Prakriti, the constitution of an individual according to Ayurveda, is the sum total of physical, psychological and physiological traits expressed in that individual. According to the principles of Ayurveda, Doshas determine one’s Prakriti (Tripathi and Sin gh, 1994). There are three Doshas: Vata, Pitta and Kapha. Doshas are defined as the fundamental, mutually antagonistic - yet reciprocal - mechanisms responsible for maintaining the homeostasis, and thus, health. When these mechanisms deviate from their state of equilibrium, the result is often ill-health and disease (Dubey et al., 2015; Patwardhan, 2013). Ayurveda constructs all its principles governing the physiological, nutritional, pathological, and pharmacological understandings around the axial framework of this theory (Jayasundar, 2010). Each of these Doshas has been ascribed with specific mutually opposite attributes (Gunas). Ayurveda proposes that a specific ‘attribute’ of a Dosha has a causal relationship with the specific trait expressed in an individual (Dubey et al., 2015). For instance, Pitta possesses the ‘Ushna’ (heat) attribute which determines the enhanced digestive and metabolic abilities of an individual, whereas, Kapha possesses ‘Shita’ (cold) attribute that causes sluggishness in digestive and metabolic abilities. In the same manner, Vata possesses Cala (mobility) attribute that makes the individual active, whereas, Kapha possesses Stimita (rigid) attribute that makes the individual less active (Dubey et al., 2015; Tripathi et al., 2011).

The Prakriti of an individual is determined by the dominance of one, two or three Doshas expressed in that individual. Though it is determined genetically, several environmental factors too contribute in its manifestation. Therefore, on the basis of one, two or three dominant Doshas expressed in an individual, one can have any one of the seven possible types of Prakriti: Vata, Pitta, Kapha, Vata-Pitta, Pitta-Kapha, Vata-Kapha, and Sama Doshaja (balanced state of all the three Doshas).

In the recent years, the individualized approach to therapeutics has received impetus with the growing understandings in the field of genetics. Several workers have investigated the possible association of constitutional types with the individual genetic make-up, metabolic abilities and chronic diseases. There have been several efforts to see whether certain physiological, haematological or biochemical tools can be used to establish a link between constitution types and other health-related parameters. (Aggarwal et al., 2010; Bhalerao and Deshpande, 2012; Dey and Pahwa, 2014; Ghodke et al., 2011; Patwardhan et al., 2005; Prasher et al., 2008).

A few workers in the past have hypothesised that certain autonomic responses might vary in accordance with the constitutional types as defined in Ayurveda (Thompson, 2005). One of the early studies in this regard has reported that the healthy individuals with Vata, Pitta and Kapha Prakriti exhibited a relative preponderance of blood Cholinesterase, Monoamine oxidase and Histaminase activity, respectively (Udupa et al., 1975). We, in one of our previous studies have reported that individuals having Pitta as a contributing component to their Prakriti, tend to show a significant rise in diastolic blood pressure immediately after isotonic exercise in comparison to others indicating a possible higher sympathetic activity (Tripathi et al., 2011). Considering the fact that certain autonomic responses might vary in accordance to age and gender of an individual, it was logical for us to hypothesise that these responses might also vary according to Prakriti (Manor et al., 1981; Moodithaya and Avadhany, 2009; Moodithaya and Avadhany, 2012). However, there are no studies in this area reporting a possible link between Prakriti and autonomic responses. If this kind of a relationship is confirmed, it would, apart from being helpful in predicting the susceptibility of an individual to certain h ealth conditions, also prove beneficial in determining one’s constitution by providing some objective and easy-to-conduct laboratory tests. This may be of value given the fact that the process of determining one’s Prkariti by itself is a challenging task (Kurande et al., 2013; Kurande et al., 2013; Tripathi et al., 2011).

With this background, we planned the present study to investigate a possible relationship between certain autonomic responses and Prakriti. We hypothesized that people belonging to Kapha-dominant Prakriti might have a higher parasympathetic activity because of the specific attributes of Kapha such as Manda (slow), Guru (heavy), Snigdha (fatty/oily), Sandra (dense) and Stimita (rigid). Similarly, we hypothesized that individuals with Vata dominant Prakriti may have a higher sympathetic activity because of the attributes such as Laghu (light), Sukshma (minuscule), Cala (mobile), and Shighra (swift) (Dubey et al., 2015).

The approval from the institutional ethics committee was obtained before starting the study.

After administering the self-assessment tool to determine Prakriti among the volunteers, we observed that no volunteer had scored zero for any Dosha. In other words, each volunteer had scored at least some points for each Dosha. Therefore, we could not name any class of volunteers to be strictly 'Ekadoshaja' (Prakriti with single Dosha) or 'Dvandvaja' (Prakriti with two Doshas). Similarly, we found no volunteer who scored equal scores for all the three Doshas and, hence, there was no 'Samadoshaja' individua l in our sample either. Therefore, we decided to classify the sample into three groups based on the primary Dosha (most dominant Dosha) that contributed to one’s Prakriti. Table 1 shows that out of 106 volunteers, the maximum number (50%) of volunteers had Kapha as the primary Dosha while minimum number (22%) of volunteers had Pitta as the primary Dosha. Table 1 also shows that the mean percentage scores for primary Dosha in one group were significantly greater (p < 0.001) than the mean percentage scores for the same Dosha in other two groups. Table 2 gives the details of distribution of the whole sample (n = 106) according to the score range for Vata, Pitta and Kapha separately.

The consolidated Table 3 shows the results of all the tests, except for pupil cycle time which are shown in Table 4. From the Table 3 it can be seen that the maximum increase in systolic and diastolic blood pressure during the cold exposure varied significantly as per primary Dosha, the increase being significantly higher in Vata group in comparison to Kapha group in both the cases (p = 0.000 and p = 0.021 respectively). However, the maximum increase in diastolic BP was significantly greater in Vata group in comparison to Pitta group too (p = 0.046). The S/L ratio significantly varied as per primary Dosha, the ratio being significantly greater in Kapha group in comparison to Vata (p = 0.024) group. The Valsalva ratio significantly varied as per primary Dosha, the ratio being significantly lower in Pitta group in comparison to Vata and Kapha groups (p = 0.035 and p = 0.000 respectively). The right pupil diameter in light varied significantly as per primary Dosha, the diameter being lower in Kapha group in comparison to Pitta and Vata groups (p = 0.002 and p = 0.036 respectively). Similarly, the left pupil diameter in light too varied significantly as per primary Dosha, the diameter being lower in Kapha group in comparison to Pitta and Vata groups (p = 0.007 and p = 0.035 respectively).

Table 4 suggests that the pupil cycle time varied significantly in right eye as per primary Dosha group, the mean cycle time being greater in Kapha group in comparison to Pitta group (p = 0.026). Similarly, the pupil cycle time varied significantly in the left eye too as per primary Dosha group. In this case too, the mean cycle time was greater in Kapha group in comparison to Pitta group (p = 0.036).

The tool that we have used in the present study assumes that each Dosha can express itself in a person to its fullest extent (100%) and calculates the percentage expression of that Dosha on ‘absolute’ basis unlike some other popular tools available for assessing Prakriti such as AyuSoft, which calculate the percentage contribution of each Dosha on a ‘relative’ basis (AyuSoft, a decision support software developed by C-DAC, 2005).

In this kind of relative calculation, if the score-wise contributions of Vata, Pitta and Kapha in an individual are, say, 5, 10 and 5 respectively, the final result displayed will be: Vata-25%, Pitta-50% and Kapha-25%. Therefore, when this kind of a tool expresses the contribution of a Dosha to be 50%, it need not necessarily mean that the concerned Dosha expresses 50% of the total traits ascribed to it in the classical Ayurveda textbooks. This is because, the denominator used in such a calculation is not the maximum ‘attainable’ scores for that Dosha, rather, it is the sum of the total scores ‘attained’ for all the three Doshas by that individual. This calculation ignores the total number of traits (i.e., the maximum attainable scores) ‘ascribed’ to a Dosha, but only considers the total number of scores ‘attained’ by an individual for each Dosha for final analysis of the results.

In the present tool that we have used in our study, however, the results are derived in terms of absolute percentage values, where, the calculation of contribution of one Dosha does not depend on the contribution of other Doshas. Therefore, if this tool expresses the contribution of a Dosha to be 50%, it definitely means that the concerned Dosha expresses 50% of the total traits ascribed to it.

Though, ‘which kind of a tool is ideal and suitable for research’ is a matter of debate, the absolute expression has certain edge over the relative expression because it gives a precise idea about the extent of expression of a particular Dosha. Further, the results obtained by this method can always be converted into ‘relative’ expression, if a researcher desires so.

From a point of scientific curiosity, we also tried classifying the sample on the basis of ‘two most dominant Doshas’. However, while doing so, we encountered a question as to how should we group the individuals with same Dosha composition but with varying dominance? For instance, if we group people with ‘Vata-Kapha’ and ‘Kapha-Vata’ into a single group, the significance of dominance would be lost, compromised and even may get nullified. Similarly, if we classify ‘Vata-Kapha’ and ‘Kapha-Vata’ into two different groups, there would be a total of ten groups, which is again, against the recommendation of the classical textbooks of Ayurveda. Therefore, we concluded that the classification of the sample by most dominant Dosha (primary Dosha) was the most rational one.

The autonomic nervous system has two components: a. Sympathetic, and, b. Parasympathetic. The sympathetic activity is dominant during emergency “fight-or-flight” situations and during exercise. The effect of sympathetic stimulation under such circumstances is to prepare the body for vigorous physical activity by increasing the blood flow to the skeletal muscles. The parasympathetic system, on the other hand, is dominant during quiet, resting conditions. The effect of the parasympathetic system in such situations is to conserve energy and to regulate basic body functions such as digestion, and, an optimal, moderate heart rate (McCorry, 2007).

According to the concept of constitution in Ayurveda, Kapha people are usually less dynamic, more stable, more relaxed and are more lethargic; whereas, the Vata and Pitta people are more excitable, anxious, aggressive, and are often volatile. These traits prompted us to propose a hypothesis that, Vata and Pitta individuals may be sympathetically dominant while the Kapha individuals may be parasympathetically dominant (Low et al., 2013).

As the results of Cold Pressor Test indicate, the sympathetic activity in Vata group is higher than that in Kapha group as far as Cold Pressor Test is concerned. Similarly, the results of S/L ratio indicate that the corresponding sympathetic activity in Vata group is higher than that in Kapha group. The results of Valsalva ratio suggest that the corresponding parasympathetic activity in Pitta group is lower than that in Vata and Kapha groups. Further, the Pupil Diameter in light was relatively smaller in Kapha group in comparison to Pitta and Vata groups suggesting that the corresponding sympathetic activity may be relatively higher in Vata and Pitta groups in comparison to Kapha group. However, since the differences in the mean pupil diameter were too small to have any clinical significance, a similar study in a large sample is recommended. The results of Pupil Cycle Time suggest that the corresponding ocular parasympathetic activity is relatively lower in Kapha group in comparison to Pitta group. This is in accordance with the observation recorded in an earlier study that cardiac parasympathetic activity may be negatively correlated with pupillary parasympathetic activity (Moodithaya and Avadhany, 2009). It is to be noted however, that all the results mentioned above were within the physiological limits in all the volunteers.

The overall impression that we could gather from this study is that Vata and Pitta individuals may have a relatively dominant sympathetic activity whereas Kapha individuals may have a relatively dominant parasympathetic activity (within the physiological limits) when it comes to cardiovascular responses. However, when the pupil cycle time is considered, the opposite seems to hold true, i.e., Kapha individuals may have a relative dominance of sympathetic activity than Pitta individuals.

A relatively small sample size of the study limits the generalizability of the results to a larger population. Volunteers belonging to both the genders were included in the study; hence, it ignores any possible gender differences with respect to autonomic responses.

The study suggests that people with Kapha as the most dominant Dosha tend to have eith er a higher parasympathetic activity or a lower sympathetic activity in comparison to other groups in the context of cardiovascular reactivity. The study also suggests a possibility that autonomic function tests, especially the ones related with cardiovascular reactivity and pupillary responses may serve as indicators to identify the primary Dosha contributing to the Prakriti in an individual. Further, the present model of grouping people depending on their ‘primary Dosha’ seems to be a useful and practical approach that researchers may like to explore, while investigating various aspects of Prakriti.