CORRELATION BETWEEN DIFFERENT DEGREES OF OBESITY AND NON- SPECIFIC LOW BACK PAIN

Document Type : Original Article

Abstract

ABSTRACT
Background: Obesity is recognized as a major public health problem
and it is associated with various musculoskeletal disorders, including
impairment of the spine and osteoarthritis. Objective: to investigate the
correlation between different degrees of obesity and non-specific low
back pain as well as the mechanical factors that may affect this
correlation. Methodology: Ninety obese females suffering from nonspecific
low back pain participated in this study; their ages ranged from
20 to 45 years. Subjects were subdivided into three groups according to
their BMI, thirty patients in each group. Group A, B and C represent
grade I, II and III obesity respectively. Outcome measures were
performed through spinal mouse that measure lumbar lordotic angle and
spinal mobility and also through Visual analogue scale and Oswestery
Disability index to detect pain severity and functional disability. Results:
There was moderate positive significant correlation between BMI, VAS,
ODI and lumbar mobility during extension, while there was moderate
negative significant correlation between BMI and LLA as well as lumbar
mobility during flexion. Conclusion: Different degrees of obesity
correlate with non-specific low back pain as well as the mechanical
factors that may affect this correlation.

Highlights

CONCLUSION:
Based on the results of the present study we can conclude that
Different degrees of obesity correlate with non-specific low
back pain as well as the mechanical factors that may affect this
correlation.
RECOMMENDATION
A similar study should be conducted on a large number
of patients to provide a wide representation of the population

Keywords

Main Subjects


CORRELATION BETWEEN DIFFERENT DEGREES
OF OBESITY AND NON- SPECIFIC LOW BACK PAIN
Ghady Y. Mohammed*; Fatma S. Amin** and Yasser M. Aneis***
* Demonstrator of Physical Therapy for Basic science department, faculty of Physical
Therapy, Deraya University
** Professor of Physical Therapy for Basic science department, Faculty of Physical
Therapy, Cairo University;
*** Assistant Professor of Physical Therapy for Basic science department, Faculty of
Physical Therapy, Cairo University.
Key Words: Obesity, Nonspecific low back pain, Spinal Mouse,
Lumbar mobility.
ABSTRACT
Background: Obesity is recognized as a major public health problem
and it is associated with various musculoskeletal disorders, including
impairment of the spine and osteoarthritis. Objective: to investigate the
correlation between different degrees of obesity and non-specific low
back pain as well as the mechanical factors that may affect this
correlation. Methodology: Ninety obese females suffering from nonspecific
low back pain participated in this study; their ages ranged from
20 to 45 years. Subjects were subdivided into three groups according to
their BMI, thirty patients in each group. Group A, B and C represent
grade I, II and III obesity respectively. Outcome measures were
performed through spinal mouse that measure lumbar lordotic angle and
spinal mobility and also through Visual analogue scale and Oswestery
Disability index to detect pain severity and functional disability. Results:
There was moderate positive significant correlation between BMI, VAS,
ODI and lumbar mobility during extension, while there was moderate
negative significant correlation between BMI and LLA as well as lumbar
mobility during flexion. Conclusion: Different degrees of obesity
correlate with non-specific low back pain as well as the mechanical
factors that may affect this correlation.
INTRODUCTION
Obesity is nowadays a pandemic condition. Obese subjects are
commonly characterized by musculoskeletal disorders and particularly by
non-specific chronic low back pain (cLBP). However, the relationship
between obesity and cLBP remains to date unsupported by an objective
measurement of the mechanical behavior of the spine and its morphology
in obese subjects. Such analysis may provide a deeper understanding of
the relationships between function of the spine in flexion, extension and
Egypt. J. of Appl. Sci., 35 (7) 2020 84-99
lateral bending and the onset of clinical symptoms (Vismara et al.,
2010).
Also, there is lack of quantitative data regarding spinal mobility
in obese subjects suffering from LBP (Shiri et al., 2010 a) and
researchers identified wide variation among studies in the frequency and
severity characterization of low back pain (Shiri et al., 2010 b).
Additionally, the analysis of the changes of spinal curvatures and
movements is very important as it reflects the complex interaction
between the anatomical and the muscular factors involved in this process
(Singer et al., 1990). However, measurement of these curves with x-ray
method for large sample, is not economical. In addition, there is a greater
awareness of the hazards and dangers of radiation exposure associated
with repeated radiographic evaluations. For these reasons, attempts are
being made to develop skin-surface devices such as Spinal Mouse (SM)
for use in examining the progression and treatment response of various
spinal disorders (Emmanuelle et al., 2011) as SM showed high testretest
reliability for evaluation of spinal curvatures and deformation in
both sagittal and the frontal planes in patients with low back problems
(Topalidou et al., 2014).
So, the aim of this research was
To investigate the correlation between different degrees of obesity and
non-specific low back pain as well as the mechanical factors that may
affect this correlation.
MATERIALS AND METHODS:
Design of the Study:
The study design was across-sectional study.
Subjects:
Ninety obese females with non-specific low back pain
participated in this study. They were recruited from outpatient clinics of
the Faculty of Physical Therapy, Deraya University; to be participants in
this research. They were subdivided into three groups according to their
BMI, thirty patients in each group. Group A with grade I obesity, Group
B with grade II obesity; and Group C with grade III obesity. The Ethics
Committee for scientific research of the Faculty of Physical Therapy,
Cairo University was approved this research (No: P.T.REC/012/002479).
All subjects signed a consent form prior to the beginning of assessment
for ethical issues. Subjects recruited based on the following inclusion and
exclusion criteria:
Inclusive criteria:
1) Age of participants range from 20-45 years old (Koes et al., 2006).
1) Obese females with non-specific low back pain.
2) Waist circumference (abdominal obesity) was equal or more than 80
cm for women (Valery et al., 2009).
85 Egypt. J. of Appl. Sci., 35 (7) 2020
3) BMI of participants was more than 30 kg/ m2, (also classified as
Grade 1 ranging from30 to 34.9, Grade 2 ranging from 35 to 39.9,
and Grade 3 more than 40) (WHO, 2016).
4) Subjects not receive any medication or diet management of obesity
throughout the study.
Exclusive criteria:
Subjects were excluded from the study if they have previous
spinal surgery, spinal cord injury or unstable neurological signs,
congenital postural deformities, cauda equine symptoms related to the
spine including changes in bowel and bladder control and females during
pregnancy.
Instrumentation:
(A)Evaluation instrumentation:
1. Standard Weight Scale (SWS) & A stadiometer
The standard medical weight scale was used to measure the weight
in kilogram and a stadiometer to measure height in meter to calculate
body mass index (BMI) of each subjects by dividing weight of subject
per kilogram on her height square per meter (Ndubuisi et al., 2016).
2. Tape Measurement
It’s a flexible form of ruler. It consists of plastic strip with linearmeasurement
markings. It is a common tool of measurement
(Aird, 1999).Tape measurement used to evaluate waist circumference
which can be a predictable for central obesity where visceral adipose
tissue is stored and hip circumferance is considered to be a separate
measurement of body size that may represent other aspects of fat
distribution (Kathrine et al., 2013).
3. Spinal Mouse Idiag M360 pro (SM):
Is a measuring device aided by an electronic computer which
measure range of motion of the spine and evaluates the spinal angle and
shape in the sagittal and frontal planes. The procedure is a non-invasive
method. The Spinal Mouse's reliability was investigated and showed high
test-retest reliability for evaluation of spinal curvatures, deformation,
spinal mobility and the position of the body in both the sagittal and the
frontal planes in patients with back or low back problems (Topalidou et
al., 2014).
4. Visual Analogue Scale (VAS):
A visual analogue scale is 100 mm horizontal line with verbal
descriptors expressing the severity of the pain sensation at each end.
Patients label the point on the line that more represent the severity of
their symptoms, since the following pain VAS cut points were
recommended: no pain (0–4 mm), mild pain (5–44 mm), moderate pain
(45–74 mm), and severe pain (75– 100 mm) (Funke, 2004).The VAS is a
Egypt. J. of Appl. Sci., 35 (7) 2020 86
widely used pain intensity assessment tool in rehab, proving to be
accurate and valid (Crossley et al., 2004).
5. Oswestry low back pain disability questionnaire (ODI):
ODI is one of several scales developed for patients with low back
pain to functionally assess daily activities. This scale was validated in
different languages including Arabic version (Vogler et al., 2008).It
consisted of 10 items; each item contains 6 levels of answers which can
be scored from 0 to 5. Such items are: pain, personal care, lifting objects,
walking, sitting, and standing, sleep disturbances induced by low back
pain, sexual and social life and travel (Algarni et al., 2014).
Evaluation Procedures:
1. Body mass index (BMI):
The weights of each subject were obtained using standard weighting
scale and heights were measured using astadiometer after removal of the
shoes, with light clothing. This equation was used for calculating body
mass index: BMI = weight per kg/ height per m2 (WHO, 2011).
2.Waist Circumference Measurement (WC):
At the end of normal expiration, WC (cm) was measured with
the patient in standing position and the measuring tape positioned at the
level of the lower floating rib (Dobbelsteyn et al., 2001).
3. Hip Circumference Measurement (HC):
HC was measured in centimeter with the patient in standing
position by applying a plastic tape over light clothes at the widest width
of the hip across the greater trochanters (WHO, 2011).
4. Waist Hip Ratio (WHR):
WHR is the WC to HC ratio that used for abdominal obesity
evaluation. For females, central obesity is classified as WHR greater than
0.85 (WHO, 2011).Sometimes the WHR appears to be a better measure
for central obesity than BMI or waist circumference, particularly among
old age people (Srikanthan et al., 2009).
5. Lumbar lordotic angle (LLA):
Values for lumbar lordosis were obtained by using a spinal mouse
(SM) that was shown to be accurate for sagittal plane evaluation of the
spine (Mannion et al., 2004 and Miyazaki et al., 2010). Participants
were instructed to remove their shirts and leave bras unhooked to allow
access to paraspinal region. The spinous process of C7 and second sacral
tubercle was marked with an eyeliner pencil. The spine scan was
performed with bare foot or wearing socks. Participants were asked to
look at a vertical column of numbers and gaze at the number at eye
height until the scan was completed (Russell et al., 2012).
6. Lumbar mobility:
The SM which measures spinal inter-segmental angles in a safely
manner also used to measure lumbar mobility in sagittal plane. The SM
87 Egypt. J. of Appl. Sci., 35 (7) 2020
went along the spinal column from C7 to S3. The participants were
instructed to take 3 consecutive positions; erect, maximal flexion and
maximal spine extension. A measurement was performed in each
position. For flexion, participants were told to touch toes with their
fingertips , keeping knees straight and their feet about 30 cm apart. For
extension, participants were instructed to extend their back as they can,
with no assistance (Post et al., 2004).
7. Pain severity:
Participants were asked about their lower back pain that
represented on a visual analog scale of pain. The answer was graded as 0
(without pain) to 10 (extreme pain possible); with mild pain being 0–3,
moderate pain being 4–6, and severe pain being 7–10 (Alexandre et al.,
2019).
7. Functional disability:
Participants were questioned about how back pain affects
ability to manage everyday life. Total score of ODI is determined by sum
all scores of applied items, dividing this score by total score (50) and
multiplying it by (100) to get the score percentage (Dobbelsteyn et al.,
2001). The score ranging from 0 percent (no disability) to 100 percent
(full disability). The scale was interpreted according to: from 0 to 20
percent: minimal disability; from 20 to 40 percent moderate disability;
from 40 to 60 percent severe disability; from 60 to 80 percent crippling
low back pain and beyond percent the person is confined to bed
(Fairbank et al.,1980).
Statistical analysis:
(1)Descriptive statistics in the form of Mean, standard deviation and
median of {demographic and clinical data} and frequencies and
percentage of categorical variables.
(2)ANOVA was carried out to compare LLA, mobility in flexion and
extension between the three groups and followed by tukeys post
hoc test to identify the significant difference between groups.
(3) Kruskal-Wallis test was conducted for comparison of the median
values of ODI and VAS between the three groups and followed
by Mann–Whitney U test to identify the significant difference
between groups.
(4)Pearson Correlation Coefficient was conducted to determine the
correlation between BMI, LLA, mobility in flexion and extension,
ODI and VAS.
(5)Simple linear regression was conducted to produce a prediction
model for the values of LLA, mobility in flexion and extension,
ODI and VAS from BMI.
Egypt. J. of Appl. Sci., 35 (7) 2020 88
The significance level for all statistical tests was set at p <
0.05and all statistical measurements were performed through the
statistical package for social sciences (SPSS) version 25 for windows.
RESULTS
Demographic data of Participants:
1. General characteristics of the subjects:
No significant difference was found between groups A, B and C
in age (F = 0.12, p = 0.88), hip circumference (F = 2.13, p = 0.12) and
WHR (F = 3.03, p = 0.054). While there was a significant difference
between groups in weight (F = 83.41, p = 0.0001), height (F = 4.3, p =
0.01), BMI (F = 300.38, p = 0.0001) and waist circumference (F = 14.76,
p = 0.0001) as in (Table1).
Table 1. Descriptive statistics of the participants:
Variables
Total
sample
(N = 90)
Group
A (N =
30)
Group
B (N =
30)
Group
C (N =
30)
Comparison between group
A, B and C
 ±SD 
±SD

±SD

±SD
F- value p- value Sig
Age (years)
31.48 ±
8.42
31.3 ±
8.35
31.06 ±
9.05
32.1 ±
8.1
0.12 0.88 NS
Weight (kg)
90.73 ±
12.6
79.15 ±
5.54
89.16 ±
6.38
103.9
± 9.78
83.41 0.0001 S
Height (cm)
156.53
± 5.11
158.33
± 4.82
156.66
± 4.77
154.6
± 5.2
4.3 0.01 S
BMI (kg/m²)
37.1 ±
5.24
31.53 ±
1.24
36.36 ±
1.48
43.41
± 2.63
300.38 0.0001 S
Waist
circumference
(cm)
103.03
± 11.56
97.8 ±
8.37
100.2 ±
9.23
111.1
±
12.28
14.76 0.0001 S
Hip
circumference
(cm)
112.63
± 11.42
110.66
± 10.07
111.13
± 9.55
116.1
±
13.74
2.13 0.12 NS
WHR
0.91 ±
0.12
0.88 ±
0.09
0.9 ±
0.08
0.96 ±
0.17
3.03 0.054 NS
 :
Mean
SD: Standard
Deviation
p value: Probability
value
S:
Significant
NS: Non
significant
Non-significant difference in WHR between groups means the
whole sample were homogenous regarding body fat distribution and
obesity type. I.e. type of obesity whether android or gynoid so the type of
obesity is not a confounding factor.
2. Comparison between the three groups (A, B and C):
The three groups A, B and C differed significantly in the
severity of non-specific low back pain, functional disability ,lumbar
curve changes and mobility in flexion and extension (p = 0.0001), (p =
0.01),(p= 0.02) ,(p = 0.01) and (p = 0.0001) respectively (Table 2).
89 Egypt. J. of Appl. Sci., 35 (7) 2020
Table 2. Severity of non-specific low back pain (VAS), Functional
disability (ODI), lumbar curve abnormality and mobility
abnormality in flexion and extension of the study group.
Pain severity
Total sample
(N = 90)
Group A (N = 30) Group B (N = 30) Group C (N = 30)
N (%) N (%) N (%) N (%)
Mild (0-3) 41 (45.6%) 21 (70%) 14 (46.7%) 6 (20%)
Moderate (4-6) 37 (41.1%) 9 (30%) 13 (43.3%) 15 (50%)
Sever (7-10) 12 (13.3%) 0 (0%) 3 (10%) 9 (30%)
χ2 value
20.25
p- value 0.0001
Sig S
Functional
disability
Total sample
(N = 90)
Group A (N = 30) Group B (N = 30) Group C (N = 30)
N (%) N (%) N (%) N (%)
Minimal
disability (0-20%)
35 (38.9%) 18 (60%) 10 (33.3%) 7 (23.3%)
Moderate
disability (21-
40%)
48 (53.3%) 12 (40%) 18 (60%) 18 (60%)
Sever disability
(41-60%)
7 (7.8%) 0 (0%) 2 (6.7%) 5 (16.7%)
χ2 value
12.47
p- value 0.01
Sig S
Lumbar lordosis
Total sample
(N = 90)
Group A (N = 30) Group B (N = 30)
Group C (N =
30)
N (%) N (%) N (%) N (%)
Flat 12 (13.3%) 4 (13.3%) 5 (16.7%) 3 (10%)
Hyperlordosis 42 (46.7%) 8 (26.7%) 14 (46.7%) 20 (66.7%)
Normal 36 (40%) 18 (60%) 11 (36.7%) 7 (23.3%)
χ2 value
10.81
p- value 0.02
Sig S
Mobility in
flexion
Total sample
(N = 90)
Group A (N = 30) Group B (N = 30)
Group C (N =
30)
N (%) N (%) N (%) N (%)
Hypomobility 37 (41.1%) 5 (16.7%) 14 (46.7%) 18 (60%)
Hypermobility 18 (20%) 10 (33.3%) 5 (16.7%) 3 (10%)
Normal 35 (38.9%) 15 (50%) 11 (36.7%) 9 (30%)
χ2 value
13.12
p- value 0.01
Sig S
Mobility in
extension
Total sample
(N = 90)
Group A (N = 30) Group B (N = 30)
Group C (N =
30)
N (%) N (%) N (%) N (%)
Hypomobility 51 (56.7%) 8 (26.7%) 21 (70%) 22 (73.3%)
Normal 39 (43.3%) 22 (73.3%) 9 (30%) 8 (26.7%)
χ2 value
16.56
p- value 0.0001
Sig S
χ2: Chi-squared value p value: Probability value S: Significant NS: Non Significant.
There was a significant increase in the percent of mild level of
pain, minimal disability and percent of normal curve in group A. while
there was a significant increase in the percent of sever level of pain,
Egypt. J. of Appl. Sci., 35 (7) 2020 90
moderate disability and the hyperlordosis in group C and also results
revealed a significant increase in the percent of normal mobility during
flexion and extension in group A while there was a significant increase in
the hypo mobility in group B and C (Table 2).
Results regarding LLA show a significant increase in LLA of
group C relative to group A (p = 0.001) and group B (p = 0.02) also
there was a significant increase in mobility during flexion of group A
compared with that of group C (p = 0.0001) and group B compared with
that of group C (p = 0.02) and also shows a significant increase in
mobility during extension of group A relative to group B (p = 0.0001)
and group C (p = 0.0001), but no significant difference in mobility during
extension between group B and C (p = 0.52) as in (Table3).
Table 3.Differances between groups regarding LLA, mobility during
flexion and extension, ODI and VAS.
LLA (degrees)
F-  ± SD value p- value Sig
Group A Group B Group C
-38.66 ± 9.38 -41.2 ± 9 -47.43 ± 8.33 7.67 0.001 S
Mobility during flexion
 ± SD F- value p- value Sig
Group A Group B Group C
64.33 ± 15.27 57.56 ± 15.23 47.6 ± 12.48 10.26 0.0001 S
Mobility during extension
 ± SD F- value p- value Sig
Group A Group B Group C
-12 ± 3.17 -7.5 ± 2.86 -6.7 ± 2.52 29.84 0.0001 S
ODI (%)
χ2 Median p- value Sig
Group A Group B Group C
18 26 27.5 16.09 0.0001 S
VAS (%)
χ2
value
Median p- value Sig
Group A Group B Group C
3 4 6 17.7 0.0001 S
χ2: Chi-squared value p value: Probability value S: Significant NS: Non Significant
Results regarding ODI show a significant decrease in ODI of
group A relative to group B (p = 0.003) and group C (p = 0.0001). Also
results show regarding VAS a significant decrease in VAS of group A
relative to group C (p = 0.0001) and group B (p = 0.008) (Table3).
3. Correlation between BMI and VAS as well as other mechanical
factors:
 There was moderate positive significant correlation between BMI and
VAS (r = 0.41, p = 0.0001) and between BMI and ODI (r = 0.42, p =
0.0001) (Table 4).
 There was moderate negative significant correlation between BMI
and LLA(r = -0.38, p = 0.0001) (Table4).
91 Egypt. J. of Appl. Sci., 35 (7) 2020
 There was moderate negative significant correlation between BMI
and mobility in flexion while moderate positive significant
correlation between BMI and mobility in extension(r = -0.43, p =
0.0001) and (r = 0.54, p = 0.0001) respectively (Table 4).
Table.4: Correlation between BMI, VAS ,LLA,Lumbar mobility and
ODI:
BMI
r value p value Sig
VAS 0.41 0.0001 S
LLA -0.38 0.0001 S
Mobility in flexion -0.43 0.0001 S
Mobility in extension 0.54 0.0001 S
ODI 0.42 0.0001 S
r value: Pearson correlation coefficient p value: Probability value S: Significant
4. Regression analysis with prediction model:
BMI can significantly predict the LLA (F = 14.88, p = 0.0001),
mobility in flexion (F = 20.93, p = 0.0001) and extension (F = 37.06, p =
0.0001), the ODI (F = 18.64, p = 0.0001) and VAS (F = 17.96, p =
0.0001) so that for each extra degree BMI, there is change in these
parameters (Table5).
Table.5 Regression analysis with prediction model of LLA, mobility
in flexion and extension, ODI and VAS from BMI:
LLA
R² B t- value p value Sig
95.0% CI
Lower Upper
0.14
Constant -16.7 -2.48 0.01 S -30.09 -3.32
BMI -0.69 -3.85 0.0001 S -1.05 -0.33
Mobility
during
flexion
R² B t- value p value Sig
95.0% CI
Lower Upper
0.19
Constant 105.53 9.75 0.0001 S 84.02 127.03
BMI -1.32 -4.57 0.0001 S -1.89 -0.74
Mobility
during
extension
R² B t- value p value Sig
95.0% CI
Lower Upper
0.29
Constant -22.89 -9.74 0.0001 S -27.55 -18.22
BMI 0.38 6.08 0.0001 S 0.25 -0.5
ODI
R² B t- value p value Sig
95.0% CI
Lower Upper
0.17
Constant -3.46 -0.52 0.6 NS -16.65 9.72
BMI 0.76 4.31 0.0001 S 0.41 1.11
VAS
R² B t- value p value Sig
95.0% CI
Lower Upper
0.17
Constant -2.53 -1.62 0.1 NS -5.64 0.56
BMI 0.17 4.23 0.0001 S 0.09 0.26
B: Regression coefficient p value: Probability value
S: Significant NS: Non significant CI: Confidence interval
Egypt. J. of Appl. Sci., 35 (7) 2020 92
DISCUSSION:
The present study investigated the correlation between different
degrees of obesity and non-specific low back pain as well as the
mechanical factors that may affect this correlation. Outcome measures
were performed through spinal mouse that measure lumbar lordotic angle
and spinal mobility and also through Visual analogue scale and
Oswestery Disability index to detect pain severity and functional
disability. Our results regarding LLA, lumbar mobility and functional
disability showed a significant increase in the hyperlordosis and
hypomobility and moderate disability in group B and C compared with
group A. While regarding pain severity, there was a significant increase
in the percent of sever level in group C. Also results showed moderate
positive significant correlation between BMI, VAS, ODI and lumbar
mobility during extension, while there was moderate negative significant
correlation between BMI and LLA as well as lumbar mobility during
flexion. The results of our study explained by the results of (Shiri et al.,
2010 b) that showed obesity could increase mechanical load by causing a
higher compressive or shear forces on the lumbar spine structures during
various activities. Additionally spinal mobility decreases with increasing
body weight which may interfere with disc nutrition. (Heikki et al.,
2015). Also, other previous study discussed the mechanism by which
females have consistently higher of CLBP is partially known as related to
exposure of the women to musculoskeletal loads due to pregnancy, child
care and doubled workday and further more less muscle and bone mass
as well as psychological characteristics (Ferreira et al., 2011; Altinel et
al., 2008 ; Catherine et al., 2010; Rodrigo, 2013).
Also the current study founded that there was a significant
difference between the three groups A, B and C in severity of nonspecific
low back pain, functional disability, lumbar curve changes and
mobility in flexion and extension (p = 0.0001) (p = 0.01) (p = 0.02) (p =
0.01) (p = 0.0001) respectively.
Also our results state that BMI can predict severity of nonspecific
low back pain, LLA, Lumbar mobility and functional disability.
So that for each extra degree in BMI, there is change in these parameters.
The findings of this study regarding lumbar curvature were in the
line with the findings of (Ndubuisi et al., 2016) who discussed the
impact of obesity on lumbosacral angles as the lumbosacral angles were
increased in persons with elevated body mass index and waist hip ratio.
This can lead to biomechanical alteration of the lumbosacral spine that
increases back pain. While (Joseph et al., 2002) compared range of
motion (ROM) of lumbar spine and lumbar lordosis between patients
with and without back pain with confounding variables as obesity and
pain level were not controlled. As to minimize the effect of pain on the
93 Egypt. J. of Appl. Sci., 35 (7) 2020
measurements, only patients with minimal or no pain at the time of
testing were included in the study. The findings of this research revealed
that no variations were found between the back pain and healthy groups
in both lumbar ROM and lordosis. This may show that lumbar range of
motion and lordosis of lumbar spine may not be the distinguishing
variables between both groups.
The findings of this study agree with the findings of (Murrie et
al., 2003) who showed that lumbar lordosis in individuals with a high
body mass index (BMI) was significantly greater. Also agree with (Guo
et al., 2008) who found that a BMI greater than 24 kg/ m2 could increase
the angle of lumbar lordosis.
The findings of this study regarding lumbar lordotic angle and
lumbar ROM is supported by (Vismara et al., 2010) who discussed the
impact of obesity and low back pain on spinal mobility in women as
obesity lead to reduce ROM of the spine due to reduced mobility in
pelvic and thoracic level and also showed that obesity with chronic back
pain is associated with an increase of lumbar lordosis.
Also the findings of this study are supported by (Lenková and
Vasilišinová 2019) who investigated spinal mobility in women with
sedentary job as obesity related to sedentary life style showing negative
changes in the spine structure and mobility in both sagittal and frontal
planes.
The findings of this study agreed with Bolgen-Cimen et al.,
2007 who discussed the role of obesity in low back pain related disability
as there was an increase of disability in patients with LBP when there
was co morbid obesity. But Bolgen-Cimen et al., 2007 disagree with the
present study as revealed that patients with LPB did not suffer from
worse pain if they were obese but they experienced a more disabled life
due to their weight as this study not demonstrated whether obesity can be
considered in the etiology of LBP, but demonstrated only whether
obesity is a factor responsible for disability in LBP patients.
The results of this study is confirmed by results of (Rodrigo et
al., 2013) that revealed increase of chronic low back pain in a southern
Brazil due to obesity as it causes overloading of the lumbosacral spine,
which become susceptible to degenerative changes.
Results of the present study regarding functional level
according to (ODI) agreed with (Alexandre et al., 2019) that discussed
pain of the lower back and alignment of the spine in sagittal plane
in obese individuals demonstrated low functional status in obese patients
compared with their non-obese counterparts.
Results of this study regarding the lumbar curvature disagreed
with the results of (James et al., 2006) who discussed the effects of BMI
on lumbar spine in individuals with no existing low back pain showed
Egypt. J. of Appl. Sci., 35 (7) 2020 94
that the impact of a degree of obesity on the standing lumbar curvature
(SLC) is not considered to have a statistically significant effect.
Our results regarding lumbar curvature and pain intensity
disagree with Hoseinifar, 2007 that stated, there no significant
correlation between BMI and low back pain however, a significant
correlation between lumbar lordosis and BMI suggesting that may be
related to some difference in population age, tool of measurement and
design of the study.
CONCLUSION:
Based on the results of the present study we can conclude that
Different degrees of obesity correlate with non-specific low
back pain as well as the mechanical factors that may affect this
correlation.
RECOMMENDATION
A similar study should be conducted on a large number
of patients to provide a wide representation of the population.
REFERENCES:
Aird, F. (1999): Mechanic's Guide to Precision Measuring Tools.
Motorbooks International.
Alexandre Peixoto de Mello ; Glaucus Cajaty dos Santos Martins ;
André Raposo Heringer ; Raphael Barbosa Gamallo ; Luiz
Felippe dos Santos Martins Filho ; Antônio Vítor de Abreu ;
Antonio Carlos Pires Carvalho and Maurício de Pinho
Gama (2019): Back pain and sagittal spine alignment in obese
patients eligible for bariatric surgery. European Spine
Journal, 28(5): 967-975.
Algarni, A.S. ; S. Ghorbel ; J.G. Jones and M. Guermazi (2014):
Validation of an Arabic version of the Oswestry index in Saudi
Arabia. Annals of physical and rehabilitation medicine, 57(9-
10): 653-663.
Altinel, L. ; K.C. Kose ; V. Ergan ; C. Isik ; Y. Aksoy ; A. Ozdemir
and D. Toprak (2008): The prevalence of low back pain and
risk factors among adult population in Opium region,
Turkey." Acta Orthop Traumatol Turc, 42(5): 328-33.
Bolgen-Cimen, O ; N Ar nc -Yncel ; M. Karabiber and C. Erdogan
(2007): Role of obesity in low back pain related disability.West
Indian Medical Journal, 56(3): 252.
Catherine, B. Johannes ; T. KimLe ; Xiaolei Zhou ; Joseph A.
Johnston and Robert H. Dworkin (2010): The prevalence of
95 Egypt. J. of Appl. Sci., 35 (7) 2020
chronic pain in United States adults: results of an Internet-based
survey." The Journal of Pain, 11(11): 1230-1239.
Crossley, K.M. ; K.L. Bennell ; Cowan, S.M. and S. Green (2004):
Analysis of outcome measures for persons with patellofemoral
pain: which are reliable and valid?. Archives of physical
medicine and rehabilitation, 85(5): 815-822.
Dobbelsteyn, C.J. ; M.R. Joffres ; D.R. MacLean and G. Flowerdew
(2001): A comparative evaluation of waist circumference, waistto-
hip ratio and body mass index as indicators of cardiovascular
risk factors. The Canadian Heart Health Surveys. International
journal of obesity, 25(5): 652-661.
Emmanuelle Chale´at-Valayer ; Jean-Marc Mac-Thiong ; Je´roˆme
Paquet ; Eric Berthonnaud and Fabienne Siani (2011):
Sagittal spino-pelvic alignment in chronic low back
pain. European Spine Journal, 20(5): 634.
Fairbank, J.C. ; J. Couper ; J.B. Davies and J.P. O’brien (1980): The
Oswestry low back pain disability questionnaire. Physiotherapy,
66 (8): 271-273.
Ferreira, G.D. ; M.C. Silva ; A.J. Rombaldi ; E.D. Wrege ; F.V.
Siqueira and P.C. Hallal (2011):Prevalence of back pain and
associated factors in adults in southern Brazil: a population-based
study. Brazilian Journal of Physical Therapy, 15(1): 31-36.
Funke, F.(2004): Vergleich Visueller Analogskalen mit
Kategorialskalen in Offline-und Online-Design (Doctoral
dissertation, Magisterarbeit im Studiengang Soziologie am
Institut für Soziologie des Fachbereichs Sozial-und
Kulturwissenschaften der Justus-Liebig-Universität Gießen).
Guo, Jin-Ming and Guo-Quan Zhang (2008): Effect of BMI and WHR
on lumbar lordosis and sacrum slant angle in middle and elderly
women China journal of orthopaedics and traumatology, 21(1):
30-31.
Heikki Frilander ; Svetlana Solovieva ; Pertti Mutanen ; Harri
Pihlajamäki ; Markku Heliövaara and Eira Viikari-Juntura
(2015): Role of overweight and obesity in low back disorders
among men: a longitudinal study with a life course
approach. BMJ open, 5:1-8.
Hoseinifar, M. ; F. Ghiasi, and A. Akbari (2007): The relationship
between lumbar and thoracic curves with body mass index and
Egypt. J. of Appl. Sci., 35 (7) 2020 96
low back pain in students of Zahedan University of Medical
Sciences. J Med science, 7(6): 984-90.
James, W. Youdas ; John H. Hollman and David A. Krause
(2006):The effects of gender, age and Body mass index on
standing lumbar curvature in persons without current low back
pain, Physiotherapy Theory and practice, 22(5): 229-237.
Joseph, K.F. Ng ; Carolyn A. Richardson ; Vaughan Kippers
and Mohamad Parnianpour (2002): Comparison of lumbar
range of movement and lumbar lordosis in back pain patients
and matched controls. Journal of Rehabilitation Medicine, 34(3):
109-113.
Kathrine, J. Vinknes ; Amany K. Elshorbagy ; Christian A. Drevon
; Clara G. Gjesdal ; Grethe S. Tell ; Ottar Nygård ; Stein E.
Vollset and Helga Refsum (2013): Evaluation of the body
adiposity index in a Caucasian population: the Hordaland health
study. American journal of epidemiology, 177(6): 586-592.
Koes, B.W. ; M. Van Tulder and S. Thomas (2006): Diagnosis and
treatment of low back pain. Bmj, 332(7555): 1430-1434.
Lenková, Rút and Veronika Vasilišinová (2019): Spinal Mobility in
Women with Sedentary Job. Acta Facultatis Educationis
Physicae Universitatis Comenianae, 59(2): 138-147.
Mannion, A.F. ; K. Knecht ; G. Balaban ; J. Dvorak and D. Grob
(2004): A new skin-surface device for measuring the curvature
and global and segmental ranges of motion of the spine:
reliability of measurements and comparison with data reviewed
from the literature. European Spine Journal, 13(2): 122-136.
Miyazaki, J. ; S. Murata ; C. Arakawa and S. Suzuki (2010):
Reproducibility of spinal curve angle measurements using
Spinal Mouse. Riagakuryoho Kagaku, 25(2): 223-6.
Murrie, V. L. ; A. K. Dixon ; W. Hollingworth ; H. Wilson and T. A.
C. Doyle (2003): Lumbar lordosis: study of patients with and
without low back pain." Clinical Anatomy: The Official Journal
of the American Association of Clinical Anatomists and the
British Association of Clinical Anatomists, 16(2): 144-147.
Ndubuisi, O.C. Onyemaechi ; Godson E. Anyanwu ; Emmanuel N.
Obikili ; Okechukwu Onwuasoigwe and Okechukwu E.
Nwankwo (2016): Impact of overweight and obesity on the
musculoskeletal system using lumbosacral angles. Patient
preference and adherence, 10: 291-296.
97 Egypt. J. of Appl. Sci., 35 (7) 2020
Post, R. B. and V. J. M. Leferink (2004): Spinal mobility: sagittal
range of motion measured with the Spinal Mouse, a new noninvasive
device. Archives of Orthopaedic and Trauma
Surgery, 124(3): 187-192.
Rodrigo, D. Meucci ; Anaclaudia G. Fassa ; Vera Mv Paniz
; Marcelo C. Silva and David H. Wegman (2013): Increase of
chronic low back pain prevalence in a medium-sized city of
southern Brazil. BMC musculoskeletal disorders,14(1): 155.
Russell, B.S. ; K.A. Muhlenkamp ; K.T. Hoiriis and C.M. DeSimone
(2012): Measurement of lumbar lordosis in static standing
posture with and without high-heeled shoes. Journal of
Chiropractic Medicine, 11(3): 145-153.
Shiri, R. ; J. Karppinen ; P. Leino-Arjas ; S. Solovieva and E.
Viikari-Juntura (2010): Incidence of nonspecific and radiating
low back pain: follow up of 24–39‐year‐old adults of the Young
Finns Study. Arthritis care & research, 62(4): 455-459.
Shiri, R. ; J. Karppinen ; P. Leino-Arjas ; S. Solovieva and
E. Viikari-Juntura (2010): The association between obesity
and low back pain: a meta-analysis. American journal of
epidemiology, 171(2): 135-154.
Singer, K. P. ; T. J. Jones, and P. D. Breidahl. (1990): A comparison
of radiographic and computer-assisted measurements of thoracic
and thoracolumbar sagittal curvature. Skeletal radiology, 19(1):
21-26.
Srikanthan, P. ; T.E. Seeman and A.S. Karlamangla (2009): Waisthip-
ratio as a predictor of all-cause mortality in high-functioning
older adults. Annals of epidemiology, 19(10): 724-731.
Topalidou, A. ; G. Tzagarakis ; X. Souvatzis ; G. Kontakis and P.
Katonis (2014): Evaluation of the reliability of a new noninvasive
method for assessing the functionality and mobility of
the spine. Acta of Bioengineering and Biomechanics, 16(1):
118-124.
Valery, P.C. ; A. Moloney ; A. Cotterill ; M. Harris ; A.K. Sinha, and
A.C. Green (2009): Prevalence of obesity and metabolic
syndrome in Indigenous Australian youths. Obesity
Reviews, 10(3): 255-261.
Vismara, L. ; F. Menegoni ; F. Zaina ; M. Galli ; S. Negrini and
P. Capodaglio (2010): Effect of obesity and low back pain on
Egypt. J. of Appl. Sci., 35 (7) 2020 98
spinal mobility:a cross sectional study in women. Journal of
neuroengineering and rehabilitation, 7(1): 1-8.
Vogler, D. ; R. Paillex ; M. Norberg; P. de Goumoëns and J.
Cabri (2008): Cross-cultural validation of the Oswestry
disability index in French. In Annals of Rehabilitation and
Physical Medicine, 51(5): 379-385. Elsevier Masson.
WHO, World Health Organization (2011): Waist circumference and waisthip
ratio: report of a WHO expert consultation, Geneva, 8-11.
WHO, World Health Organization (2016): Obesity: Definition of
obesity and overweight. Redefining Obesity and its treatment.
العلاقة بین مختمف درجات السمنة وآلام اسفل الظهر الغیر محددة
غدی یاسر محمد*، فاطمة صدیق امین**، یاسر محمد انیس***
*معید العلاج الطبیعی بقسم العموم الاساسیة، کمیة العلاج الطبیعی ، جامعة د ا ریة.
**استاذ العلاج الطبیعی بقسم العموم الاساسیة، کمیة العلاج الطبیعی، جامعة القاهرة.
***استاذ مساعد بقسم العموم الاساسیة، کمیة العلاج الطبیعی، جامعة القاهرة.
الخمفیة: تعرف السمنة بانها مشکمة صحیة عامة رئیسیة تترتبط بالعدید من الاضط ا ربات
العضمیة الهیکمیة بما فی ذلک ضعف العمود الفقری وهشاشة العظام.الهدف: د ا رسة الارتباط بین
مختمف درجات السمنة وآلام اسفل الظهر الغیر محددة وکذلک العوامل المیکانیکیة التی قد تؤثر
عمی هذا الارتباط. الاشخاص والوسائل:شارکت تسعون انثی بدینة یعانون من الام اسفل الظهر
الغیر محددة و تم اد ا رجهم فی الد ا رسه و تت ا روحت اعمارهم من عشرون الی خمسة واربعون
عاما. تم تقسیمهم الی ثلاث مجموعات متساویة طبقا لمؤشر کتمة الجسم. ثلاثون مریضا فی
کل مجموعة. تمثل المجموعات)أ، ب، ج( السمنة من الدرجة الاولی والثانیة والثالثة عمی
التوالی. تم اج ا رء مقاییس النتائج من خلال الماوس الفقری والذی یقیس ال ا زویة القطنیة و حرکة
العمود الفقری وایضا من خلال المقیاس التناظری البصری ومؤشر الاعاقة اوسویستری لمکشف
عن شدة الالم والاعاقة الوظیفیة.النتائج:کانت هناک علاقة ارتباط معنویة موجبة معتدلة بین
مؤشرکتمة الجسم و المقیاس التناظری البصری ومؤشر الاعاقة اوسویستری والحرکة القطنیة اثناء
التمدید لمخمف بینما هناک ارتباط سمبی معتدل بین مؤش کتمة الجسم و ال ا زویة القطنیة وکذلک
الحرکة القطنیة اثناء التمدید للأمام. الخلاصة: ترتبط درجات السمنة المختمفة بآلام اسفل
الظهر الغیر محددة بالاضافة الی العوامل المیکانیکیة التی قد تؤثر عمی هذا الارتباط.
الکممات الدالة: السمنة، آلام اسفل الظهر الغیر محددة، الماوس الفقری و مدی الحرکة فی
الفق ا رت القطنیة.
99 Egypt. J. of Appl. Sci., 35 (7) 2020

REFERENCES:
Aird, F. (1999): Mechanic's Guide to Precision Measuring Tools.
Motorbooks International.
Alexandre Peixoto de Mello ; Glaucus Cajaty dos Santos Martins ;
André Raposo Heringer ; Raphael Barbosa Gamallo ; Luiz
Felippe dos Santos Martins Filho ; Antônio Vítor de Abreu ;
Antonio Carlos Pires Carvalho and Maurício de Pinho
Gama (2019): Back pain and sagittal spine alignment in obese
patients eligible for bariatric surgery. European Spine
Journal, 28(5): 967-975.
Algarni, A.S. ; S. Ghorbel ; J.G. Jones and M. Guermazi (2014):
Validation of an Arabic version of the Oswestry index in Saudi
Arabia. Annals of physical and rehabilitation medicine, 57(9-
10): 653-663.
Altinel, L. ; K.C. Kose ; V. Ergan ; C. Isik ; Y. Aksoy ; A. Ozdemir
and D. Toprak (2008): The prevalence of low back pain and
risk factors among adult population in Opium region,
Turkey." Acta Orthop Traumatol Turc, 42(5): 328-33.
Bolgen-Cimen, O ; N Ar nc -Yncel ; M. Karabiber and C. Erdogan
(2007): Role of obesity in low back pain related disability.West
Indian Medical Journal, 56(3): 252.
Catherine, B. Johannes ; T. KimLe ; Xiaolei Zhou ; Joseph A.
Johnston and Robert H. Dworkin (2010): The prevalence of
95 Egypt. J. of Appl. Sci., 35 (7) 2020
chronic pain in United States adults: results of an Internet-based
survey." The Journal of Pain, 11(11): 1230-1239.
Crossley, K.M. ; K.L. Bennell ; Cowan, S.M. and S. Green (2004):
Analysis of outcome measures for persons with patellofemoral
pain: which are reliable and valid?. Archives of physical
medicine and rehabilitation, 85(5): 815-822.
Dobbelsteyn, C.J. ; M.R. Joffres ; D.R. MacLean and G. Flowerdew
(2001): A comparative evaluation of waist circumference, waistto-
hip ratio and body mass index as indicators of cardiovascular
risk factors. The Canadian Heart Health Surveys. International
journal of obesity, 25(5): 652-661.
Emmanuelle Chale´at-Valayer ; Jean-Marc Mac-Thiong ; Je´roˆme
Paquet ; Eric Berthonnaud and Fabienne Siani (2011):
Sagittal spino-pelvic alignment in chronic low back
pain. European Spine Journal, 20(5): 634.
Fairbank, J.C. ; J. Couper ; J.B. Davies and J.P. O’brien (1980): The
Oswestry low back pain disability questionnaire. Physiotherapy,
66 (8): 271-273.
Ferreira, G.D. ; M.C. Silva ; A.J. Rombaldi ; E.D. Wrege ; F.V.
Siqueira and P.C. Hallal (2011):Prevalence of back pain and
associated factors in adults in southern Brazil: a population-based
study. Brazilian Journal of Physical Therapy, 15(1): 31-36.
Funke, F.(2004): Vergleich Visueller Analogskalen mit
Kategorialskalen in Offline-und Online-Design (Doctoral
dissertation, Magisterarbeit im Studiengang Soziologie am
Institut für Soziologie des Fachbereichs Sozial-und
Kulturwissenschaften der Justus-Liebig-Universität Gießen).
Guo, Jin-Ming and Guo-Quan Zhang (2008): Effect of BMI and WHR
on lumbar lordosis and sacrum slant angle in middle and elderly
women China journal of orthopaedics and traumatology, 21(1):
30-31.
Heikki Frilander ; Svetlana Solovieva ; Pertti Mutanen ; Harri
Pihlajamäki ; Markku Heliövaara and Eira Viikari-Juntura
(2015): Role of overweight and obesity in low back disorders
among men: a longitudinal study with a life course
approach. BMJ open, 5:1-8.
Hoseinifar, M. ; F. Ghiasi, and A. Akbari (2007): The relationship
between lumbar and thoracic curves with body mass index and
Egypt. J. of Appl. Sci., 35 (7) 2020 96
low back pain in students of Zahedan University of Medical
Sciences. J Med science, 7(6): 984-90.
James, W. Youdas ; John H. Hollman and David A. Krause
(2006):The effects of gender, age and Body mass index on
standing lumbar curvature in persons without current low back
pain, Physiotherapy Theory and practice, 22(5): 229-237.
Joseph, K.F. Ng ; Carolyn A. Richardson ; Vaughan Kippers
and Mohamad Parnianpour (2002): Comparison of lumbar
range of movement and lumbar lordosis in back pain patients
and matched controls. Journal of Rehabilitation Medicine, 34(3):
109-113.
Kathrine, J. Vinknes ; Amany K. Elshorbagy ; Christian A. Drevon
; Clara G. Gjesdal ; Grethe S. Tell ; Ottar Nygård ; Stein E.
Vollset and Helga Refsum (2013): Evaluation of the body
adiposity index in a Caucasian population: the Hordaland health
study. American journal of epidemiology, 177(6): 586-592.
Koes, B.W. ; M. Van Tulder and S. Thomas (2006): Diagnosis and
treatment of low back pain. Bmj, 332(7555): 1430-1434.
Lenková, Rút and Veronika Vasilišinová (2019): Spinal Mobility in
Women with Sedentary Job. Acta Facultatis Educationis
Physicae Universitatis Comenianae, 59(2): 138-147.
Mannion, A.F. ; K. Knecht ; G. Balaban ; J. Dvorak and D. Grob
(2004): A new skin-surface device for measuring the curvature
and global and segmental ranges of motion of the spine:
reliability of measurements and comparison with data reviewed
from the literature. European Spine Journal, 13(2): 122-136.
Miyazaki, J. ; S. Murata ; C. Arakawa and S. Suzuki (2010):
Reproducibility of spinal curve angle measurements using
Spinal Mouse. Riagakuryoho Kagaku, 25(2): 223-6.
Murrie, V. L. ; A. K. Dixon ; W. Hollingworth ; H. Wilson and T. A.
C. Doyle (2003): Lumbar lordosis: study of patients with and
without low back pain." Clinical Anatomy: The Official Journal
of the American Association of Clinical Anatomists and the
British Association of Clinical Anatomists, 16(2): 144-147.
Ndubuisi, O.C. Onyemaechi ; Godson E. Anyanwu ; Emmanuel N.
Obikili ; Okechukwu Onwuasoigwe and Okechukwu E.
Nwankwo (2016): Impact of overweight and obesity on the
musculoskeletal system using lumbosacral angles. Patient
preference and adherence, 10: 291-296.
97 Egypt. J. of Appl. Sci., 35 (7) 2020
Post, R. B. and V. J. M. Leferink (2004): Spinal mobility: sagittal
range of motion measured with the Spinal Mouse, a new noninvasive
device. Archives of Orthopaedic and Trauma
Surgery, 124(3): 187-192.
Rodrigo, D. Meucci ; Anaclaudia G. Fassa ; Vera Mv Paniz
; Marcelo C. Silva and David H. Wegman (2013): Increase of
chronic low back pain prevalence in a medium-sized city of
southern Brazil. BMC musculoskeletal disorders,14(1): 155.
Russell, B.S. ; K.A. Muhlenkamp ; K.T. Hoiriis and C.M. DeSimone
(2012): Measurement of lumbar lordosis in static standing
posture with and without high-heeled shoes. Journal of
Chiropractic Medicine, 11(3): 145-153.
Shiri, R. ; J. Karppinen ; P. Leino-Arjas ; S. Solovieva and E.
Viikari-Juntura (2010): Incidence of nonspecific and radiating
low back pain: follow up of 24–39‐year‐old adults of the Young
Finns Study. Arthritis care & research, 62(4): 455-459.
Shiri, R. ; J. Karppinen ; P. Leino-Arjas ; S. Solovieva and
E. Viikari-Juntura (2010): The association between obesity
and low back pain: a meta-analysis. American journal of
epidemiology, 171(2): 135-154.
Singer, K. P. ; T. J. Jones, and P. D. Breidahl. (1990): A comparison
of radiographic and computer-assisted measurements of thoracic
and thoracolumbar sagittal curvature. Skeletal radiology, 19(1):
21-26.
Srikanthan, P. ; T.E. Seeman and A.S. Karlamangla (2009): Waisthip-
ratio as a predictor of all-cause mortality in high-functioning
older adults. Annals of epidemiology, 19(10): 724-731.
Topalidou, A. ; G. Tzagarakis ; X. Souvatzis ; G. Kontakis and P.
Katonis (2014): Evaluation of the reliability of a new noninvasive
method for assessing the functionality and mobility of
the spine. Acta of Bioengineering and Biomechanics, 16(1):
118-124.
Valery, P.C. ; A. Moloney ; A. Cotterill ; M. Harris ; A.K. Sinha, and
A.C. Green (2009): Prevalence of obesity and metabolic
syndrome in Indigenous Australian youths. Obesity
Reviews, 10(3): 255-261.
Vismara, L. ; F. Menegoni ; F. Zaina ; M. Galli ; S. Negrini and
P. Capodaglio (2010): Effect of obesity and low back pain on
Egypt. J. of Appl. Sci., 35 (7) 2020 98
spinal mobility:a cross sectional study in women. Journal of
neuroengineering and rehabilitation, 7(1): 1-8.
Vogler, D. ; R. Paillex ; M. Norberg; P. de Goumoëns and J.
Cabri (2008): Cross-cultural validation of the Oswestry
disability index in French. In Annals of Rehabilitation and
Physical Medicine, 51(5): 379-385. Elsevier Masson.
WHO, World Health Organization (2011): Waist circumference and waisthip
ratio: report of a WHO expert consultation, Geneva, 8-11.
WHO, World Health Organization (2016): Obesity: Definition of
obesity and overweight. Redefining Obesity and its treatment.