Effects of Grounding (Earthing) on Massage Therapists: An Exploratory Study

It is well known that massage therapists often develop a number of health problems relatively early on in their career. A preliminary study showed that grounding massage therapists during their work may alleviate some of the health problems they encounter. A doubled-blind randomized controlled trial was designed to examine the effects of working and sleeping grounded for 4 weeks on massage therapists’ blood viscosity, stress (through HRV), inflammation (IFN- γ , IL-6, TNF- α , and hsCRP) and oxidative stress (MPO and MDA) biomarkers. The results show stress reduction as measured by heart rate, respiratory rate and hear rate variability (HRV) and a lowering effect on blood viscosity that lasted for at least one week after ungrounding, with systolic blood viscosity becoming significantly lower at the end of the study. Inflammation markers (IFN- γ , TNF- α , and hsCRP) increased rapidly, within one week, after ungrounding. The findings suggest that grounding is beneficial for massage therapists in multiple domains relevant to health and wellbeing.


Earthing (Grounding)
Earthing, or grounding, are terms interchangeably used to describe the condition of being in direct contact with the earth (ground). Examples of grounding

Study Design and Procedures
Participants were explained the research protocol and signed the consent form approved by the IRB. A study staff member then asked each massage therapist to complete the Chopra Center medical form. The staff member also explained how to fill the Heart Monitor Log Form (to be filled at the end of every day of work). All massage techniques used at the Chopra Center were included in this project. The staff member also gave to each participant a Grounded Beauty Tummy Band (earthing.com, Thousand Palms, CA) with two number coded grounding cords and with instructions on how to use the Grounded Beauty Tummy Band at home and how to connect the second cord to the grounded mat in the massage room. Instructions were given on where and when to go to give a blood sample. Blood samples were taken by a licensed phlebotomist at the beginning of the study, at the end of week 5 and at the end of week 6.
At the end of the first week, a study staff member met with massage therapists to collect the log forms, make sure they were filled properly and that the protocol was followed. The staff member also took back the two number coded grounding cables and replaced them with two cables coded with different numbers. The process of exchanging cables for another set with a different number code was repeated every week and it was established to help maintain the double-blind nature of the study. Heart Monitor Log forms were collected at the end of every week at the same time a new set of cables was given except at the end of week 6 when no cables were given (that was the end of their participation in the study). Finally, a study staff member recorded any comment from the massage therapists related to their participation in the study.
A double-blind Randomized Controlled Trial (RCT) procedure was used based on the stepped wedge design. In a stepped wedge design, an intervention is rolled-out sequentially to the trial participants (either as individuals or clusters of individuals) over a number of time periods. The order in which the different individuals or clusters receive the intervention is determined at random and, by the end of the random allocation, all individuals or groups will have received the intervention. Stepped wedge designs incorporate data collection at each point where a new group (step) receives the intervention [11] [12]. In this project there were two interventions: grounding and sham-grounding. Each intervention was identified by a number coded band around the cord, the signification of the number code (grounded or sham grounded) not being known to the massage therapists, study staff and researchers. The number code was only known to the person who prepared the cables for this study. Except for the number coding band, all cords looked alike but the modified cords did not allow electrical conduction from the earth to the mat. The number coding information was kept secret until after the last week of the last cluster was completed and after all the log forms and blood sample results were received by the principal investigator (PI).
Therapists were randomly assigned to a cluster, or cohort. The duration of each cohort's participation was 6 weeks and was divided as follows: • First week of participation subjects were not grounded.
• The next 4-week period they were grounded.
• The last week they were not grounded.

Grounding Equipment and Method
Grounding (earthing) was accomplished in two ways: first using a grounding mat placed on the floor around the massage table in the massage room and through the use of a grounding tummy band that participants used at home during sleep. A study staff checked that the ground outlets used by massages therapists at the Chopra Center were working properly and massage therapists were given a ground checker to verify that their home grounding system was working properly. They were blinded to when they were or were not grounded, receiving a different "grounding" cord at the start of each week of the study. On weeks 1 and 6, therapists were given number coded cords that did not ground them (placebo cord) while they were given proper number coded grounding cords (active grounding cords) at weeks 2, 3, 4 and 5. In order for them not to suspect which week they were grounded or not, new number coded cords were given every week.

Blood Viscosity
Blood viscosity is an important factor affecting the ability of blood to circulate in the blood vessels. It is a factor contributing to cardiovascular disease [13], a risk factor for type 2 diabetes mellitus [14], and a predictor of decline in general cognition [15]. Since blood is a non-Newtonian fluid, its viscosity varies greatly during a cardiac cycle. Blood viscosity also varies with the anatomical configuration of an artery. For example, blood viscosity at the aorta is different from that at the coronary artery because the sheer rate is different at the two locations.
Blood viscosity is high at low shear rates and low at high shear rate. Normal blood viscosity varies from 3.8 cP (38 mP) at high shear rate (300 s −1 ) to about 20 cP (200 mP) at low shear rate (1 s −1 ). Blood viscosity at high shear rate is called systolic blood viscosity (SBV), analogous to systolic blood pressure, while blood viscosity at low shear rate is termed diastolic blood viscosity (DBV) [16].
Historically, accurately measuring blood viscosity was a difficult task that required the use of rotational viscometers that allowed testing for blood viscosity at a single shear rate. It was a time-consuming process and technically demand-

Biomarkers
Blood samples, which were collected in EDTA, were drawn at the beginning of week 1, and at the end of weeks 5 and 6 by a certified phlebotomist and imme-

Heart Rate Variability
Hearth Rate Variability (HRV) is an established measure of autonomic nervous system modulation of the cardiovascular system [19]. In this study, heart rate was recorded from a portable HRV monitor (Zephyr Biopatch sensor, Medtronic, Annapolis, MD). Subjects were given the Biopatch before their first day of work and they were instructed to wear the Biopatch sensor on the first work day of week 1, and on the last work day of week 5 and week 6. They were instructed to start the Biopath (i.e. start the recording of their HR data) at 8 am and to keep it recording until at least 30 minutes after they finish working on their last client.
HRV was calculated for four 10-minute periods for each of these 3 days. The 4 periods were: the first 10 minutes after they put on the Biopatch, the last 10 minutes before they work on their first patient, the first 10 minutes after they worked on the last patient and the last 10 minutes of the day. Participants were allowed to engage in free movement during the intervals at the beginning and end of the work day (sitting, standing, or walking). They were standing during the intervals immediately before and after the massages.
Variables calculated for each of the 10-minute periods from raw data included: • Average Heart Rate (HR); • Average Respiratory Rate (RR); • SDNN: the standard deviation of the interval between normal heart beats (the NN interval)  [20] using the VivoSense software platform (VivoSense, Inc., Newport Beach, CA). Digitized ECG data were analyzed to detect the R-wave peaks of the QRS complex. The power spectrum density (PSD) of the HRV signal was assessed using the nonparametric Welch periodogram method with Fast Fourier Transform (FFT) [21]. Since participants were allowed to move during intervals of HR/HRV recording (e.g., not required to remain stationary and sitting in a chair) we utilized a multi-step process to identify and remove artifacts from the signal that may be generated by motor activity. First, the beat-to-beat ECG waveform was visually inspected and missing or unidentified R-peaks were manually relabeled. RR interval artifacts were subsequently removed with linear spline interpolation. Third, an automated VivoSense artifact marking algorithm was also applied to identify and remove ectopic beats and spurious HR (excluding HR above 220 or below 30 bpm) before HRV data output. We developed an Heart Monitor Log Form to have a written record of exactly at what time in the morning participants put the BioPatch on and at what time they took it off. Test for difference in means (non-paired). Chi-square was used to determine significance between cohorts' gender distribution. We considered the usual 0.05 as the threshold for statistical significance. Chi-square analysis, however, indicated there was not a significant gender difference between the two cohorts (χ statistic = 2.62, p = 0.11). Age was not significantly different between the two Cohorts (t = 0.89, p = 0.38). However, BMI was significantly higher for males compared to females (t = 3.79, p = 0.002).

Blood Viscosity
Blood viscosity results are presented in Table 2 for cohorts and Table 3 for     Table 2 that Cohort A started week 1 with a significantly higher average blood viscosity than Cohort B for both SBV and DBV (p = 0.018 and p = 0.012, respectively).
Also, DBV was significantly lower for Cohort B at week 6 (p = 0.047).  Table 4 presents biomarker results for the concentration levels of IFN-γ, IL-6, TNF-α, hsCRP (markers of inflammation) and MPO and MDA (markers of oxidative stress). For Cohort A, IFN-γ average concentration was significantly higher at week 6 compared to week 1 and week 5 (p = 0.035 and 0.040, respectively). For Cohort B, TNF-α average concentration was higher at week 6 compared to week 1 (p = 0.023), while hsCRP average concentration was significantly higher at week 6 compared to week 1 and week 5 (p = 0.034 and 0.019, respectively). Looking at both cohorts combined, it can be seen that TNF-α average concentration was higher at week 6 compared to week 1 (p = 0.047) while hsCRP average concentration was significantly higher at week 6 compared to week 5 and week 1 (p = 0.015 and 0.017, respectively).    Table 4 for average concentration values). The same table also shows that TNF-α average concentration was significantly higher for Cohort A at week 1 (p = 0.038), and also when comparing all weeks combined (p = 0.009). Similarly, MPO average concentration was significantly higher for Cohort A at week 6 (p = 0.021), and also when comparing all weeks combined (p = 0.003). week 5 compared to week 1 (p =0.032), TNF-α average concentration was significantly lower at week 1 compared to week 5 and week 6 (p = 0.048 and 0.016, respectively), hsCRP average concentration was significantly higher at week 6 compared to week 1 and week 5 (p = 0.007 and 0.004, respectively), and MPO average concentration was higher at week 6 compared to week 1 (p = 0.047).

Blood Biomarkers
There are no significant results for male participants.  and all weeks combined. It can be seen that IFN-γ average concentration was significantly higher for males compared to females at week 6 (p = 0.013; see Table 6 for average concentration values). Also, TNF-α average concentration was significantly higher for males on week 1, week 5 and all weeks combined (p = 0.001, 0.030, and 0.00005, respectively). These results are not statistically significant (see Table 11). According to Table 10 (and Table 9), Cohort A had a significantly higher average HR at week 6 compared to week 1 (87.2 vs. 85.0; p = 0.027). Statistical analyses between weekly HR averages for Cohort B and for both cohorts combined produce no significant result.

LF
According to Table 10 and  Table 9 and

LF/HF
For LF/HF the results are similar as with LF, with week 5, week 6 and all weeks combined showing significantly higher average LF/HF value for Cohort A according to Table 9 and Table 10 (p = 0.002, 0.019, and 0.00002, respectively).
Also, Table 11 shows that Cohort A has significantly higher average LF/HF value at week 5 compared to week 1 (5.37 vs. 4.43; p = 0.013). This is also similar to LF.

Discussion
This exploratory study was conducted to extend a prior pilot study which examined the wellbeing effects of grounding on massage therapists being grounded while they performed their massage work [5]. This current study extended those findings by using a larger set of assessments and providing grounding during the therapist's night's sleep in addition to them being grounded while they performed their massage work.
While there are numerous findings to discuss, we begin with the random assignment process itself as it has a bearing on the subsequent discussion. Even though participants were randomly assigned to each group, the randomization process did not yield equitable cohorts in terms of gender, although this difference was not statistically significant (Table 1). There were several significant cohort baseline differences for some of the physiological data. First, both systolic blood viscosity (SBV) and diastolic blood viscosity (DBV) were statistically  Table   3 shows that males had significantly higher SBV and DBV than females for all weeks (except for SBV at week 5). Since Cohort B had only one male participant, this result implies that the lower blood viscosity for Cohort B at all weeks seen in Table 2 can be attributed at least partially to the fact that this cohort had fewer males. Also, Table 3 shows significant decreases in female blood viscosity at week 6 compared to week 5, for both SBV and SDV, while there were no significant results for male participants. This result implies that the significant decrease in SBV for Cohort B at week 6 compared to week 5 seen in Table 2 is most likely due to the female participants. From these results, it is clear that gender composition had an effect on cohorts' average blood viscosity. There is a known dependence of the oxygen delivery index (ODI) to hematocrit and SBV and it is also well known that females have a slightly lower hematocrit in general [13].
Since Cohort B was almost exclusively composed of females while Cohort A had the same number of females and males, it is likely that the difference in gender composition between cohorts contributed to blood viscosity (both SBV and DBV) to be slightly lower for Cohort B. However, it is not clear that gender composition was to only explanation for the lower blood viscosity of Cohort B.
A second indication that the cohorts were different from the start comes from blood biomarkers (Tables 4-8). From  Table 7 shows that females from Cohort A had a significantly higher MPO average concentration for all weeks compared to females from Cohort B (p = 0.0004). This last result indicates that there is probably another factor than gender making Cohort A higher in blood viscosity and biomarkers than Cohort B. We propose that this other factor could be time of the year as will be explained below. Also, from Table 8 (and Table 6 for average concentrations), IFN-γ average concentration was significantly higher for males at week 6 and male TNF-α average concentration was also significantly higher than that of females for week 1, week 5 and for all weeks combined. These results are other indications that male physiology is different than that of females and that gender composition contributed to differences in blood viscosity and biomarkers between cohorts.
A third line of evidence for basic physiological differences between cohorts comes from HRV analysis. LF, HF and LF/HF average values between cohorts  Tables 9-11). Also, for all three variables, Cohort A values are significantly different at week 5 and week 6. These results mean that each cohort autonomic nervous system (ANS) reacted differently during the duration of their participation. Why would Cohort A start and stay with higher levels of inflammation and stress compared to Cohort B during the entire time of their participation? We see two potential explanations. One explanation is because of difference in gender composition as already explained, however, we have seen evidence that this explanation cannot be the whole story (see Table 7 and related explanations). Another plausible explanation is time of the year. and that is what we observe in the data i.e. for all weeks combined, LF and LF/HF are significantly lower for Cohort B, while HF is significantly higher for Cohort B compared to Cohort A. In light of these very significant differences between cohorts, extra attention was given to each cohort and their difference in gender composition (for blood viscosity and biomarkers).
Coming back to blood viscosity, the normal range for SBV is between 3.7 and 4.4 cP while it is between 8.9 and 12.4 cP for DBV. According to results presented in Table 2, Cohort A started their first week of participation with normal levels of blood viscosity going down to lower levels during their participation time while Cohort B started with lower than normal levels of blood viscosity at week 1, stayed lower than normal for the entire duration of their participation, and became even lower at week 6 (the end of their participation time, after being ungrounded for one week). Table 2 also shows that SBV was significantly lower at week 6 compared to week 1 for Cohort A while a significant decrease in SBV was observed at week 6 compared to week 5 for Cohort B. These results show a tendency for blood viscosity to be lower at week 6 and suggest that the effect of grounding continue to improve blood viscosity at least one week after the end of the 4-week grounding period. Finally, Table 3 shows significantly lower SBV and DBV at week 6 for female participants but not for males, reinforcing the hypothesis that female participants were the reason for the decrease in blood viscosity at week 6 seen in Table 2 for Cohort B. However, gender composition cannot explain why SBV was significantly lower at week 6 compared to week 1 for Cohort A in Table 2, suggesting that gender composition is not involved in the production of this result.
Turning our attention to blood biomarkers, Table 4 shows that for Cohort A IFN-γ average concentration was significantly higher at week 6 compared to week 1 and week 5. The same table shows that for Cohort B TNF-α average concentration was significantly higher at week 6 compared to week 1 and hsCRP average concentration was higher at week 6 compared to week 1 and week 5. For both cohorts combined, TNF-α average concentration was higher at week 6 than at week 1 and also hsCRP concentration was higher at week 6 compared to week 5 and week 1. Since IFN-γ, TNF-α and hsCRP are markers of inflammation, these results suggest a tendency for inflammation to increase markedly one week after participants stopped grounding (end of week 6, when blood samples were taken for the last time). These results seem to contradict blood viscosity results. ponentially at high hematocrit [16]. Another possible explanation is that grounding may decrease hematocrit in grounded participants and that effect may override or precede the increase in inflammation by some weeks resulting in temporary small decreases in SBV as seen in Table 2 and Table 3. A third possible explanation is that grounding may increase deformability of erythrocytes (because of the increase in absolute zeta potential due to extra electrons in the body) for some time even after ungrounding [22]. Since the number of participants in each cohort was small, research with more participants (and more methods of analysis) is needed in order to determine which of the 3 hypotheses (or combination of hypotheses) is (are) correct. Table 9 and Table 10 show results for HR. According to these tables, Cohort A had a significantly higher average HR at week 6 compared to week 1, an indication of increased level of stress above the level of stress at the beginning of the According to the Task Force [20], SDNN, the square root of variance between inter-beat intervals, reflects all the cyclic components responsible for variability in the period of recording (10 minutes in our case). It has been established that low SDNN (or HRV) is a factor increasing the risk of cardiovascular problems including heart attacks [28] [29]. Consequently, an increase in HRV is considered a positive outcome [30]. According to Table 9 and  Table 9 and Table 11, at week 5, week 6, and for all weeks combined Cohort B had a significantly lower mean average LF/HF than Cohort A (p = 0.002, 0.019 and 0.00002, respectively). Also, Cohort A had a significantly higher average LF/HF value at week 5 compared to week 1, an indication of increased stress.
Again, these results are consistent with all other HRV related results.
A limitation of this study is the modest number of participants. For this reason, we highlighted in blue probabilities between 0.05 and 0.1 as possibly of interest to help design future studies with a larger number of participants. Also, this study suggests the importance of gender differences and the time of the year for doing such an experiment. It is best to make sure gender composition is similar in all cohorts and it is best to avoid setting up an experiment close to holidays. Another limitation is that the present design did not allow us to investigate independently the effects of BMI from those due to gender. In addition, physiological data (HR, HRV) were obtained in participants allowed to move freely during measurement intervals, and variations in motor activity and posture may have affected these measures. The level of physical activity (intensity of motion and exertion) during the massage event may also differ between participants, thus influencing HR and respiratory rate after the massage. Future studies could examine HRV during periods of rest (e.g., sitting quietly in a chair) to address these issues. In futures studies, an assessment of general stress level for several cohorts starting at different time points may confirm the present conclusions regarding the differences at baseline. Finally, it would be interesting to assess if perceived level of stress correlates with changes in biomarkers.

Conclusion
This exploratory study showed that grounding massage therapists while they performed massages and at night reduces stress as indicated by HR, RR, LF, HF and LF/HF. It also showed that the lowering effect of grounding on blood viscosity lasts for at least one week after ungrounding, with systolic blood viscosity becoming significantly lower at the end of the study as compared to the initial pre-intervention value. Inflammation markers (IFN-γ, TNF-α, and hsCRP) increased rapidly after ungrounding, within a week, suggesting the importance of grounding on a regular basis, preferably daily. Abnormally stressful situations lasting for long periods of time can partially decrease the benefits of grounding, but not eliminate them. This study's findings suggest that grounding is beneficial for massage therapists in several domains relevant to health and wellbeing