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:
· Original (primary) research articles
· Studies published in peer-reviewed journal
· Studies with any design, reporting prevalence of use of homeopathy
· 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 PagÃ¡n & 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|
|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.
|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
|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).
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.
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