OBJECTIVE—This study compared the prevalence and pattern of use of complementary and alternative medicine (CAM) in individuals with and without diabetes and identified factors associated with CAM use.

RESEARCH DESIGN AND METHODS—The 1996 Medical Expenditure Panel Survey, a nationally representative sample of the U.S. noninstitutionalized civilian population, was analyzed. Estimates of CAM use in individuals with common chronic conditions were determined, and estimates of CAM use in patients with diabetes were compared with that in individuals with chronic medical conditions. Patterns of use and costs of CAM use in patients with diabetes were compared with those in nondiabetic individuals. Multiple logistic regression was used to determine independent predictors of CAM use in individuals with diabetes, controlling for age, sex, race/ethnicity, household income, educational level, and comorbidity.

RESULTS—Individuals with diabetes were 1.6 times more likely to use CAM than individuals without diabetes (8 vs. 5%, P < 0.0001). In the general population, estimates of CAM use were not significantly different across selected chronic medical conditions, but diabetes was an independent predictor of CAM use. Among individuals with diabetes, older age (≥65 years) and higher educational attainment (high school education or higher) were independently associated with CAM use.

CONCLUSIONS—Diabetes is an independent predictor of CAM use in the general population and in individuals with diabetes. CAM use is more common in individuals aged ≥65 years and those with more than high school education.

Diabetes is a chronic debilitating medical condition that affects ∼16 million individuals in the U.S.; ∼2,200 new cases of diabetes are diagnosed each day (1). Diabetes is associated with significant morbidity and mortality. It is the leading cause of end-stage renal disease and amputation of the lower extremity in the general population and the leading cause of new cases of blindness in individuals aged 20–74 years. In addition, diabetes is the seventh leading cause of death in the U.S. (2). Furthermore, diabetes imposes significant financial burden on individuals with the disease. The annual medical cost associated with diabetes is ∼98 billion dollars, including direct and indirect medical costs and lost productivity (3).

Complementary and alternative healthcare and medical practices, i.e. complementary and alternative medicine (CAM), are functionally defined as treatments and healthcare practices that are not taught widely in medical schools and are not generally available in U.S. hospitals (4). The National Center for Complementary and Alternative medicine (NCCAM) defines CAM as those healthcare and medical practices that are not currently an integral part of conventional medicine (5). The NCCAM definition restricts the term “conventional medicine” to medicine practiced by holders of MD (medical doctor) or DO (doctor of osteopathy) degrees, some of whom may also practice CAM (5).

### Factors associated with use of CAM

The independent predictors of CAM use in both the general population and in individuals with diabetes are shown in Table 3. In the general population, women, those with high school education or more, those in poor physical health, those who were employed, and those with diabetes or diabetes in combination with other chronic medical conditions were most likely to use CAM. In addition, Hispanics and blacks were less likely to use CAM than whites and individuals of other races or ethnicities. Individuals who lived in the West were more likely to use CAM than those living in the Northeast, Midwest, or South. Finally, individuals with private health insurance were less likely to use CAM than those who were uninsured.

Among individuals with diabetes, those aged ≥65 years were three times more likely to use CAM than those aged <65 years. Individuals with high school education and higher were 2.4 times more likely to use CAM than those who had not completed high school. Sex, race/ethnicity, household income, and comorbidity were not significant predictors of CAM use in individuals with diabetes.

This study has shown that although individuals with diabetes are more likely to use CAM than individuals without diabetes, estimates of CAM use in individuals with diabetes are comparable to those in individuals with other common chronic medical conditions. In addition, using nationally representative data, this study has provided preliminary estimates on pattern of use, associated costs, and factors associated with CAM use in individuals with diabetes.

The estimates of CAM use in this study differ considerably from those of Eisenberg et al. (4,6) but closely approximate those from two other studies using data from the MEPS (7,9). There are three possible reasons for these differences. One reason is the heterogeneity of CAM practices (5,14), which means that estimates of CAM use will change depending on what is included or excluded in the definition of CAM. The second reason is the oversampling of Hispanics and blacks and the use of direct household interview rather than telephone interviews in MEPS. This approach may have increased the proportion of minorities and individuals of lower socioeconomic status, who have been shown to have lower usage of CAM (6, 7). The third reason is the difference in target population and study hypothesis across studies. This is particularly obvious in the MEPS sample. When Bausell et al. (7) focused on adults aged ≥18 years, they found that 9% of U.S. adults visited CAM providers. However, when Druss and Rosenheck (9) used the same data set with similar age cutoffs, but tested different hypotheses, they found that 6.5% of the U.S. population used both conventional and unconventional therapies. Both studies differ from our study, in which no age category was excluded and the emphasis was on CAM use as opposed to visits to CAM providers.

Patients with diabetes and other common chronic medical conditions were more likely to use CAM than individuals in the general population. This is not surprising because earlier studies have linked increased CAM use with the presence of chronic as opposed to acute or life-threatening medical conditions (4,8). However, the finding that diabetes is an independent predictor of CAM use in the general population is surprising, particularly because the presence of multiple chronic comorbid conditions did not explain the association between diabetes and CAM use. Adjusting for covariates, individuals with only diabetes were two times more likely to use CAM, whereas individuals with diabetes and additional chronic conditions were 1.8 times more likely to use CAM than the general population without chronic medical conditions. This observation will need to be explored in future studies.

Nutritional advice and lifestyle diet, spiritual healing, herbal remedies, massage, and meditation were the most frequently used CAM treatments among individuals with diabetes; this pattern approaches the pattern of CAM use in the general population (4,6,15,16). Although nutritional counseling and lifestyle modification are essential components of routine diabetes care, it is important to recognize that in this study, such advice/diets were obtained from CAM providers. The MEPS definition of CAM, which is similar to the NCCAM definition (5), implies that nutritional advice and lifestyle diets provided by CAM practitioners differ from conventional nutritional/dietary recommendations endorsed by diabetes educators or physicians.

Examples of nutritional advice and lifestyle diets offered by CAM practitioners include Ayuverdic diets, naturopathic or homeopathic nutrition/diets, and orthomolecular therapies such as magnesium, melatonin, or megadoses of vitamins (5). In addition, special diets, such as those proposed by Drs. Atkins, Ornish, Pritikin, and Weil, also qualify as CAM lifestyle nutrition/diets (5). It is unlikely that nutritional advice and lifestyle diets offered by CAM practitioners are consistent with the American Diabetes Association guidelines for dietary management of diabetes (17). In addition, it is currently unknown whether additional nutritional advice and lifestyle diets by CAM practitioners complement and reinforce American Diabetes Association guidelines or conflict with conventional dietary recommendations.

Spiritual healing in MEPS refers to healing by someone other than self, such as the clergy or a spiritualist, and differs from self-prayer. This differentiation is important because an earlier study (6) reported that although only 7% of the U.S. population reported spiritual healing by others, up to 35% of the U.S. population used self-prayer as a form of treatment. Spiritual healing was the second most common type of CAM used by individuals with diabetes (21%) and the third most frequently used CAM in individuals without diabetes (24%). This finding suggests that substantial percentages of the U.S. population believe and seek spiritual healing as a form of treatment.

It seems that the search for spiritual healing may be well founded, based on the results of a recent study (18). This systematic review of 23 trials and 2,774 patients found that prayer and distant healing yielded statistically significant treatment effects in 13 patients (57%), no effect over control interventions in 9 patients (39%), and a negative effect in 1 patient (4%). In contrast, the use of herbal remedies, which was reported by 20% of individuals with diabetes, has not been shown to improve glucose control and may even be harmful in individuals with diabetes (19,20).

There are some limitations to this study. A major limitation is the small number of individuals with diabetes that used CAM in the 1996 MEPS household sample. This limited the type of analysis that could be performed and the number of independent predictors of CAM entered into the multiple logistic regression models. However, the MEPS is the first nationally representative survey that provides detailed information about the use of CAM and has data on medical conditions. The MEPS offers an exceptional opportunity to provide baseline data on CAM use in individuals with diabetes in the U.S. noninstitutionalized civilian population.

A second limitation of this study is that MEPS based CAM use on visits to a practitioner and excluded treatments obtained by individuals without consultation with a CAM practitioner. This may decrease the estimates of CAM use in both comparison groups. Recall bias is another potential limitation. Studies have shown that self-reports are reliable for the diagnosis of diabetes (21,22), but no studies validate recall of visits to CAM practitioners. If recall was low, it was likely similarly low across the sample because there are no obvious reasons to expect differential reporting of CAM use. The fourth limitation is the ambiguous definition of CAM (5,14), which allows for estimates that are dependent on the inclusion and exclusion criteria used to define CAM. This limitation may interfere with the ability of researchers to compare findings across studies.

The major implication of this study is that individuals with diabetes seem to use CAM as a complement rather than as an alternative to conventional treatment. In this study, 57% of individuals with diabetes who used CAM discussed it with their regular physician and 43% were actually referred to CAM users by a physician. This is reassuring because it means that patients with diabetes are not abandoning conventional treatments, which have been rigorously tested, for unconventional treatments, which lack properly designed efficacy trials. On the other hand, it means that health care providers will need to acknowledge CAM use, learn to discuss CAM use with their patients, and be able to do so candidly and without prejudice.

In an editorial published in the Journal of the American Medical Association, Wayne Jonas said “alternative medicine is here to stay” and that the challenge of the health care community is to “separate the pearls from the mud” (23). The increase in prevalence of diabetes (1), the search by patients for holistic medicine, and the skepticism some patients have about the efficacy of modern medicine (24) make the appropriateness of this statement even more evident. Differentiating efficacious CAM treatments from bogus treatments will remain a daunting task, and the absence of properly designed and conducted efficacy trials for many treatments further complicates the problem (25). Nonetheless, to foster collaboration with patients, health care providers must respect patients’ wishes to use CAM and provide unbiased advice about CAM treatments to patients. In addition, health care providers will need to understand the benefits and limitations of currently available alternative treatments.

There are three important areas for future research. First, there is a need to replicate the findings from the 1996 MEPS in current surveys. Second, there is an urgent need to use rigorous research designs to establish the efficacy of several complementary and alternative treatments that are currently being used by individuals with diabetes. Third, future studies must determine the effectiveness of CAM use in typical clinical situations and the effect of CAM on the quality of life in individuals with diabetes.

Table 1—

Sample characteristics of individuals with diabetes in 1996 (n = 825)

n%
Age ≥ 65 years 356 44
Women 472 55
Race/ethnicity
Hispanic 172 11
Black 157 17
White/other 496 72
Married 475 59
Census region
Northeast 158 19
Midwest 185 24
South 311 38
West 158 19
Physical health
Excellent, very good, or good 421 52
Mental health
Excellent, very good, or good 691 85
Education
High school or more 463 61
Poverty
Household income >125% federal poverty level 583 78
Health insurance
Private 481 63
Public 272 29
Uninsured 72
Employed 281 35
Comorbidity (diabetes versus diabetes + 1 or more chronic condition)
Diabetes only 318 36
Chronic comorbid conditions
Diabetes and hypertension 374 46
Diabetes and ischemic heart disease 221 28
Diabetes and COPD 54
Diabetes and cancer 66 10
n%
Age ≥ 65 years 356 44
Women 472 55
Race/ethnicity
Hispanic 172 11
Black 157 17
White/other 496 72
Married 475 59
Census region
Northeast 158 19
Midwest 185 24
South 311 38
West 158 19
Physical health
Excellent, very good, or good 421 52
Mental health
Excellent, very good, or good 691 85
Education
High school or more 463 61
Poverty
Household income >125% federal poverty level 583 78
Health insurance
Private 481 63
Public 272 29
Uninsured 72
Employed 281 35
Comorbidity (diabetes versus diabetes + 1 or more chronic condition)
Diabetes only 318 36
Chronic comorbid conditions
Diabetes and hypertension 374 46
Diabetes and ischemic heart disease 221 28
Diabetes and COPD 54
Diabetes and cancer 66 10
Table 2—

Comparison of pattern of use among all CAM users in 1996 by diabetes status

With diabetes (n = 62)Without diabetes (n = 889)P
Acupuncture 11 0.1800
Massage therapy 19 35 0.0110
Herbal remedies 20 33 0.0565
Biofeedback 0.4853
Meditation training 14 11 0.7058
Homeopathic therapy 10 0.0259
Spiritual healing 21 24 0.6112
Hypnosis 0.0102
Other alternative therapy 0.9317
Provider of CAM
Physician 0.3515
Nurse 13 0.0275
Homeopath/naturopath 1.0000
Chiropractor 12 0.3984
Clergy/spiritualist 18 20 0.8200
Massage therapist 16 32 0.0099
Acupuncturist 0.9652
Herbalist 14 0.0165
Use pattern and costs of CAM
Used CAM for specific health problem 81 63 0.0075
Discussed CAM use with regular physician 57 29 0.0024
Referred by physician to CAM provider 43 10 0.0010
CAM covered by insurance (yes) 27 12 0.0549
Mean number of visits to CAM provider 9 (2) 13 (2) 0.1781
Mean amount spent for CAM 414 (269) 236 (26) 0.5106
With diabetes (n = 62)Without diabetes (n = 889)P
Acupuncture 11 0.1800
Massage therapy 19 35 0.0110
Herbal remedies 20 33 0.0565
Biofeedback 0.4853
Meditation training 14 11 0.7058
Homeopathic therapy 10 0.0259
Spiritual healing 21 24 0.6112
Hypnosis 0.0102
Other alternative therapy 0.9317
Provider of CAM
Physician 0.3515
Nurse 13 0.0275
Homeopath/naturopath 1.0000
Chiropractor 12 0.3984
Clergy/spiritualist 18 20 0.8200
Massage therapist 16 32 0.0099
Acupuncturist 0.9652
Herbalist 14 0.0165
Use pattern and costs of CAM
Used CAM for specific health problem 81 63 0.0075
Discussed CAM use with regular physician 57 29 0.0024
Referred by physician to CAM provider 43 10 0.0010
CAM covered by insurance (yes) 27 12 0.0549
Mean number of visits to CAM provider 9 (2) 13 (2) 0.1781
Mean amount spent for CAM 414 (269) 236 (26) 0.5106

Data are % or means (SEM).

Table 3—

Independent predictors of CAM use in the general population and among individuals with diabetes in 1996

General populationPeople with diabetes
n 21,571 825
Age ≥65 years 0.73 (0.48–1.11) 3.05 (1.40–6.67)*
Age <65 (reference) 1.00 1.00
Women 2.17 (1.82–2.83)* 1.72 (0.90–3.33)
Men (reference) 1.00 1.00
Hispanic 0.71 (0.52–0.98)* 1.10 (0.50–2.41)
Black 0.52 (0.33–0.82)* 0.81 (0.35–1.91)
White/other (reference) 1.00 1.00
Married 0.93 (0.75–1.14)
Not married 1.00
High school and higher 2.78 (1.96–3.85)* 2.43 (1.16–5.08)*
Less than high school (reference) 1.00 1.00
Northeastern 0.39 (0.28–0.54)*
Midwestern 0.43 (0.31–0.59)*
Southern 0.42 (0.33–0.54)*
Western (reference) 1.00
Poor physical health 1.56 (1.11–2.17)*
Good physical health (reference) 1.00
Poor mental health 1.19 (0.74–1.87)
Good mental health (reference) 1.00
Private insurance 0.71 (0.53–0.95)*
Public insurance 0.79 (0.54–1.16)
Uninsured (reference) 1.00
Employed 1.48 (1.13–1.94)*
Not employed (reference) 1.00
125% + of poverty 1.33 (0.98–1.80) 1.29 (0.64–2.61)
<125% of poverty (reference) 1.00 1.00
Diabetes alone 2.16 (1.35–3.45)* 1.00 (Reference)
Diabetes + other chronic conditions 1.76 (1.06–2.95)* 1.11 (0.54–2.26)
No comorbidity (reference) 1.00 1.00 (0.41–2.44)
General populationPeople with diabetes
n 21,571 825
Age ≥65 years 0.73 (0.48–1.11) 3.05 (1.40–6.67)*
Age <65 (reference) 1.00 1.00
Women 2.17 (1.82–2.83)* 1.72 (0.90–3.33)
Men (reference) 1.00 1.00
Hispanic 0.71 (0.52–0.98)* 1.10 (0.50–2.41)
Black 0.52 (0.33–0.82)* 0.81 (0.35–1.91)
White/other (reference) 1.00 1.00
Married 0.93 (0.75–1.14)
Not married 1.00
High school and higher 2.78 (1.96–3.85)* 2.43 (1.16–5.08)*
Less than high school (reference) 1.00 1.00
Northeastern 0.39 (0.28–0.54)*
Midwestern 0.43 (0.31–0.59)*
Southern 0.42 (0.33–0.54)*
Western (reference) 1.00
Poor physical health 1.56 (1.11–2.17)*
Good physical health (reference) 1.00
Poor mental health 1.19 (0.74–1.87)
Good mental health (reference) 1.00
Private insurance 0.71 (0.53–0.95)*
Public insurance 0.79 (0.54–1.16)
Uninsured (reference) 1.00
Employed 1.48 (1.13–1.94)*
Not employed (reference) 1.00
125% + of poverty 1.33 (0.98–1.80) 1.29 (0.64–2.61)
<125% of poverty (reference) 1.00 1.00
Diabetes alone 2.16 (1.35–3.45)* 1.00 (Reference)
Diabetes + other chronic conditions 1.76 (1.06–2.95)* 1.11 (0.54–2.26)
No comorbidity (reference) 1.00 1.00 (0.41–2.44)

Data are adjusted odds ratio (95% CI).

*

Statistically significant at P < 0.05;

diabetes plus one chronic condition;

diabetes plus two or more chronic conditions.

This study was funded by grants (1P01HS1087-01 and 1K08HS11418-01 to L.E.E.) from the Agency for Health Care Research and Quality, Rockville, MD, and the Centers for Disease Control and Prevension (Grant U501CC417281-02 to L.E.E. and D.Z.).

The concents of this article reflect the personal opinions of the authors and do not represent the official opinion of either the Agency for Health Care Research and Quality or the Centers for Disease Control and Prevention.

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Address correspondence and reprint requests to Leonard E. Egede, MD, MS, Medical University of South Carolina, McClennan-Banks Adult Primary Care Clinic, P.O. Box 250100, Charleston, SC 29425. E-mail: egedel@musc.edu.

Received for publication 22 May 2001 and accepted in revised form 17 October 2001.

A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.