Engineering, 2013, 5, 7-11 Published Online October 2013 (
Copyright © 2013 SciRes. ENG
Treatment Principles of Obesity with Chinese Herbal
Medicine: Literature Analysis by Text Mining
Yunyu Huang1*, Lianjie Wang1*, Shidong Wang1, Feng Cai2, Guang Zheng3, Aiping Lu2,4,
Xiuchen Yu1#, Miao Jiang2#
1Beijing Dongzhimen Hospital affiliated to Beijing University of Chinese Medic i ne, Beijing, China
2Institute of Basic Research in Clinical Medi c ine, China Academy of Chinese Medical Sciences, Beijing, China
3School of Information Science-Engineering, Lanzhou University, Lanzhou, China
4Hong Kong Baptist University School of Chinese Medicine, Kowloon, Hong Kong, China
Received September 2012
Obesity represents a social health prob lem worldwide, associated with serious health r i sk s and increased mortality. The
prevalence of obesity is reported to be increasing in both developed and developing countries. Obesity is associated
with a significant range of comorbidities and is linked with increases in mortality, thus the treatment of obesity is very
important. Chinese herbal medicine (CHM) has been used for we ight management both in China and in western coun-
tries for many years, the effectiveness and safety of CHMs in obesity have been prov ed. Yet the principles of treating
obesity with CHMs are hard to manage due to the complexity of TCM theory. In this study, a novel text mining method
was developed based on a comprehensive collection of literatures in order to explore th e treatment principles more in-
tuitively. Networks of TCM patterns and CHMs w hich are most frequently used in obesity treatment are built-up and
analyzed, two major principles are explor ed in treating obesity: one is resolving phlegm and dampness, the other is
clearing heat and reinforcing deficiency. These findings might guide the clinicians in treatment of obesity.
Keywords: Obesity; Chinese Herbal Medicine; Pattern; Traditional Chinese Medicine; Te x t Mining
1. Introduction
Obesity [defined as a body mass index (BMI) 30 kg/m2]
represents a considerable worldwide health problem,
associated with serious health risks and increased mortal-
ity. The prevalence of obesity is reported to be increasing
worldwide [1]. At present, 35.5% among adult men and
35.8% among adult women in the United States are con-
side red to be obese [2], in England the prevalence of ob-
esity is reported to have increased between 1993 and
2004 from 13.6% to 24.0% among men and from 16.9%
to 24.4% among women. Some minority groups, such as
Hispanic and African Americans, have higher overweight
and obesity rate s t han th e white population [3]. In line
with the global trend, the rate of obesity in China con-
tinues to i ncreas e , overweight and obesity also pose a
challenge to public health in China. According to Ch i -
nese definition, 303 million Chinese are over-weight
(body mass index, BMI 24 kg/m2). Among them, 73
million are clinically obese (BMI 28 kg/m2) [4].
Obesity is associated with a significant r ange of com-
orbidities and is linked with increases in mortality, w hich
is usually the result of the combination of genetic factors
and an inappropriate lif e style, characterized by inade-
quate nutrition and lack of regu l ar physical activity. It is
closely associated with the development of type 2 di-
abetes, hypertension, dyslipidemia, and cardiovascular
disease, among other medical problems [5].
Expert panels spons or e d by both the World Health
Organization and the National Institutes of Health have
recommended that obese adults, as well as those who are
overweight and have comorbid conditions, lose 10% of
their initial weight [6,7]. A comprehensive program of
lifestyle modification is conside r ed the first option for
achieving this goal [7]. Lifestyle modification, also re-
ferred to as behavioral we ight control, includes 3 primary
components: diet, exercise, and behavior therapy [8].
For obese patients who cannot achieve or maintain a
healthy weight by non-pharmacological means, drug
therapy is recommended in combination with non-ph a r-
macological interventions such as dietary modifications
and exercise [9]. Yet the costs are high. Compared with
lifestyle advice, the mean incremental cost-effectiveness
ratio for orlistat (sibutramine, rimonabant) ranged be-
tween £970 (£6941, £9303) and £59,174 (£10,042,
*Equal contributions to this work.
#Correspondi ng author.
Copyright © 2013 SciRes. ENG
£35,876) [9].
Despite these conditions, patient surveys indicate that
less than one-half of obese individuals are advised by
their physicians to lose weight [10], the reason is possi-
bly lying in that physicians feel ill-equipped to provide
treatment or that the available treatments for obesity are
ineffective [11].
Chinese herb al medicine (CHM) has been used for
weight management both in China an d in western co un-
tries, traditional Chinese medicine (TCM) has a distinc-
tive and systematic cognition of obesity according to the
specific theory framework. Randomized, controlled clin-
ical trials published on CHMs for weight management
have proved the effectiveness and safe t y of some CHM
formulae [12,13]. A number of animal studies support
the use of CHM formulas for treating obesity and have
shown other beneficial effects [14-16], the potential me-
chanism of actions of many Chinese herbs that are tradi-
tionally used for weight management has also b een ex-
Howeve r , due to the complexity of TCM theory, the
treatment principles of obesity are complicated a nd mys-
terious. In order to exp lore the treatment principles more
intuitively, a novel text minin g method was developed
based on a comprehensive collection of literatures [17].
The study would provide an accessible way for under-
standing the treatment principles for obesity with CHM s.
2. Material and Methods
2.1. Data Collection
The dataset were downloaded from SinoMed
( sp) with the query
term of “obes ity” on Jane 22, 2012. Thi s dataset contains
38,051 recor d s of litera tures on clinical practices or
theoretical research on obesity. In th is dataset, each
record/paper is tagged with an unique ID. These recor ds
contain the title, keywords, and abstract of published
papers [17].
2.2. Data Filtering
1) TCM Patter: Pattern (also called as Syndrome, or
Zheng) differentiation is regar ded as the key ro le in the
clinical practise of TCM traditional Chinese medicine
[18]. Usually, pattern identification is the basis of the
prescription of herb formulae, CHMs, or other TCM
therapies. Thus it is natural and intuitive to filter out the
pattern and then tr y to find the association rules b etw een
pattern and CHMs. The top TCM patterns in obesity are:
pulmonary stagnation of phlegm (Tan shi zu fei), fol-
lowed with stagnation of liver qi (Gan qi yu jie) and kid-
ney yin deficiency (Shen yin xu).
2) Chinese herbal medicine: Based on the keyword list
of CHMs (b oth legal names and other popular names are
included for calculation), we filtered the CHMs in the
plain text format, and then co nv erted a ll popular names
into legal names. All the CHMs were tagged with th eir
unique paper ID. Based on the unique paper ID, we could
construct the pairs of co-existed CHMs as they do coe x -
isted in literature. F or example, in one paper, CHMs of
Huangqi (Radix Astragali seu Hedysari), Rens hen (Radix
Ginseng), and Shengdihuang (Radix Rehmanniae Recens)
are mentioned. Then, the pairs of co-existed CHMs of
“Huangqi-Renshen”, “Huangqi-Shengdihuang”, and “Ren -
shen -Shengdihuang” are constructed.
3. Results
In this paper, fo cused on obesity, we explo red the prin-
ciples of pattern diffe rentiation and CHMs prescription
and the association between the two aspects under the
framework of TCM theory from 38,051 literatures. Th e
network con s truction is based on the analysis of net-
works of pattern and CHM correlated with obesity in
literature. The conn ections a mong thes e networks are
built-up under the professional knowledge of TCM.
3.1. Major TCM Patterns in Obesity
Pattern identification is regarded as the first step during
TCM clinical practice procedure. After the pattern is ap-
proved, the treatment principle can be determined. For
example, when the pattern of blood stasis is approved,
then the treatment principle of active blood and resolve
stasis is determined. In our results, 122 TCM patterns are
detected to be related with obesity, and the top 10 TCM
patterns in obesity are presented in Figure 1.
3.2. Most Frequently Prescribed CHMs in
Obesity Treatment
Altogether 174 CHMs are mined from the literature in
treatment of obesity. As herbal formulae are composed
by the CHMs, the list of mos t frequently used CH M s can
certainly provide the information of TCM treatment
principles more effectively due to the stablity and uni-
queness of each CHMs rather than formulae which can
be renamed easily after slight regulation. The top 10 fre-
quently prescribed CHMs are shown in Figure 2.
3.3. Networks of the Pattern and CHMs in
The networks of patterns and CHMs in obesity treatment
can be constructed based on the co-existence frequency
among patterns or CHMs, respectively. By checking
these two networks, the correlation between TCM pat-
terns and CHMs can be analyzed and explored. In order
Copyright © 2013 SciRes. ENG
Figure 1. Top 10 TCM patterns in obesity.
Figure 2. Top 10 frequently prescribed CHMs in treatment
of obesity.
to achieve better visualization, the CHM network is sim-
plified to preserve 11 CHMs which are the most fre-
quently used in combination in treating obesity. The net-
works of pattern and CHMs with their correlation on
obesity is demonstrated in Figure 3. The major correla-
tion between TCM patterns identification and CHMs are
demonstrated with arrows.
4. Conclusions and Discussion
Based on the analysis described in previous section, it
naturally comes to the point that TCM treatment prin-
ciples of a disease can be reasonably mined out and pre-
sented from dataset downloaded from SinoMed which
contains 38,051 records. Compared with th e knowledge
of obesity in textbook, most knowledge is covered by the
si mple and succinct networks demonstrated in Figure 3
which can be summarized with the following points and
their internal connections.
1) TCM networks of patterns and CHMs can be
constructed and analyzed
In this study, through mass calculation on dataset on
obesity, the main aspects of TCM networks were built-up.
The main TCM organs (different from modern medical
concept) involved in ob esit y development are lung,
spleen, liver, kidney and stomach. The pathogenesis re-
lated with obesity includes Dampness-Phlegm, Qi-de-
pression, Deficiency of Qi/Yin/Yang, and Pathogenic fire.
To follow the matter of course, CHMs most frequ ently
pre s cribed in obesity treatment can be grouped into 2
major classes, one group is responsible for resolving
phlegm and dampness, the other is for clearing heat and
reinforcing deficiency. These major principles might
Figure 3. The network of TCM patterns and CHMs in treatment of obesity. Network of patters is shown in the upper part,
network of CHMs in lower part. Bigger shape represents higher frequencies. The lines between the shapes represent the
co-existent correlations between the two patterns/CHMs. Arrows represent the correlation between the TCM patterns and
050100 150
Qi deficiency in splee n
Y in de fi ci e ncy i n Li ver a nd
Excessiv e Hea t in Stoma ch an d
Yang deficiency in Kidn ey
S t ag na t ion of QI due t o
D efi c ie ncy of bot h yi n a nd yang
Y in de fi ci e ncy i n ki d ney
S t ag na t ion of li ve r qi
P ul monary st ag nat i o n of ph l egm
020 40 60 80100
BAI ZHU (Rhizoma Atra ctylodis
FU LING (Poria)
SHAN ZHA (Fructus C ratae g i)
HUANG LIAN (R hizoma C optid is )
DAN SHEN (Radix Salviae
HUANG QI (Radix Astr ag ali se u
TIAN DONG (R adix Asp aragi )
BAI JI (Rhizoma Bletillae)
DA HUANG (Radix et Rhizoma
Copyright © 2013 SciRes. ENG
guide the clinicians in treatment of obesity.
2) Internal connections among networks
Through directed text mining, the internal connections
among TCM networks were also found. These internal
connections can be group e d into two major hierarchical
clusters. Each cluster is associated with one major kind
of patterns. The major treatment principles of TCM
treatment of obesity can be explored by text mining me-
thod and summarized in a succinct figure.
3) TCM Network might be useful in both TCM
clinical practices and scientific researches
The ne tw ork demonstrated in Figure 3 can be tak en as
a high level of abstraction on the treatment of obesity out
of dataset containing 27,442 recor ds. From the view point
of clinicians, it can be tak e n as a kind of refer e nce. F rom
the view point of basic researchers, this re sult might be
useful to illuminate some further studies in obesity.
5. Acknowledgements
This work was partially su pported by National Science
Foundation of China (No. 30902003 and 81072982).
2012' Traditional Chinese medicine Professional project
(No. 201207012).
[1] A. E. Caballero, “Endothelial Dysfunction in Obesity and
Insulin Resistance: A Road to Diabetes and Heart Dis-
ease,” Obesity Research, Vol. 11, No. 11, 2003, pp. 1278-
[2] K. M. Flegal, M. D. Carroll, B. K. Kit and C. L. Ogden,
Prevalence of Obesity and Trends in the Distribution of
Body Mass Index among US Adults, 1999-2010,” JA MA,
Vol. 307, No. 5, 2012, pp. 491-497.
[3] K. M. Flegal, M. D. Carroll, C. L. Ogden and L. R. Curtin,
Prevalence and Trends in Obesity among US Adults,
1999-2008,” JAMA, Vol. 303, No. 3, 2010, pp. 235-241.
[4] Y. Gao, S. Griffiths and E. Y. Chan, “Community-Based
Interventions to Reduce Overwei ght and Obesity in China:
A Systematic Review of the Chinese and English Litera-
ture,” Journal of Public Health (Oxford), Vol. 30, No. 4,
2008, pp. 436-448.
[5] F. X. Pi-Sunyer, “The Obesity Epidemic: Pathophysiolo-
gy and Consequences of Obesity,” Obesity Research, Vol.
10, No. Suppl 2, 2002, pp. 97S-104S.
[6] “Obesity: Preventing and Managing the Global Epidemic.
Report of a WHO Consultation,” World Health Organi-
zation Technical Report Series, Vol. 894, 2000, pp. i-xii,
[7] “Clinical Guidelines on the Identification, Evaluation, and
Treatment of Overweight and Obesity in Adults—The
Evidence Report. National Institutes of Health, Obesity
Research, Vol. 6, No. Suppl 2, 1998, pp. 51S-209S.
[8] Clinical Guidelines on the Identification, Evaluation, and
Treatment of Overweight and Obesity in Adults,” WMJ,
Vol. 79, No. 9, 1998, pp. 20-21, 24-25, 27-37.
[9] R. Ara, L. Blake, L. Gray, M. Hernandez, M. Crowther, A.
Dunkley, F. Warren, R. Jackson, A. R ees, M. Stevenson,
et al., “What Is the Clinical Effectiveness and Cost-Ef-
fectiveness of Using Drugs in Treating Obese Patients in
Primary Care? A Systematic Review,” Health Technology
Assessment Journal, Vol. 16, No. 5, 2012, pp. iii-xiv, 1-
[10] D. A. Galuska, J. C. Will, M. K. Serdula and E. S. Ford,
“Are Health Care Professionals Advising Obese Patients
to Lose Weight?” JAMA, Vol. 282, No. 16, 1999, pp.
[11] J. E. Harris, V. Hamaday and E. Mochan, “Osteopathic
Family Physicians Attitudes, Knowledge, and Self-Re-
ported Practices Regarding Obesity,” The Journal of the
American Osteopathic Association, Vol. 99, No . 7, 1999,
pp. 358-365.
[12] G. B. Lenon, K. X. Li, Y. H. Chang, A. W. Yang, C. Da
Costa, C. G. Li, M. Cohen, N. Mann and C. C. Xue: Ef-
ficacy and Safety of a Chinese Herbal Medicine Formula
(RCM-104) in the Management of Simple Obesity: A
Randomized, Placebo-C ontro lled Clinical Trial,” Evidence-
Based Complementary and Alternative Medicine, Vol.
2012, 2012, Article ID: 435702.
[13] C. Hioki, K. Yoshimoto and T. Yoshida, “Efficacy of
Bofu-Tsusho-San, an Oriental Herbal Medicine, in Obese
Japanese Women with Impaired Glucose Tolerance,” Cli-
nical and Experimental Pharmacology and Physiology,
Vol. 31, No. 9, 2004, pp. 614-619.
[14] N. A. Talpur, B. W. Echard, V. Manohar and H. G.
Preuss, “Influence of a Combination of Herbs on Appetite
Suppression and Weight Loss in Rats,” Diabetes, Obesity
and Metabolism, Vol. 3, No. 3, 2001, pp. 181-185.
[15] K. Ohno, H. J. Chung, I. Maruyama and T. Tani, “Bofut-
sushosan, a Traditional Chinese Formulation, Prevents
Intimal Thickening and Vascular Smooth Muscle Cell
Proliferation Induced by Balloon Endothelial Denudation
in Rats,” Biological & Pharmaceutical Bulletin, Vol. 28,
No. 11, 2005, pp. 2162-2165.
[16] M. Kang, J. W. Oh, H. K. Lee, H. S. Chung, S. M. Lee, C.
Kim, H. J. Lee, D. W. Yoon, H. Choi, H. Kim, et al.,
“Anti-Obesity Effect of PM-F2-OB, an Ant i -Obesity
Herbal Formulation, on Rats Fed a High-Fat Diet,” Bio-
logical & Pharmaceutical Bulletin, Vol. 27, No. 8, 2004,
pp. 1251-1256.
[17] G. Zheng, M. Jiang, X. He, J. Zhao, H. Guo, G. Chen, Q.
Zha and A. Lu, “Discrete Derivative: A Data Slicing Al-
gorithm for Exploration of Sharing Biological Networks
between Rheumatoid Arthritis and Coronary Heart Dis-
ease,” BioData Mining, Vol. 4, 2011, p. 18.
[18] M. Jiang, C. Zhang, G. Zheng, H. Guo, L. Li, J Yang, C.
Copyright © 2013 SciRes. ENG
Lu, W. Jia and A. Lu, “Traditional Chinese Medicine
Zheng in the Era of Evidence-Based Medicine: A Litera-
ture Analysi s,” Evidence-Based Complementary and Al-
ternative Medicine, Vol. 2012, 2012, Artic le ID: 409568.