly (P<0.05) higher as compared to obesity
defined by the BMI cut-off. W-HR was the most important independent predictor (odds ratio: 2.8;
95% Cl: 1.02-7.83) of atherogenic dyslipidaemia on multivariate logistic regression analysis. On ROC
curve analysis the suggested appropriate cut-offs of BMI were; males 24.0 kg/m2 (sensitivity, 74.7%,
and specificity, 79.7%), and females 23.0 kg /m2 (sensitivity, 85.7% and specificity, 62.5%). According
to the suggested lower limits of BMI, an additional 15 per cent dyslipidaemic patients will be diagnosed
as obese.
Interpretation & conclusion: The observations in dyslipidaemic Asian Indians suggest high prevalence
rates of generalized and abdominal obesity, and that high values of W-HR alone predisposes to
atherogenic dyslipidaemia. Further, obesity may be optimally defined by a lower cut-off of BMI. The
revised criteria for the BMI-based diagnosis of obesity will lead to a more rational management of
dyslipidaemia in Asian Indians.
Key words Asian Indian - hyperlipidaemia - obesity - percentage body fat - receiver operating characteristics (ROC)
curve - skinfolds - waist-hip ratio
Asian Indians are commonly dyslipidaemic and
are predisposed to develop accelerated
atherosclerosis1 . Besides elevated levels of total
cholesterol (TC) and low-density lipoprotein
cholesterol (LDL-C), high levels of serum
triglycerides (TG) and low levels of high-density
lipoprotein cholesterol (HDL-C) add to the
atherogenic risk. Such a profile of dyslipidaemia
commonly accompanies obesity and insulin
resistance. Asian Indians have a characteristic
obesity phenotype, consisting of relatively lower
body mass index (BMI), excess body fat, abdominal
and truncal adiposity, and less lean tissue 2-4. Excess
body fat and lesser amount of lean tissue
170
MISRA et al : ROC CURVE ANALYSIS IN DYSLIPIDAEMIC ASIAN INDIANS
complement each other in volume and weight so
that the value of BMI does not increase. However,
there might be differences in this phenotype between
immigrant and native Asian Indians. Further, the
phenotype will also depend upon the level of
acculturation, socio-economic status, dietary habits,
activity profile, and geographical location of the
subjects with in India.
BMI is an imperfect measure of obesity as it is
calculated by combined estimates of fat, bone,
muscles and body water5. Therefore, variations in
any of these four constituents due to pathological or
physiological perturbations would alter the value of
BMI. In Asian Indians, the relative contribution of
fat is more and muscle is decreased; therefore,
theoretically BMI would not accurately assess
obesity6. Studies have demonstrated the unreliability
of BMI in predicting obesity 6-10 , particularly in
Asian Indians 6,10. In such a situation, body fat would
constitute the only true measure of obesity.
Assessment of obesity would be further jeopardized
in metabolic diseases such as type 2 diabetes
mellitus and dyslipidaemia where more alterations
of body composition are seen. Moreover, it is
extremely important to accurately diagnose obesity
in diabetic and/or dyslipidaemic patients for correct
application of lifestyle measures and drug therapy.
High values of simple body measurements like BMI
and waist-hip ratio (W-HR) identify subjects with
an increased metabolic risk11,12, however, such
assumptions and the definitions of cut-offs of each
parameter are based on the data from the Caucasian
populations 13,14. Therefore, we hypothesized that the
current cut-off of BMI does not denote the true
measure of obesity in non-diabetic dyslipidaemic
Asian Indians when the percentage body fat (%BF)
is used as the reference standard. Moreover, there is
a paucity of data on the anthropometric profile and
its correlations with various lipid parameters of
dyslipidaemic patients of all ethnic groups
particularly Asian Indians. Specifically, body fat as
a measure of obesity has not been previously
evaluated in the dyslipidaemic subjects. Further,
comparative anthropometric data of dyslipidaemic
patients and healthy subjects are not available.
In this study, therefore, we have described the
anthropometric parameters, percentage of BF and
171
lipid profiles of dyslipidaemic patients and compared
them to the historical healthy controls. Finally, based
on the ROC curve analysis, we have proposed a
revised cut-off of BMI for non-diabetic
dyslipidaemic Asian Indians.
Material & Methods
The study was carried out from 1996 to December
2000, at the Department of Medicine, All India
Institute of Medical Sciences, New Delhi, a tertiary
referral teaching and research medical center in
northern India. Ambulatory patients diagnosed as
having dyslipidaemia were included based on
the following; TC > 5.2 mmol/l (200 mg/dl), serum
TG > 2.36 mmol/l (200 mg/dl), and/or
HDL-C<0.91mmol/l (35 mg/dl). The hyperlipidaemic
patients were referred to the research clinic from the
medical out patients department, and departments of
cardiology, dermatology and gastroenterology. The
high lipid levels were confirmed again in the
research laboratory. Consecutive hyperlipidaemic
patients attending the research clinic were recruited
for the study, unless excluded by exclusion criteria
such as acute illnesses, end-organ failure, acute
myocardial infarction and pregnancy. Patients were
interviewed, examined, and investigated obtaining
informed consent. The same clinician performed
clinical
examination
and
anthropometric
measurements.
Anthropometric measurements : Height (to the
nearest 0.1 cm) and body weight (to the nearest
0.1 kg) were recorded without shoes while allowing
only light indoor clothes. BMI was calculated by
using the formula weight (kg)/height (m)2. Waist
circumference (WC) was measured midway between
the iliac crest and the lowermost margins of the ribs.
Hip circumference was measured at the maximum
circumference of the buttocks. Mean of three
readings of each measurement was taken for the
calculation of W-HR. Biceps, triceps, subscapular
and suprailiac skinfolds were measured to the nearest
1 mm on the right side of the body using Lange
skinfolds calipers (Beta Technology Inc, USA). A
mean of three readings was recorded at each site of
measurement. Biceps and triceps skinfolds were
measured at the level of nipple line and midway
172
INDIAN J MED RES, APRIL 2003
between the acromion process of the scapula and
the olecranon process respectively. Skinfolds at the
inferior angle of the scapula and at the iliac crest
superiorly in the mid-axillary line were measured
for subscapular and supra-iliac skinfolds. Ratio of
subscapular and triceps skinfolds (SS-TR ratio),
peripheral skinfolds (sum of biceps and triceps
skinfolds) and central skinfolds (sum of subscapular
and suprailiac skinfolds) were calculated. A standard
equation15 validated for Asian Indians 16 was used
for calculation of body fat (BF) from the sum of
skinfolds at 4 sites (sigma 4SF).
Biochemical investigations: Blood samples were
obtained after 12 h overnight fast. An oral glucose
tolerance test was performed according to the
standard criteria 17 . Patients diagnosed to have
impaired glucose tolerance or diabetes mellitus were
excluded from the study. Estimations of blood
glucose, TC, TG and HDL-C levels were performed
according to the methods described earlier 18-20 .
Value of LDL-C was calculated using Freidewald’s
equation21 . Non-HDL cholesterol was calculated by
deducting the value of HDL-C from the value of
TC.
Definitions: Obesity was defined by using twin
criteria, first by BMI as >25kg/m2 as defined by the
World Health Organization14 , and by percentage of
BF as >25 per cent in males and >30 per cent in
females22. High WC was defined as >102 cm in men
and > 88 cm in women23. High W-HR was defined
as >0.95 in males and >0.80 in females24. These
criteria of generalized and abdominal obesity have
been derived from the data of Caucasian populations.
Sigma 4SF was defined as high when the value
exceeded 50mm4 . Atherogenic dyslipidaemia as a
test group was defined when a patient had the
following lipid parameters; a combination of
TG>2.36 mmol/l (200mg/dl) and HDL-C<0.91mmol/
l (35 mg/dl); or HDL<0.91mmol/l (35 mg/dl) only.
Any other type of dyslipidaemia was labelled as
control dyslipidaemia.
Statistical analysis: After confirming the
approximate normality, descriptive statistics for
anthropometric and biochemical parameters were
computed by arithmetic mean and standard
deviation. Z-test/Student’s ‘t’ test as appropriate was
applied to determine the level of statistical
significance of mean difference among male and
female subjects. Percentage of BF was considered
as the reference standard for the ROC curve analysis
of BMI for males and females for various
anthropometric and biochemical parameters.
Bivariate and multivariate logistic regression
analysis was performed to assess the strength
of association as measured by odds ratio and
95 per cent confidence intervals (CI) between
various anthropometric variables as the potential
predictors of atherogenic dyslipidaemia (outcome
variable). STATA 7.0 intercooled version software
(STATA Corp., Houston, Texas, USA) was used for
statistical analysis. All the statistical tests used for
analysis were two-tailed. In this study, P-value <
0.05 was considered as statistically significant.
Results
The data of 217 dyslipidaemic patients were
analysed. Mean age of males (n=157) was
38.7±13.2 yr (range 18-82 yr) while it was
41.9±12.0 yr (range 15-58 yr) for females (n=60).
Fifty one (32.5%) males and none of the females
were smokers. Comparative statistics were carried
out with data in healthy non-diabetic urban Asian
Indian subjects (123 healthy subjects, 86 males,
age range: 18-75 yr, and 37 females, age range:
20-69 yr) studied earlier in the same center by the
same research team4 .
Among dyslipidaemic subjects, 37 (24.2%) males
and one female consumed alcohol on a regular basis.
Definite history of cerebrovascular accidents and
coronary heart disease (CHD) was available in one
male each, and none and one female, respectively.
No subject reported symptoms of peripheral vascular
disease. Hypertension was equally prevalent in males
[32 (21.1%)] and females [14 (23.3%)].
Anthropometric profile and body fat analysis of
dyslipidaemic patients : Mean BMI of females
(26.9±4.8 kg/m2) was higher than males (24.0±4.8
kg/m2 ) (P<0.001), while mean values of WC, and
waist-height ratio were statistically comparable in
both genders. Values of biceps skinfolds (P<0.001),
triceps skinfolds (P<0.001), subscapular skinfolds
MISRA et al : ROC CURVE ANALYSIS IN DYSLIPIDAEMIC ASIAN INDIANS
(P<0.01), sigma 4 SF (P<0.001), and percentage of
BF (P<0.001) were significantly higher in females
(Table I). However, SS/TR ratio, and central to
peripheral skinfolds ratio were higher in men as
compared to women (P<0.001). High values of WC
were recorded in 44.4 per cent of males and in 7.0
per cent of females (P<0.001). Based on BMI, 39.5
per cent males and 66.7 per cent females were
defined as obese (P<0.01) while using percentage of
BF as criteria of obesity, 54.6 per cent males and
86.4 per cent females were categorized as obese
(P<0.001). Importantly, prevalence of patients with
obesity was significantly (P<0.05) higher when
determined by per cent BF as compared to those
categorized based on BMI. BF/BMI ratio, a relative
index of body fat and BMI, was higher in females as
compared to males (P<0.001).
Biochemical profile: There were no significant
differences in the mean values of fasting blood
glucose, serum TG, TC, LDL-C, non-HDL
cholesterol, and HDL-C between male and female
dyslipidaemic patients (Table II). High mean
values of TC and TG were recorded in 86.6 and
173
38.2 per cent of males and 90.3 and 27.2 per cent of
females, respectively. Further, 13.3 per cent males
and 8.3 per cent females had low levels of HDL-C
alone. A combination of high levels of TG and low
levels of HDL-C was observed in 3.8 per cent males
and 1.6 per cent females. Finally, a combination of
high levels of TC and TG was observed in 28 per
cent males and 13 per cent females.
Data were analyzed combining surrogate markers
of abdominal obesity and abnormal lipid variables.
A combination of high values of serum TG and WC
was observed in 34.3 per cent males and 23.3 per
cent of females. Similarly, high values of serum TG
and W-HR were recorded in 34.4 per cent males and
23.3 per cent females. Further, 1.9 per cent males
and 6.9 per cent females had high values of serum
TG, WC and W-HR.
Data were also analysed for patients having high
values of TC and surrogate markers of abdominal
obesity. High values of serum TC and WC were
observed in 78.3 per cent males and 80.0 per cent of
females respectively. Likewise, high values of serum
Table I. Anthropometric profile of dyslipidaemic patients
Anthropometric variable
Males
Females
n
n
(kg/m2 )
157
24.0±4.7
60
Waist circumference (cm)
142
84.5±12.5
54
83.9±12.5
Biceps skinfolds (mm)
Triceps skinfolds (mm)
152
152
9.8±8.3
15.3±10.4
59
59
17.3±8.4**
23.6±10.5**
Subscapular skinfolds (mm)
152
21.4±10.5
59
26.0±10.5*
Suprailiac skin folds (mm)
Sigma 4SF (mm)
152
152
28.9±11.9
72.0±35.9
59
59
30.8±11.9
98.1±36.2**
Central skinfolds (mm)
152
45.7±21.1
59
56.9±21.2**
Peripheral skinfolds (mm)
Central: peripheral skinfolds ratio
152
152
25.9±17.5
2.1±0.7
59
59
41±17.6**
1.5±0.7**
Subscapular: triceps skinfolds ratio
152
1.6±0.6
59
1.2±0.6**
% Body fat
Waist circumference (cm):
Hip (cm) ratio
152
143
25.8±7.5
0.53±0.35
59
54
37.9±7.5**
0.54±0.35
% Body fat/BMI ratio
152
1.07±0.25
57
1.43±0.30**
Body mass index
26.9±4.8**
All values are mean±SD; *P<0.01, **P<0.001 compared to males, Peripheral skinfolds: sum of biceps and triceps skinfolds, Central
skinfolds: Sum of subscapular and suprailiac skinfolds, Sigma 4SF: Sum of four skinfolds
174
INDIAN J MED RES, APRIL 2003
percentage of BF revealed 56.6 per cent sensitivity
(95%Cl: 45.2 - 67.5) and 85.5 per cent specificity
(95%Cl: 74.9 - 92.8) for males and 71.7 per cent
sensitivity (95% Cl: 58.8 - 84.7) and 54.5 per cent
specificity (95% Cl: 39.5 - 69.5) for females
(Table III, Fig.). However, when the cut-off for
obesity in males was lowered to BMI >24 kg/m2
(proposed), sensitivity increased substantially
specificity decreased marginally, overall
misclassification decreased, positive predictive value
increased and negative predictive value decreased
compared to BMI > 25 kg/m2. When the proposed
limit of BMI to diagnose obesity in females was
lowered to >23 kg/m2; sensitivity, specificity, and
positive predictive value increased and overall
misclassification and negative predictive value
decreased. It is important to note that additional 15.6
per cent males and 15 per cent of females would be
diagnosed as obese in case BMI limits are lowered
as suggested.
Table II. Biochemical profile of dyslipidaemic patients
Biochemical variable
Males
(n=157)
Females
(n=60)
Fasting blood glucose (mmol/l)
4.7±1.5
5.0±2.3
Total cholesterol (mmol/l)
6.1±1.5
6.2±1.4
Serum triglycerides (mmol/l)
2.2±1.5
1.9±0.9
LDL-C (mmol/l)
4.2±1.5
4.1±1.6
Non-HDL-cholesterol (mmol/l)
5.1±1.6
5.2±1.4
HDL-C (mmol/l)
1.0±0.3
1.0±0.1
LDL-C: HDL-C ratio
3.8±4.3
4.0±12.2
Total cholesterol: HDL-C ratio
5.8±4.5
6.0±10.9
All values are mean±SD, LDL-C, Low-density lipoprotein
cholesterol, HDL-C, High-density lipoprotein cholesterol.
The mean differences in biochemical parameters in males and
females were statistically not significant (P>0.05)
TC and W-HR were recorded in 78.3 per cent males
and 80.0 per cent females respectively. On Pearson’s
correlation coefficient analysis, anthropometric
parameters, anthropometric ratios, and percentage of
BF correlated to the fasting blood glucose; (r=0.27,
P< 0.05 in males) only, and not to the lipid variables.
ROC curve analysis: ROC curve for the conventional
cut-off of BMI >25 kg/m2 against reference of
Comparison of anthropometric profile of
dyslipidaemic patients with healthy subjects :
Comparative statistics with data in healthy nondiabetic urban Asian Indian subjects studied earlier4
in the same center by the same research team using
similar research instruments are given in Table IV.
It must be noted, however, that the time period for
conducting the two studies were different (January
Table III. Test characteristics (95% Cl) of body mass index as a measure of obesity using percentage of body fat as the reference
Males
Females
Conventional
Proposed
Conventional
Proposed
BMI >25 kg/m2
BMI>24 kg/m2
BMI >25kg/m2
BMI>23kg/m2
Sensitivity
56.6
(45.2-67.5)
74.7
(65.4-84.0)
71.7
(58.8-84.7)
85.7
(75.9-95.5)
Specificity
85.5
(74.9-92.8)
79.7
(71.1-88.3)
54.5
(39.5-69.5)
62.5
(49.0-76.0)
Positive predictive
value
82.4
(70.1-91.2)
81.6
(73.2-89.9)
86.8
(76.0-97.6)
93.3
(84.3-100.3)
Negative predictive
value
62.1
(51.6-71.9)
72.4
(62.7-82.0)
33.3
(11.8-54.6)
26.3
(14.0-38.6)
Overall
misclassification
30.2
(23.0-38.2)
23.0
(14.0-32.1)
31.5
(19.5-43.4)
17.5
(6.9-28.1)
Test characteristics (%):
Obesity (Standard): Males: per cent body fat > 25 per cent, Females: percentage of body fat > 30 per cent
MISRA et al : ROC CURVE ANALYSIS IN DYSLIPIDAEMIC ASIAN INDIANS
175
Fig. Receiver operating characteristics curve showing optimal sensitivity and specificity of cut-offs of
body mass index as measures of obesity in males and females using percentage of body fat as standard
reference in dyslipidaemic Asian Indians.
Table IV. Comparison of anthropometric parameters between dyslipidaemic patients and healthy controls 4
Anthropometric
parameter
Males
_______________________________________
Dyslipidaemic
Healthy
patients
controlsa
(n= 157)
(n=86)
Body mass index (BMI)
(kg /m2 )
Waist circumference
(cm)
Waist- hip ratio
Skinfold thickness (mm)
Biceps
Triceps
Subscapular
Suprailiac
Sigma 4 SF
Central skinfolds
24.0±4.7*** (157)
21.4±3.7
26.9±4.7*** (60)
23.3±5.5
84.5±12.5* (143)
79.6±11.4
83.9±12.5*
(57)
77.4±12.6
0.6±0.1
0.8±0.5
(51)
0.8±0.1
8.3±5.8
14.6±7.8
18.0 ±8.8
21.3±10.6
63.1±30.2
40.2±18.5
17.4±8.3*
23.6±10.5
26.0±10.6
30.7±11.9**
98.0 ±36.1*
56.8±21.2*
(59)
(59)
(59)
(59)
(59)
(59)
14.0±6.6
22.1±6.7
23.4±8.5
24.6±7
84.0±24.4
48±14.1
0.9±0.5
(142)
9.8±8.3 (152)
15.3±10.4 (152)
21.3±10.5 (152)
28.2±11.8*** (l 52)
72.0±35.9* (152)
45.7±21.1* (152)
Females
____________________________________
Dyslipidaemic
Healthy
Patients
controls a
(n=60)
(n=37)
Peripheral skinfolds
25.2±17.5 (152)
23±13.2
41.0±17.6 (59)
36.0±12.2
Central: peripheral
2.1±0.7* (152)
1.9±0.4
1.5+0.7
(59)
1.3±0.3
skinfolds ratio
Subscapular: triceps
1.2±0.6*** (152)
1.3±0.4
1.2±0.6
(59)
1.1±0.3
skinfolds ratio
Per cent Body fat (BF)
25.8±7.5*** (152)
21.5±6.1
37.9±7.5*
(59)
35±4.3
Per cent BF/BMI ratio
1.1±0.5 (152)
0.98±0.02
1.4+0.3
1.52±0.03
*Data from reference 4, All values are mean± SD, *P<0.05, **<0.01,***<0.001 compared to healthy controls, Peripheral skinfolds: sum
of biceps and triceps skinfolds, Central skinfolds: Sum of subscapular and suprailiac skinfolds, Sigma 4SF: Sum of four skinfolds
176
INDIAN J MED RES, APRIL 2003
to December 1999 for healthy subjects)4 . BMI for
healthy males was 21.4±3.7 kg/m2 and for healthy
females 23.3±5.5 kg/m2. Percentage BF was
21.3±7.6 for healthy males and 35.4±5.0 for females.
Mean values of BMI were higher in dyslipidaemic
males (P<0.001) and females (P<0.01) as compared
to the healthy subjects. Significantly higher mean
values of other variables in dyslipidaemic subjects
were; WC (P<0.05 in both genders), suprailiac
skinfolds (P<0.001 in males and P<0.01 in females),
sigma 4SF (P<0.05 in both genders), central
skinfolds (P<0.05 in both genders), centralperipheral skinfolds ratio (P<0.05 in males and
P=NS in females), and percentage of BF (P<0.001
in males and P<0.05 in females). Mean value of
biceps skinfolds was higher in dyslipidaemic females
when compared to normal females (P<0.05), and
value of SS/TR ratio was higher in dyslipidaemic
males (P<0.001). Further, percentage prevalences of
subjects with the following abnormal variables were
significantly more in the dyslipidaemic subjects;
BMI >25 kg/m2 (males, P<0.01, females, P<0.05),
high WC (females P<0.05), W-HR (females
P<0.001), and high percentage of BF (males
P<0.001).
Table V. Anthropometric profile (mean±SD) of subjects in
atherogenic dyslipidaemia group and control dyslipidaemia
groups
Anthropometric
parameters
n
Control
dyslipidaemia
n
Atherogenic
dyslipidaemia
126
51
83.6±12.7
84.3±13.0
17
3
87.7±10.9
88.3±12.3
123
51
0.9±0.1
0.8±0.2
19
2
0.9±.06
0.8±.03
131
21
25.1±7.2
37.9±7.6
54
5
30.2±7.2**
38.2±5.9
131
54
68.9±32.1
98.7±45.3
21
5
87.3±28.1*
104.9±41.9
WC (cm):
Males
Females
Waist-hip ratio:
Males
Females
Per cent Body fat:
Males
Females
Sigma 4 SF:
Males
Females
*P<0.05, **P<0.01 compared to control dyslipidaemia.
Antherogenic dyslipidaemia group: Dyslipidaemic patients with
serum triglycerides>2.36mmol/l and high-density lipoprotein
cholesterol <0.91mmol/L; or high-density lipoprotein cholesterol
<0.91mmol/L, *Control dyslipidaemia group: Patients having
dyslipidaemic profile other than above, WC, Waist
circumference, Sigma 4 SF, sum of four skinfolds
Table VI. Results of bivariate and stepwise multivariate logistic regression analysis of anthropometric parameters with atherogenic/
control dyslipidaemia as outcome variables
Anthropometric
parameters
Control
dyslipidaemia
group (%)
Atherogenic
dyslipidaemia
group (%)
Statistical
significance
Unadjusted
OR
(95% Cl)
Adjusted
OR
(95% Cl)
101 (52.9)
90 (47.1)
14 (53.8)
12 (46.7)
χ2=0.01,
P= NS
1.0
0.9 (0.4-2.2)
—
Body mass index
Non-obese
Obese
WC
Normal
147 (83.0)
16 (80.0)
χ2=0.11,
1.0
—
High
30 (17.0)
4 (20.0)
P=NS
1.2 (0.4-3.9)
Waist-hip ratio
Normal
97 (56.4)
6 (28.6)
χ2=5.82,
1.0
1.0
High
75 (43.6)
15 (71.4)
P<0.05
3.2 (1.2-8.7)
2.8(l.0-7.8)
% Body fat
Non-obese
72 (63.7)
5 (13.2)
χ2=3.81,
1.0
—
Obese
113 (36.3)
21 (81.8)
P=NS
2.6 (0.9-7.4)
NS: Statistically not significant (P>0.05), Atherogenic dyslipidaemia group: Dyslipidaemic patients with serum triglycerides
>2.36mmol/l and high-density lipoprotein cholesterol <0.91mmol/l; or high-density lipoprotein cholesterol <0.91 mmol/l, Control
dyslipidaemia group: Patients having dyslipidaemic profile other than above; WC, Waist circumference
MISRA et al : ROC CURVE ANALYSIS IN DYSLIPIDAEMIC ASIAN INDIANS
Anthropometric profile of subjects in the atherogenic
dyslipidaemia group vs. other dyslipidaemic
patients: Mean values of per cent BF and sigma 4
SF in males were significantly higher in the
atherogenic dyslipidaemia group as compared to
control dyslipidaemia group (Table V). Further,
when these anthropometric parameters were
dichotomized into obese and non-obese as per the
conventional cut-offs, W-HR, and percentage of BF
were positively associated with the atherogenic
dyslipidaemia. When these variables were
simultaneously considered in multivariate logistic
regression model, W-HR emerged as the single most
important independent predictor of atherogenic
dyslipidaemia. A dyslipidaemic male/female having
high W-HR, with normal BMI, normal WC and
normal percentage of BF would have almost three
times greater risk of having atherogenic
dyslipidaemia as compared to a male/female subject
with normal values of W-HR, BMI, WC and
percentage of BF (Table VI).
Discussion
Comparison of anthropometric parameters
between non-diabetic dyslipidaemic patients of the
current study and non-diabetic healthy controls from
the same population4 showed that the dyslipidaemic
subjects had higher BMI, percentage of BF and WC.
Of note, BMI and percentage of BF were 12.6 per
cent and 20.2 per cent higher in dyslipidaemic male
patients, and 15.4 per cent and 8.3 per cent higher in
dyslipidaemic females, respectively as compared to
healthy subjects. Hence, when they became
dyslipidaemic, males gained comparatively more
body fat as compared to the increase in BMI, and
females had more increase in the BMI as compared
to gain in body fat. Further, it appears that abdominal
obesity became more pronounced in dyslipidaemic
females, and truncal obesity and to some extent
abdominal obesity in dyslipidaemic males.
Prognostic information of the cardiovascular risk
could be usefully obtained by combining values of
anthropometry and lipid levels. According to a recent
study25 excess serum TG and WC levels suggested
the metabolic syndrome denoted by hyperinsulinaemia, hyperapolipoprotein B, and small,
dense LDL and increased risk of CHD. Of concern,
177
in the current study, is the observed combination of
high values of TG and WC in about 34 per cent
males and 23 per cent of the females having
dyslipidaemia indicating that about one third of
dyslipidaemic subjects would be at a substantial risk
for CHD. Further, we noted that about 80 per cent
of dyslipidaemic patients had abdominal obesity and
high levels of TC. Theoretically the latter
combination of abnormalities would also become the
cause of high risk for CHD, though the exact
magnitude of risk has not been investigated.
High levels of TG and low levels of HDL-C
characterize the dyslipidaemia of insulin resistance
syndrome 26 , frequently observed in Asian
Indians 27,28. A combination of these abnormalities,
or low levels of HDL-C alone, termed as atherogenic
dyslipidaemia analysed in the study showed that a
high value of W-HR alone, even when other
parameters such as percentage of BF and BMI were
normal, increased the risk of atherogenic
dyslipidaemia three-fold. This observation is of
particular importance indicating that the high W-HR
could be metabolically detrimental even if a person
is non-obese and has normal WC. It must be noted,
however, that the cut-offs for WC and W-HR used
in the study are those taken from the data of
Caucasian populations 23,24. In particular, the cut-off
for WC is probably unsuitable for Asian Indians,
since the circumference of the waist is relatively
larger in the Caucasians population because of a
larger body frame and more lean mass.
As observed earlier in normal healthy non-diabetic
Asian Indians 4, the discrepancy between the two
measures for diagnosis of obesity was also observed
in the current study, higher numbers of obese
patients were diagnosed using percentage of BF cutoff as the defining criteria. On lowering the limits
of BMI the optimal sensitivity and predictive values
were obtained for both the genders, and additional
15 per cent more subjects could be defined as obese.
Consistent with these data, others10,29 have also
shown poor sensitivity and specificity of BMI for
diagnosis of obesity in the Asian ethnic groups using
ROC curve analysis Deurenberg-Yap et al10
suggested that for the diagnosis of obesity (using
reference of BMI of 30 kg/m2) limits of BMI need
178
INDIAN J MED RES, APRIL 2003
to be lowered to 27 kg/m2 for Malays and Chinese
and 26 kg/m2 for Asian Indians. These investigators
included apparently normal subjects in difference to
the our study. Taking cognizance of such data the
World Health Organization and International Obesity
Task Force have suggested lowering the limits of
BMI for the diagnosis of overweight and obesity to
23 kg/m2 and 25 kg/m2 respectively 14,30. We suggest
different BMI limits for Asian Indian males and
females, no such action has been previously
proposed. We have also proposed lower limit of BMI
to define obesity in type 2 diabetes mellitus based
on the ROC curve analysis 31 .
lifestyle measures to reduce body weight or more
specifically body fat below the newly defined limits.
Acknowledgment
Authors acknowledge Shri Ramesh Giri for supervising the
study, the staff of Clinical Pharmacology, Department of
Medicine, All India Institute of Medical Sciences, New Delhi,
including Shri Inder Taneja, Shri Gian Chand, Smt. Alice Jacob
for performing various blood investigations and Shri R.L. Taneja
for performing quality control of various biochemical tests.
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Reprint requests : Dr Anoop Misra, Professor, Department of Medicine, All India Institute of Medical Sciences
Ansari Nagar, New Delhi 110029, India
e-mail: [email protected]