Sains Malaysiana 46(4)(2017): 567–573
http://dx.doi.org/10.17576/jsm-2017-4604-08
Assessment of Abdominal
Obesity using 3D Body Scanning Technology
(Penilaian Keobesan
Abdomen menggunakan Teknologi Pengimbasan Badan 3D)
SUHANA
JAPAR1,
THAMILVAANI
MANAHARAN2,
ASMA
AHMAD
SHARIFF2,4,
ABDUL
MAJID
MOHAMED2,4,
AMIR
FEISAL
MERICAN
ALJUNID
MERICAN*2,3
1Institute
of Graduate Studies, University of Malaya, 50603 Kuala Lumpur, Federal
Territory
Malaysia
2Centre of Research for
Computational Sciences and Informatics in Biology, Bioindustry,
Environment, Agriculture and Healthcare (CRYSTAL), University of
Malaya, 50603 Kuala Lumpur, Federal Territory, Malaysia
2Institute of Biological
Sciences, Faculty of Science, Centre of Research for Computational
Sciences and Informatics for Biology, Bioindustry, Environment,
Agriculture and Healthcare (CRYSTAL)
University
of Malaya, 50603 Kuala Lumpur, Federal Territory, Malaysia
3Institute
of Biological Sciences, Faculty of Science, University of Malaya,
50603 Kuala Lumpur, Federal Territory, Malaysia
4Centre for Foundation
Studies in Science, University of Malaya, 50603 Kuala Lumpur, Federal
Territory, Malaysia
Received: 15 July 2016/Accepted:
30 September 2016
ABSTRACT
Abdominal obesity is
an important contributor for health risk factors such as hypertension,
diabetes mellitus and hypercholesterolemia. Therefore, the application
of a proper method is important prerequisite in performing abdominal
obesity assessment. In this study, we applied 3D body scanning technology
to measure waist circumference (WC), hip circumference (HC)
and waist to hip ratio (WHR) precisely in an effort to improve
the current health assessment for abdominal obesity. A total of
200 Malaysian women with sedentary lifestyle, aged between 18 and
60 years participated in this study. Paired t-test was used to determine
the differences between the automated (3D body scanner) and manual
measurements of WC,
HC
and WHR.
3D body scanner measurements show that 27% of subjects had mild
abdominal obesity (80 - 90 cm) and 34.5% of subjects had severe
abdominal obesity (≥90 cm) based on WC cutoff points. Based on WHR
cutoff points, 57% of subjects had abdominal obesity
(≥0.85) while the remaining were without abdominal obesity
(<0.85). Lower percentages of abdominal obesity prevalence were
reported for both WC and
WHR
categories using manual measurements. We also found
that in normal BMI category, 8.5% of subjects have mild abdominal obesity
based on automated measurements while only 5.5% of subjects were
identified on manual measurements. The result of this study indicated
that 3D body scanner provided better assessment method as it enables
detection of abdominal obesity in more subjects based on WC and
WHR
categories. Public agencies are encouraged to consider
the application of 3D body scanning in health assessment of abdominal
obesity.
Keywords: Abdominal
obesity; body mass index; waist circumference; waist to hip ratio;
3D body scanner
ABSTRAK
Keobesan abdomen adalah penyumbang
penting kepada faktor risiko kesihatan seperti tekanan darah tinggi,
kencing manis dan hiperkolesterolemia. Oleh itu, penggunaan kaedah
yang betul adalah satu komponen penting dalam menjalankan penilaian
keobesan abdomen. Dalam kajian
ini, kami menggunakan teknologi pengimbasan badan tiga dimensi (3D)
untuk mengukur lilitan pinggang, lilitan pinggul dan nisbah pinggang
ke pinggul secara tepat dalam usaha untuk meningkatkan penilaian
kesihatan semasa bagi keobesan abdomen. Seramai 200
wanita Malaysia yang berusia antara 18 hingga 60 tahun mengambil
bahagian dalam kajian ini. Ujian-t berpasangan digunakan untuk menentukan
perbezaan antara automatik (pengimbas badan 3D) dan ukuran manual
WC, HC dan WHR.
Ukuran pengimbas badan 3D menunjukkan bahawa 27% daripada subjek
mempunyai keobesan abdomen sederhana (80
- 90 cm) dan 34.5% daripada subjek mempunyai keobesan abdomen teruk (≥90
cm) berdasarkan kategori WC.
Berdasarkan kategori WHR, 57% daripada subjek mempunyai keobesan abdomen (≥0.85)
manakala selebihnya adalah tanpa keobesan abdomen (<0.85).
Peratusan yang lebih rendah untuk keobesan abdomen dilaporkan
bagi kedua-dua kategori WC dan WHR menggunakan
ukuran manual. Kami juga mendapati bahawa dalam kategori indeks
jisim tubuh (BMI)
normal, 8.5% daripada subjek mempunyai keobesan abdomen yang sederhana
berdasarkan pengukuran automatik manakala hanya 5.5% daripada subjek
berdasarkan ukuran manual. Hasil kajian ini menunjukkan bahawa pengimbas
badan 3D menyediakan kaedah penilaian yang lebih baik kerana ia
membolehkan pengesanan lebih banyak subjek yang mempunyai keobesan abdomen berdasarkan
kategori WC dan WHR. Agensi awam digalakkan untuk
mempertimbangkan penggunaan pengimbasan badan 3D dalam penilaian
kesihatan untuk keobesan abdomen.
Kata kunci: Indeks jisim
tubuh; keobesan abdomen; lilitan pinggang;
nisbah pinggang ke pinggul; pengimbas badan 3D
REFERENCES
Chopra, S.M., Misra, A., Gulati, S. & Gupta, R. 2013. Overweight,
obesity and related non-communicable diseases in Asian Indian girls
and women. European Journal of Clinical Nutrition 67(7):
688-696.
Dong, J., Ni, Y.Q., Chu, X., Liu, Y.Q., Liu, G.X., Zhao, J., Yang,
Y.B. & Yan, Y.X. 2015. Association between the abdominal obesity
anthropometric indicators and metabolic disorders in a Chinese population.
Public Health 131: 3-10.
Fryar, C.D., Gu, Q. & Ogden, C.L. 2012. Anthropometric reference
data for children and adults: United States, 2007- 2010. Vital
and Health Statistics 11(252): 1-48.
Han, H., Nam, Y. & Choi, K. 2010. Comparative analysis of 3D
body scan measurements and manual measurements of size Korea adult
females. International Journal of Industrial Ergonomics 40(5):
530-540.
IBM SPSS Statistics for windows. Version 22.0. IBM Corp. Armonk,
NY: IBM Corp. 2013.
Jaeschke, L., Steinbrecher, A. & Pischon, T. 2015. Measurement
of waist and hip circumference with a body surface scanner: Feasibility,
validity, reliability, and correlations with markers of the metabolic
syndrome. PloS one 10(3): e0119430.
Kuehnapfel, A., Ahnert, P., Loeffler, M., Broda, A. & Scholz,
M. 2016. Reliability of 3D laser-based anthropometry and comparison
with classical anthropometry. Scientific Reports. p. 6.
National Health and Morbidity Survey (NHMS): http://www. moh.gov.my/index.php/file_manager/dl_item/
(Accessed on 1 March 2015).
Norafidah, A.R., Azmawati, M.N. & Norfazilah, A. 2013. Factors
influencing abdominal obesity by waist circumference among normal
BMI population. Malaysian Journal of Public Health Medicine 13(1):
37-47.
Paquette, S. 1996. 3D scanning in apparel design and human engineering.
Computer Graphics and Applications 16(5): 11-15.
Pepper, M.R., Freeland-Graves, J.H. & Yu, W. 2010. Validation
of a 3-dimensional laser body scanner for assessment of waist and
hip circumference. Journal of the American College of Nutrition
29(3): 179-188.
Simmons, K.P. & Istook, C.L. 2002. 3-D body scanning measurement
procedures: Are they the same as traditional physical anthropometric
procedures? In Proceedings of the International Foundation of
Fashion Technology Institutes (IFFTI) 4th International Conference,
Nov 7-11, Hong Kong Polytechnic University, Hong Kong. pp. 579-590.
Soileau, L., Bautista, D., Johnson, C., Gao, C., Zhang, K., Li, X.,
Heymsfield, S.B., Thomas, D. & Zheng, J. 2016. Automated anthropometric
phenotyping with novel Kinect-based three-dimensional imaging method:
Comparison with a reference laser imaging system. European Journal
of Clinical Nutrition 70(4): 475-481.
Stefan, D.B., Wohlgemuth, S.D., Gilbert, D.A. 2011. Theory and practical
steps to introducing a new 3D public health indicator to replace
BMI using existing population based multidimensional reference measurement
sets. 5th International 3D Technologies Conference. Lugano,
Switzerland. pp. 299-312.
Treleaven, P. & Wells, J. 2007. 3D body scanning and healthcare
applications. Computer 40(7): 28-34.
Wang, S., Liu, Y., Li, F., Jia, H., Liu, L. & Xue, F. 2015. A
novel quantitative body shape score for detecting association between
obesity and hypertension in China. BMC Public Health 15(1):
7.
Wells, J.C.K., Ruto, A. & Treleaven, P. 2008. Whole-body three-dimensional
photonic scanning: A new technique for obesity research and clinical
practice. International Journal of Obesity 32: 232-238.
Wells, J.C.K., Treleaven, P. & Charoensiriwath, S. 2012. Body
shape by 3-D photonic scanning in Thai and UK adults: Comparison
of national sizing surveys. International Journal of Obesity
36: 148-154.
WHO expert consultation. 2004. Appropriate body-mass index for Asian
ppopulations and its implications for policy and interventions strategies.
The Lancet 36: 157-163.
Wu,
S., Wang, R., Jiang, A., Ding, Y., Wu, M., Ma, X., Zhao, Y. &
He, J. 2014. Abdominal obesity and its association with
health-related quality
of life in adults: A population-based study in five Chinese cities.
Health and Quality of Life Outcomes 12(1): 100.
Yang, C.Y., Peng, C.Y.,
Liu, Y.C., Chen, W.Z. & Chiou, W.K. 2011. Surface anthropometric
indices in obesity-related metabolic diseases and cancers. Chang
Gung Medical Journal 34(1): 1-22.
*Corresponding
author; email: merican@um.edu.my
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