Scientific Research

Use of Homeopathy in Treatment of Diabetes: Prevalence and Correlates

The growing incidence of chronic and incurable diseases has led to the increased use of complementary and alternative medicine (CAM) in recent years. Homeopathy is one of the most popular CAM systems of treatment. Recent observational study supports the use of Homeopathy for the management of diabetes; therefore, it is important to know the prevalence and pattern of use of homeopathy among diabetic patients. In this study, the author systematically reviewed the published research papers on prevalence and correlates of use of homeopathy in diabetic patients. The prevalence of diabetes ranges from 0.7% to 12.9% on the basis of 4 papers reviewed. The prevalence is higher in developing country like India. Levels of education, the desire for early and maximum benefit and geographic area were found as the co-related factors in use of homeopathy in this study. A large scale population-based study is needed to gather deeper knowledge about prevalence and correlates of use of homeopathy in diabetic patients for the better management of diabetes – one of the most threatening chronic diseases of our time.

Keywords: Homeopathy; Diabetes; Prevalence; CAM


Complementary and alternative medicine (CAM) is gaining popularity throughout the world, with an increase in the number of practitioners as well as the number of patients consulting them (BMJ, 1996). Population-based studies conducted in industrialized countries such as Australia, Scotland, UK, Taiwan, Singapore and the United States of America (USA), report that one-half to two-thirds of adults use CAM (Emslie et al., 1996, MacLennan et al., 2002, Lew-Ting 2003, Lim et al., 2005, Tindle et al., 2005).  The growing incidence of chronic and incurable diseases has led to the increased use of CAM in recent years (Eisenberg et al., 1998; Dunning, 2003). Diabetes mellitus (DM) is one such chronic and incurable disease which is highly prevalent worldwide. It is one of the major burdens of diseases of the twenty first century (WHO-IDF, 2004).  Worldwide, every ten seconds, at least one person dies from diabetes and its complications (Siegel & Narayan, 2008).

Conventional medicine for diabetes has been geared toward regulating blood glucose with a combination of dietary modification, insulin and/or oral agents, maintaining ideal body weight, exercising regularly and self-monitoring of blood sugar (WHO-IDF, 2004). Good glucose control can, however, be difficult for many people with diabetes, because these conventional treatment plans require change of behaviour and lifestyle (Dunning, 2003). Due to the chronic nature of the disease, the debilitation of complications, the threat of death and the complexities of treatment plans, people with diabetes often work proactively to manage their condition, optimize their health and  try to alleviate complications through use of CAM (Dunning, 2003, Bell et al., 2006).

Homeopathy is one of the most popular CAM systems of treatment (BMJ, 1996). A recent observational study (Pomposelli et al., 2009) reported that “complementary homeopathic therapy of diabetic neuropathy was feasible and had promising effects in symptom scores and cost savings“; the study also concluded that “it is possible to treat patients with homeopathy, monitored by the conventional diabetes specialist, without any major problem of compatibility between the two forms of therapy“. However, while there is evidence in support of the use of homeopathy for the management of diabetes, it is important to know the prevalence and pattern of use of homeopathy among diabetic patients. This study aims to investigate the prevalence and correlates of use of homeopathy in diabetic patients.


This study is a comprehensive literature review of published studies in peer reviewed journals. In this review the research question is: What is known about prevalence and correlates of use of homeopathy in diabetic patients? To answer the research question the author searched the available studies with pre-requisite criteria. Then the author critically examines those studies, and finally summarizes the findings of the selected studies in a descriptive manner.

To achieve this aim, the research question has been broken down into the following objectives –

·         To investigate the prevalence of use of homeopathy in diabetic patients

·         To know the pattern of the use of homeopathy in diabetic patients

·         To find out the correlates of use of homeopathy in diabetic patients

An extensive search was performed at the following electronic databases for published (in English language only) studies: AMED (Allied and Complementary Medicine), Ovid MEDLINE, EMBASE, PubMed; BioMed Central; EBSCOhost (Academic Search Complete & CINAHL Plus). Diabetes, homeopathy (& homoeopathy), prevalence, CAM, complementary medicine, alternative medicine and pattern of uses are the key words which were used to search the electronic database. References of the primarily obtained article were also screened for eligible studies. The inclusion and exclusion criteria applied in this study were as follows:

Inclusion criteria

·        Original (primary) research articles

·        Studies published in peer-reviewed journal

·        Studies with any design, reporting prevalence of use of homeopathy

Exclusion criteria

·        Studies other than survey were excluded

·        Studies not in English Language

·        Studies that reported combined use with other CAM, but where separate quantitative data of prevalence of use of homeopathy wasn’t available.

Data from all selected studies were extracted in a summary table under the following headings:

·        Study type (survey method)

·        Study site

·        Study year

·        Sample Size

·        Sampling procedure

·        Demography of the sample (age, gender, ethnicity, socioeconomic status and educational status)

·        Prevalence of use of Homeopathy

·        Factors associated  with the use of homeopathy

Quality of the eligible studies was assessed according to the review article of Loney & Stratford (1999). Critical examination of the studies was carried out according to the guidelines of Loney et al (1998).


Literature search yielded fourteen studies. Five studies were excluded as they reported prevalence of overall CAM but homeopathy was not included (Egede, 2004; Schoenberg et al, 2004; Lind et al, 2006; Hasan et al, 2009 and Dunning, 2003). The study conducted by Garrow & Egede (2006a) was excluded as that did not report prevalence of homeopathy separately; this study reported acupuncture, Ayurveda, biofeedback, chelation, energy healing or Reiki therapy, hypnosis, massage, naturopathy, and homeopathy combined into an “other” group because very few respondents with diabetes used these treatments (as they proclaimed in their study). Another study (Garrow & Egede, 2006b) was excluded as it did not report prevalence of homeopathy, but reported association between complementary and alternative medicine use, preventive care practices and use of conventional medical services among adults with diabetes. The study conducted by Pagán & Tanguma, (2007) explored affordability and use of complementary and alternative medicine by adults with diabetes and that was excluded from the review as prevalence of use of homeopathy in diabetic patients was missing. Another study was excluded as it was a review (Chang et al, 2007) and not a primary study.

Lastly, five studies met the inclusion criteria; and were selected for final review. A close examination revealed that two papers (Mehrotra et al, 2004; Kumara et al, 2004) out of five selected reported the same data from a single study. Among these two papers the former one (Mehrotra et al, 2004) was included in this study because of its relevancy, while the latter (Kumara et al, 2004) was excluded to avoid duplication.  Finally, four studies were included for this study. Identification details of the studies included in this review are given in table 1.

Table 1 Studies included for analysis in this review
Running head First author Journal Publication year
Prevalence of complementary medicine usage within Leese G.P. Practical Diabetes International 1997
Use of Complementary and Alternative Medicine Yeh G.Y. American Journal of Public Health 2002
Use of complementary and alternative Mehrotra R. The National Medical Journal of India 2004
Use of complementary and alternative medicine Dannemann K. Pediatric Diabetes 2008

Three studies reported both prevalence of use of homeopathy and determinants of use in diabetic patients (Mehrotra et al, 2004; Dannemann et al, 2008). The last study (Yeh et al, 2002) reported only the prevalence of use of homeopathy among diabetic patients. Only one study was a nationally representative survey (Yeh et al, 2002), others were sporadic surveys. One survey was conducted in India, one in USA, one in UK and the other one in Germany.

Two studies included diabetic patients of all ages (reference), one study included only patients over eighteen (reference) and another study (reference) was conduct among diabetic children age range 1 to 18. Samples from every  socio-economic status were included in all studies.

Prevalence of use of homeopathy among diabetic patients varied from 0.7% to 12.9%.  Lowest prevalence (0.7%) was reported in USA and was a national representative telephone survey. On the other hand, highest (12.9%) usage was found at India. Another two studies from developed countries, United Kingdom and Germany, found the prevalence of use of homeopathy in diabetic patients 4.5% and 7.9% respectively. In Germany, homeopathy is the CAM system of treatment most used by diabetic patients.

None of the studies reported determinants of use of homeopathy specifically, but just of overall CAM. However, determinants of use of CAM such as high levels of education and the desire for early and maximum benefit, have been reported (Mehrotra et al, 2004). Geographical areas were also found significant in use of CAM, for example higher usage of CAM was found in West Germany compared with the East Germany (Dannemann et al, 2008). It has also been reported that patients who suffer from diabetes for a long time are more likely to perceive benefit from CAM,  therefore those diabetic patient use and recommend CAM more than the patients who are suffering for a short time. Details of finding showed in table 2

Table 2 Result
Study Study Setting Study site/year Sample Size/procedure Age of the Participants use of Homeopathy Co-related factors
Yeh et al, 2002 at USA Telephone survey Nationally representative / Nov ’97 and Feb ’98 2055 respondents


18+ 0.7 % Not reported
Leese et al, 1997 at UK Questionnaire interviewed by a research nurse Diabetic Clinic

Study period not reported

328 approached, 246 agreed to be interviewed./ Convenience sample 16 to 86

Mean 52±1

4.5% Previous use of CAM

Patient who had diabetes for long were more likely to perceive benefit from CAM

Mehrotra et al, 2004 at India Semi-structure interview Outpatient endocrine clinic /1999-2001 493/systematic random sampling All age

Mean age 48.8 years


12.9% The desire for early and maximum

Benefit, high levels of education (p=0.02)

Dannemann et al, 2008 at Germany self-completed survey In four pediatric diabetes

centers in Germany /

Nov ’04 to Dec ’05.


Cluster sampling

1-18 yrs. mean

11.9  3.8 yr

7.9 % Significant higher usage of CAM was found in West Germany compared with the East (25.0 vs. 14.0%, p , 0.05).

One study (Dannemann et al, 2008) that explored use of CAM in children with type 1 diabetes, found the majority of CAM users were motivated by the wish to try everything and a conviction that CAM has less side effects, while their expectations were an improved well-being of the child and the prevention of microvascular and neurological complications. This study did not report whether these findings were statistically significant or not.

Critical assessment of methodology and quality

Critical evaluations of the studies included in this review were done according to the guidelines of Loney & Stratford (1999) and Loney et al (1998). Among eight parameters of the guidelines, the “sample size” parameter was adjusted for this review, as the original guidelines referred to dementia which is a relatively more rare disease than diabetes. Using a conservative sample size estimate of proportion for this review of dementia, prevalence of use of homeopathy in diabetic patients, (assumptions based on Mehrotra et al, 2004) the adequate sample size has been set at ?450. Detail scoring for methodology of the studies is shown in table 3, and discussed below.

Table 3 Quality assessment

Methodological Parameter


1.    Random sample or whole population 2.    Unbiased sampling frame (i.e. census data) 3.    Adequate sample size or calculate sample size 4.    Measures were the standard 5.    Outcomes measured by unbiased assessors 6.    Adequate response rate (70%), refusers described 7.    Confidence intervals, subgroup analysis 8.    Study subjects described Total Point
Dannemann et al, 2008 1 0 0 1 0 0 1 1 4
Mehrotra et al, 2004 1 0 1 1 0 0 0 1 4
Yeh et al, 2002 1 1 1 1 0 0 1 1 6
Leese et al, 1997 1 0 0 1 0 1 1 0 4

A survey (observational study) is the appropriate study design to determine the prevalence of particular health problems or use of any therapy. If the whole population of interest is not surveyed, then the best sampling technique is random (probability) sampling of persons from a defined subset of the population. Stratification (sampling purposely from subgroups) may be required to appropriately represent subgroups (O’Rourke, 2005, Sim & Wright 2000). All the studies included in this review are survey and the sampling procedure is appropriate (Table 3, parameter 1). For larger surveys, cluster sampling is sometimes used as employed by Dannemann et al, (2008) one of the studies included in this review. In cluster sampling, groups of individuals are selected as the survey unit. Dannemann et al, surveyed four pediatric diabetes centerers in Germany, two from west Germany (Bonn and Stuttgart) and two from East Germany (Leipzig and Berlin).

Type of sampling frame from which subjects are selected is important (Hennekens & Buring 1987). Census data provide one of the few data sets from which one can draw a sample that is thought to have minimal bias, since certain groups of persons are thought not to be excluded as they might be in an electoral list or telephone list (Sica, 2003). Only one study (Yeh et al, 2002) has used census data for sampling among the studies included in this review (Table 3, parameter 2). The rest of the three studies were conducted in a diabetic clinic, limiting their generalisability over a greater population.

A large sample size produces narrow confidence limits, which is undoubtedly important if the prevalence of a given condition is low. Small sample sizes produce large confidence intervals, making the findings less precise. It is critical to be as confident as possible that any changes in health care policy are based on results that did not occur by chance due to probability sampling inadequacy. (Slavin, 1995) Sample size required to estimate a proportion with a specified degree of precision (for example 95% confidential intervals) can be calculated (Katchigan, 1986: pp 158-9). Using a conservative sample size estimate of proportion for this review of dementia, prevalence of use of homeopathy in diabetic patient (assumptions based on Mehrotra et al, 2004) the adequate sample size has been taken as ?450. In only two studies adequate samples have been surveyed (Yeh Table 3 parameter 3).

It is important that published studies describe the measurement units well enough so that the outcome measures can be compared (Grimes & Schulz, 2002). Since health problems can be defined in many ways, the measurement of the problem must be the best possible one (Greenhalgh, 2006). In the prevalence of use of homeopathy in diabetic patients, surveys are based on interview and self reported prevalence was recorded. In cases with this type of self reported prevalence, recall bias is a potential problem that may distort the result of the study. Recall bias occurs when exposure information is differentially misclassified for subjects with and for those without the condition under examination (Rothman, 2002: pp 94-112.). Recall bias can be particularly problematic in studies where subjects are interviewed to collect information (Sica, 2003). In this review, all the included studies were scored 1 point for appropriate measurement (table 3 parameter 4). However, Dannemann et al, (2008) should get extra weight for this parameter as they mention recall bias as the limitation of the study, which indicates that the researchers were aware of this bias.

Considerable judgment by assessors is required to determine the presence of some health outcomes under scrutiny; thus it is best that trained assessors are independent and not aware (i.e. blinded) of the subjects’ clinical status and the purpose of the study. It is important that the subjects under assessment include those thought to be negatives as well as positive (Lijmer et al, 1999). In case of the studies under review, no studies reported anything about the blinding of the interviewer (table 3 parameter 5). It could introduce serious bias if the interviewers are aware of the study’s purpose prior to the study, as the interviewers may have an inclination for or against homeopathy.

The greater the numbers of selected subjects who are lost to follow-up, the less valid the estimates are. A response rate in population surveys of two thirds to three quarters has been suggested to be generalizable to the population samples (Marshall, 1987). In this review a response rate of 70% has been chosen as acceptable. Since a large number of dropouts, refusals or “not founds” among the subjects selected may jeopardize a study’s validity, the authors should describe the reasons for non-response and compare persons in the study with those not in the study as to their socio-demographic characteristics (Response bias – Sica, 2003). If the reasons for non-response seem unrelated to the outcome measured and the characteristics of those individuals not in the sample are comparable to those in the study, researchers may be able to justify a more modest response rate (Loney et al, 1998). Among the four studies included in this review, only one study reported adequate response rate (table 3 parameter 6), while other studies did not even described the refusers.

The seventh parameter of the quality assessment is the estimate of prevalence of use of homeopathy in diabetic patients given with confidence intervals (CI) and in detail by subgroup or not. The quantitative results from studies of prevalence are proportions or rates over a fixed period of time (Szklo & Nieto, 2000). The prevalence rates found in studies reviewed provide only estimates of the true prevalence of use of homeopathy in the larger population. Confidence intervals then indicate the level of confidence one can have in the estimates and their range (Oliveira et al, 2006). Since some subgroups are very small, 95% confidence intervals have been taken as standard. Among the four studies included in this review only one study (Mehrotra et al, 2004) did not mention CI nor describe the subgroup.

Certain diseases and health issues are known to vary in prevalence across different geographic regions and population sectors. The status of homeopathy also varies by country and region (ECH, 2007).  With some health problems, rates for women may differ from those for men. Moreover, socio-demographic variables, such as educational status, may vary between countries. Therefore, the study sample needs to be described in enough detail that other researchers can determine if it is comparable to the population of interest to them. Furthermore, the socio-demographic characteristics of the subjects must be reported in order to understand the applicability of the results. Similarly, providing a comparison of study participants with those who refused or were ineligible can help others determine for whom the study group is representative. All studies included in this review have described their subjects and refusal except one study (parameter 8).

Overall, most of the studies (3 out of 4) scored 4 while the highest score was 8 for eight methodological parameters. In that sense, most of the studies are of average quality. Only one study scored 6 (Yeh et al, 2002). Sampling method of all the studies was unbiased, but no studies measure the outcomes by unbiased assessors (no blinding).

Key findings

Discussions & Conclusion

In this review, the prevalence range of use of homeopathy among diabetic patients, based on the findings of four papers, was 0.7 % to 12.9% with the lowest prevalence found in the USA and the highest in India. The reported range is in accordance with the report of ASSOCHAM (The Associated Chambers of Commerce and Industry of India) “Homeopathy is an effective means of treating chronic ailments. These ailments include …… diabetes, and obesity.” “.. reasons for growing homeopathy market in India, saying that homeopathy, besides providing an effective means of treating chronic ailments is also available and easily accessible online to over 1 crore patients across the country.” (ASSOCHAM, 2007).

Level of education increases the probability of use of homeopathy for diabetes and goes against the traditional belief that people use CAM (including homeopathy) due to fewer side effects with this type of treatment. Geographic area is also a significant predictor for use of CAM (and homeopathy). A large scale population-based survey or cohort study is needed to find out why diabetic patients use homeopathy, and what their expectation of homeopathy are, for the better management of diabetic patients.

The interpretation of the findings of this review are subject to a series of limitations. First of all, as any other systematic literature review, data was not collected by the author, which implies an over-reliance on the veracity of the data published. Secondly the number of papers included in analysis were only four, which prevents the author from producing strong statements about the final results. No meta-analysis was attempted for which the results of pooled data are not available here. Also, some of the inclusion/exclusion criteria can be interpreted as biases, e.g. only published articles and only studies published  in English. In spite of all these limitations, the author believes that this review will encourage more population based studies and reviews, to find an overview of the prevalence of use of homeopathy and its pattern and correlates in diabetic patients.


ASSOCHAM – The Associated Chambers of Commerce and Industry of India (2007) Homeopathy Emerging With Big Bang, Likely To Be Rs. 26 Billion Industry: ASSOCHAM, Sunday, December 09, 2007 [Online] Available at: [Accessed on: 10/07/2009]

Begg CB, McNeil BJ. (1988) Assessment of radiologic tests: control of bias and other design considerations. Radiology; 167: pp565 – 569.

Bell R.A., Suerken C.K., Grzywacz J.G., Lang W., Quandt S.A. & Arcury T.A. (2006) Complementary and alternative medicine use among adults with diabetes in the United States. Alternative Therapies in Health and Medicine; 12(5): pp16-22.

BMJ (1996) Complementary medicine is booming worldwide. BMJ; 313: pp131-133.

Chang H Y, Wallis M, Tiralongo E. (2007) Use of complementary and alternative medicine among people living with diabetes: literature review. Journal of Advanced Nursing; 58(4): pp307-19.

Dannemann K, Hecker W, Haberland H, Herbst A, Galler A, Schäfer T, Brähler E, Kiess W, Kapellen TM. (2008) Use of complementary and alternative medicine in children with type 1 diabetes mellitus – prevalence, patterns of use, and costs. Pediatric Diabetes; 9(3 Pt 1): pp228-35

Dunning T (2003) Complementary therapies and diabetes. Complementary Therapies in Nursing and Midwifery; 9(2): pp74-80.

ECH – European Committee for Homeopathy (2007) The position of Homeopathy in Europe.  [Online] Available at: [Accessed on: 10/07/2009]

Egede L E (2004) Complementary and alternative medicine use with diabetes. Geriatric Times; 5(2): pp

Eisenberg D.M., Davis R.B., Ettner S.L., Appel S., Wilkey S., Van Rompay M. et al. (1998) Trends in alternative medicine use in the United States, 1990-1997: Results of a follow-up national survey. JAMA: The Journal of the American Medical Association; 280(18): pp1569-1575.

Emslie M., Campbell M. & Walker K. (1996) Family Medicine Complementary therapies in a local healthcare setting. Part 1: is there real public demand? Complementary Therapies in Medicine; 4(1): pp39-42.

Garrow D, Egede L E. (2006a) National patterns and correlates of complementary and alternative medicine use in adults with diabetes. Journal of Alternative and Complementary Medicine; 12(9): pp895-902

Garrow D, Egede L E. (2006b) Association between complementary and alternative medicine use, preventive care practices, and use of conventional medical services among adults with diabetes. Diabetes Care; 29: pp15-19

Greenhalgh T., (2006) How to read a paper: the basics of evidence-based medicine. BMJ Books & Blackwell Publisher, United Kingdom.

Grimes D. A., & Schulz K., F., (2002) Descriptive studies: what they can and cannot do. Lancet 359: pp. 145-49

Hasan S S, Ahmed S I, Bukhari N I and Wei Loon W C (2009) Use of complementary and alternative medicine among patients with chronic diseases at outpatient clinics. Complementary Therapies in Clinical Practice; ARTICLE IN PRES

Hennekens C. H., Buring J., E. (1987) Analysis of epidemiologic studies: evaluating the role of bias. In: Hennekens C., H., Buring J., E. and Mayrent S., L. eds. Epidemiology in medicine. Lippincott Williams & Wilkins. pp. 272-286.

Katchigan S (1986) Statistical analysis: an interdisciplinary introduction to univariate and multivariate methods. New York: Radius Press.

Kumara D., S. Bajajb, R. Mehrotra (2006) Knowledge, attitude and practice of complementary and alternative medicines for diabetes. Public Health; 120: pp705-711

Leese GP, Gill GV, Houghton GM (1997) Prevalence of Complementary medicine usage within a diabetes clinic. Practical Diabetes International; 140: pp207-8

Lew-Ting C.Y. (2003) Who uses non-biomedical, complement and alternative health care? Socio-demographic un-differentiation and the effects of health needs. Taiwan Journal Public Health; 22(3): pp155-166.

Lijmer JG, Mol BW, Heisterkamp S, et al (1999) Empirical evidence of design-related bias in studies of diagnostic tests. JAMA 282: pp1061-1066.

Lim M.K., Sadarangani P., Chan H.L. & Heng J.Y. (2005) Complementary and alternative medicine use in multiracial Singapore. Complementary Therapies in Medicine; 13(1): pp16-24.

Lind BK, Lafferty WE, Grembowski DE, Diehr PK. (2006) Complementary and alternative provider use by insured patients with diabetes in Washington State. Journal of Alternative and Complementary Medicine; 12(1): pp71-7.

Loney P L, Stratford P W. (1999) The prevalence of low back pain in adults: a methodological review of the literature. Physical Therapy; 79(4): pp384-96.

Loney P L, Chambers LW, Bennett KJ, Roberts JG, Stratford PW (1998) Critical appraisal of the health research literature: prevalence or incidence of a health problem. Chronic Diseases in Canada; 19(4): pp170-6.

MacLennan A.H., Wilson D.H. & Taylor A.W. (2002) The escalating cost and prevalence of alternative medicine. Preventive Medicine; 35(2): pp166-173.

Marshall V (1987) Factors affecting response and completion rates in some Canadian studies. Canadian Journal of Aging; 1: pp385 – 401.

Mehrotra R, Bajaj S, Kumar D. (2004) Use of complementary and alternative medicine by patients with diabetes mellitus. The National Medical Journal of India; 17(5): pp243-5.

Oliveira G. J., D.D.S., M.Sc.; Cláudio R. Leles, D.D.S., M.Sc., Ph.D. (2006), Critical appraisal and positive outcome bias in case reports published in Brazilian dental journals, Journal of Dental Education, 70(8): pp. 869-74.

O’Rourke A., (2005) Critical appraisal. In Bowling A., and Ebrahim S., (eds) Handbook of health research method: investigation, measurement and analysis. Open University Press. Berkshire; England.

Pagán J A, Tanguma J. (2007) Health care affordability and complementary and alternative medicine utilization by adults with diabetes.  Diabetes Care; 30(8): pp2030-1

Pomposelli R, Piasere V, Andreoni C, Costini G, Tonini E, Spalluzzi A, Rossi D, Quarenghi C, Zanolin ME, Bellavite P. (2009) Observational study of homeopathic and conventional therapies in patients with diabetic polyneuropathy. Homeopathy; 98(1): pp17-25.

Rothman KJ. (2002) Biases in study design. In: Epidemiology: an introduction. New York, NY: Oxford University Press.

Schoenberg NE, Stoller EP, Kart CS, Perzynski A, Chapleski EE. (2004) Complementary and alternative medicine use among a multiethnic sample of older adults with diabetes. Journal of Alternative and Complementary Medicine; 10(6): pp1061-6

Sica G. T., (2006) Bias in research studies. Radiology 238(3): pp. 780-89

Siegel K, Narayan KV. (2008) The Unite for Diabetes campaign: Overcoming constraints to find a global policy solution. Globalization and Health; 4: p3

Sim J., Wright C., (2000) Research in health care: concepts, designs and methods. Stanley Thomes (Publishers) Ltd. Cheltenham, United Kingdom.

Slavin R. E., (1995) Best evidence synthesis: an intelligent alternative to meta-analysis. Journal of clinical epidemiology. 48(1): pp. 9-18

Szklo M., Nieto, F., J., (2000) Identifying noncausal associations: confounding. In: Epidemiology: beyond the basics, 2nd ed. Jones & Bartlett Publishers, Sudbury.

Tindle H.A., Davis R.B., Phillips R.S. & Eisenberg D.M. (2005) Trends in use of complementary and alternative medicine by US adults: 1997-2002. Alternative Therapies in Health and Medicine; 11(1): pp42-49.

WHO -IDF (2004), Diabetes Action Now, World Health Organization, [Online]. Available at: [Accessed on: 10/11/2008]

Yeh GY, Eisenberg DM, Davis RB, Phillips RS. (2002) Use of complementary and alternative medicine among persons with diabetes mellitus: results of a national survey. American Journal of Public Health; 92(10): pp1648-52.

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About the author

Dhiman Roy

Dr. Dhiman Roy (B H M S, MSc, PhD) studied Public Health at University of East London, UK and homeopathy at University of Central Lancashire, UK, and received his PhD as a Research Fellow at Institute of Environmental Science - IES, University of Rajshai, BD. He has been a lecturer at Khulna Homeopathic Medical College & Hospital - KHMC&H (Khulna, BD) and Director and Homeopathic Consultant DRHF, Khulna, BD. Dr. Roy is also IACH E-Learning Course Coordinator at Alonissos, Greece and an Environment and Homeopathic Consultant. Visit him at his website: and at


  • sir u’ve really contributed so much in the care of diabetic patients through ur numerous publications.kudos

  • Dear Doctor,

    Your article is marvelous; a real research work, giving the most important statistical facts about the prevalence of diabetes mellitus in various regions.
    I have administered homeopathic medicines to diabetics in combination with allopathic treatment and the results were very encouraging.
    1. Generalized weakness and lethargy were cured.
    2. Diabetic complications of eyes,brain,nerves,skin, kidneys and cardiovascular system were prevented/delayed in most of the cases and treated in a reasonable number of patients.
    3. Diabetics who developed resistance to oral anti diabetics were given homeopathic medicines and they again became sensitive to the same allopathic medicine and responded well to the same treatment.

    Wish you best of luck!

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