Diabetes mellitus is a chronic progressive disorder that affects millions of
people worldwide with devastating human, social and economic impact (Watkins,
1993). Today, around 250 million people worldwide are living with Diabetes
and by 2025 this total is expected to increase to over 380 million (Hossain
et al., 2007). The prevalence of diabetes has reached epidemic proportions.
India has today become the diabetic capital of the world with over 20 million
diabetics and this number is projected to increase to 57 million by 2025 (King
et al., 1998; Sridhar, 2000). WHO predicts
that developing countries will bear the brunt of this epidemic in the 21st century.
Currently, more than 70% of people with diabetes live in low and middle income
countries. An estimated 285 million people, corresponding to 6.4% of the world's
adult population, live with diabetes in 2010. The number is expected to grow
to 438 million by 2030, corresponding to 7.8% of the adult population. While
the global prevalence of diabetes is 6.4%, the prevalence varies from 10.2%
in the Western Pacific to 3.8% in the African region. However, the African region
is expected to experience the relatively higher increase. Over 70% of the current
cases of diabetes occur in low and middle income countries. With an estimated
50.8 million people living with diabetes, India has the world's largest diabetes
population, followed by China with 43.2 million. The largest age group currently
affected by diabetes is between 40-59 years. By 2030 this record
is expected to move to the 60-79 age group with some 196 million cases (IDF,
2011). Diabetes mellitus is one of the major causes of premature illness
and death worldwide. Non-communicable diseases including diabetes account for
60% of all deaths worldwide.
Lack of sufficient diagnosis and treatment: In developing countries,
less than half of people with diabetes mellitus are diagnosed. Without timely
diagnoses and adequate treatment, complications and morbidity from diabetes
rise exponentially. Type 2 diabetes mellitus can remain undetected for many
years and the diagnosis is often made from associated complications or incidentally
through an abnormal blood or urine glucose test (Hossain
et al., 2007; Behnam-Rassouli et al.,
Diabetes costs-a burden for families and society: The financial burden
borne by people with diabetes and their families as a result of their disease
depends on their economic status and the social insurance policies of their
countries. In the poorest countries, people with diabetes and their families
bear almost the whole cost of the medical care they can afford. The World Health
Organization (WHO) predicted net losses in national income from diabetes and
cardiovascular disease of International Dollars (ID) 557.7 billion in China,
ID 303.2 billion in the Russian Federation, ID 336.6 billion in India, ID 49.2
billion in Brazil and ID 2.5 billion in Tanzania (2005 ID), between 2005 and
2015 (WHO, 2005).
History of diabetes mellitus: The ancient Indian scriptures Rig and
Atharva Vedas (around 5000BC) mention health and diseases including 20 types
of obstinate urinary disorders called Prameha. Prameha can be translated as,
passing of excessive urine. Over time an Indian system of medicine,
called Ayurveda, has evolved and two important sources for this impressive knowledge
and practice are the writings of physicians Charaka (Sharma,
1981) and Sushruta (Bhishagratna, 1991). It is believed
that Charaka and Sushruta practiced Ayurveda around 200BC. Ayurveda is a comprehensive,
theoretical, diagnostic and clinical system (Bodeker, 2001)
with an emphasis on prevention. Figure 1 shows a classification
of Prameha by people and by disease and we see that 4 types of Prameha are incurable
and the other 16 can either be cured or the condition of the person can be stabilised
on treatment. The diagnosis of a particular type of disease is sometimes made
from detailed examinations of urine.
The correspondence between diabetes mellitus and Prameha has been discussed
by Murthy and Singh (1989), Roy
et al. (1992) and Manyam (2004). The most
serious form of Prameha is Madhumeha where the disease is well advanced possibly
through an improper early management of less serious types of Prameha. Madhumeha
corresponds to diabetes mellitus. The symptoms described by Sushruta for a person
born with Madhumeha are similar to the symptoms of type 1 diabetes mellitus.
Ayurvedic descriptions for a person who acquires Madhumeha correspond to the
descriptions for a person with type 2 diabetes mellitus and these include family
history of diabetes, obesity, improper diet, lack of exercise etc. (Sharma,
The word diabetes mellitus was used in 2nd century AD to describe passing of
excess urine. Discovery that damaged pancreas and in particular damage to a
cluster of cells called Islets of Langerhans causes diabetes was made in the
19th century. Insulin was discovered in 1922 and subsequently injection of manufactured
insulin was a very major advancement in controlling diabetes in the western
allopathic system of medicine. At present, diabetes if detected early can be
treated quite successfully (Haque et al., 2011).
Prameha purvaroopa (pre-diabetes) signs and symptoms: Often, pre-diabetes
has no signs or symptoms. It is a condition, if left unattended; the person
might go on to develop diabetes. Allopathic system of medicine treats it as
a condition and medicines are prescribed to treat prediabetes. But
since it is only a hint that the person might develop diabetes in
future, it can be very well reversed with suitable lifestyle changes and by
including some very simple herbs in diet. Ayurveda explains the following pre
diabetes symptoms: Coating (on teeth) and secretion (from eyes/nose), depleting
oral hygiene, burning sensation in feet and palms, a feeling of stickiness in
whole body, lethargy of mind and body etc.
|| Classification of prameha by people and disease
According to modern parameters, a fasting blood sugar level of 100-125 mg dL-1
and post prandial blood sugar level of around 140 mg dL-1 is considered
as pre diabetes (Bhishagratna, 1991).
Ayurveda for prevention of prameha and madhumeha (Type 2 diabetes mellitus):
Ayurveda is a traditional Indian system of medicine that evolved in India over
a very long period of time with roots in the ancient sacred Vedas of the Indus
river civilization (Svoboda, 1992). Progress in Ayurveda,
greatly hindered by the British rule in India, has been very marked since India
became independent in 1947. At present, Ayurveda is a part of the national health
system in India and the interest in Ayurveda is rapidly spreading to a number
of countries across the globe. The following eight subspecialties of Ayurveda
indicate the wide scope of Ayurvedic medicine.
||Shalya tantra-general surgery
||Kaumar Bharitya-paediatrics and obstetrics/ gynaecology
||Rasayana tantra-nutrition, detoxification and rejuvenation
||Vajikarana-sexual health and aphrodisiacs
In Ayurveda, the emphasis is given on establishing and maintaining the balance
of the various systems within the human body, rather than focusing on the treatment
of individual symptoms. A fundamental concept is that a human being has an inherited
constitution which can be described by various combinations of three fundamental
energies called doshas. The three doshas are Vata, Pitta and Kapha.
A person with a good inherited constitution can become ill due to imbalances
in the doshas and a basic aim of Ayurvedic treatments would be to remove the
imbalances in doshas. This concept of disturbed balance of doshas could mean
that with Ayurveda two persons with the same outwardly visible symptoms may
require very different treatments. In general, Ayurvedic treatments include
a typical combination of: diet, exercise, massage, herbal remedies, yoga and
meditation (Manyam, 2004; Hankey,
Ayurveda treatment for prameha: An excellent review provides wide range
of information about treatment of Ayurveda for the care of people with diabetes
(Hardy et al., 2001). The first step in the treatment
however is to determine the essential prakruti (constitution) of the individual
which depends on which dosha is predominant and will reflect the energies and
tendencies within. Knowledge of prakruti allows the selection of appropriate
habits and lifestyle to enhance the maintenance of health and will suggest:
||The most effective means to prevent disease from arising
||The prognosis of both simple and complex diseases
||The most effective treatment
||The recuperative capacity of an individual
||The best dietary regimen for that individual
||How to compound herbal formulations to the best advantage
||The most beneficial rejuvenative program
In Ayurveda, treatment structure can broadly be classified as follows:
Shodhana-purification treatment: This aims at removal of the causative factors of somatic and psychosomatic diseases. The process involves internal and external purification through the use of Panchakarma.
Shamana-palliative treatment: Shamana involves the suppression of vitiated doshas by which the disturbed dosha returns to normal without creating an imbalance of other doshas. This is achieved by the use of appetisers, digestives, exercise, exposure to sun, fresh air etc. In this form of treatment, palliatives and sedatives are used.
Pathya vyavastha-diet and activity appropriate to ones path (pathya): Recommendations are made with respect to diet, activity, habits and emotional status with a view to impeding pathogenetic processes. The emphasis is on finding a diet that stimulates agni and optimises the digestion and assimilation of food in order to ensure strength of the dhatus (tissues).
Nidana parivarjan-avoidance of disease causing factors: Known disease causing factors in the diet and lifestyle of the patient are avoided in order to determine the aggravation of the associated doshas.
Sattvavajaya- psychotherapy: This mainly concerns the area of mental disorders and includes a wide range of approaches to restrain the mind from desires for unwholesome objects and cultivate courage, memory and concentration.
Rasayana-rejuvenation therapy: Healthy rasa dhatu is essential to produce healthy blood and other tissues.
Rasayana is the process of replenishment of the quality and quantity of the bodys fluid. Rejuvenative substances enhance ojas, prevent the premature damage to body tissues and promote an individuals health through strength and vitality.
Also the other treatment options used in Ayurveda are: Dhyana-meditation, Ahar-diet,
Abhyanga-self massage, Aushadhi chikitsa-herbal therapies, Dincharya-daily routine,
Ritucharya-seasonal routine, Anashana-fasting, panchakarma The five purification
therapies, Yoga-Stretching exercise. In addition, there are several types of
glucose-lowering plant drugs in Ayurveda which have been tested for their efficacy
in the treatment of prameha (Joseph and Jini, 2011;
It is absolutely clear that Ayurveda cannot replace allopathic medicine for
the care of people with diabetes mellitus. Examples of the strengths of allopathic
medicine are: insulin injections for type 1 diabetes mellitus; dialysis; and
kidney transplants. However, Ayurveda has very important contribution in the
prevention of type 2 diabetes mellitus (Sharma and Patki,
2010). As Fig. 1 shows according to Ayurveda there are
20 forms of prameha (urinary disorders). Four are due to Vata, 6 result from
Pitta and 10 are caused by Kapha. Prameha is mainly caused by Kapha. All forms
of prameha if not treated, eventually develop into Madhumeha (diabetes mellitus).
This detailed classification creates a good scope for the prevention of diabetes
by interventions before Prameha and before Madhumeha. In Ayurveda a collection
of pre-disease signs and symptoms is called Prameha Purvaroopa and for Prameha
there are many such signs and symptoms. Ayurvedic interventions for prevention
of Prameha and Madhumeha could involve herbal medicines, massages, nutritional
advice, yoga etc. and they would take the persons constitution, family
history and prameha type into account.
NATURAL HISTORY OF PRAMEHA
The natural history model of Prameha has been formulated using expert opinion
of practicing Ayurveda physician. Two differing states of Madhumeha were explained
by the Ayurveda physician: 1) a mild form that consists of sweetness of body,
urine and sweat in addition to the symptoms of any of the other 19 types of
kaphaja, pittaja or vataja pramehas and 2) severe madhumeha, the 20th type of
prameha described under vataja prameha which is incurable and can lead to death;
this can be compared to diabetes mellitus (Manyam, 2004).
Further discussions led to the development of the natural history given in Fig.
2 which illustrates a model for the progression of patients with Prameha.
Risk groups for prameha: The Ayurveda physician suggested that the most
significant risk factor for acquiring Prameha is the persons levels of
obesity and other important risk factors are diet and life style. In the western
system, obesity is an overall body condition measured typically by the body
mass index. In Ayurveda, in addition to an overall appearance (overall obesity)
fat deposits over various parts of the body are also important and these distributed
deposits can be described as partial obesity. Thus in Ayurveda obesity is summarised
as the overall/partial condition. These risk factors determine the type of Prameha
that a person could be at risk of developing. For example, an excessively thin
person has the risk of contracting Vataja Prameha regardless of diet and life
style. Excessively fat/fat people have the risk of developing Kaphaja Prameha,
Pittaja Prameha and Madhumeha Tridoshaja depending on diet and lifestyle. The
Ayurveda physician suggested the use of eight risk groups defined by overall/partial
obesity, diet and life style. Quantifying the risk of developing the prameha
in each risk group imposed a formidable challenge as no numerical data was available.
|| Natural history of prameha
A persons risk group can be easily identified by an Ayurveda physician
(Elder, 2004). Table 1 shows the eight
risk groups and the rough estimates of corresponding risk of developing Prameha
after using the appropriate weightings (weight 1 for lower risk and weight 8
for higher risk etc.). It is interesting to note that excessively thin people
have the highest risk of developing Prameha.
Transition probabilities and distributions of transition times of stay:
The required transition probabilities and the durations were obtained through
expert opinion (Practicing Ayurveda Physician). The Ayurveda expert was able
to provide the estimates for the severest (shortest dwelling time) and the mildest
(longest dwelling time) cases for each state. Weibull distribution was chosen
as being the most appropriate statistical model to model the necessary transition
times in each state. We estimated the parameters of Weibull distribution using
percentile points (Marks, 2005). The estimations of
minimum and maximum dwelling times have been used as the 5 and 95th percentile
points in the algorithm to find the parameters of the Weibull distribution.
Table 2 shows the estimated parameters of the Weibull distributions
for the natural history transitions without any preventive treatments.
|| Prameha risk groups
The two parameter Weibull model is given by the following mathematical equation:
Interventions for prevention of prameha and madhumeha: The Ayurveda
physician explained the various interventions for preventing Prameha at the
Prameha Purvaroopa stage and the interventions for preventing Madhumeha at the
Prameha stage. Five intervention programmes chosen for evaluation by the Prameha
model are listed below.
||Treatment at no prameha stage for all (100% coverage)
||Treatment at prameha purvaroopa stage for all (100% coverage)
||Treatment at no prameha stage and Prameha purvaroopa stage for all (100%
||Treatment at no prameha and prameha purvaroopa stages for high risk groups
1, 3 and 5
These interventions would mean longer stays in the durations of stay in the
better stages with corresponding changes in the parameters of the Weibull distributions.
The approximate durations of these longer stays along with the estimate of cost
of interventions were provided by expert opinion (Ajgaonkar,
1984; Upadhayay and Pandey, 1984).
A cost-effectiveness computer simulation model for prameha: The computer
simulation models have been used in health research and policy since the 1960s
(Elveback and Varma1965: Handyside
and Morris, 1967).
|| Weibull parameters for transition time in years.
In a review of simulation modeling in population health and health care delivery
prior to 2000, Fone et al. (2003) identified
near about 182 papers covering a wide range of topics, including hospital scheduling,
communicable diseases, screening, cost of illness and economic evaluation (Fone
et al., 2003).The approach of using computer simulation modeling
to evaluate the beneficial effects of Ayurveda is a novel one. To our knowledge,
as yet no work has been published in modelling disease processes as described
in Ayurveda. An operational model for prameha has been developed. This detailed
simulation tool, at the level of individual patients, has been designed for
use by clinicians for cost-effectiveness evaluations of various intervention
and patient care options. Further, it has been shown that the operational models
can be powerful tools for making effective decisions about effective and efficient
health care (Shahani, 1996; Sayyad
et al., 2002; Sayyad et al., 2011).The
approach taken ensures that the model incorporates the evolved risk groups in
the community, together with the natural history of the underlying disease and
options for early detection and treatment of patients (Shahani
et al., 1994, 2008). The model was built
using SIMUL8 (Simul8 Corporation, Boston, USA), a simulation software and enhanced
with MS-Excel front and back-end interface (Harper et
al., 2003). SIMUL8 is a computer package for discrete event simulation.
It allows the user to create a visual model of the system under investigation
by drawing objects directly on the screen. Typical objects may be queues or
service points. The characteristics of the objects can be defined in terms of,
for example, capacity or speed. Once the system has been modelled a simulation
can be undertaken. The flow of work items around the system is shown by animation
on the screen so that the appropriateness of the model can be assessed. When
the structure of the model has been confirmed, then a number of trials can be
run and the performance of the system may be described statistically. Statistics
of interest may be average waiting times, utilisation of work centers or resources,
etc. (Shalliker and Ricketts, 2002). Figure
3 shows a screenshot of the prameha model built in SIMUL8.
Illustrative results from the model: The simulation model of the natural
history incorporates eight prameha risk groups (Table 1),
transition times and transition probabilities among the different states of
Fig. 2, intervention options and the costs of the interventions.
Information on transition time and the probability of transition and the cost
of treatment for the different risk groups has been obtained using the expert
opinion. The model takes a cohort of people aged more than 30 years through
time. Both the cohort size and time horizon are user-defined. The transition
from No Prameha to Prameha Purvaroopa is governed by each risk groups
associated probability of developing Prameha (Table 1). Once
a patient has made this initial transition, the patient enters the natural history
model and is simulated to progress through the states (death is the final state
they can reach). Dwelling times in each state are sampled from the appropriate
statistical distributions, as fitted to the information obtained through the
expert clinical opinion, as shown in Table 2. For example,
the time from No Prameha to Prameha Purvaroopa (in years) follows a Weibull
distribution with parameters α = 5.0 and β = 3.6 for risk group 1.
Movement among states is governed by user-defined probabilities.
The model allows for the evaluation of clinical interventions (Ayurveda treatments)
to patients within Prameha Purvaroopa and/or Prameha states (Harper
et al., 2003). The effects of these interventions are modelled through
changes to the transition probabilities and dwelling times in each stage. For
example, patients with Prameha Purvaroopa receiving treatment might subsequently
stay within the same state for the remainder of their life, thus avoiding the
transition to Prameha. Associated costs of interventions are defined as the
costs per patient per year (in Rupees) and the model calculates the corresponding
health care costs for each intervention programme (Shahani,
Figure 4 shows the MS-Excel front-end screen used to define the risk groups for Prameha and any associated interventions. The user is allowed to change any of the following parameters: percentage of patients in each risk group, percentage from each group likely to develop Prameha, percentage of patients from each group receiving treatment in Prameha prurvaroopa and Prameha states and associated costs per patient for treatment (in Indian Rupees (Rs)). The flexibility of the developed tool allows clinicians to evaluate different treatment options targeted at different risk groups.
The cost of treatment estimates: The Ayureda Physician provided the
information on the frequency of treatment at no prameha. Vamana and /or virechana
therapy may be done once a year in healthy people which costs roughly Rs 2250
each. In healthy people, a non-medicated oil basti may also be used. In general
one session incorporates 7 sittings costing Rs 700 at the rate of Rs 100 each.
A person may have a maximum of 14 sittings each year. For treating people at
prameha purvaroopa intervention adapted may be basti that uses medicated
oil which costs Rs 150 per sitting.
|| A screenshot of the prameha model
|| Defining intervention strategies: the model front-end
In addition there are consultation and medication charges that varies considerably
across different parts of India. Also Ayurveda physician may advise the investigations
of modern clinical risk factors (such as fasting glucose, lipid profile etc.),
the cost of such investigations has also been included in the model (Manyam,
Intervention case studies: Results from the Prameha model were obtained
through simulations. A cohort of 5000 men and a cohort of 5000 women were used
for the model that runs over a period of 40 years. The following response variables
were recorded for each scenario: the total costs of the intervention program
and the number of patients who reach at the different states of the prameha
over the 40 years (Harper et al., 2003).
|| Evaluation of ayurvedic preventive treatments for men No.
and % of men in various stages of the model after 40 simulated years
|| Evaluation of ayurvedic preventive treatments for women No.
and % of men in various stages of the model after 40 simulated years
Table 3 and 4 show the predicted evaluations
of the selected intervention options for men and women, respectively.
We see that as expected, interventions reduce the number and the percentages of people reaching the more serious stages of Prahema. For example with treatment 4 (treating all men at no Prameha stage and Prameha Purvaroopa) the percentage of men reaching Kaphaja Prameha would reduce from 0.7% (the case of no treatment) to 0% and the cost would be Rs 866 million over 40 years. The corresponding reduction for treating high risk men only would be from 0.7 to 0.1% at a cost of Rs 536 million. For severe Madhumeha the reductions would be from 7.2 to 3.9% for 100% coverage and from 7.2 to 5.0% for treating high risk men only. It is interesting to note that if all men at Prameha Purvaroopa stage are treated then only 5.7% of the population of men would develop severe madhumeha and the cost of this intervention over 40 years would be Rs 144 million only.
Similarly if all women at prameha purvarroopa stage are treated then only 5.5% of them would develop severe madhumeha and the cost of this intervention over 40 years would be Rs 138 million only which is much lesser than the cost (Rs 941 million) of treatment option 4 (treating all women at no Prameha stage and Prameha Purvaroopa stage).
Model validation: The model validation is an essential part of the model
development process if models are to be accepted and used to support decision
making. The methodology of model validation has been discussed by Fone
et al. (2003) Philips et al. (2004)
and Shah et al. (2010). Sargent
(2005) described the general approach to verification and validation
of computer simulation models and specific techniques that can be used for these
purposes (Sargent, 2005). The term model validation
can be simplified by recognizing that the evidence supporting a given use of
a model can be obtained by examining: 1) the process of model development; 2)
the performance of the model and 3) the quality of decisions based on the model
(Kopec et al., 2010). The verification of the
model has been achieved on careful experimentation of the simulation, by tracing
particular entities through the model and noting the performance measures to
see if the changes visible in the simulation are reasonable in light of the
changes made to the users input. Expert opinion of Ayurveda physician
has guided significantly the entire validation process of model development
and the decision making based on the model (Venkata Raju,
This study has demonstrated the value of a multidisciplinary study of the care of people with prameha. The systems modelling approach adopts appropriate clinical knowledge, mathematical modelling, together with the development of easy to use models on personal computers.
India currently witnesses the escalating epidemic of diabetes and related disorders
than any one country and so there is an urgent need to prevent it. It is important
to understand that in the absence of any real data, expert opinion and a dynamic
approach has been used in almost the entirety of the model. Much effort has
been made in incorporating reality into the model by gaining as much realistic
numerical data as possible through lengthy discussions with the Ayurveda consultant.
Quantitative measures of the risk of suffering from Prameha have been formulated using the expert opinion which can be of help in the care of people with Prameha. These Prameha risk groups are then fed into a developed simulation model, at the level of individual patients, for cost-effectiveness evaluations of various intervention and patient care options. The approach taken ensures that the model incorporates the evolved risk groups in the community, together with the natural history of Prameha and options for early detection and treatment of patients. Case studies demonstrate how the model may be used to evaluate different interventions and patient care options.
Thus, in this study we demonstrate the clinically and economically beneficial effects of the Ayurveda treatment at the Prameha Purvaroopa (pre-diabetes) stage which would facilitate the prevention of diabetes in a developing country such as India. It is therefore important to create an awareness among Indians regarding the signs, symptoms and treatment of pre-diabetes.
We sincerely thank Dr. Mark Elder from SIMUL8 Corporation, Boston, USA for sponsoring us free Licence Simul8 software. We also thank the referees for their valuable suggestions.