| Abstract|| |
Context: The use of complementary and alternative medicine (CAM) is common among type 2 diabetes mellitus (T2DM) patients in Indonesia and may potentially affect adherence to prescribed diabetes medication, leading to uncontrolled blood sugar levels and complications. Aims: The objectives of this study were to analyze the association of CAM use with adherence to prescribed diabetes medication and to identify predictors of low adherence to prescribed diabetes medication. Settings and Design: A cross-sectional survey was done in a secondary health care facility in Bandung city, Indonesia. Data were collected between February and April 2014 from 114 respondents selected through consecutive sampling. Statistical Analysis Used: Chi-square test and ordinal logistic regression were used for statistical analysis. Results: The result showed that 64.9% of the respondents used CAM with herbal products (54.4%), ceragem (16.7%), and massage (12.3%) as the most widely used types. CAM use was found to significantly decrease adherence to prescribed diabetes medication (P < 0.05). The multivariate analysis suggested that the predictors of low adherence were CAM used [adjusted odds ratio (ORadj) 6.16; 2.44-15.52], gender (ORadj2.57; 1.05-6.31), and age (ORadj4.25; 1.53-11.31). Conclusions: CAM use decreased adherence to prescribed medication in T2DM patients. Gender and age were also associated with adherence. Instead of ignoring CAM use among patients, health professionals should have increased awareness and better training about CAM so that they can provide patients with relevant information and assist them in their decision-making regarding CAM use.
Keywords: Adherence, complementary and alternative medicine (CAM), prescribed medication, type 2 diabetes mellitus (T2DM)
|How to cite this article:|
Alfian SD, Sukandar H, Arisanti N, Abdulah R. Complementary and alternative medicine use decreases adherence to prescribed medication in diabetes patients. Ann Trop Med Public Health 2016;9:174-9
|How to cite this URL:|
Alfian SD, Sukandar H, Arisanti N, Abdulah R. Complementary and alternative medicine use decreases adherence to prescribed medication in diabetes patients. Ann Trop Med Public Health [serial online] 2016 [cited 2020 Jul 11];9:174-9. Available from: http://www.atmph.org/text.asp?2016/9/3/174/179108
| Introduction|| |
Diabetes mellitus is one of the most common chronic diseases in nearly all countries and continues to increase in prevalence and significance, as changing lifestyles lead to reduced physical activity and increased obesity., A 69% increase in the number of adults with diabetes in developing countries is predicted between 2010 and 2030. In Indonesia, the number of people with diabetes reached 21.3 million and is expected to increase 2.5 times in 2030.
Complementary and alternative medicine (CAM) refers to a wide range of clinical therapies outside of conventional medicine. The Indonesia Ministry of Health categorizes CAM into four domains: Skill-based therapy, biologically based therapy, spiritual therapy, and supernatural therapy. Biologically based practices are the CAM modalities most commonly used and studied for the treatment of diabetes. Based on the Indonesia Socioeconomic Survey, CAM is used by 40% of the Indonesian population and this percentage increase every year. CAM use is common among type 2 diabetes mellitus (T2DM) patients and its prevalence has a wide range (17-72.8%) due to the different definitions of CAM in studies. Diabetes patients have been found to be 1.6 times more likely to use CAM than individuals without diabetes. Several studies have also reported that those who use CAM are more likely to report poorer health status and to suffer from conditions associated with chronic pain, disability, or psychological impairment. Previous research has suggested that T2DM patients who use CAM are less likely to use conventional medical services. In addition, some studies have indicated that CAM use is associated with decreased use of preventive care services.
Effective and successful glucose control requires appropriate and timely use of medication over the entire period of treatment, which is often lifelong. The clinical impact of drug therapies for diabetes has been limited by poor rates of adherence. Different studies have shown that adherence to diabetes treatment is highly varied and may range 1.4-88.0%. According to the World Health Organization (WHO), patients' adherence to long-term therapy for chronic diseases was only 50% in developed countries and even lower in developing countries. This finding is supported by a previous study, which reported that adherence to diabetes medicine in Makassar, Indonesia was 34.5%. Low adherence to prescribed diabetes medication leads to worse treatment outcomes and damages to vital organs. Treatment failure is in turn associated with reduced treatment benefits and can have a negative financial burden on both individual patients and the society at large.
Numerous studies have explored potential predictors of adherence to medicine across various conditions. Frequently cited predictors include unmodifiable variables such as age, sex, ethnicity, income, education, and comorbidity. Thus, in this study, we explored CAM use as a modifiable predictor of adherence among T2DM patients in a secondary health care facility in Bandung city, Indonesia.
| Materials and Methods|| |
A cross-sectional survey was done in a secondary health care facility in Bandung city, Indonesia from February to April 2014. Assuming a prevalence rate of 35%, a minimum sample size of 114 was determined to provide true values at 95% confidence level. Data were collected from 114 patients who met the following inclusion criteria: Persons with confirmed T2DM for over 3 months and with prescribed diabetes medication, >18 years of age, and attending a secondary health care center in Bandung city, Indonesia.
Adherence was assessed by using the eight-item Morisky Medication Adherence Scale (MMAS). The MMAS scale has been used as a self-reported measure of adherence to medication for many chronic diseases including diabetes and has shown good reliability and predictive validity. All questions were translated into Bahasa Indonesia and proven to be valid (r > 0.3) and reliable (Cronbach's α = 0.724).
Respondents were classified under low adherence if their score were less than 6, under medium adherence if they scored 6 or 7, and under high adherence if the score was 8. The findings were described in term of frequencies, percentages, means, and standard deviations. The association of sociodemographic factors (gender, age, educational, income, duration of diabetes, and family history of diabetes) and CAM use with adherence to prescribed diabetes medication was determined by using a chi-square test. The results were considered statistically significant at P ≤ 0.05. Ordinal logistic regression was used to identify independent predictors of adherence under three outcome levels, i.e., low, medium, and high adherence, with low adherence as the reference variable.
The study protocol was approved by the Universitas Padjadjaran Ethics Committee No. 93/UN6.C2.1.2/KEPK/PN/2014. All patients provided informed consent to participate in the study.
| Results|| |
The study included a sample of 114 patients with T2DM. [Table 1] shows the sociodemographic information and clinical characteristics of the sample. The respondents were predominantly female and 60-69 years old with a mean age of 61.1 ± 9.6 years. Most received primary education (42%), were not working/retired (86%), and had an average monthly household income below the regional minimum salary (72%). Most of the respondents (56%) were diagnosed with diabetes over 5 years ago, and 54% had no family history of the disease. [Table 2] provides a summary of the differences in characteristics between CAM and non-CAM users.
|Table 1: Socio-demographic and clinical characteristics of respondents (n = 114)|
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|Table 2: Association of characteristics between patients who used CAM and those who did not use CAM (n = 114)|
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The prevalence of CAM use among T2DM patients was 64.9%. Some patients used more than one type of CAM as shown in [Table 3]. Biological therapy, which involves the use of herbal products (83.78%), was the most widely used CAM type, followed by ceragem (25.68%) and massage (18.92%). Surprisingly, none of the patients sought help from a spiritual or religious master.
|Table 3: Type of CAM used by T2DM patient in Secondary Health Care, Bandung City, Indonesia|
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The self-reported adherence to prescribed diabetes medication as measured by the MMAS showed that the majority of patients had low adherence (51%), followed by medium adherence (34.2%), and high adherence (21.1%). The chi-square test result suggested that CAM use was significantly associated with adherence to prescribed diabetes medication (P< 0.05).
Multivariate ordinal logistic regression analysis was used to identify predictors of adherence. Three variables were found to predict nonadherence to prescribed diabetes medication: CAM use adjusted odds ratio (ORadj) 6.16], gender (ORadj2.57), and age (ORadj4.15). The results of the multivariate analysis with ordinal logistic regression are shown in [Table 4].
| Discussions|| |
With the increasing rates of childhood and adult obesity, the prevalence of T2DM is expected to increase in the future. At the same time, the care of T2DM patients has been influenced by a growing interest in CAM, which unfortunately is largely neglected by health care providers. Indonesia has a high prevalence of diabetes, alongside a long tradition of CAM use. In this study, a 64.9% prevalence of CAM use among T2DM patients is reported. This result is higher than those found by other studies in the United Kingdom (46%), Australia (46%), and Saudi Arabia (30%). The percentage is comparable with those in India (68%) and Mexico (62%) but lower than that in the United States (73%).
A previous study has reported that older female patients with higher levels of education and household income were more likely to be CAM users. However, the present study found no significant relationship between CAM use and gender, mean age, education, or household income. This could be because the studied population consisted of diabetes patients who might be more likely to use CAM therapies that have been embedded into their beliefs and cultural heritage, regardless of sociodemographic status. Other possible reasons for such a finding were the large number of CAM healers in Indonesia and the long tradition of CAM use in the country.
This study found that biological therapy, which involves the use of herbal products, was the most widely used CAM type (83.78%). This result is similar to those of several previous studies, which found herbal products to be the most widely used by T2DM patients among the types of CAM. The highest use of herbal products in T2DM patients found in this study may be due to the fact that such products are widely available, relatively cheap, and inherent in the cultures and ancestral beliefs of the people. In addition, people believe that consuming bitter-tasting herbal products can neutralize the “sweetness present in the blood” of T2DM patients, although this belief has not been scientifically proven. Several studies have found that people who use CAM felt more congruent with their own values, beliefs, and philosophical orientations toward health and life.
The herbal products used by T2DM patients often have more than one active ingredient and treat a variety of symptoms. In this study, the patients were found to use not only known herbal compositions but also unknown ones. Therefore, health providers should provide information about the efficacy, effectiveness, adverse effects, and possible reaction of herbal products to help patients make decisions related to CAM use.
Surprisingly, the second most frequently used CAM types is ceragem. Ceragem is an automated machine used to restore the function of the whole body. It combines thermal and massage therapy with infrared heat radiation emitted through jade and epoxy carbon panel. This new type of CAM is from Korea.
Medication adherence is also affected by local culture and religious affiliations, which influence individual medication behaviors. CAM use can complicate the treatment regimen received by patients with T2DM, resulting in low adherence to the prescribed diabetes medication. This finding is supported by previous research, which reported that the number of treatments received affect the adherence to prescribed diabetes medication. CAM users are both logistically and psychologically burdened and may need to sacrifice part or all of their prescribed diabetes medication to be able to continue using CAM. CAM use should thus be monitored by health care providers to prevent low adherence to prescribed diabetes medication, which can lead to uncontrolled blood sugar levels and treatment failure, causing further complication.
Based on the multivariate analysis, the predictors that affect the low adherence to prescribed diabetes medication are CAM use [adjusted odds ratio (ORadj) 6.16; 2.44-15.52], male (ORadj2.57; 1.05-6.31), and 60-69 years of age (ORadj4.25; 1.53-11.31). T2DM patients who use CAM were found to be 6.16 times more likely to have low adherence to their prescribed diabetes medication compared with non-CAM patients. This result is higher than that found by Abebe et al., who reported that the risk of low adherence to prescribed diabetes medication was 2.9 for those who use CAM. An additional reason for low adherence to prescribed diabetes medication was that patients believed in CAM healers more than in allopathic medicine. A good doctor-patient relationship is important to encouraged patients to talk to their doctors about their CAM use and thus ensure proper monitoring of their adherence to prescribed diabetes medication.
Another predictor of low adherence to prescribed diabetes medication is gender. Compared with females, male patients have a higher risk (2.57) of low adherence to prescribed diabetes medication. This result is similar to that of Wong et al., who reported that male patients have worse blood glucose level control than female. In general, female patients pay more attention to and show greater care for their health than do men.
The last predictor of low adherence to prescribed diabetes medication is age 60-69 years. Patient within this age range have a higher risk (4.15) of low adherence to prescribed diabetes medication compared with other ages. This is because patients within this age range intentionally choose to not adhere to their prescribed diabetes medication to avoid the side effects. In addition, these patients also find it difficult to maintain such adherence over a long period.
There are several limitations to this study. First, the study did not included patients' clinical data, which could help identify the effect of CAM use on their physiology. Second, the data were based on the respondents' self-reported medication adherence and thus may have been affected by recall bias. Nevertheless, the MMAS has been validated and is one of the most widely used self-reported measures of adherence. Thus, it is unlikely that our estimates are seriously underestimated.
A deeper understanding of the patterns of CAM use among T2DM patients will not only help health professionals provide more information to patients but will also help policymakers create relevant frameworks for future policy as well as guide investigators in the further development of CAM research.
| Conclusions|| |
The results of this study suggest that CAM use decreases adherence to prescribed medication in T2DM patients. T2DM patients who use CAM were found to be 6.16 times more likely to have low adherence to their prescribed diabetes medication compared with non-CAM users. Instead of ignoring CAM use among patients, health professionals should have increased awareness and better training about CAM so that they can provide patients with relevant information and assist them in their decision making regarding CAM use.
Financial support and sponsorship
Conflicts of interest
Sofa D. Alfian, Hadyana Sukandar, Nita Arisanti, and Rizky Abdulah declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
| References|| |
Shaw JE, Sicree RA, Zimmet PZ. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract 2010;87:4-14.
Abebe SM, Berhane Y, Worku A. Barriers to diabetes medication adherence in North West Ethiopia. Springerplus 2014;3:195.
Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: Estimates for the year 2000 and projections for 2030. Diabetes Care 2004;27:1047-53.
Birdee GS, Yeh G. Complementary and alternative medicine therapies for diabetes: A clinical review. Clin Diab 2010;28:147-55.
Ministry of Health Republic of Indonesia. Ministry of Health Act No 1076/Menkes/SK/VII/2003 about the Implementation of Traditional Medicine. Jakarta; Ministry of Health Republic of Indonesia 2003; p.1-23.
Chang HY, Wallis M, Tiralongo E. Use of complementary and alternative medicine among people living with diabetes: Literature review. J Adv Nurs 2007;8:307-19.
Egede LE, Ye X, Zheng D, Silverstein MD. The prevalence and pattern of complementary and alternative medicine use in individual with diabetes. Diabetes Care 2002;25:324-9.
Wolsko P, Ware L, Kutner J, Lin CT, Albertson G, Cyran L, et al
. Alternative/complementary medicine: Wider usage than generally appreciated. J Altern Complement Med 2000;6:321-6.
Astin JA. Why patients use alternative medicine: Results of a national study. JAMA 1998;279:1548-53.
Robinson AR, Crane LA, Davidson AJ, Steiner JF. Association between use of complementary/alternative medicine and health-related behaviours among health fair participants. Prev Med J 2002;34:51-7.
Osterberg L, Blaschke T. Adherence to medication. N
Engl J Med 2005;353:487-97.
Raum M, Krämer HU, Rüter G, Rothenbacher D, Rosemann T, Szecsenyi J, et al
. Medication non-adherence and poor glycaemic control in patients with type 2 diabetes mellitus. Diabetes Res Clin Pract 2012;97:377-84.
World Health Organizations. Adherence to Long Term Therapies: Evidence for Action. Geneva 2003; p. 1-209.
Lestari D, Citrakesumasari, Alharini S. Effort of Caring and Behaviour OF Diabetes Mellitus Type 2 Patients in Maradekaya Health Center Makassar [Thesis]. Makassar: University of Hasanuddin; 2013. p. 1-14.
Wroth TH, Pathman DE. Primary medication adherence in a rural population: The role of the patient-physician relationship and satisfaction with care. J Am Board Fam Med 2006;19:478-86.
Morisky DE, Ang A, Krousel-Wood M, Ward HJ. Predictive validity of a medication adherence measure in an outpatient setting. J Clin Hypertens (Greenwich) 2008;10:348-54.
Krapek K, King K, Warren SS, George KG, Caputo DA, Mihelich K, et al
. Medication adherence and associated hemoglobin A1c in type 2 diabetes. Anna Pharmacother 2004;38:1357-62.
Thomas KJ, Nicholl JP, Coleman P. Use and expenditure on complementary medicine in England: A population based survey. Complement Ther Med 2001;9:2-11.
Manya K, Champion B, Dunning T. The use of complementary and alternative medicine among people living with diabetes in Sydney. BMC Complement Altern Med 2012;12:2.
Al-Saeedi M, Elzubier AG, Bahnassi AA, Al-Dawood KM. Patterns of belief and use of traditional remedies by diabetic patients in Mecca, Saudi Arabia. East Mediterr Health J 2003;9:99-107.
Kumar D, Bajaj S, Mehrotra R. Knowledege, attitude and practice of complementary and alternative medicines for diabetes. Public Health 2006;120:705-11.
Argáez-López N, Wacher NH, Kumate-Rodríguez J, Cruz M, Talavera J, Rivera-Arce E, et al
. The use of complementary and alternative medicine therapies in type 2 diabetic patients in mexico. Diabetes Care 2003;26:2470-1.
Bell RA, Suerken CK, Grzywacz JG, Lang W, Quandt SA, Arcury TA. Complementary and alternative medicine use among adults with diabetes in the United States. Altern Ther Health Med 2006;12:16-22.
Villa-Caballero L, Morello CM, Chynoweth ME, Prieto-Rosinol A, Polonsky WH, Palinkas LA, et al
. Ethnic differences in complementary and alternative medicine use among patients with diabetes. Complement Ther Med 2010;18:241-8.
Ogbera AO, Dada O, Adeleye F, Jewo PI. Complementary and alternative medicine use in diabetes mellitus. West Afr J Med 2010;29:158-62.
Lee Y, Park BN, Kim SH. The effects of heat and massage application on autonomic nervous system. Yonsei Med J 2011;52:982-9.
Collins-McNeil J, Edwards CL, Batch BC, Benbow D, McDougald CS, Sharpe D. A culturally targeted self-management program for African Americans with type 2 diabetes mellitus. Can J Nurs Res 2012;44:126-41.
Cherniack EP. Complementary medicine use is not associated with non-adherence to conventional medication in the elderly: A retrospective study. Complement Ther Clin Pract 2011;17:206-8.
Owen-Smith A, Diclemente R, Wingood G. Complementary and alternative medicine use decreases adherence to HAART in HIV-positive women. AIDS Care 2007;19:589-93.
Mann DM, Ponieman D, Leventhal H, Halm EA. Predictors of adherence to diabetes medications: The role of disease and medication beliefs. J Behav Med 2009;32:278-4.
Haque M, Emerson SH, Dennison CR, Navsa M, Levitt NS. Barriers to initiating insulin therapy in patients with type 2 diabetes mellitus in public-sector primary health care centers in Cape Town. S Afr Med J 2005;95:798-802.
Wong MC, Kong AP, So WY, Jiang JY, Chan JC, Griffiths SM. Adherence to oral hypoglycemic agents in 26,782 Chinese patients: A cohort study. J Clin Pharmacol 2011;51:1474-82.
Garjani A, Rahbar M, Ghafourian T, Maleki N, Garjani A, Salimnejad M, et al
. Relationship of pharmacist interaction with patient knowledge of dispensed drugs and patient satisfaction. East Mediterr Health J 2009;15:934-43.
le Grand A, Hogerzeil HV, Haaijer-Ruskamp FM. Intervention research in rational use of drugs: A review. Health Policy Plan 1999;14:89-102.
Sofa Dewi Alfian
Raya Bandung Sumedang KM 21, Jatinangor - 45363
Source of Support: None, Conflict of Interest: None
[Table 1], [Table 2], [Table 3], [Table 4]