자율신경실조증

The vagus nerve represents the main component of the parasympathetic nervous system, which oversees a vast array of crucial bodily functions, including control of mood, immune response, digestion, and heart rate. It establishes one of the connections between the brain and the gastrointestinal tract and sends information about the state of the inner organs to the brain via afferent fibers. In this review article, we discuss various functions of the vagus nerve which make it an attractive target in treating psychiatric and gastrointestinal disorders. There is preliminary evidence that vagus nerve stimulation is a promising add-on treatment for treatment-refractory depression, posttraumatic stress disorder, and inflammatory bowel disease. Treatments that target the vagus nerve increase the vagal tone and inhibit cytokine production. Both are important mechanism of resiliency. The stimulation of vagal afferent fibers in the gut influences monoaminergic brain systems in the brain stem that play crucial roles in major psychiatric conditions, such as mood and anxiety disorders. In line, there is preliminary evidence for gut bacteria to have beneficial effect on mood and anxiety, partly by affecting the activity of the vagus nerve. Since, the vagal tone is correlated with capacity to regulate stress responses and can be influenced by breathing, its increase through meditation and yoga likely contribute to resilience and the mitigation of mood and anxiety symptoms.

Prevalence of functional somatic syndromes (FSS) in the general population varies with observed overlap between syndromes. However, studies including a range of FSS are sparse. We investigated prevalence and characteristics of various FSS and the unifying diagnostic construct bodily distress syndrome (BDS), and identified mutual overlap of the FSS and their overlap with BDS. We included a stratified subsample of 1590 adults from a randomly selected Danish general population sample (n = 7493). Telephonic diagnostic interviews performed by three trained physicians were used to identify individuals with FSS and BDS. Prevalence of overall FSS was 9.3%; 3.8% for irritable bowel, 2.2% for chronic widespread pain, 6.1% for chronic fatigue, 1.5% for whiplash associated disorders, and 0.9% for multiple chemical sensitivity. Prevalence of BDS was 10.7% where 2.0% had the multi-organ type. FSS were highly overlapping with low likelihood of having a “pure” type. Diagnostic agreement of FSS and BDS was 92.0%. Multi-syndromatic FSS and multi-organ BDS were associated with female sex, poor health, physical limitations, and comorbidity. FSS are highly prevalent and overlapping, and multi-syndromatic cases are most affected. BDS captured the majority of FSS and may improve clinical management, making the distinction between multi- and mono-syndromatic patients easier.

Study participants: A stratified sample of 2450 (32.7%) participants were invited to participate in the interview, and 1590 (64.9%) accepted and completed. Their median age was 54 years (IQR: 44–63 years), 59.3% were women, and 67.9% had more than three years of vocational training. Comparison analyses revealed no differences between the interviewees and decliners regarding sex and vocational training. However, with a median age of 56 years (IQR: 46–64, p = 0.003), decliners were older than interviewees and had lower risk of a poor self-perceived health (22.7% of interviewees had a poor self-perceived health compared to 16.7% of decliners, RR: 1.4, 95% CI: 1.2–1.6, p < 0.001) and limitations in daily activities (26.2% of interviewees had limitations in daily activities compared to 19.2% of decliners, RR: 1.4, 95% CI: 1.2–1.6, p < 0.001).

For 60 participants, a diagnosis could not be established; either because the participants were under further examination by their family physician or hospital, or because the interviewer could not obtain sufficient information during the interview. In these cases, we conservatively rated the participant as not having an FSD.

Functional somatic syndromes: Weighted prevalence of having at least one FSS was 9.3% (95% CI: 8.1–10.6), and all FSS were generally more prevalent in women (Table 1). FSS prevalence seemed to be consistent across age groups (Supplementary Material Table 1).

Prevalence of cases with only one FSS, i.e. having a “pure” type of FSS, was 5.5% (95% CI: 4.5–6.8) (Table 1). These cases tended to be younger than non-cases, and they had higher risk of having a poor health and physical and mental comorbidities. However, these associations were only statistically significant for some of the pure FSS (Table 1).

A substantial fraction of cases within each FSS type had more than one FSS, and 20 out of 26 possible combinations of the five FSS were found. The likelihood of having only one FSS in its pure form was low ranging from 18.8% for CWP to 43.5% for IB (Fig. 1).

Compared with non-cases, multi-syndromatic FSS cases were generally younger and they had higher risk of being unemployed, to have a poor self-perceived health, to have limitations in daily activities, to have physical and mental comorbidities, and to have received a FSS diagnosis by a physician (Table 1). In contrast to cases with only one FSS, the majority of these associations were strong and statistically significant. Hence, multi-syndromatic FSS cases seemed to be stronger associated with several negative outcomes than those only having one FSS. Data on age, sex, social factors, physical health, and comorbidity are displayed as percentages in Supplementary Material Table 2.

Bodily distress syndrome: BDS had a weighted prevalence of 10.5% (95% CI: 9.3–11.9) (Table 2). As for FSS, prevalence of BDS was also consistent across age groups (Supplementary Material Table 1).

Cases of BDS were younger than non-cases, and they had high risk of being unemployed, having a poor health, limitations in daily activities, physical and mental comorbidity, and to have received a FSS diagnosis by a physician (Table 2). All associations were especially strong for the multi-organ type of BDS. Data on age, sex, social factors, physical health, and comorbidity are displayed as percentages in Supplementary Material Table 3.

Overlaps of functional somatic syndromes and bodily distress syndrome: The prevalence of those having at least one FSS and/or BDS was 12.1% (95% CI: 10.7–13.6). Overall diagnostic agreement between any of the five FSS and BDS was 92.0% (95% CI: 90.6–93.3) (Table 3), corresponding to a kappa of 0.78, p < 0.0001. Compared to FSS, BDS had a sensitivity of 90.2% (95% CI: 86.6–93.1) and a specificity of 92.6% (95% CI: 90.9–94.0). A Receiver Operating Characteristics curve is displayed in Supplementary Material Fig. 1.

Background: Functional somatic symptoms and disorders are common and complex phenomena involving both bodily and brain processes. They pose major challenges across medical specialties. These disorders are common and have significant impacts on patients’ quality of life and healthcare costs.

Main body: We outline five problems pointing to the need for a new classification: (1) developments in understanding aetiological mechanisms; (2) the current division of disorders according to the treating specialist; (3) failure of current classifications to cover the variety of disorders and their severity (for example, patients with symptoms from multiple organs systems); (4) the need to find acceptable categories and labels for patients that promote therapeutic partnership; and (5) the need to develop clinical services and research for people with severe disorders. We propose ‘functional somatic disorders’ (FSD) as an umbrella term for various conditions characterised by persistent and troublesome physical symptoms. FSDs are diagnosed clinically, on the basis of characteristic symptom patterns. As with all diagnoses, a diagnosis of FSD should be made after considering other possible somatic and mental differential diagnoses. We propose that FSD should occupy a neutral space within disease classifications, favouring neither somatic disease aetiology, nor mental disorder. FSD should be subclassified as (a) multisystem, (b) single system, or (c) single symptom. While additional specifiers may be added to take account of psychological features or co-occurring diseases, neither of these is sufficient or necessary to make the diagnosis. We recommend that FSD criteria are written so as to harmonise with existing syndrome diagnoses. Where currently defined syndromes fall within the FSD spectrum – and also within organ system-specific chapters of a classification – they should be afforded dual parentage (for example, irritable bowel syndrome can belong to both gastrointestinal disorders and FSD).

Conclusion: We propose a new classification, ‘functional somatic disorder’, which is neither purely somatic nor purely mental, but occupies a neutral space between these two historical poles. This classification reflects both emerging aetiological evidence of the complex interactions between brain and body and the need to resolve the historical split between somatic and mental disorders.

Background: Anxiety disorders increase risk of future cardiovascular disease (CVD) and mortality, even after controlling for confounds including smoking, lifestyle, and socioeconomic status, and irrespective of a history of medical disorders. While impaired vagal function, indicated by reductions in heart rate variability (HRV), may be one mechanism linking anxiety disorders to CVD, prior studies have reported inconsistent findings highlighting the need for meta-analysis.

Method: Studies comparing resting-state HRV recordings in patients with an anxiety disorder as a primary diagnosis and healthy controls were considered for meta-analysis.

Results: Meta-analyses were based on 36 articles, including 2086 patients with an anxiety disorder and 2294 controls. Overall, anxiety disorders were characterized by lower HRV [high frequency (HF): Hedges’ g = −0.29. 95% CI: −0.41 to −0.17, p < 0.001; time domain: Hedges’ g = −0.45, 95% CI: −0.57 to −0.33, p < 0.001] than controls. Panic disorder (n = 447), post-traumatic stress disorder (n = 192), generalized anxiety disorder (n = 68), and social anxiety disorder (n = 90), but not obsessive–compulsive disorder (n = 40), displayed reductions in HF HRV relative to controls (all ps < 0.001).

Conclusion: Anxiety disorders are associated with reduced HRV, findings associated with a small-to-moderate effect size. Findings have important implications for future physical health and well-being of patients, highlighting a need for comprehensive cardiovascular risk reduction.

Included studies: The search of electronic databases for HRV research in anxiety revealed 4149 studies as at October 2013; these were reduced to 194 after examining study abstracts and then to 36 after reviewing the study methods (Figure 1).

Impact of anxiety disorders on HRV: High frequency HRV was reduced in participants with any anxiety disorder, regardless of specific diagnosis, relative to healthy controls [Hedges’ g = −0.29 (−0.41 to −0.17); SE = 0.06; p < 0.001], a finding associated with a small effect size. Egger’s regression test (p = 0.43) indicated no evidence of publication bias. The Q statistic was significant (Q = 51.39, p = 0.002) indicating study heterogeneity (I2 statistic = 35.8%). To examine findings in further detail, we examined effect sizes in specific anxiety disorders (see Table 2, which displays the summary effect sizes for each disorder; and Supplementary Material, which displays the relevant forest plots for each analysis.). HF HRV was significantly reduced in patients with GAD and SAD, findings associated with a moderate effect size, as well as in those with PD and PTSD, findings associated with a small effect size. Findings for OCD, specific phobia, and those studies in which anxiety disorders were grouped were all non-significant.

Moderator analysis revealed no significant differences across anxiety disorder diagnoses (Q = 6.83; p = 0.34). There was no evidence of heterogeneity between studies using different diagnostic criteria including DSM-III, DSM-IV, or ICD-10 (Q = 0.85, p = 0.65), nor was there heterogeneity for use of medication (Q = 0.1, p = 0.75), co-morbid psychiatric diagnoses (Q = 0.29, p = 0.59), or co-morbid medical disorders (Q = 0.004, p = 0.95). No evidence of heterogeneity between studies using short-term versus long-term recordings was obtained either (Q = 2.92, p = 0.09).

Low frequency HRV did not differ between participants with any anxiety disorder and controls [Hedges’ g = −0.08 (−0.31–0.15); SE = 0.09; p = 0.49]. Egger’s regression test (p = 0.001) indicated evidence of publication bias and the Q statistic was significant (Q = 85.02, p < 0.001) (I2 statistic = 75.3%). However, LF HRV did not differ for any anxiety disorder relative to healthy controls (Table 2). Moderator analyses revealed that LF HRV did not differ across anxiety disorders (Q = 3.73, p = 0.59); nor was there any evidence of heterogeneity from other factors.

Time domain HRV was reduced in participants with any anxiety disorder relative to controls [Hedges’ g = −0.7 (−1.45– 0.05); SE = 0.38; p = 0.07], a finding associated with a moderate effect size. While this finding was at trend levels, the overall Q statistic was significant (Q = 1027.39, p < 0.001) and the I2 statistic was 98.2% indicating high variance between studies, highlighting a need to further inspect these data. Egger’s regression test (p < 0.001) also indicated evidence of publication bias. After the exclusion of a clear outlier (see Supplementary Material), HRV was significantly reduced in those with anxiety disorders relative to healthy controls [Hedges’ g = −0.45 (−0.57 to −0.33); SE = 0.06; p < 0.001], and there was no longer evidence of heterogeneity between studies (Q = 18.46, p = 0.43, I2 statistic = 2.5%). Egger’s regression test still revealed evidence of publication bias (p = 0.01). TD HRV was significantly reduced in patients with PTSD and GAD, findings associated with a moderate effect size, as well as in PD, SAD, and Specific Phobias, findings associated with a small effect size (see Table 2). Follow-up moderator analyses revealed no difference in summary effect sizes between disorders (Q = 2.8, p = 0.73). No evidence of heterogeneity from other factors was observed.

Increasing numbers of COVID-19 patients, continue to experience symptoms months after recovering from mild cases of COVID-19. Amongst these symptoms, several are related to neurological manifestations, including fatigue, anosmia, hypogeusia, headaches and hypoxia. However, the involvement of the autonomic nervous system, expressed by a dysautonomia, which can aggregate all these neurological symptoms has not been prominently reported. Here, we hypothesize that dysautonomia, could occur in secondary COVID-19 infection, also referred to as “long COVID” infection. 39 participants were included from December 2020 to January 2021 for assessment by the Department of physical medicine to enhance their physical capabilities: 12 participants with COVID-19 diagnosis and fatigue, 15 participants with COVID-19 diagnosis without fatigue and 12 control participants without COVID-19 diagnosis and without fatigue. Heart rate variability (HRV) during a change in position is commonly measured to diagnose autonomic dysregulation. In this cohort, to reflect HRV, parasympathetic/sympathetic balance was estimated using the NOL index, a multiparameter artificial intelligence-driven index calculated from extracted physiological signals by the PMD-200 pain monitoring system. Repeated-measures mixed-models testing group effect were performed to analyze NOL index changes over time between groups. A significant NOL index dissociation over time between long COVID-19 participants with fatigue and control participants was observed (p = 0.046). A trend towards significant NOL index dissociation over time was observed between long COVID-19 participants without fatigue and control participants (p = 0.109). No difference over time was observed between the two groups of long COVID-19 participants (p = 0.904). Long COVID-19 participants with fatigue may exhibit a dysautonomia characterized by dysregulation of the HRV, that is reflected by the NOL index measurements, compared to control participants. Dysautonomia may explain the persistent symptoms observed in long COVID-19 patients, such as fatigue and hypoxia.

Trial registration: The study was approved by the Foch IRB: IRB00012437 (Approval Number: 20-12-02) on December 16, 2020.

Characteristics of the participants were described in Table 1. Median average for age was 48 [12] years for patients with long COVID-19 with fatigue, 39 [10] years for patients with long COVID-19 without fatigue and 43 [9] years for the control group. Few patients of our study group presented comorbidities, only 3 patients with hypertension for long COVID-19 groups and one patient for control group, and only one patient with diabetes in long COVID-19 groups. No significant differences were observed for age (p = 0.085), gender (p = 0.594), comorbidities (hypertension (p = 0.688), diabetes (p = 0.377) and respiratory diseases (p = 0.224) between the three groups of the study population). 2 patients of the long COVID-19 group with fatigue and only one patient of the long COVID-19 group without fatigue were hospitalized and received oxygen therapy (p = 0.399). None of the participants of the study were hospitalized in ICU. 6 (54.6%) patients of long COVID-19 group with fatigue and 8 (53.3%) patients of the long COVID-19 group without fatigue presented loss of taste and smell (p = 0.951) (Table 1).Table 1Characteristics of the study population.ParametersCOVID-19 with fatigue groupCOVID-19 without fatigue groupControl groupP valueN = 12N = 15N = 12Age (years)48 [12]39 [10]43 [9]0.085Female5 (41.7)9 (60.0)7 (58.3)0.594Hypertension2 (16.7)1 (6.7)1 (8.3)0.688Diabetes0 (0)1 (6.7)0 (0)0.377Respiratory diseases2 (16.7)1 (6.7)0 (0)0.224Previous cardiovascular events0 (0)0 (0)0 (0)–Previous oxygen therapy#*2 (18.2)1 (7.1)–0.399ICU hospitalization0 (0)0 (0)––Neurological symptoms after COVID-190 (0)0 (0)––Cardiac damages after COVID-190 (0)0 (0)––Loss of taste and smell*6 (54.6)8 (53.3)–0.951Weight before COVID-19 (kg)*85 [31]66 [28]–0.062Weight at NoL test (kg)85 [37]63 [26]80 [21]0.101Height (m)1.75 [0.2]1.66 [0.1]1.76 [0.2]0.499BMI before COVID-19 (kg/m2)*26.4 [8.6]23.4 [6.9]–0.229BMI at NoL test (kg/m2)25.2 [8.8]22.7 [5.9]25.0 [7.1]0.246Loss of weight (median %)*0 [9.3]0 [9.8]–0.632HR (bpm)73 [17]70 [11]72 [22]0.708SBP (mmHg)130 [20]130 [33]121 [29]0.749DBP (mmHg)89 [12]70 [19]76 [22]0.056NIJMEGEN score*36 [15]20 [18]–0.002PCL-5 score*31 [18]18 [19]–0.00130 s of up and down test*4 [3]5 [2]–0.192Oxygen saturation (%)98 [3]98 [3]98 [2]0.663Duration from first symptoms of plong COVID-19 (months)*7.5 [1.7]7.0 [2.2]–0.157BMI: body mass index.HR: heart rate.SBP: systolic blood pressure.DBP: diastolic blood pressure.ICU: intensive care unit.*Only comparison between “covid-19 participants with fatigue and covid-19 participants without fatigue”.#Oxygen therapy was administrated through low-flow nasal cannula.Categorical values were presented as number and percentage, continuous variables were presented as median and interquartile range (IQR).

Moreover, no difference was observed duration from first symptoms of long COVID-19 between the long COVID-19 participants with fatigue and thus without fatigue (respectively 7.5 [1.7] vs 7.0 [2.2], p = 0.157). Long COVID-19 participants with fatigue presented higher values of NIJMEGEN and PCL-5 scores (respectively, 36 [15] vs 20 [18] p = 0.002 and 31 [18] vs 18 [19], p = 0.001) but not for loss of body mass exceeding 10% (respectively 0 [9.3] vs 0 [9.8], p = 0.632) and the 30 s of up and down test (respectively, 4 [3] vs 5 [2], p = 0.192,) than long COVID-19 participants without fatigue. No neurological symptoms were reported during COVID-19 episode, except loss of taste and smell for 14 patients, but with no difference between the two groups (p = 0.951). No cardiac damage were reported by the patients (Table 1).

Figure 1 shows the different curves of the NOL index for long COVID-19 participants with and without fatigue compared to control participants. A significant dissociation over time between long COVID-19 participants with fatigue and control participants was observed (p = 0.046). A trend towards significant dissociation over time was observed between long COVID-19 without fatigue and control participants (p = 0.109). No difference over time was observed between the two groups of long COVID-19 participants (p = 0.904).Figure 1NoL index changes over time according to the group of participants. 12 participants with COVID-19 and fatigue; 15 participants with COVID-19 without fatigue, 12 control participants. Step 1 five minutes lying down; Step 2 five minutes standing; Step 3 thirty seconds of flexion/extension and step 4: two minutes sitting down. Measures were performed each five seconds.

Background: Heart rate variability (HRV) as an accurate, noninvasive measure of the Autonomous Nervous System (ANS) can reflect mental health (e.g., stress, depression, or anxiety). Tai Chi and Yoga (Tai Chi/Yoga), as the most widely practiced mind–body exercises, have shown positive outcomes of mental health. To date, no systematic review regarding the long-lasting effects of Tai Chi/Yoga on HRV parameters and perceived stress has been conducted. Objective: To critically evaluate the existing literature on this topic. Methods: Five electronic databases (Web of Science, PubMed, Scopus, SportDiscus and Cochrane Library) were searched from the start of the research project to July 2018. Study selection, data extraction, and study quality assessment were independently carried out by two reviewers. The potentially identified randomized controlled trials (RCT) reported the useful quantitative data that were included only for meta-analysis. Results: meta-analysis of 17 medium-to-high quality RCTs showed significantly beneficial effects on HRV parameters (normalized low-frequency, Hedge’s g = −0.39, 95% CI −0.39 to −0.56, p < 0.001, I2 = 11.62%; normalized high-frequency, Hedge’s g = 0.37, 95% CI 0.22 to −0.52, p < 0.001, I2 = 0%; low-frequency to high-frequency ratio, Hedge’s g = −0.58, 95% CI −0.81 to −0.35, p < 0.001, I2 = 53.78%) and stress level (Hedge’s g = −0.80, 95% CI −1.17 to −0.44, p < 0.001, I2 = 68.54%). Conclusions: Stress reduction may be attributed to sympathetic-vagal balance modulated by mind–body exercises. Tai Chi/Yoga could be an alternative method for stress reduction for people who live under high stress or negative emotions.

3.1. Eligible Study Selection: Two-hundred and sixty-two records were retrieved from five electronic databases and other sources. After duplicates were removed, 129 documents were further assessed based on the titles and abstracts of articles, leading to 85 irrelevant articles excluded. Based on the pre-determined inclusion criteria, we performed full-text article assessment. Of 44 full-text articles, 27 were excluded because researchers investigated the acute effects of mind–body exercise (n = 5), no Tai Chi/Yoga was implemented as the primary intervention (n = 2), Yoga training took place at a heated environment (n = 1), non-randomized controlled trials were used (n = 11), outcome of interest was not reported (n = 3), children or youth were included as study participants (n = 2), and resting measure of HRV was not performed (n = 3). Therefore, we included 17 RCTs in this review. The process of study selection is presented in Figure 1.

3.2. Study Characteristics: Study characteristics of 17 eligible RCTs (Tai Chi = 4 and Yoga = 13) are summarized in Table 1. The earliest study regarding the effects of mind–body exercise (Yoga) on HRV was published in 1997, followed by a study in 2009. The remaining studies were published between 2012 and 2018. While 12 RCT involved healthy individuals, five other studies reported people with disease (low back pain, chronic heart failure, nasopharyngeal carcinoma, or fibromyalgia). Sample size (attrition rate from zero to 46.8%) varied greatly across studies, ranging from 26 to 355 (mean age ranged from 25.85 to 71.4). Mind–body exercise intervention duration lasted 6 to 19 weeks, the number of weekly sessions ranged from one to seven (each session length took 30 to 90 min). Control group involved either passive (unaltered lifestyle, waitlist, watching TV) or active condition (usual care/standard care, bicycle training, standard prenatal exercise, mindfulness training, usual physical activity, stretching, or other gym exercise). Given the safety of patients in two studies, researchers allowed all patients to receive chemoradiotherapy or standard medical therapy. Electrocardiogram was the most commonly used tool for HRV measure, with recording length of ≥5 min. Of 17 studies, no adverse events occurred during mind–body exercise intervention.

3.3. Methodological Quality of Randomized Controlled Trials: Methodological quality of 17 RCTs were assessed using the adapted PEDro scale. Sum scores across studies ranged from five to nine points, indicating fair-to-high quality. Taking into account each individual item, allocation concealment was only used in six studies while high retention rate of ≥85% was found in nine studies. Other points were deducted due to the lack of blinded assessors and intention-to-treat analysis. Baseline equivalence and between-group comparison were each absent in one study, respectively (Table 2).

3.4. Effects of Mind–Body Exercises on Psycho-Physiological Parameters: As mentioned previously, only outcomes that were reported in at least four studies were meta-analyzed. In addition, because reporting of HRV components (LF, HF, LF/HF ratio, nLF, nHF, nLF/nHF ratio) varied greatly across studies, the most commonly used measures were selected for meta-analysis. Based on this principle, the nLF (sympathetic and vagal modulation), the nHF (vagal modulation), and LF/HF ratio (sympathovagal balance) were finally considered for meta-analysis.

We meta-analyzed the data (12 studies including 14 comparisons) regarding the effects of mind–body exercises on the nLF (greater negative value indicating better sympathetic and vagal modulation). The funnel plot is visually asymmetrical because three outlying comparisons (values of Hedge’s are close to −2), with Egger’s regression intercept = −3.04, p = 0.028. After removing three outliers, the funnel plot (Egger’s regression intercept = −1.73, p = 0.07) is symmetrically observed in Figure 2. The study results of remaining studies indicate that mind–body exercises significantly decreased the nLF, as compared to other control groups (Hedge’s g =−0.39, 95% CI −0.39 to −0.56, p < 0.001, I2 = 11.62%, Q test = 11.62; Figure 3).

For nHF, we meta-analyzed the data from 12 studies (14 comparisons). An asymmetric funnel plot was visually observed and presented two outlying studies. After removing the outliers, the funnel plot is symmetrically presented in Figure 4. The study results of remaining studies indicate that mind–body exercises significantly increased the nHF, as compared to other control groups (Hedge’s g = 0.37, 95% CI 0.22 to −0.52, p < 0.001, I2 = 0%, Q test = 6.22; Figure 5).

For LF/HF ratio, we meta-analyzed the data from 11 studies (because two studies include two control groups, the number of comparisons is 13 in total), with greater negative value indicating better sympathovagal balance. We visually detected an outlying study (Hedge’s g = −5) based on the Funnel plot along with the Egger’s Regression Test (Egger’s regression intercept = −3.74, p = 0.018). After removing this outlier, the symmetric funnel plot (Egger’s regression intercept = −1.96, p =0.16) is presented in Figure 6. The results of the meta-analysis indicate that a significant benefit in favor of mind–body exercises on modulating sympathetic-vagal balance in adults (Hedge’s g = −0.58, 95% CI −0.81 to −0.35, p < 0.001, I2 = 53.78%, Q test = 23.8; Figure 7). Because more than ten studies investigated the effects of mind–body exercises on the LF/HF ratio, we performed sub-analyses for health status and style of mind–body exercise. No significant difference was observed between healthy individuals and people with diseases (chronic low back pain, chronic heart failure, and depressive symptoms) as well as between Tai Chi and Yoga, so we do not present the study results in the text. A meta-regression was performed for weekly total time. It was observed that a significant effect for weekly training time in Tai Chi/Yoga (β = −0.00086, 95% CI −0.00234 to −0.00063, p = 0.013); A negative relationship was observed between weekly training time and LF/HF ratio.

We meta-analyzed the data for stress (7 studies with 9 comparisons). Following the sensitivity analysis for stress-related studies, we removed two outlying comparisons, the study results of meta-analysis indicate that mind–body exercises significantly reduced stress level (Hedge’s g = −0.80, 95% CI −1.17 to −0.44, p < 0.001, I2 = 68.54%; Figure 8).