Abstract
Background
According to Ayurveda, the traditional medical system of India, doshas are a combination of characteristics based on a five-element philosophy that drive our mental and physical tendencies. When the doshas, or functional principles, are out of balance in quality or quantity, wellbeing is adversely affected and symptoms manifest.
Objective
This study examined relationships among imbalances in the doshas (termed Vikruti) reported via questionnaire and Western measures of psychological states.
Materials and methods
Study participants were 101 women (n = 81) and men (n = 20), mean age 53.9 years (SD = 11.7; range 32–80). Participants completed questionnaires to categorize their Vikruti type and psychological states, which included depressed mood (CESD), anxiety (PROMIS), rumination & reflection (RRQ), mindfulness (MAAS), stress (PSS), and quality of life (Ryff).
Results
Multivariate general linear modeling, controlling for age, gender and body mass index (BMI), showed that Vata imbalance was associated with more anxiety (p ≤ 0.05), more rumination (p ≤ 0.01), less mindfulness (p ≤ 0.05), and lower overall quality of life (p ≤ 0.01). Pitta imbalance was associated with poorer mood (p ≤ 0.01) and less mindfulness (p ≤ 0.05), more anxiety (p ≤ 0.05) and stress (p ≤ 0.05). Kapha imbalance was associated with more stress (p ≤ 0.05), more rumination (p ≤ 0.05) and less reflection (p ≤ 0.05).
Conclusion
These findings suggest that symptoms of mind-body imbalances in Ayurveda are differentially associated with western assessments of psychological states. Ayurvedic dosha assessment may be an effective way to assess physical as well as emotional wellbeing in research and clinical settings.
Keywords: Vikruti, Dosha, Mood, Anxiety, Quality of life
1. Introduction
Over the ages, numerous taxonomic systems have been developed to categorize individuals according to constitutional phenotypes, including Hippocrates' humors [1], and in more modern times Friedman and Rosenman's behavior patterns [2] as well as William Sheldon's somatotypes [3], to name a few.
Ayurvedic Medicine, the traditional medical system of India, is based on Tridoshic theory; the three doshas are vata, pitta, and kapha [4]. In Ayurveda, the constitutional phenotype, or psychobiological tendencies, is called Prakruti, and refers to the inherent balance of a unique combination of mental and physical qualities which show up as predictable patterns in the mind-body system within an individual [5]. This ideal constitutional balance of an individual is determined at birth and grossly correlates with the individual's patterns of gene expression [6]. The constitution or physical manifestation of the doshas determine physical and structural characteristics, metabolic tendencies, personality, and disease susceptibility. The three doshas are forces that contain different proportions of the five elements air, fire, earth, ether and water [5], and thus contain parallels to Hippocrates' humors and Traditional Chinese Medicine's constitutional taxonomy system, which are also related to the elements and elemental classification [1], [7].
According to Ayurveda, all living species contain all three doshas in unique combinations since each dosha is required for life. In general, vata dosha provides the force of movement and transport, pitta promotes metabolism, and kapha provides structure. Vata contains the elements of air and ether and thus represents the force required for all movement. Pitta contains the elements of fire and water and its governing action focuses on digestion and metabolism. Kapha contains the elements water and earth and is the force that promotes structure and stability. Kapha dosha also provides lubrication, growth, storage, and strength of immunity. In addition to the body as a whole, the doshas reside and operate within each cell of the body. At the cellular level, Vata is responsible for the circulation of nutrients and the excretion of the cellular waste products of metabolism. Pitta metabolizes nutrients and produces cellular energy; the waste products are removed by Vata. Kapha provides cellular structure via cell and organelle membranes as well as storage via vesicles.
Ayurvedic theories view that the psychobiological tendencies of each Prakruti possess innate vulnerabilities to stress and illness [5], [8], [9]. Recent studies have sought to examine such vulnerabilities according to Western classification of ailments. Manyam and Kumar, for example, demonstrated greater incidence of idiopathic Parkinson's disease (PD) in individuals with Vata constitution, as compared to Pitta or Kapha constitutions [8]. Telles et al. documented greater day-time somnolence in Kapha constitution and greater incidence of nighttime insomnia in individuals with Vata constitution, consistent with Ayurvedic theory [10]. Bell et al. reported that Kapha constitution appeared to be protective from osteoporosis yet at greater risk for obesity, whereas Vata constitution was protective from obesity yet associated with constipation, irritable bowel syndrome, and panic attacks [11]. Seeking potential genetic linkages among constitution types, Prasher et al. examined genome wide expression, biochemical, and hematological parameters and reported significant differences among each constitutional type [6].
In Ayurveda, as with other taxonomic systems, it is understood that when the psychobiological tendencies of the basic constitution are out of balance, illness can ensue [5], [8]. The imbalance itself is called Vikruti in Ayurveda and is defined as a vitiation of the constitution or inherent doshic imbalance that provides strong tendencies towards pathological states [5], [8]. It is not clear from the studies reviewed above on Prakruti, whether the Vikruti imbalances were also (inadvertently) taken into consideration in those studies, although it is clinically appreciated that in cases of extreme Vikruti, the imbalance can mask the constitution. What is most relevant for a diagnosis to inform personalized treatment is the Vikruti assessment, which describes the particular state of current imbalance and symptomatology. While Prakruti describes the balance of the doshas at conception, Vikruti refers to the balance of the doshas in the present and thus defines the nature of imbalance or illness. Ayurvedic treatment seeks to restore the balanced state of Prakruti in the patient.
With these considerations in mind, this study examined associations among Vikruti imbalances as assessed via questionnaire and Western descriptions of psychological states. We hypothesize that Western diagnoses and descriptors of psychological status correlate to specific imbalances in the doshas. Understanding correlates among diagnostics used across various medical systems is of interest to integrative researchers and clinicians; studies on this topic are currently lacking and warranted. For psychological states, we used a standardized panel of questionnaires examining anxiety, negative mood, rumination & reflection, mindfulness, stress, and overall quality of life.
2. Materials & methods
2.1. Study participants and design
This study represents a secondary analysis of The Self-Directed Biological Transformation Initiative (SBTI), which was a multi-dimensional Ayurvedic Medicine wellbeing intervention study that has been reported on elsewhere [12], [13].
Participants were recruited from the University of California (UC) San Diego in La Jolla, CA and the Chopra Center for Wellbeing in Carlsbad, CA. Eligible individuals were English-speaking women and men aged 30–80 years of age with no current major medical or mental illnesses and willing to refrain from drinking more than one alcoholic beverage per day during the weeklong study. Individuals who had previously participated in a yoga or meditation retreat of any kind within the past 12 months, or who were using illicit drugs, were excluded from participation. There were no expenses for participation in the study. The UC San Diego Institutional Review Board (IRB) approved the study (#140564) and all study subjects provided written informed consent prior to participation (ClinicalTrials.Gov number NCT02241226).
2.2. Assessments
The participants completed the following questionnaires to categorize their Vikruti type and their psychological states, and the corresponding data was used in our analyses.
Vikruti Questionnaire. This 60-item questionnaire was developed by a team of physicians at the Chopra Center for Wellbeing trained in Ayurvedic Medicine and has been used clinically for the past 15 years. It begins with a brief Prakruti assessment, then assesses Vikruti for each of the three doshas [11]. The questionnaire is based on classic Ayurvedic descriptions for symptoms that occur when a particular dosha is out of balance, or vitiated. The participant is asked to rate the symptoms as “very often”, “sometimes”, or “not often” with a score of 5, 3, and 1, respectively. A higher Vikruti score equates to more imbalance, or accumulation, of that respective dosha.
PROMIS Anxiety Scale. An 8-item scale that is part of the National Institute of Health research initiative, the Patient-Reported Outcomes Measurement System (PROMIS) and Assessment Center, assessing the full range of anxiety symptoms [14].
Center for Epidemiology Studies-Depression (CES-D). A 20-item self-report screening tool for depressive symptoms developed by the National Institute of Mental Health [15], [16].
Perceived Stress Scale (PSS). A 10-item scale which assesses the degree to which situations in one's life are appraised as stressful [17].
Mindful Attention Awareness Scale (MAAS). A 15-item scale that assesses trait mindfulness, namely a state of mind in which attention, informed by awareness of the present, observes what is taking place [18].
Rumination-Reflection Questionnaire (RRQ). A 25-item scale that assesses both rumination and reflection, with rumination defined as self-attentiveness motivated by perceived threats, losses, or injustices to the self, and reflection defined as self-attentiveness motivated by curiosity or epistemic interest in the self [19].
Ryff Scale of Wellbeing. This 84-item questionnaire assesses psychological wellbeing [20].
2.3. Data analysis
Using the SPSS Dimension Reduction Factor Analysis program, the respective Vikruti Questionnaire scores were reduced to a single factor score for each factor that came out with an Eigenvalue > 1. The data reduction results were as follows: Vata: a single factor, Eigenvalue 1.42; 70.8% of variance; Pitta: a single factor, Eigenvalue 1.44; 69.3% of variance; Kapha: a single factor, Eigenvalue 1.48; 73.9% of variance. For each Vikruti factor, we then conducted separate Multivariate General Linear (MGL) models, which are suitable for simultaneous assessment of multiple dependent variables within the same design matrix. Note that unlike how the doshas themselves are traditionally examined by a specific category, Vikruti are examined more linearly in terms of degree of imbalance. In three separate MGL models, the fixed factors were the respective Vikruti mind-body factor, with the other two Vikruti factors serving as covariates. For example, in one model Vata Vikruti was the fixed factor and Pitta Vikruti and Kapha Vikruti served as covariates. These covariate controls were used to isolate the unique relationship of each respective Vikruti to the dependent variables independent of the influence of the other two Vikruti. Age, gender and BMI were also used as covariates. For each MGL model, the dependent variables simultaneously assessed were anxiety, poor mood, mindfulness, rumination & reflection, stress, and quality of life (SPSS version 24.0).
3. Results
In total, 101 women and men (80.2% female) completed the study (see Table 1 for sample characteristics).
Table 1.
Participant characteristics.
| Characteristics (N=101) | Mean ± SD or % |
|---|---|
| Age (years) | 53.9 ±11.7 |
| Body mass index (kg/m2) | 23.7 ± 4.1 |
| Gender (% female) | 80.2 |
| Vikruti scores | |
| Vata | 42.9 ± 12.7 |
| Pitta | 39.2 ± 10.6 |
| Kapha | 38.5 ± 12.8 |
| Vata Vikruti Factor | Eigenvalue 1.42 accounting for 70.8% of variance |
| Pitta Vikruti Factor | Eigenvalue 1.44 accounting for 69.3% of variance |
| Kapha Vikruti Factor | Eigenvalue 1.48 accounting for 73.9% of variance |
| Anxiety (PROMIS) | 17.6 ± 6.6 |
| Mood (CESD) | 11.7 ± 11.1 |
| Stress (PSS) | 13.7 ± 6.9 |
| Mindfulness (MAAS) | 4.08 ± 0.88 |
| Rumination (RRQ) | 3.05 ± 0.94 |
| Reflection (RRQ) | 4.10 ± 0.68 |
| Wellbeing (Ryff) | 396.8 ± 56.5 |
Results from the multivariate general linear models are presented in Table 2. Neither age, gender or BMI were significant covariates for any of the models. For Vata Vikruti, the overall model was significant (F = 15.38, partial eta squared 0.987; p < 0.001). Significant dependent variable associations were more anxiety (F = 2.79; p ≤ 0.05) and more rumination (F = 3.61; p ≤ 0.01) and less mindfulness (F = 2.73; p ≤ 0.05) and less quality of life (F = 5.90; p ≤ 0.01). For Pitta Vikruti, the overall model was significant (F = 9.17, partial eta squared 0.969; p ≤ 0.01). Significant dependent variable associations were less mindfulness (F = 2.24; p ≤ 0.05), poorer mood (F = 2.10; p ≤ 0.01) and more anxiety (F = 2.25; p ≤ 0.05) and more stress (F = 2.07; p ≤ 0.05). For Kapha Vikruti, the overall model was significant (F = 5.91; partial eta squared 0.948; p < 0.001). Significant dependent variables were more stress (F = 2.81; p ≤ 0.01), more rumination (F = 2.07; p ≤ 0.05) and less reflection (F = 2.27; p ≤ 0.05).
Table 2.
Predictors of Vikruti imbalances.
| Vata Vikruti Factor |
| More anxiety∗ |
| Less mindfulness∗ |
| More rumination∗∗ |
| Less quality of life∗∗ |
| Pitta Vikruti Factor |
| More anxiety∗ |
| Less mindfulness∗ |
| Poorer mood∗∗ |
| More stress∗ |
| Kapha Vikruti Factor |
| More stress∗∗ |
| More rumination∗ |
| Less reflection∗ |
∗p ≤0.05; ∗∗p ≤0.01.
4. Discussion
Prior studies examining Ayurvedic dosha classifications focused almost exclusively on Prakruti [5], [8], [9], [10], [11], the basic constitutional classification. The Vikruti classification of imbalances, however, has received very little attention in the literature. As Vikruti is descriptive of the current state of imbalance, it has more implications for personalized treatment options, whereas the Prakruti has more predictive implications.
We found that those with more imbalanced, or vitiated Vata, as measured via the Ayurvedic questionnaire had more anxiety and rumination as well as less mindfulness and poorer overall quality of life. Individuals with more dominant Vata dosha are understood to be inherently more vulnerable to anxiety, panic attacks, and insomnia [10], [11]. Interestingly, neural models of brain types among the constitutions have been proposed [21] with the ‘Vata brain-type’ having a high range of activity in the prefrontal cortex and limbic systems, leading to experiencing high arousal and over-reacting, and being vulnerable to have excessive fears and phobias [21]. Constitutionally, Vata is understood to be associated with signaling pathways that regulate cell growth and differentiation [6]. Interestingly, in the current exploratory analysis, we observed greater anxiety and rumination with lower quality of life and levels of mindfulness in subjects reporting Vata-type symptoms.
For those with reporting symptoms of imbalanced Pitta, we found more anxiety and stress as well as less mindfulness. Pitta-dominant individuals tend to experience more ulcers, bleeding disorders, and skin diseases [22]. In aging investigations, Pitta-dominant individuals had a higher basal metabolic rate and energy usage which predisposes such individuals to greater tissue loss and premature aging compared to Kapha individuals who tended toward delayed aging [23]. Studies correlating metabolic differences among Prakruti types with metabolic markers have revealed that Pitta-dominant individuals are fast- and Kapha-dominant individuals are slow-metabolizers based on drug metabolizing enzyme markers. In a rheumatoid arthritis (Vikruti) cohort stratified into 3 dosha-dominant subtypes (i.e. Vata, Pitta Kapha), the Pitta-dominant patient subgroup had more mutations in oxidative stress pathways compared to the Vata or Kapha subgroups [24]. Genopsycho-somatotyping of different types classified Pitta-dominant types as more androgenic with tendencies towards frustration, aggression, irritability, and impatience when out of balance [25]. Interestingly, in the current study we have observed poorer mood and less mindfulness in the individuals with Pitta imbalance which may be related to the inherently higher androgen levels in these subjects that may increase further during states of Vikruti.
Higher Kapha Vikruti scores were associated with more stress and rumination and less reflection. In a study of coronary artery disease (CAD) patients divided into dosha subgroups, the Kapha-dominant subgroup correlated with more inflammatory markers, CAD risk factors (hypertension, diabetes, dyslipidemia), and insulin resistance compared to the other groups [26]. Studies report that Kapha-dominant individuals display greater markers for metabolic syndrome, cardiovascular disease and chronic inflammation. Kapha individuals tend towards higher blood lipids (e.g. high total cholesterol, triglycerides, and LDL/HDL ratio), uric acid which is a predictor of cardiovascular mortality, and atherosclerotic risk factors (e.g. high LDL and downregulation of genes in fibrinolysis pathways) [6]. We speculate that this slower metabolism in Kapha-dominant types induces metabolic stress that is later perceived as stressful by the individual and could manifest later as an imbalance.
Limitations of this study include that Vikruti was assessed by questionnaire and not by other traditional methods such as pulse method of diagnosis [27], [28]. In addition, we studied individuals who were relatively healthy and had no overt disease.
How do Ayurvedic physicians approach treating Vikruti imbalances? Disharmony among the doshas are managed by dietary and lifestyle interventions, including herbs, proper diet, massage, daily routine, meditation, yoga and detoxification. Herbal treatments with Withania somnifera or Ashwagandha, for example, are used to treatment stress and anxiety [29], [30]. Treatments often include what is called Panchakarma, a form of cleansing and detoxification [13], [31]. These Ayurvedic approaches help eliminate the Vikruti and restore the foundational constitution and are found to improve wellbeing and health [12], [13], [32]. For example, we recently examined the effects of a brief intensive multi-dimensional Ayurvedic intervention which included herbs, vegetarian diet, meditation, yoga, and massage and found significant improvements in psychosocial wellbeing and metabolomics profiles related to health [12], [13].
5. Conclusion
In summary, these findings provide further insight into traditional Ayurvedic diagnostic methods for assessing imbalances in mental wellbeing, which we found mapped with several Western measures of psychological states. Ayurvedic dosha assessment tools such as questionnaires may represent effective means to help assess physical as well as emotional wellbeing in research and integrative clinical settings. Demonstrating correspondence between Vikruti and such Western markers may help inform biomedical research and personalized therapy by informing diagnostics. While Prakruti is relevant for insight into the genetic background and disease susceptibly of patients, the Vikruti assessment is important to inform personalized treatment for the particular state of current imbalance, symptomatology, and pathology. Understanding the current Vikruti in an individual informs treatment to systematically restore the balanced state of Prakruti. Understanding associations between Ayurvedic Vikruti diagnoses and genetic or biochemical makers is of interest to integrative health researchers and will, where applicable, facilitate further understanding and potential integration of Ayurveda with modern scientific and clinical investigation.
Source of support
One or more authors have received funding and/or advisory fees from health companies for other projects. C.T.P. is a UC San Diego Post-Doctoral Fellow partially supported by the Chopra Foundation. S.P. and L.W. are employed by the Chopra Center. S.G.K. is a consultant to the Chopra Center.
Conflict of interest
Chopra centre for wellbeing, CA.
Acknowledgements
Authors acknowledge the support by The Fred Foundation, The MCJ Amelior Foundation, The Chopra Foundation, The National Philanthropic Trust, and The Walton Family Foundation. Authors also thank the many individual donors who supported the study.
Footnotes
Peer review under responsibility of Transdisciplinary University, Bangalore.
Supplementary data related to this article can be found at https://doi.org/10.1016/j.jaim.2018.02.001.
Appendix A. Supplementary data
The following is the supplementary data related to this article:
References
- 1.Yapijakis C. Hippocrates of Kos, the father of clinical medicine, and Asclepiades of Bithynia, the father of molecular medicine. Review. In Vivo. 2009;23(4):507–514. [PubMed] [Google Scholar]
- 2.Friedman M., Rosenman R.H. Type A Behavior Pattern: its association with coronary heart disease. Ann Clin Res. 1971;3(6):300–312. [PubMed] [Google Scholar]
- 3.Sheldon W.H. The somatotype, the morphophenotype and the morphogenotype. Cold Spring Harb Symp Quant Biol. 1950;15:373–382. doi: 10.1101/sqb.1950.015.01.035. [DOI] [PubMed] [Google Scholar]
- 4.Pandey M.M., Rastogi S., Rawat A.K. Indian traditional ayurvedic system of medicine and nutritional supplementation. Evid Based Complement Alternat Med. 2013;2013:376327. doi: 10.1155/2013/376327. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Chopra A., Doiphode V.V. Ayurvedic medicine. Core concept, therapeutic principles, and current relevance. Med Clin North Am. 2002;86(1):75–89. doi: 10.1016/s0025-7125(03)00073-7. vii. [DOI] [PubMed] [Google Scholar]
- 6.Prasher B., Negi S., Aggarwal S., Mandal A.K., Sethi T.P., Deshmukh S.R. Whole genome expression and biochemical correlates of extreme constitutional types defined in Ayurveda. J Transl Med. 2008;6:48. doi: 10.1186/1479-5876-6-48. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Cheng S.-C., Lin C.-H., Chang Y.-J., Lee T.-H., Ryu S.-J., Chen C.-H. Fire-heat and Qi deficiency syndromes as predictors of short-term prognosis of acute ischemic stroke. J Altern Complement Med. 2013;19(8):721–728. doi: 10.1089/acm.2012.0546. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Manyam B.V., Kumar A. Ayurvedic constitution (Prakruti) identifies risk factor of developing Parkinson's disease. J Altern Complement Med. 2013;19(7):644–649. doi: 10.1089/acm.2011.0809. [DOI] [PubMed] [Google Scholar]
- 9.Samarakoon S.M., Chandola H.M., Ravishankar B. Effect of dietary, social, and lifestyle determinants of accelerated aging and its common clinical presentation: a survey study. Ayu. 2011;32(3):315–321. doi: 10.4103/0974-8520.93906. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Telles S., Pathak S., Kumar A., Mishra P., Balkrishna A. Ayurvedic doshas as predictors of sleep quality. Med Sci Monit. 2015;21:1421–1427. doi: 10.12659/MSM.893302. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Bell C., Heidel R.E., Sunega J., Drisko J. Ancient wisdom. Can ayurvedic prakruti provide invaluable insights into integrative medicine? Ayurveda J Health. 2017;27:27–34. [Google Scholar]
- 12.Mills P.J., Wilson K.L., Pung M.A., Weiss L., Patel S., Doraiswamy M. The self-directed biological transformation initiative and well-being. J Altern Complement Med. 2016;22(8):627–634. doi: 10.1089/acm.2016.0002. [DOI] [PubMed] [Google Scholar]
- 13.Peterson C.T., Lucas J., John-Williams Lisa St., Will Thompson J., Arthur Moseley M., Patel S. Identification of altered metabolomic profiles following a panchakarma-based ayurvedic intervention in healthy subjects: the self-directed biological transformation initiative (SBTI) Sci Rep. 2016;6:32609. doi: 10.1038/srep32609. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Broderick J.E., DeWitt E.M., Rothrock N., Crane P.K., Forrest C.B. Advances in patient-reported Outcomes: the NIH PROMIS((R)) measures. EGEMS (Wash DC) 2013;1(1):1015. doi: 10.13063/2327-9214.1015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Radloff L.S. The use of the center for epidemiologic studies depression scale in adolescents and young adults. J Youth Adolesc. 1991;20(2):149–166. doi: 10.1007/BF01537606. [DOI] [PubMed] [Google Scholar]
- 16.Andresen E.M., Malmgren J.A., Carter W.B., Patrick D.L. Screening for depression in well older adults: evaluation of a short form of the CES-D (Center for Epidemiologic Studies Depression Scale) Am J Prev Med. 1994;10(2):77–84. [PubMed] [Google Scholar]
- 17.Cohen S., Kamarck T., Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385–396. [PubMed] [Google Scholar]
- 18.Brown K.W., Ryan R.M. The benefits of being present: mindfulness and its role in psychological well-being. J Pers Soc Psychol. 2003;84(4):822–848. doi: 10.1037/0022-3514.84.4.822. [DOI] [PubMed] [Google Scholar]
- 19.Trapnell P.D., Campbell J.D. Private self-consciousness and the five-factor model of personality: distinguishing rumination from reflection. J Pers Soc Psychol. 1999;76(2):284–304. doi: 10.1037//0022-3514.76.2.284. [DOI] [PubMed] [Google Scholar]
- 20.Ryff C.D., Singer B. Psychological well-being: meaning, measurement, and implications for psychotherapy research. Psychother Psychosom. 1996;65(1):14–23. doi: 10.1159/000289026. [DOI] [PubMed] [Google Scholar]
- 21.Travis F.T., Wallace R.K. Dosha brain-types: a neural model of individual differences. J Ayurveda Integr Med. 2015;6(4):280–285. doi: 10.4103/0975-9476.172385. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Dey S, Pahwa P. Prakriti and its associations with metabolism, chronic diseases, and genotypes: possibilities of new born screening and a lifetime of personalized prevention. J Ayurveda Integr Med. 2014;5(1):15–24. doi: 10.4103/0975-9476.128848. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Purvya M.C., Meena M.S. A review on role of prakriti in aging. Ayu. 2011;32(1):20–24. doi: 10.4103/0974-8520.85719. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Juyal R.C., Negi S., Wakhode P., Bhat S., Bhat B., Thelma B.K. Potential of ayurgenomics approach in complex trait research: leads from a pilot study on rheumatoid arthritis. PLoS One. 2012;7(9):e45752. doi: 10.1371/journal.pone.0045752. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Rizzo-Sierra C.V. Ayurvedic genomics, constitutional psychology, and endocrinology: the missing connection. J Altern Complement Med. 2011;17(5):465–468. doi: 10.1089/acm.2010.0412. [DOI] [PubMed] [Google Scholar]
- 26.Mahalle N.P., Kulkarni M.V., Pendse N.M., Naik S.S. Association of constitutional type of Ayurveda with cardiovascular risk factors, inflammatory markers and insulin resistance. J Ayurveda Integr Med. 2012;3(3):150–157. doi: 10.4103/0975-9476.100186. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Kurande V., Waagepetersen R.., Toft E., Prasad R. Intrarater and interrater reliability of pulse examination in traditional Indian Ayurvedic medicine. Integr Med Res. 2013;2(3):89–98. doi: 10.1016/j.imr.2013.07.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Niemi M., Stahle G. The use of ayurvedic medicine in the context of health promotion–a mixed methods case study of an ayurvedic centre in Sweden. BMC Complement Altern Med. 2016;16:62. doi: 10.1186/s12906-016-1042-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Pratte M.A., Nanavati K.B., Young Y., Morley C.P. An alternative treatment for anxiety: a systematic review of human trial results reported for the Ayurvedic herb ashwagandha (Withania somnifera) J Altern Complement Med. 2014;20(12):901–908. doi: 10.1089/acm.2014.0177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Chandrasekhar K., Kapoor J., Anishetty S. A prospective, randomized double-blind, placebo-controlled study of safety and efficacy of a high-concentration full-spectrum extract of ashwagandha root in reducing stress and anxiety in adults. Indian J Psychol Med. 2012;34(3):255–262. doi: 10.4103/0253-7176.106022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Deshpande H. Assessment of quality of life in patients with skin disorders undergoing ayurvedic Panchakarma (biopurification) as management. J Evid Based Complement Altern Med. 2016;21(3):215–220. doi: 10.1177/2156587215615026. [DOI] [PubMed] [Google Scholar]
- 32.Deshpande H., Shivakumar, Kavita M.B., Tripathy T.B., Chaturvedi A. Healthcare and disease management in Ayurveda. Altern Ther Health Med. 2001;7(2):44–50. [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.