breath research

January 15, 2019

11 min read

Proper Breathing Brings Better Health

Stress reduction, insomnia prevention, emotion control, improved attention—certain breathing techniques can make life better. But where do you start?

By Christophe André

Breathing is like solar energy for powering relaxation: it’s a way to regulate emotions that is free, always accessible, inexhaustible and easy to use.

Ruslan Ivanov Getty Images

As newborns, we enter the world by inhaling. In leaving, we exhale. (In fact, in many languages the word “exhale” is synonymous with “dying.”) Breathing is so central to life that it is no wonder humankind long ago noted its value not only to survival but to the functioning of the body and mind and began controlling it to improve well-being.

As early as the first millennium B.C., both the Tao religion of China and Hinduism placed importance on a “vital principle” that flows through the body, a kind of energy or internal breath, and viewed respiration as one of its manifestations. The Chinese call this energy qi, and Hindus call it prana (one of the key concepts of yoga).

A little later, in the West, the Greek term pneuma and the Hebrew term rûah referred both to the breath and to the divine presence. In Latin languages, spiritus is at the root of both “spirit” and “respiration.”

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Recommendations for how to modulate breathing and influence health and mind appeared centuries ago as well. Pranayama (“breath retention”) yoga was the first doctrine to build a theory around respiratory control, holding that controlled breathing was a way to increase longevity.

In more modern times, German psychiatrist Johannes Heinrich Schultz developed “autogenic training” in the 1920s as a method of relaxation. The approach is based partly on slow and deep breathing and is probably still the best-known breathing technique for relaxation in the West today. The contemporary forms of mindfulness meditation also emphasize breathing-based exercises.

In fact, every relaxation, calming or meditation technique relies on breathing, which may be the lowest common denominator in all the approaches to calming the body and mind. Research into basic physiology and into the effects of applying breath-control methods lends credence to the value of monitoring and regulating our inhalations and exhalations.

Yoga and meditation have inspired many of the breathing exercises used today. The benefits of controlled respiration were first theoretically posited centuries ago by the practitioners of pranayama yoga. Credit: Getty Images

Mind under the Influence

Even a rudimentary understanding of physiology helps to explain why controlled breathing can induce relaxation. Everyone knows that emotions affect the body. When you are happy, for instance, the corners of your mouth turn up automatically, and the edges of your eyes crinkle in a characteristic expression. Similarly, when you are feeling calm and safe, at rest, or engaged in a pleasant social exchange, your breathing slows and deepens. You are under the influence of the parasympathetic nervous system, which produces a relaxing effect. Conversely, when you are feeling frightened, in pain, or tense and uncomfortable, your breathing speeds up and becomes shallower. The sympathetic nervous system, which is responsible for the body’s various reactions to stress, is now activated. Less well known is that the effects also occur in the opposite direction: the state of the body affects emotions. Studies show that when your face smiles, your brain reacts in kind—you experience more pleasant emotions. Breathing, in particular, has a special power over the mind.

This power is evident in patients who have breathing difficulties. When these difficulties are sporadic and acute, they can trigger panic attacks; when they are chronic, they often induce a more muted anxiety. It is estimated that more than 60 percent of people with chronic obstructive pulmonary disease (COPD) have anxiety or depressive disorders. These disorders probably stem in part from concerns about the consequences of the disease (what could be more distressing than struggling to breathe?), but purely mechanical factors may contribute as well: the difficulty these patients experience often leads to faster breathing, which does not necessarily improve the quality of their oxygen supply but can aggravate their physical discomfort and anxiety.

Rapid breathing can contribute to and exacerbates panic attacks through a vicious circle: fear triggers faster breathing, which increases fear. In 2005 Georg Alpers, now at the University of Mannheim in Germany, and his colleagues observed significant and unconscious hyperventilation when people who had a driving phobia took their vehicles on the highway (where they might not be able to pull over if they become agitated).

Whether anxiety derives from breathing problems or other causes, it can be eased by a number of breathing techniques derived from traditional Eastern approaches (see “Six Techniques for Relieving Stress”). For example, “follow your breath,” an exercise that focuses attention on breathing, is one of the first steps in mindfulness meditation, whereas alternate nostril breathing comes from yoga. Combining reassuring thoughts with breathing is an approach incorporated into sophrology, a technique that emphasizes harmony of body and mind and that borrows exercises from many approaches, including yoga and mindfulness.

Overall, research shows that these techniques reduce anxiety, although the anxiety does not disappear completely. Breathing better is a tool, not a panacea. Some methods have been validated by clinical studies; others have not. But all of those I describe in this article apply principles that have been proved effective. They aim to slow, deepen or facilitate breathing, and they use breathing as a focal point or a metronome to distract attention from negative thoughts.

Spotlight on Cardiac Coherence

A close look at one popular technique—cardiac coherence—offers more detail about the ways that breathing exercises promote relaxation. With the help of biofeedback, the approach attempts to coordinate breathing with heart rate, slowing and steadying breathing to slow and stabilize the heartbeat.

The method was developed based on the understanding that slow, deep breathing increases the activity of the vagus nerve, a part of parasympathetic nervous system; the vagus nerve controls and also measures the activity of many internal organs. When the vagus nerve is stimulated, calmness pervades the body: the heart rate slows and becomes regular; blood pressure decreases; muscles relax. When the vagus nerve informs the brain of these changes, it, too, relaxes, increasing feelings of peacefulness. Thus, the technique works through both neurobiological and psychological mechanisms.

Cardiac coherence’s stabilization of the heartbeat can dampen anxiety powerfully. Conversely, patients with overactive heartbeats are sometimes misdiagnosed as victims of panic attacks because their racing heartbeat affects their mind.

A typical cardiac coherence exercise involves inhaling for five seconds, then exhaling for the same amount of time (for a 10-second respiratory cycle). Biofeedback devices make it possible to observe on a screen how this deep, regular breathing slows and stabilizes the beats. (The space between two heartbeats on the display is never exactly the same, but it becomes increasingly more consistent with this technique.) Several studies have confirmed the anxiety-diminishing effect of these devices, although the equipment probably has more influence on the motivation to do the exercises (“It makes it seem serious, real”) than on the physiological mechanisms themselves. Simply applying slow breathing with the same conviction and rigor could well give the same result.

Some versions of cardiac coherence recommend spending more time on exhaling than on inhaling (for example, six and four seconds). Indeed, your heart rate increases slightly when you inhale and decreases when you exhale: drawing out the second phase probably exerts a quieting effect on the heart and, by extension, on the brain. This possibility remains to be confirmed by clinical studies, however.

Other work suggests that the emotional impact of the breathing done in cardiac coherence and various other kinds of exercises stems not only from effects on the periphery—on the parasympathetic nervous system—but also from effects on the central nervous system. Breathing may well act directly on the brain itself.

In 2017, for instance, Mark Krasnow of Stanford University and his colleagues showed in mice that a group of neurons that regulates respiratory rhythms (the pre-Bötzinger complex in the brain stem) controls some of the activity of the locus coeruleus, a region involved in attention, wakefulness and anxiety. Breathing techniques may influence this seat of emotions by modulating the activity of the pre-Bötzinger complex.

Beyond any direct effects produced by slowed breathing, the attention given to inhaling and exhaling may play a role in the brain’s response. In 2016 Anselm Doll and his colleagues, all then at the Technical University of Munich, showed that this attentional focus eases stress and negative emotions, in particular by activating the dorsomedial prefrontal cortex, a regulatory area of the brain, and by reducing activity in the amygdala, which is involved in these emotions.

In addition, paying attention to breathing causes most people to slow it down and to deepen it, which as I have mentioned, is soothing. Cognitive resources are limited, and so when individuals concentrate on breathing, they are not thinking about their worries. Those who practice mindfulness learn to notice when their attention drifts away from breathing and goes back to their concerns, and they train themselves to return periodically to their breathing. This refocusing has a relaxing effect on anyone and helps to combat ruminative thinking in people who have anxiety or depression, especially those who are particularly prone to negative thoughts that run in a loop.

When to Use Breathing Techniques

What is the best time to apply slow-breathing techniques? One is during occasional episodes of stress—for example, before taking an exam, competing in a sporting event or even attending a routine meeting at work. In 2017 Ashwin Kamath of Manipal University in India and his colleagues studied stage fright before a public speaking engagement. The participants, all medical students, spent 15 minutes doing alternate nostril breathing—that is, slowly inhaling through one nostril and exhaling through the other by applying finger pressure to the side of the nose not being used. Compared with members of the control group, participants experienced somewhat less stress when speaking publicly.

These exercises may also help when insomnia strikes. In 2012 Suzanne M. Bertisch of Harvard Medical School and her colleagues reported, based on survey data, that more than 20 percent of American insomniacs do these breathing exercises to sleep better. They may be on to something. In 2015 Cheryl Yang and her team at National Yang-Ming University in Taiwan showed that 20 minutes of slow breathing exercises (six respiration cycles per minute) before going to bed significantly improves sleep. Insomniac participants went to sleep faster, woke up less frequently in the night and went back to sleep faster when they did wake up. On average, it took them only 10 minutes to fall asleep, almost three times faster than normal. The investigators attributed the results both to the calming mediated by the parasympathetic system and to the relaxing effect of focused breathing.

But respiratory techniques do not work only for acute stresses or sleep problems; they can also relieve chronic anxiety. They are particularly effective in people with psychiatric disorders such as phobias, depression and post-traumatic stress disorder. In 2015 Stefania Doria and her colleagues at Fatebenefratelli e Oftalmico Hospital in Milan, Italy, offered 10 training sessions of two hours each, spread out over two weeks, to 69 patients with anxiety or depressive disorders. The training included a varied set of breathing techniques (such as abdominal breathing, acceleration and deceleration of rhythm, and alternate nostril breathing.), combined with some yoga stretches. The researchers observed a significant decrease in symptoms at the end of the protocol. Even better, improvement was maintained two and six months later, with follow-up sessions just once a week and some home practice during this period.

Breathing exercises also help to counter the accumulation of minor physical tension associated with stress. Therapists recommend doing them regularly during the day, during breaks or at moments of transition between two activities: you simply stop to adjust your posture and allow yourself a few minutes of quiet breathing. Therapists often suggest the “365 method”: at least three times a day, breathe at a rhythm of six cycles per minute (five seconds inhaling, five seconds exhaling) for five minutes. And do it every day, 365 days a year. Some studies even suggest that, in addition to providing immediate relief, regular breathing exercises can make people less vulnerable to stress, by permanently modifying brain circuits. In a practice that may seem counterintuitive, however, counselors may encourage some anxious patients to breathe rapidly instead of slowly, as part of an effort to train them to cope with their anxieties (see box “Inhale for Panic!”).

But why confine breathing techniques to negative emotions? It is also worth applying them during pleasurable moments, to take the time to appreciate and remember them. In short, one can pause and breathe for enjoyment as well as to calm down.

Open Questions

Tradition and experience encourage the use of respiratory-control techniques, and scientific studies increasingly suggest that it is a good idea. Nevertheless, further research is still needed, particularly given that some studies lack control groups. One exception stands out: focusing on breathing often is not a good idea for people having a panic attack that stems from anxiety over their physical state (also known as interoceptive anxiety). In this case, focusing on physiology, such as muscle tension or breathing, may actually amplify panic (“Now that I’m paying attention to it, my breathing doesn’t seem regular. Am I choking? What will happen if I suddenly stop breathing?”) For these people, breathing techniques should be tested and practiced under the supervision of a therapist.

Otherwise, considering how often everyone experiences emotional discomfort in their everyday life and its negative consequences on health, we would all do well to regularly pay attention to the way we breathe. Start with brief periods of conscious, quiet breathing several times a day. Breathing is like solar energy for powering relaxation: it’s a way to regulate emotions that is free, always accessible, inexhaustible and easy to use.

In fact, I am mystified that controlled breathing is not recommended and practiced more widely. Perhaps it is perceived as too simple, commonplace and obvious to be a remedy. Faced with the complexity of negotiating the ups and downs of human life, many people may assume that simple solutions cannot be effective.

Or maybe we are intimidated by the sacred aspect of breathing, by its connection to life and, especially, to death. In the 1869 novel The Man Who Laughs, Victor Hugo wrote: “Generations are puffs of breath, that pass away. Man respires, aspires, and expires.” Ultimately, we don’t like to think that we are nothing more than “puffs of breath.”

Six Techniques for Relieving Stress

Here are some commonly used breathing techniques. Five to 10 minutes of exercise can relieve sporadic stress and even fend off panic attacks. More regular practice can lower the daily levels of anxiety.

Stand Up Straight

Posture is important for breathing: hold yourself straight, without stiffness, shoulders back, sitting or standing. This body posture facilitates the free play of the respiratory muscles (of the diaphragm and between the ribs). Good posture enables your body to breathe properly on its own.

Follow Your Breath*

Simply observe your respiratory movements: be aware of each inhalation and exhalation. Focus on the sensations you feel as air passes through your nose and throat or on the movements of your chest and belly. When you feel your thoughts drift (which is natural), redirect your attention to your breath.

Abdominal Breathing

Breathe “through your stomach” as much as possible: start by inflating your belly by inhaling, as if to fill it with air, then swell your chest; as you exhale, first “empty” your stomach, then your chest. This type of breathing is easier to observe and test while lying down, with one hand on your stomach.

Rhythmic Breathing

Near the end of each inhalation, pause briefly while mentally counting “1, 2, 3” and holding the air before exhaling. This counting while not breathing can also be done after exhaling or between each inhalation or exhalation. It is often recommended for anxious patients to calm anxiety attacks because it induces a beneficial slowing of the breathing rate.

Alternate Nostrils*

Breathe in and out slowly through one nostril, holding the other one closed using your finger; then reverse and continue by alternating regularly. There are many variations of this exercise—for example, inhaling through one nostril and exhaling through the other. Research suggests that what is most important, aside from slowing the breathing rhythm, is breathing through the nose, which is somewhat more soothing than breathing through your mouth.

Think Reassuring Thoughts While Breathing

With each breath, think soothing thoughts (“I am inhaling calm”). With each exhalation, imagine that you are expelling your fears and worries (“I am exhaling stress”).

*Technique validated by clinical studies.

Inhale for Panic!

Whereas slow breathing soothes, overly rapid breathing can induce feelings of stress and anxiety. This phenomenon is used in behavioral therapy sessions to train anxious patients to confront their emotions directly. By deliberately hyperventilating, patients artificially trigger an unpleasant anxiety, which they get accustomed to feeling and learn to put in perspective. This technique also enables them to see that poor breathing habits amplify their fear.

Christophe André is a psychiatrist at the Sainte-Anne Hospital Center in Paris and a pioneer in the therapeutic use of meditation in France. He has contributed significantly to the practice’s dissemination, especially through his writings, which include the international best seller Mindfulness: 25 Ways to Live in the Moment through Art (Rider, 2014).

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• Data Descriptor
• Open access
• Published: 14 February 2024

A Clinical Breathomics Dataset

• Ping-Hung Kuo 1 ,
• Yue-Chen Jhong 2 ,
• Tien-Chueh Kuo   ORCID: orcid.org/0000-0002-4794-0134 2 , 3 ,
• Yu-Ting Hsu 2 ,
• Ching-Hua Kuo 3 , 4 , 5 &
• Yufeng Jane Tseng   ORCID: orcid.org/0000-0002-8461-6181 2 , 6  

Scientific Data volume  11 , Article number:  203 ( 2024 ) Cite this article

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• Metabolomics

This study entailed a comprehensive GC‒MS analysis conducted on 121 patient samples to generate a clinical breathomics dataset. Breath molecules, indicative of diverse conditions such as psychological and pathological states and the microbiome, were of particular interest due to their non-invasive nature. The highlighted noninvasive approach for detecting these breath molecules significantly enhances diagnostic and monitoring capacities. This dataset cataloged volatile organic compounds (VOCs) from the breath of individuals with asthma, bronchiectasis, and chronic obstructive pulmonary disease. Uniform and consistent sample collection protocols were strictly adhered to during the accumulation of this extensive dataset, ensuring its reliability. It encapsulates extensive human clinical breath molecule data pertinent to three specific diseases. This consequential clinical breathomics dataset is a crucial resource for researchers and clinicians in identifying and exploring important compounds within the patient’s breath, thereby augmenting future diagnostic and therapeutic initiatives.

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Background & summary.

Breathomics is a field of research that examines the metabolic activity in a system through the analysis of volatile organic compounds (VOCs) 1 . VOCs are highly volatile, gaseous organic molecules that can reflect the metabolic activity in the human body or the interaction between the human body and the environment through inhaled air, food, drink, and drugs 2 . In respiratory diseases, the close contact between VOCs and the respiratory tract makes them an important compound for understanding airway diseases 1 , 2 , 3 , 4 , 5 , 6 , 7 or lung cancer 2 , 8 , 9 .

VOCs can be obtained from human exhaled gas or exhaled breath condensate (EBC) samples 10 , 11 , 12 ; both of these sampling methods are noninvasive compared to other diagnostic procedures, such as bronchoscopy, bronchoalveolar lavage, and biopsy 2 , 13 . Exhaled breath is more actively studied than biological samples, such as saliva, breast milk, sweat, epithelial tissue, urine, or feces 14 , 15 , 16 .

Gas chromatography-mass spectrometry (GC‒MS) 14 , 15 , 16 , 17 , 18 , 19 , 20 and electronic noses (eNoses) 21 , 22 , 23 are two common methods used to analyze VOCs. GC‒MS has high sensitivity and potential for identifying and quantifying unknown components. Nevertheless, its clinical implementation can be complex due to the need for highly trained personnel and the laborious analysis procedure 2 , 24 . On the other hand, eNoses 2 are easy to use, cost-effective, and capable of real-time monitoring, but their lack of selectivity and susceptibility to interference can affect their reliability and robustness 14 , 15 , 16 .

In the COVID-19 pandemic, advancements within the realm of breathomics research have been swift and substantial. Despite such progress, a discernible lack of comprehensive datasets dedicated to breath research remains. Recognizing this deficit, we present the clinical breathomics dataset to bridge this gap. The release of this indispensable dataset marks a seminal phase in community sharing for this research domain. It is a valuable asset for further explorations into breath studies, aiding researchers in unraveling the intricate biomedical underpinnings of various diseases. Moreover, this robust dataset is a credible validation tool for ongoing and future breath studies focused on asthma, bronchiectasis, and COPD, further bolstering the field’s collective research endeavors.

Ethics statement

All methods employed in this study complied with relevant guidelines and regulations. The use of the Asthma Control Test (ACT) and Global Initiative for Asthma (GINA) control status was approved by the Research Ethics Committee C of the National Taiwan University Hospital. Participants were recruited from May 2011 to April 2014 and provided written informed consent. The study was registered with ClinicalTrials.gov, with the identifiers NCT01439737 and NCT01410422.

Study subjects

Subjects of studies can be divided into asthma, bronchiectasis, and COPD. After analyzing breath samples by headspace solid-phase microextraction combined with gas chromatography time-of-flight mass spectrometry (HS-SPME GC-TOF-MS). These clinical data were then combined with previously collected clinical asthma data with the same method described in the following sections. Overall, we have identified 104 VOCs in data from 53 clinical asthma samples, 35 bronchiectasis samples, and 33 COPD samples in this dataset.

Collection of exhaled breath condensate samples

Samples of exhaled breath condensate (EBC) were collected from healthy individuals using the commercial device RTube ® (Respiratory Research, Charlottesville, VA, USA). The subjects were instructed to fast for 8 hours before sample collection. The aluminum sleeve of the device was precooled at −80 °C for 20 minutes before each sample collection. Participants were asked to inhale and exhale through their mouth and breathe tidally for 15 minutes without wearing a nose clip and to temporarily discontinue the EBC collection if they needed to swallow saliva or felt the urge to cough. The exhaled breath was condensed and collected in a polypropylene-based tube, and the EBC samples were stored at −80 °C immediately until analysis. EBC samples collected from 5–7 individuals were pooled as quality control (QC) samples and separated into multiple vials for analytical method development to ensure optimal sample quality. Throughout the entire experiment, we employed the pooled QC samples across batches to uphold a consistent level of quality.

HS-SPME sampling procedure

Detecting compounds in exhaled breath condensate (EBC) can be challenging due to the samples’ low concentrations of volatile and nonvolatile compounds. Sample preconcentration techniques, such as solid-phase microextraction (SPME), are necessary to overcome this problem. SPME, invented in the late 1980s 25 , offers efficiency, simplicity, and minimal solvent consumption, making it a popular choice for preconcentrating compounds in biological gas matrices 25 , 26 , 27 , 28 , 29 , 30 . The preconcentration mechanism relies on establishing equilibrium between the matrix and a fused silica fiber coating. The analytes are then desorbed from the fiber and injected into gas chromatography (GC) or liquid chromatography.

Before analysis, the EBC sample vials were cleaned twice in a sonicator with deionized water, ethanol, and acetone. The vials were then dried under a nitrogen stream and combined with 0.5 mL of EBC sample and 200 mg of NaCl. The headspace was then sampled using a PDMS/DVB fiber and extracted at 45 °C for 4 hours.

After extraction, the SPME fiber was immediately transferred to the GC injector port at 250°C and heated for 3 minutes in splitless mode to thermally desorb the analytes into the GC column, avoiding the loss of the extracted substances and minimizing analyte evaporation. Before each sample extraction, the SPME fiber was cleaned in the GC injection port at 250°C for 30 minutes to prevent sample carryover. To ensure accuracy, we conducted a blank run to make sure the cleaning process of the fiber was executed thoroughly before analysis.

GC-TOF-MS analyses

All analyses were performed on a LECO Pegasus 4D time-of-flight mass spectrometer (GC-TOF-MS) (Leco Corporation, St. Joseph, MI, USA). The Pegasus 4D GC-TOF-MS was equipped with Agilent 7890a gas chromatography. The chromatographic column was a 30 m DB-5MS capillary column (5% phenyl, 95% dimethylpolysiloxane) with an internal diameter of 250 μm (Agilent Technologies, Santa Clara, CA). The oven began at a holding temperature of 50 °C for 2 minutes, then increased to 280 °C at 10 °C/min. The temperature was held at 280 °C for 5 minutes. The helium carrier gas flow rate was set at 1 mL/min. The electron energy was 70 eV, and the ion source temperature was 240 °C. The TOF-MS detector was operated at 1500 V and in auto-detection mode. The analytes were acquired in full scan mode with a mass range of 40–550 m/z.

GC‒MS data analysis and compound identification

Data obtained from the MS analysis, stored in RAW file format, were subjected to processing employing LECO ChromaTOF ® software (version 4.33). This software version is specially optimized for enhanced compatibility and functionality with the Pegasus instrument. The cdf files, obtained from different disease groups, were analyzed separately using the eRah R package 31 . This package automates the processes of compound deconvolution, sample alignment, and metabolite identification through GC spectral library matching. The software’s user manual outlines the procedures involved in the analysis, such as deconvolution, alignment, missing compound recovery, and naming. The NIST 20 MS/MS spectral libraries were utilized as the reference GC‒MS library during the identification process for matching spectra.

Data Records

The clinical breathomics dataset is available as open access on the figshare online repository 32 . This dataset consists of an in-house R script file, a Python script file, a spreadsheet file for metadata, three comma separate values (CSV) files and a spreadsheet file for the intersection of the detected compounds (gcms_analysis.R, heatmap.py, CBD_metadata_for_ver3.xlsx, Asthma_peaktable_ver3.csv, Bronchi_peaktable_ver3.csv, COPD_peaktable_ver3.csv and Intersection_of_detected_compounds.xlsx)

gcms_analysis.R - an R script for GC-MS data analysis.

heatmap.py – a Python script for performing the heat map analysis from 3 peak tables.

CBD_metadata_for_ver3.xlsx – a spreadsheet file for metadata including gender, age, ACT (Asthma Control Test) score, CAT (COPD Assessment Test) score, and the pulmonary function data.

Asthma_peaktable_ver3.csv – a peak table with 131 rows (metabolites) and 53 columns (samples). The column headers are patients’ IDs. The first column is the PubChem CID (PubChem Compound Identification), and the second column is the IUPAC name of the chemical compound.

Bronchi_peaktable_ver3.csv – a peak table with 120 rows (metabolites) and 35 columns (samples). The column headers are patients’ IDs. The first column is the PubChem CID, and the second column is the IUPAC name of the chemical compound.

COPD_peaktable_ver3.csv – a peak table with 123 rows (metabolites) and 33 columns (samples). The column headers are patients’ IDs. The first column is the PubChem CID, and the second column is the IUPAC name of the chemical compound.

The identified peak tables corresponding to asthma, bronchiectasis, and COPD were represented through heat map visualizations, as depicted in Figs.  1 – 3 .

Heat map analysis of 131 metabolites in 53 asthma patients. Each column represents a metabolite, and each row represents a sample. Both rows and columns are clustered using correlation distance and single linkage.

Heat map analysis of 120 metabolites in 35 bronchiectasis patients. Each column represents a metabolite, and each row represents a sample. Both rows and columns are clustered using correlation distance and single linkage.

Heat map analysis of 123 metabolites in 33 COPD patients. Each column represents a metabolite, and each row represents a sample. Both rows and columns are clustered using correlation distance and single linkage.

Intersection_of_detected_compounds.xlsx – a spreadsheet file with the intersection of the detected compounds of three peak tables.

Dataset extraction from clinical gc‒ms data analysis

The peak table for each disease group was compiled manually by merging the results from the ‘alignList’ and ‘idList’ generated by the eRah analysis (generated from the alignment and identification processes, respectively). The peak table includes information about the most closely matched compound name, the PubChem CID, the clinical sample group, and the chromatographic peak intensity of each identified compound obtained after deconvolution. To better visualize the relationship between compounds and diseases, each clinical sample’s chromatographic peak intensities were scaled using min-max scaling (ranging from 0 to 1). The scaled peak table was then used to generate group box plots and dot plots using the R package ‘ggplot’ to depict the scaled intensity of each identified compound for the three disease groups (asthma, bronchiectasis, and COPD). 131, 120, and 123 compounds were identified in the asthma, bronchiectasis, and COPD groups, respectively. The intersection of the compounds of three peak tables is displayed in a spreadsheet file in the figshare repository.

Technical Validation

The compounds identified from our clinical GC‒MS analysis were detected and consistent with some published literature sources. Our results were consistent with the presence of undecane 22 , 33 , 1-ethyl-3-methyl benzene 34 , and cyclohexane 35 as important compounds for COPD in previous studies. They showed that n-heptane could distinguish between VOC patterns in patients with acute exacerbation of COPD (AECOPD) and stable COPD 35 . Additionally, decane was shown to be associated with oxidative stress and inflammation 36 , making it an important compound for asthma screening.

Usage Notes

The clinical breathomics dataset consists of 3 peak tables of the EBC samples from asthma, bronchiectasis, and COPD subjects and a spreadsheet file for metadata. Furthermore, it is important to acknowledge that the pulmonary function data contained in the metadata could impact the volume of exhaled breath and subsequently influence the detected intensity of the VOCs. Therefore, we suggest that the pulmonary function data should be taken into account and the total data scaling and normalization should be conducted in the pre-processing. For the missing value in the peak tables, we recommend doing missing value imputation before statistical analyses.

Code availability

The in-house R and Python scripts for GC-MS and heat map analysis are available in the figshare repository ( https://doi.org/10.6084/m9.figshare.23522490.v6 ).

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Acknowledgements

This work was financially supported by the National Science and Technology Council (NSTC 111-2320-B-002-043-MY2, MOST 110-2320-B-002-038), the Taiwan Food and Drug Administration (MOHW112-FDA-D-114-000611), the ‘Center for Advanced Computing and Imaging in Biomedicine (NTU-112L900703)’ and the ‘Center of Precision Medicine’ from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan. We thank resources from the Drug Research Center and Department of Pharmacy of National Taiwan University, which were used to perform GC‒MS analysis. Our heartfelt thanks go to the Laboratory of Computational Molecular Design and Metabolomics and the Department of Computer Science and Information Engineering of National Taiwan University for the resources they made available to us as we conducted these studies.

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Ping-Hung Kuo

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Yue-Chen Jhong, Tien-Chueh Kuo, Yu-Ting Hsu & Yufeng Jane Tseng

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Tien-Chueh Kuo & Ching-Hua Kuo

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Ching-Hua Kuo

Department of Pharmacy, School of Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei, 10055, Taiwan

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P.C.K., C.H.K. and Y.J.T. conceived the project. P.C.K. collected the patient samples. C.H.K. performed GC-MS experiments. Y.C.J. performed the clinical MS data analysis. Y.T.H. performed the heat map analysis. Y.C.J., T.C.K., Y.T.H. and Y.J.T. wrote the manuscript.

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Kuo, PH., Jhong, YC., Kuo, TC. et al. A Clinical Breathomics Dataset. Sci Data 11 , 203 (2024). https://doi.org/10.1038/s41597-024-03052-2

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Breath research in times of a global pandemic and beyond: the game changer

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Research: Why Breathing Is So Effective at Reducing Stress

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Studies found it outperformed other techniques over both the short and long term.

Anxiety in the workplace is a serious problem. What can you do to stay calm, rational, and productive when dealing with a stressful situation? In several recently published studies, the authors explored the effectiveness of different techniques and found that one method — SKY Breath Meditation — offered the best results for both immediate and long-term stress reduction. This comprehensive series of breathing and meditation exercises engages the parasympathetic nervous system, which is responsible for the body’s “rest and digest” activities, helping you to calm down and think rationally in the face of stress. These simple techniques can help you sustain greater emotional wellbeing and lower your stress levels at work and beyond.

When U.S. Marine Corp Officer Jake D.’s vehicle drove over an explosive device in Afghanistan, he looked down to see his legs almost completely severed below the knee. At that moment, he remembered a breathing exercise he had learned in a book for young officers. Thanks to that exercise, he was able to stay calm enough to check on his men, give orders to call for help, tourniquet his own legs, and remember to prop them up before falling unconscious. Later, he was told that had he not done so, he would have bled to death.

• Emma Seppälä , PhD, is a faculty member at the Yale School of Management, faculty director of the Yale School of Management’s Women’s Leadership Program and bestselling author of SOVEREIGN (2024) and The Happiness Track (2017). She is also science director of Stanford University’s Center for Compassion and Altruism Research and Education . Follow her work at emmaseppala.com , http://www.iamsov.com or on Instagram . emmaseppala
• Christina Bradley is a doctoral student in the Management & Organizations department at the University of Michigan’s Ross School of Business. Her research focuses on how to talk about emotions at work.
• Michael R. Goldstein , Ph.D., is a Postdoctoral Research Fellow at Beth Israel Deaconess Medical Center and Harvard Medical School. He is a Licensed Clinical Psychologist and his research examines the physiological mechanisms of mind-body interventions for insomnia.

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People also looked at

Systematic review article, how breath-control can change your life: a systematic review on psycho-physiological correlates of slow breathing.

• 1 Department of Surgical, Medical, Molecular and Critical Area Pathology, University of Pisa, Pisa, Italy
• 2 Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
• 3 National Research Council, Institute of Clinical Physiology, Pisa, Italy
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Background: The psycho-physiological changes in brain-body interaction observed in most of meditative and relaxing practices rely on voluntary slowing down of breath frequency. However, the identification of mechanisms linking breath control to its psychophysiological effects is still under debate. This systematic review is aimed at unveiling psychophysiological mechanisms underlying slow breathing techniques (<10 breaths/minute) and their effects on healthy subjects.

Methods: A systematic search of MEDLINE and SCOPUS databases, using keywords related to both breathing techniques and to their psychophysiological outcomes, focusing on cardio-respiratory and central nervous system, has been conducted. From a pool of 2,461 abstracts only 15 articles met eligibility criteria and were included in the review. The present systematic review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

Results: The main effects of slow breathing techniques cover autonomic and central nervous systems activities as well as the psychological status. Slow breathing techniques promote autonomic changes increasing Heart Rate Variability and Respiratory Sinus Arrhythmia paralleled by Central Nervous System (CNS) activity modifications. EEG studies show an increase in alpha and a decrease in theta power. Anatomically, the only available fMRI study highlights increased activity in cortical (e.g., prefrontal, motor, and parietal cortices) and subcortical (e.g., pons, thalamus, sub-parabrachial nucleus, periaqueductal gray, and hypothalamus) structures. Psychological/behavioral outputs related to the abovementioned changes are increased comfort, relaxation, pleasantness, vigor and alertness, and reduced symptoms of arousal, anxiety, depression, anger, and confusion.

Conclusions: Slow breathing techniques act enhancing autonomic, cerebral and psychological flexibility in a scenario of mutual interactions: we found evidence of links between parasympathetic activity (increased HRV and LF power), CNS activities (increased EEG alpha power and decreased EEG theta power) related to emotional control and psychological well-being in healthy subjects. Our hypothesis considers two different mechanisms for explaining psychophysiological changes induced by voluntary control of slow breathing: one is related to a voluntary regulation of internal bodily states (enteroception), the other is associated to the role of mechanoceptors within the nasal vault in translating slow breathing in a modulation of olfactory bulb activity, which in turn tunes the activity of the entire cortical mantle.

Introduction

Breathing is intimately linked with mental functions. In the millenary eastern tradition, the act of breathing is an essential aspect of most meditative practices, and it is considered a crucial factor for reaching the meditative state of consciousness, or “Samadhi” (Patanjali, Yoga Sutras). The breath is called “Prana,” which means both “breath” and “energy” (i.e., the conscious field that permeates the whole universe). “Prana-Yama” (literally, “the stop/control,” but also “the rising/expansion of breath”) is a set of breathing techniques that aims at directly and consciously regulating one or more parameters of respiration (e.g., frequency, deepness, inspiration/expiration ratio). Pranayama is primarily related to yoga practice, but it is also part of several meditative practices ( Jerath et al., 2006 ).

A growing number of scientific studies in the field of Contemplative Neuroscience ( Thompson, 2009 ) are reporting accurate descriptions of mental and somatic effects elicited by meditation. The large number of published studies has led to the need of reviews and meta-analyses with the aim of eliminating possible confounding factors, stemming from the heterogeneity of the investigated meditative techniques, differences among experimental designs across studies, and from the overuse of subjective assessments in meditative effects' evaluation. The purpose of these scientific efforts is threefold: (i) building a shared and standardized taxonomy of meditation techniques ( Lutz et al., 2007 ; Ospina et al., 2007 ; Nash and Newberg, 2013 ; Van Dam et al., 2018 ); (ii) identifying psychophysiological correlates of meditation and of meditation-related practices ( Sperduti et al., 2012 ; Fox et al., 2014 ; Boccia et al., 2015 ; Lomas et al., 2015 ; Tang et al., 2015 ; Gotink et al., 2016 ); (iii) assessing the effectiveness of meditative techniques as treatments in different preclinical and clinical conditions ( Ospina et al., 2007 ; Chiesa et al., 2011 ; Creswell, 2017 ).

Heuristically, it is commonly acknowledged that breathing techniques are profoundly intermingled with cognitive aspects of meditation, and in eastern culture, their role for achieving altered states of consciousness is undisputed. A common belief of western culture is that breathing control has beneficial effects on health status, such as wellness, relaxation and stress reduction (nearly a million results googling the keywords “pranayama,” and “wellness,” or “stress”). Nevertheless, western science has paid little attention to the investigation of the effects of pure breathing control on neural correlates of consciousness, and on specific mental functions.

Returning on meditative practices, the main issue in unveiling the basic mechanisms underlying their effects is to disentangle those related to breathing control from those associated with non-respiratory cognitive components such as focused attention and mental imagery.

To our best knowledge, only ten dedicated reviews tackle the effects of Pranayama, without succeeding in the identification of a common psychophysiological model ( Srinivasan, 1991 ; Brown and Gerbarg, 2005a ; Singh et al., 2009 ; Sengupta, 2012 ; Brown et al., 2013 ; Nivethitha et al., 2016 ; Brandani et al., 2017 ; Russo et al., 2017 ; Kuppusamy et al., 2018 ; Saoji et al., 2018 ). Some authors have even attempted at modeling the effects of Pranayama ( Brown and Gerbarg, 2005b ; Jerath et al., 2006 ; Brown et al., 2013 ; Gard et al., 2014 ; Riley and Park, 2015 ; Schmalzl et al., 2015 ), but a general consensus on the identification of the psychophysiological mediators that link Pranayama to its beneficial outcomes is still lacking. Other authors, focusing their attention on the benefits of Pranayama in different pathological conditions (e.g., asthma, hypertension, insomnia, anxiety, and depression), involuntarily added further confounding factors for the identification of Pranayama's basic mechanisms: the main issue is the lack of a consistent knowledge of physiological mechanisms leading to the beneficial effects of Pranayama and, from a clinical standpoint, their interaction with pathophysiological ones underlying the abovementioned diseases.

In western culture, breathing techniques were developed independently from any religious or spiritual belief or purpose, and nowadays are mainly used for therapeutic aims (e.g., biofeedback, progressive relaxation, autogenic training). These breathing techniques are often referred to as paced breathing ( Stancák et al., 1993 ) and are based on slowing down the breath frequency. Paced breathing has been associated with relaxation and well-being ( Jerath et al., 2015 ), while fast breathing has been often mutually linked to anxiety and stress ( Homma and Masaoka, 2008 ).

To our best knowledge, both for Pranayama and paced breathing, no systematic review focusing either on their basic mechanisms or on their effects in healthy subjects has ever been published (but see Lehrer and Gevirtz, 2014 ; Mather and Thayer, 2018 ).

Objectives and Research Question

The aim of this review is the identification of common psychophysiological mechanisms underlying the beneficial effects of slow breathing techniques (<10 breath per minute) by systematically reviewing the scientific literature. Only studies involving healthy humans, avoiding thus possible confounding effects due to pathological conditions, and dealing with the voluntary modulation of breathing (Pranayama and paced breathing) were included. It is in fact crucial to distinguish between slow breathing techniques, and other techniques that simply direct attention to the act of breathing (e.g., breath awareness, breath counting) or slow down breath as a consequence of other attentional practices (e.g., Transcendental Meditation, Nidra Yoga). Studies based on self-reports instruments alone were not included, as their reliability is severely weakened by the absence of objective measures, a major and common problem when dealing with contemplative sciences ( Schmalzl et al., 2015 ). We focused on studies investigating both changes of physiological parameters related to central and/or autonomic nervous systems activity in slow breathing techniques trials, and their relationships with behavioral outputs.

The physiological parameters taken into account in this systematic review are brain activity, investigated by Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI), and autonomic activity, studied by Heart Rate Variability (HRV), Respiratory Sinus Arrhythmia (RSA), and Cardio-Respiratory Synchronization.

To develop an effective search strategy, we adopted the Population, Intervention, Comparison, Outcomes and Study Design (PICOS) worksheet (see Methods and Table 1 ).

Table 1 . PICOS.

Search Strategy

This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines ( Moher et al., 2009 ). PRISMA comprises a 27-item checklist that has to be completed in order to improve quality of systematic reviews ( Moher et al., 2009 ). The check-list is reported in Supplementary Table 1 . The protocol of this systematic review has been submitted for registration in PROSPERO database, international prospective register for systematic reviews, with ID number 105537 ( https://www.crd.york.ac.uk/prospero/ ).

A systematic search of MEDLINE and SCOPUS electronic databases has been performed. The initial search was conducted in March 2016, while the final search was carried out in April 2018. Boolean operators “AND” and “OR” were applied for combining keywords related to breathing techniques and to their physiological outcomes. A search example for the slow breathing techniques is the combination of the following keywords: “Pranayama” OR “Breathing Technique” OR “Breathing Exercise” OR “Paced Breathing” OR “Controlled Breathing” OR “Slow Breathing” OR “Deep Breathing” OR “Metronome Breathing” OR “Yoga” OR “Heart Rate Variability Biofeedback.” A search example for the physiological outcomes is the combination of the following keywords: “Cardiorespiratory Synchronization” OR “Cardiorespiratory Coupling” OR “Cardiorespiratory Interaction” OR “Cardiorespiratory Coherence” OR “Respiratory Sinus Arrhythmia” OR “Heart Rate Variability” OR “Electroencephalogram” OR “Magnetic Resonance Imaging” OR “Functional Connectivity”. We searched both for extended names and their acronyms. The complete list of search keywords is reported in Appendix 1 .

Study Design

Following PICOS strategy, we defined the inclusion and exclusion criteria (Table 1 ). Studies identified from the literature search were included if:

- They were conducted on healthy humans (both expert or naïve for breathing techniques)

- Any technique of breath control that directly slows the breath down to 10 breaths per minute was used

- A comparison technique (e.g., spontaneous breathing) or control groups (active interventions, no-intervention) was included

- A physiological outcome was measured, related to cardio-respiratory system or central nervous system (i.e., EEG, fMRI, HRV, RSA, and Cardio-Respiratory Synchronization), together with a psychological/behavioral outcome (assessed with a psychometric quantitative approach).

We considered eligible for the inclusion all studies assessing physiological parameters during slow breathing techniques (state effect), immediately after (state effect), and after long-term interventions (trait effect).

Studies identified from the literature search were excluded if:

- Young (<18 years) and/or old (>65 years) subjects were recruited

- The population comprised any chronic or acute pathology

- Breathing was paced at a frequency higher than 10 b/min

- Techniques do not comprise an active and direct modulation of breathing, investigating instead “passive” breathing techniques (i.e., breathing modulation as a by-product of other meditation/attentional/yoga techniques, e.g., Breath Awareness, Nidra Yoga, Transcendental Meditation, Tai Chi Chuan, QiGong)

- The intervention was not limited to breathing exercises, but included also other techniques as meditation, visualization, or required specific yoga postures (e.g., specific position and movements as in Hatha Yoga)

- The protocol used active emotional induction (e.g., fear, anger or stress induction)

- Measured a physiological parameter of no interest, or measured only a physiological or a psychological/behavioral parameter alone

- They were case reports

- The applied methodologies and/or techniques were not well-described or replicable

- Not published in a peer-reviewed journal

- Not available in full-text and/or in English language.

Flow Diagram

The research of the studies, according to databases, terms and quantity of returned studies, is presented in Table 2 . A complete flowchart of the study selection process is presented in Figure 1 .

Table 2 . Study research.

Figure 1 . Flowchart of the study selection process.

Study Selection and Characteristics

Two independent reviewers (AZ. and AP) checked an early pool of 2,461 abstracts collected from the search engines' outputs. Titles and abstracts were screened, and 2,303 studies were removed either because they were duplicated or of no interest for the systematic review. The remaining 158 full-text papers were checked for the eligibility criteria. At the end of the analysis, 15 articles meeting the eligibility criteria were retained and included in the review. Seven studies ( Stark et al., 2000 ; Edmonds et al., 2009 ; Tsuji, 2010 ; Park and Park, 2012 ; Lin et al., 2014 ; Van Diest et al., 2014 ; Critchley et al., 2015 ) dealt with slow paced breathing. Five studies investigated the effects of HRV Biofeedback ( Lehrer et al., 2003 ; Siepmann et al., 2008 ; Sakakibara et al., 2013 ; Gruzelier et al., 2014 ; Gross et al., 2016 ), two studies ( Fumoto et al., 2004 ; Yu et al., 2011 ) analyzed the effects of Zen Tanden Breathing, and one ( Kharya et al., 2014 ) investigated Prana-Yoga Breathing.

Descriptions of the methodologies employed in the included studies and their main results are presented in Tables 3 , Tables 4 , respectively, while details about physiological and psychological/behavioral data found in the studies are reported in Appendix 2 .

Table 3 . Included studies.

Table 4 . Outcomes.

Synthesized Findings

Breath and the cardio-respiratory system, slow paced breathing and the cardio-respiratory system.

An association between cardio-respiratory parameters and psychological/behavioral outcomes related to slow paced breathing was found coherently in four studies. Edmonds et al. (2009) showed that paced breathing sessions at 6 b/min with different inspiration/expiration ratios increased the Standard deviation of all NN intervals (SDNN) and HRV in the Low Frequency (LF) range, while reducing contributions both in the High Frequency (HF) and in the Very Low Frequency (VLF) ranges. A relationship was found between physiological variables and psychological/behavioral outcomes: using single-item scales, participants reported the strongest perceived ease and comfort level in association with the breathing condition characterized by the highest SDNN and LF values. Park and Park (2012) found an increase of HF power paralleled by a decrease in LF/HF ratio during paced breathing at 10 b/min as compared to spontaneous breathing. No significant difference between the two conditions was observed when considering LF power. Personality traits were evaluated using the Temperament and Character Inventory ( Lee and Hwang, 2009 ). Cooperativeness showed an inverse correlation with HF power, while Self-Transcendence was inversely correlated with both LF and HF power. Lin et al. (2014) , during paced breathing at 6 and 5.5 b/min with two different inspiration/expiration ratios (5:5 and 4:6), found higher SDNN, LF power and LF/HF ratio, and no significant differences in HF power coherently for all paced breathing sessions as compared to the control condition (spontaneous breathing). All paced breathing sessions were associated with an increased subjective perception of relaxation as compared to the control condition; at variance, no difference in subjectively perceived anxiety was found between paced breathing and control sessions. Van Diest et al. (2014) observed higher RSA, higher LF and lower HF power during 6 b/min paced breathing with different inspiration/expiration ratios, as compared to 12 b/min. Paced breathing at 6 b/min was characterized, at a subjective level, by higher positive energy, higher pleasantness, and lower arousal levels, as measured with the Smith Relaxation States Survey ( Smith, 2001 ), when compared to 12 b/min breathing.

Only two studies found no clear association between cardio-respiratory parameters and psychological/behavioral outcomes related to slow paced breathing. Stark et al. (2000) found that paced breathing at 9 b/min was associated with higher HRV, LF, and HF power, and higher LF/HF ratio, as compared with higher paced breathing frequencies (12, 15, and 18 b/min). However, no difference in emotional scores of the Self-Assessment Manikin Scale ( Bradley and Lang, 1994 ) and in a single-item mental effort measure was found among these different paced breathing frequencies. Kharya et al. (2014) found no difference in HF and LF power, and LF/HF ratios between Prana-Yoga (slow breathing), Sudarshan Kriya Yoga (fast breathing), and control condition (spontaneous breathing), after 150 days of practice (5 days a week/30 min a day). On the psychological/behavioral side, an improvement in the Life Style Management Scale was found in Prana-Yoga group as compared to controls.

HRV biofeedback and the cardio-respiratory system

An association between cardio-respiratory parameters and psychological/behavioral outcomes related to HRV Biofeedback was found in three studies. Lehrer et al. (2003) found that 10 sessions of biofeedback (keeping the breathing frequency in the 5.4 b/min-to-6 b/min range for 30 min) induced an increase in HRV and LF power, and a concurrent decrease in HF power, as compared to the control condition (spontaneous breathing). It is important to highlight that high HRV total power was maintained during a post-session resting-state period, during which respiratory frequency returned to normal. Moreover, indicating a cumulative effect of Biofeedback training, HRV was significantly higher at the end of each session (the last 5 min) than at the beginning (the first 5 min). Subjects after the biofeedback session reported significantly lower adverse effects, as measured by the Side Effects of Relaxation Scale ( Kotsen et al., 1994 ) (e.g., anxiety, intrusive thoughts, or fear of losing control), but no effects on relaxation, as measured with the Relaxation Inventory ( Crist et al., 1989 ). Gross et al. (2016) found that 5 sessions of HRV Biofeedback increased total HRV (HRV total power and SDNN) and LF power in members of the support and management staff of elite sport environment, compared to baseline. At the psychological/behavioral level there were no changes in lifestyle variables, and in emotional regulation based on cognitive reappraisal and expression suppression [as measured with the Emotion Regulation Questionnaire ( Gross and John, 2003 )]. However, authors found increased habitual use of adaptive, somatic-based, emotional regulation strategies after HRV Biofeedback interventions (as measured with the Somatic Strategies and Somatic Suppression scale, Gross et al., 2016 ). Gruzelier et al. (2014) investigated the effects of 10 sessions of HRV Biofeedback on dance conservatoire students, compared to a no-intervention group. They found a significant increase in SDNN only in the HRV Biofeedback group. At the psychological/behavioral level, anxiety levels (assessed with the Depression, Anxiety, and Stress Scale, Lovibond and Lovibond, 1995 ) decreased in the HRV Biofeedback group as compared with the control group. There was no difference in the other psychological variables assessed (i.e., creativity, with the Insight Problems and the Alternate Uses Tests).

Two studies found no clear association between cardio-respiratory parameters and psychological/behavioral outcomes related to HRV Biofeedback. Sakakibara et al. (2013) compared the effects of HRV Biofeedback, autogenic training, and no-treatment control on healthy young adults, practiced before bedtime, on HRV during the two following nights. They found that HF power increased during sleep only in the Biofeedback group, whereas it did not change in the autogenic training and in control groups. Moreover, HF power was higher during both nights in the HRV Biofeedback group, compared to autogenic training and control groups. However, authors found no differences in state anxiety (measured before bedtime with the State-Trait Anxiety Inventory, Spielberger et al., 1983 ) between the three groups. Siepmann et al. (2008) enrolled both depressed and healthy subjects, who attended 6 sessions of HRV biofeedback, and were compared with healthy subjects during an active control condition. No significant changes of HRV were observed in healthy subjects after HRV Biofeedback sessions. Moreover, no psychological/behavioral changes, as measured with the Beck Depression Inventory ( Beck et al., 1961 ) and the State-Trait Anxiety Inventory, were registered.

Breath and Central Nervous System

Four studies consistently found an association between neurophysiological parameters and psychological/behavioral outcomes. Fumoto et al. (2004) found that voluntary abdominal breathing (Zen Tanden Breathing) at 3–4 b/min significantly reduced alpha peak at 10 Hz at the EEG and induced significantly higher alpha2 activity (10–13 Hz) in the parietal areas as compared to spontaneous breathing. At a subjective level, participants reported improved vigor-activity in the Profile of Mood States ( McNair et al., 1971 ) subscale scores, and reduced anxiety, evaluated with both Profile of Mood States subscale and State-Trait Anxiety Inventory ( Spielberger et al., 1983 ) (even if the between-condition score difference was not significant). Yu et al. (2011) , during Zen Tanden Breathing at 3–4 b/min, found significantly increased level of oxygenated hemoglobin, as measured by Near-Infrared Spectroscopy, in the anterior part of the prefrontal cortex (Brodmann area 9 and 10), paralleled by an increase in EEG alpha band activity, and a decrease in theta band with respect to spontaneous breathing. After Zen Tanden Breathing, subjects reported reduced scores in Tension-Anxiety, Depression-Dejection, Anger-Hostility, and Confusion subscales of the Profile of Mood States as compared to the control condition. During paced breathing at 10 b/min, Park and Park (2012) found decreased EEG theta power on left frontal, right temporal and left parietal areas, and increased alpha power over the whole cortex as compared to spontaneous breathing. Personality traits such as Harm Avoidance, Novelty Seeking, Persistence, Self-Directedness, and Self-Transcendence (Temperament and Character Inventory subscales), positively correlated with EEG alpha power. Critchley et al. (2015) , in a fMRI study, found increased Blood Oxygenation Level Dependent (BOLD) activity in a large number of brain areas during paced breathing at 5.5 b/min, as compared to 10 b/min. Sub-cortical structures included: (1) the dorsal length of the pons, (2) thalamic regions, (3) cerebellum, (4) striatum, (5) Kölliker-Fuse (sub-parabrachial nucleus), (6) parabrachial nuclei, (7) locus coeruleus, (8) periaqueductal gray, (9) hypothalamus, (10) hippocampus. Activated cortical areas were: (1) motor, (2) supplementary motor, and (3) parietal cortices. Across all participants, a trend for increased alertness (measured with a single-item visual analog scale) was found during 5.5 b/min condition when compared to the control condition. This is the only study included in this review that attempted a correlation between brain activity and HRV: authors found a positive correlation between HRV and activations of the medulla and hippocampus, and a negative one with activity in the anterior insula, dorsomedial prefrontal cortex and left occipital cortex.

Finally, Tsuji (2010) did not find any difference between slow (4 b/min) and spontaneous breathing either when considering EEG alpha power or mood self-assessment using the Two-Dimensional Mood Scale ( Sakairi et al., 2013 ). A possible explanation of these negative findings could stem from the low statistical power of the study (only ten subjects were enrolled).

Risk of Bias

The vast majority of records checked were focused on the contribution of slow breathing techniques on the clinical outcomes of chronic and acute pathologies, and therefore were excluded from the review. Many studies investigated the effects of interventions characterized by a combination of breathing techniques, postures and meditation, while others investigated the effects of emotional stimulation while performing a specific breathing technique. As paced breathing was either intermingled with other kind of interventions or used during active stimulation of the subjects (e.g., anger or stress induction), all these studies were excluded from the review, as they did not allow the unambiguous identification of the specific psychophysiological effects of breath modulation. A large number of studies were excluded as they focused on techniques not aimed at a conscious regulation of breathing, requiring, on the contrary, the meditator not to attempt any control on his/her own breathing rhythm, but rather to observe it in a non-judgmental way. Finally, several other studies lacked a rigorous description of the experimental set-up and of the applied methodologies, impeding thus the study replicability, and were consequently excluded from the review (for reasons for the exclusions of all studies, see Figure 1 ).

As regards the included studies, 10 adopted within-subject designs, and 5 adopted pre-post designs. No studies adopted longitudinal or randomized controlled designs. Risk of bias and methodological quality of the included studies were assessed independently by the first two authors (AZ and AP), using two different tools. Disagreements between the reviewers were resolved by discussion with a third reviewer (AG). As regards within-subject designs, the Single-Case Reporting Guideline In Behavioural Interventions (SCRIBE) Statement ( Tate et al., 2016a , b ) was followed. As regards pre-post designs, a Quality Assessment Tool adapted from several published systematic reviews (see Cummings et al., 2008 ) was adopted. Both assessment tools revealed that the quality of the included studies ranged from sufficient to good. Regarding within-subjects designs, the main concerns were related to the absence of any blinding condition (which intrinsically depends on the slow breathing techniques interventions), lack of description of participants demographic data, and missing access to raw databases and to protocol designs. Regarding pre-post designs, the main concerns relate to sampling methods, sample sizes non-statistically justified, and lacking of randomization in group assignment. Check-lists are presented for within-subjects and for pre-post designs in Supplementary Tables 2 , 3 , respectively.

Summary of Main Findings

We have herein reviewed the literature on the psychophysiological effects of both eastern and western slow breathing techniques with the aim of identifying the physiological mediators at the basis of their demonstrated psychological and behavioral beneficial effects. We found interesting albeit limited evidence of a relationship between physiological parameters and psychological/behavioral outcomes in healthy subjects undergoing slow breathing techniques. We must underline that the paucity of collected evidence is mostly ascribable to the heterogeneity of the investigated techniques and of the participants selection criteria. Consequently, in some cases, results stemming from different studies lead to contradictory conclusions (see Table 4 ). Moreover, no study explicitly estimated the correlations between physiological modifications and psychological/behavioral outcomes, with the notable exception of Park and Park (2012) , which, however, focused on the correlation between changes of HRV- and EEG-related physiology (during slow breathing techniques) and stable personality traits, and not on psychological/behavioral state changes directly related to slow breathing techniques. In spite of these limitations, we identified some common trends when considering specific cardio-respiratory and central nervous system parameters on the one side, and positive psychological/behavioral outcomes on the other.

Slow breathing techniques (related both to slow paced breathing and to HRV Biofeedback) seem to interact with the cardio-respiratory system by increasing HRV and RSA, suggesting thus a strong involvement of the parasympathetic nervous system ( Reyes del Paso et al., 1993 ; Berntson et al., 1997 ). At variance, when considering HF and LF power, a heterogeneous and contradictory set of outcomes was found, mainly depending on the breathing frequency: Park and Park (2012) , and Stark et al. (2000) observed HF power increases (slow breathing techniques vs. control condition), while other studies found no changes ( Siepmann et al., 2008 ; Kharya et al., 2014 ; Lin et al., 2014 ) or even HF power decreases ( Lehrer et al., 2003 ). Moreover, Sakakibara et al. (2013) found that an HRV Biofeedback session before sleep increased HF during sleep in the following night. When considering LF power, a group of studies highlighted increases in the slow breathing techniques-control comparison ( Stark et al., 2000 ; Lehrer et al., 2003 ; Edmonds et al., 2009 ; Lin et al., 2014 ; Van Diest et al., 2014 ; Gross et al., 2016 ), while other authors found no difference between the two conditions ( Park and Park, 2012 ; Kharya et al., 2014 ).

Despite these contradictions, a common trend emerges in some of the included studies, namely the association between the increase of HRV-SDNN power and of LF power during slow breathing techniques (at near 6 b/min) and psychological/behavioral outcomes of decreased anxiety ( Gruzelier et al., 2014 ), side effects of relaxation ( Lehrer et al., 2003 ), and arousal ( Van Diest et al., 2014 ), together with increased ease and comfort ( Edmonds et al., 2009 ), relaxation ( Lin et al., 2014 ), positive energy and pleasantness ( Van Diest et al., 2014 ) and, interestingly, somatic-based emotional control strategies ( Gross et al., 2016 ). We hypothesize that increased HRV and LF power could be an important physiological substrate related to psychological/behavioral positive outcomes of slow breathing techniques. However, it is important to stress the fact that abovementioned studies did not measure HRV features immediately after the session, but during the slow breathing techniques (with the notable exception of Lehrer et al., 2003 ). This can be a confounding factor, because slow breathing at 6 b/min can amplify oscillations at the breath frequency in the LF power band ( Aysin and Aysin, 2006 ). However, the study from Lehrer et al. (2003) provides evidence that HRV power can stay high during a post-session resting-state period, during which respiratory frequency returns to normal.

When considering the central nervous system, slow breathing techniques were often paralleled by increases of alpha and decreases of theta power ( Fumoto et al., 2004 ; Yu et al., 2011 ; Park and Park, 2012 ), when considering scalp EEG activity, a finding that may reflect the brain “idle” state at rest ( Ben-Simon et al., 2008 ) and the synchronization in the Default Mode Network (DMN) ( Knyazev et al., 2011 ). Measured with by Near-Infrared Spectroscopy, Yu et al. (2011) reported increased levels of oxygenated hemoglobin in the anterior part of the prefrontal cortex. Moreover, in the only fMRI study ( Critchley et al., 2015 ), slow breathing techniques were found to increase BOLD activity in the prefrontal, motor, and parietal cortices, areas related to voluntary breathing, as well as in sub-cortical areas as the pons, the thalamus, the sub-parabrachial nucleus, the periaqueductal gray, and the hypothalamus, areas involved also in the regulation of internal bodily states. The authors found also that insular activation anti-correlated with HRV power. The modulation of central nervous system activity by slow breathing techniques, resulting in increase of EEG alpha power and decrease of EEG theta power was reliably found to be associated with positive outcomes, improving vigor-activity, and reducing anxiety, depression, anger and confusion when considering psychological/behavioral outcomes ( Fumoto et al., 2004 ; Yu et al., 2011 ).

Starting from the results reported in this systematic review, the construction of a psychophysiological model of slow breathing techniques can be attempted. In general, slow breathing techniques enhance interactions between autonomic, cerebral and psychological flexibility, linking parasympathetic and CNS activities related to both emotional control and well-being. Slow breathing techniques seem to promote a predominance of the parasympathetic autonomic system with respect to the sympathetic one, mediated by the vagal activity ( Streeter et al., 2012 ; Brown et al., 2013 ). The vagus nerve in turn, transmits interoceptive information from gastrointestinal, cardiovascular and pulmonary systems to the central nervous system through the Nucleus of the Tractus Solitarius. The enhancement of vagal tone within the cardiovascular system is reflected by the increase of both HRV power and RSA. It is worth underlining that HRV modulation is highly dependent on the respiration frequency, increasing along with the slowing of breath ( Song and Lehrer, 2003 ). RSA on its side is consistently considered a robust index of parasympathetic activity ( Reyes del Paso et al., 1993 ), and it has proven to be mainly driven by two mechanisms: (1) the decrease of intrathoracic pressure during inhalation that promotes an increase of venous return, which in turn is registered by stretch receptors causing increases in heart rate (Bainbridge Reflex, Bainbridge, 1915 ), and (2) the inhibition of vagal cardiac efferent activity due to the stimulation of pulmonary C-fiber afferents ( Shykoff et al., 1991 ; Horner et al., 1995 ; De Burgh Daly, 2011 ). There is growing evidence suggesting an active role of RSA in regulating homeostasis and improving oxygen uptake ( Hayano et al., 1996 ; Yasuma and Hayano, 2004 ) and pulmonary gas exchange during slow breathing techniques ( Bernardi et al., 1998 ; Giardino et al., 2003 ). In this framework, we found consistent proofs linking the slowing of breath rhythm to increases in RSA ( Van Diest et al., 2014 ). Jerath et al. (2006) hypothesized another slow breathing techniques-related mechanism, which would explain the parasympathetic nervous system activity predominance. He hypothesized an involvement of lungs stretch receptors (i.e., Herin Breuer's reflex) and of stretching pulmonary connective tissue (fibroblasts). The stretching of lung tissue in fact produces inhibitory signals, as the fibroblasts activity fosters a slow adaptation of stretch receptors and hyperpolarization currents ( Matsumoto et al., 2000 ; Kamkin et al., 2005 ).

Slow breathing techniques at 9–10 b/min, is usually associated with HF power increase ( Stark et al., 2000 ; Park and Park, 2012 ): of note, HF power is usually considered an index of parasympathetic activation ( Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology, 1996 ). On the contrary, slower breathing (at around 6 b/min) increases LF power ( Stark et al., 2000 ; Lehrer et al., 2003 ; Edmonds et al., 2009 ; Lin et al., 2014 ; Van Diest et al., 2014 ), and is usually associated with sympathetic activation ( Vincent et al., 2008 ). However, as already mentioned, the interpretation of these results is not so straightforward since very low respiratory frequencies overlap the frequency interval of LF power (0.04–0.15 Hz), possibly causing a “false-positive” increase of power ( Aysin and Aysin, 2006 ).

Subsequently, the shift toward a parasympathetic predominance is conveyed to the central nervous system via the Nucleus of the Tractus Solitarius, which sends its projection to the thalamus and limbic system via the parabrachial nucleus ( Streeter et al., 2012 ; Brown et al., 2013 ). In this framework, Critchley et al. (2015) found an anti-correlation between insular BOLD activity and HRV during slow breathing techniques.

At the same time, slow breathing techniques are necessarily driven by brain top-down processes stemming from the voluntary shift of attention toward breath monitoring aiming at the active control of breathing rhythm. The nature of these top-down processes could be inferred from the model developed by Gard et al. (2014) for yoga, which, while being a more complex discipline involving physical and mental practices, shares some notable commonalities with slow breathing techniques. Gard's model hypothesizes that yoga may involve top-down components such as attention, working memory, and executive monitoring. Brain networks associated with these functions are the central executive network, including both the dorsolateral prefrontal and the posterior parietal cortices ( Goulden et al., 2014 ), and the fronto-parietal network, including the dorsolateral prefrontal and the anterior cingulate cortices, the inferior frontal junction, the pre-supplementary motor area, and the intraparietal sulcus ( Seeley et al., 2007 ; Vincent et al., 2008 ; Harding et al., 2015 ). Taylor et al. (2010) in a review about mind-body therapies (i.e., techniques focusing on functional links between mind and body) such as slow breathing techniques, suggested the existence of an executive homeostatic network as a fundamental substrate of these practices. This network includes the anterior cingulate, the prefrontal and the insular cortices, areas involved in physiological self-awareness and cognitive modulation. This hypothesis is partially supported by Critchley et al. (2015) and Yu et al. (2011) , who found BOLD activations in the anterior prefrontal, motor, supplementary motor and parietal cortices during slow breathing techniques.

At the EEG level, slow breathing techniques are associated with reductions in theta and increases in alpha activity. The increase of alpha power is in line with the results described in a recent systematic review dealing with the neurophysiology of mindfulness ( Lomas et al., 2015 ), and has been interpreted as an index of an increased inwardly directed attention (i.e., to the self-regulated act of breathing). We hypothesized that the progressive sensory deafferentation occurring during slow breathing techniques induces an inward directed attentional shift allowing both alpha increase and higher DMN synchronization. The thalamus, strongly engaged in a burst mode activity in the alpha range, impedes the expression of other pacemakers such those underlying theta rhythms. According to this hypothesis, the deepening of meditative state allows the emergence of theta rhythm which owing to its off-periods, plays a fundamental role in altering the state of consciousness.

Unexpectedly, the majority of slow breathing techniques studies did not directly investigate slow breathing techniques effects on the state of consciousness, even if its modification is considered one of the mail goals of Pranayama ( Iyengar, 1985 ). To our best knowledge, only one study analyzed breath-related alterations of the state of consciousness, but it adopted a fast breathing technique (Holotropic Breathwork, Rock et al., 2015 ). We speculate that the subjective experience of an altered state of consciousness depends on the rearrangement of cortical functional connectivity, in particular within the DMN, a set of cortical structures whose activity was found to be associated with altered states of consciousness induced by meditation ( Brewer et al., 2011 ), by psychedelic substances ( Carhart-Harris et al., 2014 ), and by sleep ( Chow et al., 2013 ).

Another neurophysiological framework explaining the link between slow breathing techniques and consciousness is related to the fine-tuning of thalamic and cortical activities exerted by the olfactory bulb. The neural patterns of this structure are modulated by the mechanical stimulation of the olfactory epithelium during nostril breathing ( Fontanini and Bower, 2006 ; Piarulli et al., 2018 ). Even if not specified in all studies (see Table 3 ), it is plausible that the majority of slow breathing techniques are performed via nasal respiration ( Jerath et al., 2006 ). Moreover, as historically noted ( Ramacharaka, 1903 ), nostril breathing is a fundamental aspect of every form of meditation. Studies on the animal model, as well as on specific Pranayama techniques, suggest that nasal breathing is able to modulate both the autonomic system and brain activity through receptors located in the superior nasal meatus, which are sensitive both to mechanical and chemical stimuli ( Wrobel and Leopold, 2005 ; Buonviso et al., 2006 ; Kepecs et al., 2006 ). Early studies both on the animal model and humans found a direct relationship between nasal stimulation and brain activity, independent from thoracic respiratory activity, which was abolished by anesthesia of the nasal mucosa ( Adrian, 1942 ; Hobson, 1967 ; Servít and Strejckovà, 1976 ; Servit and Strejckovà, 1979 ; Kristof et al., 1981 ; Servít et al., 1981 ; Sobel et al., 1998 ). More recently, other studies demonstrated the presence of significant oscillations at the same frequency of the respiratory rate in a number of brain cortical and subcortical areas, which disappeared after tracheotomy, and were restored, independently from thoracic respiration, by the rhythmic delivery of air-puffs into the nasal cavity. These areas included the olfactory bulb, the piriform cortex, the somatosensory cortex, the prefrontal cortex, and the hippocampus ( Fontanini et al., 2003 ; Ito et al., 2014 ; Viczko et al., 2014 ; Yanovsky et al., 2014 ; Lockmann et al., 2016 ; Nguyen Chi et al., 2016 ; Biskamp et al., 2017 ; Liu et al., 2017 ; Wu et al., 2017 ; Zhong et al., 2017 ). The modulating effect of nostril breathing on the activity of the piriform cortex, amygdala and hippocampus has been unambiguously demonstrated in humans ( Zelano et al., 2016 ).

Based on these evidence, a recently published study from our laboratory ( Piarulli et al., 2018 ) found that ultra-slow mechanical stimulation of olfactory epithelium induced an enhancement of delta-theta EEG activity over the whole cortex, mainly involving DMN structures, associated to a reversal of the overall information flow directionality from postero-anterior to antero-posterior, and to an altered state of consciousness, phenomenologically overlapping those experienced in deep meditative states.

Taken together, these results confirm that nasal stimulation represents the fundamental link between slow breathing techniques, brain and autonomic activities and psychological/behavioral outputs. Future studies should be aimed at verifying this hypothesis, possibly comparing brain activity during slow respiration when performing nasal breathing with that detected during mouth breathing.

Limitations

A general consideration emerging from this systematic review is the lack in scientific literature of a standardized methodology, both when considering the experimental design and the description of breathing techniques. The initial aim of this work was to conduct a meta-analysis of the existent literature, but due to the heterogeneity of the selected experimental groups, of the interventions, and of the outcomes, a statistical pooling was infeasible. This issue was already highlighted in Gotink et al. (2016) and in Posadzki et al. (2015) when dealing with yoga and mindfulness-based interventions, respectively. As an indication for future research, future research will have to: (i) directly disentangle the role of each aspect of breathing and meditation practices; (ii) measure both physiological and psychological/behavioral variables, in order to draw correlations and (possibly) causal connections between slow breathing techniques and health; (iii) investigate long-term effects of slow breathing techniques practice, adopting more robust longitudinal studies; and (iv) consider the possibility of adverse effects of slow breathing techniques.

Moreover, in order to increase methodological quality in breathing technique's research, we propose a checklist their precise description in scientific literature. Nash and Newberg (2013) have recently stated the importance of breath in every meditation technique. In their attempt to create a taxonomy for meditation, breath is the eighth point that must be described for a scientific definition of a meditation technique. However, they suggest to state only “whether there are any specific recommendations for type or control of breathing.” In order to promote a more standardized research on breathing techniques, we propose to adopt an expanded checklist, as it follows:

I Specifying whether breath is consciously attended or not

II Specify if other techniques are associated with breathing (e.g., “feeling the breath in the body,” sounds with mouth, breath-related mantras, breath-related imagery, etc.)

III Specify the mean breathing frequency and, if present, any significant breathing frequency variations

IV Specify whether during respiration the air passes through the mouth or through the nostrils (both, left, right, alternate), or through both mouth and nostrils

V Specify the presence and the duration of inspiration (if any) and expiration pauses (if any)

VI Specify the Inspiration/Expiration ratio

VII Specify whether the breath is thoracic or abdominal

VIII Specify (if applicable) what type of metronome is used

IX Specify (if applicable) the air pressure during the inspiratory phases.

Conclusions

We found evidence of increased psychophysiological flexibility linking parasympathetic activity, CNS activities related to emotional control and psychological well-being in healthy subjects during slow breathing techniques. In particular, we found reliable associations between increase of HRV power and of LF power, increase of EEG alpha and decrease of EEG theta power, induced by slow breathing techniques at 6 b/min, and positive psychological/behavioral effects. This evidence is unfortunately weakened by the lack of clear methodological descriptions that often characterizes slow breathing techniques literature. Further studies are thus needed to unambiguously assess these links. Only few authors have attempted to systematically describe the psychophysiological effects of slow breathing techniques, and a fewer number have attempted to relate them to meditation practice. Breath seems to be confined to an “ancillary” role when compared to other important mechanisms such as cognitive or affective ones.

Finally, more research is needed to disentangle the pure contribution of breathing in a variety of meditation techniques. As stated by Nash and Newberg (2013) , different methods (e.g., attentional-based and breath-based techniques) could lead to similar states. We herein proposed a brief check-list that could help to improve research on this topic. In our opinion, it is possible that certain meditative practices and slow breathing techniques share, up to a point, similar mechanisms. Some converging data exist regarding the mutual relationships between HRV, RSA, theta, and alpha EEG bands activity, the activation of cortical and sub-cortical brain areas, and positive psychological/behavioral outcomes. In addition, the role that nostrils (and more specifically, the olfactory epithelium) play during slow breathing techniques is not yet well considered nor understood: evidence both from animal models and humans support the hypothesis that a nostril-based respiration stimulating the mechanoceptive properties of olfactory epithelium, could be one of the pivotal neurophysiological mechanisms subtending slow breathing techniques psychophysiological effects.

Author Contributions

AG, EG, and AZ conceived the idea. AZ and AP conducted the literature search and analysis. AZ, AP, EG, and AG wrote the paper. ML, DM, and BN contributed to the writing. All authors reviewed the manuscript.

The present work is funded by LAID-Smart Bed Project: an integrated platform for evaluating sleep quality in the general population. POR CREO FESR 2014–2020, Aging Project: Technological and Molecular innovation for improving health in elderly people; National Research Council flagship project, and University of Pisa, ECSPLAIN-FP7–IDEAS-ERC- ref.338866.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

This work was supported entirely by the Associazione Yoga e Terapie Naturali A.S.D.—YogaRegale.it (via fornace Braccini, 74, Pontedera, PI, Italy, CF01598320503). We also want to thank the 1-year specialization programme (Master di I Livello) in Neuroscience, Mindfulness and Contemplative Practices of the University of Pisa, and the Lama Tzong Khapa Insitute of Pomaia (PI). We gratefully thank Dr. Eleonora Vaccariello for her helpful comments on text.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnhum.2018.00353/full#supplementary-material

Abbreviations

DMN, Default Mode Network.

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Zelano, C., Jiang, H., Zhou, G., Arora, N., Schuele, S., Rosenow, J., et al. (2016). Nasal respiration entrains human limbic oscillations and modulates cognitive function. J. Neurosci. 36, 12448–12467. doi: 10.1523/JNEUROSCI.2586-16.2016

Zhong, W., Ciatipis, M., Wolfenstetter, T., Jessberger, J., Müller, C., Ponsel, S., et al. (2017). Selective entrainment of gamma subbands by different slow network oscillations. Proc. Natl. Acad. Sci. U.S.A. 114, 4519–4524. doi: 10.1073/pnas.1617249114

Keywords: slow breathing, breath-control, pranayama, paced breathing, EEG, fMRI, HRV, psychophysiology

Citation: Zaccaro A, Piarulli A, Laurino M, Garbella E, Menicucci D, Neri B and Gemignani A (2018) How Breath-Control Can Change Your Life: A Systematic Review on Psycho-Physiological Correlates of Slow Breathing. Front. Hum. Neurosci . 12:353. doi: 10.3389/fnhum.2018.00353

Received: 21 June 2018; Accepted: 17 August 2018; Published: 07 September 2018.

Reviewed by:

Copyright © 2018 Zaccaro, Piarulli, Laurino, Garbella, Menicucci, Neri and Gemignani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Angelo Gemignani, [email protected]

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What focusing on the breath does to your brain, different breathing patterns activate our brain networks related to mood, attention, and body awareness, a new study suggests..

Slow down, and pay attention to your breath . It’s not merely commonsense advice. It also reflects what meditation, yoga, and other stress-reducing therapies teach: that focusing on the timing and pace of our breath can have positive effects on our body and mind. A recent study in the Journal of Neurophysiology may support this, revealing that several brain regions linked to emotion, attention, and body awareness are activated when we pay attention to our breath.

Paced breathing involves consciously inhaling and exhaling according to a set rhythm. For example, you might inhale for four counts, exhale for six, and repeat. Prior research shows that paced breathing exercises can both focus attention and regulate the nervous system . To date, however, we have known little about how this affects brain function in humans.

These findings represent a breakthrough because, for years, we’ve considered the brain stem to be responsible for the process of breathing. This study found that paced breathing also uses neural networks beyond the brain stem that are tied to emotion, attention, and body awareness. By tapping into these networks using the breath, we gain access to a powerful tool for regulating our responses to stress.

Your brain on paced breathing

In this study, researchers at the Feinstein Institute for Medical Research wanted to better understand how the brain responds to different breathing exercises. They recruited six adults already undergoing intracranial EEG monitoring for epilepsy. (EEG monitoring involves placing electrodes directly onto the brain to record electrical activity and see where seizures originate.) These adults were asked to take part in three breathing exercises while their brains were being monitored.

In the first exercise, participants rested with their eyes open for about eight minutes while breathing normally. They then sped up their breath to a rapid rate for just over two minutes, while breathing through the nose, then slowed back down to regular breathing. They repeated this cycle eight times.

In the next exercise, participants counted how many times they inhaled and exhaled for two-minute intervals, and reported how many breaths they’d taken. Researchers monitored how many breaths participants took during each interval, noting when responses were correct and incorrect.

Lastly, participants completed an attention task while wearing a device that monitored their breathing cycle. In it, they viewed a video screen containing black circles in different fixed locations. They were asked to press one of four keyboard keys as quickly as possible when they saw one of the circles change from black to white.

At the end of the study, researchers looked to see how participants’ breathing rates varied across different tasks and noted whether their brain activity changed depending on which task they were doing. They found that breathing affects brain regions including the cortex and midbrain more widely than previously thought.

Managing stress: Is it all in the breath?

What they found was increased activity across a network of brain structures, including the amygdala, when participants breathed rapidly. Activity in the amygdala suggests that quick breathing rates may trigger feelings like anxiety, anger, or fear. Other studies have shown that we tend to be more attuned to fear when we’re breathing quickly. Conversely, it may be possible to reduce fear and anxiety by slowing down our breath.

The present study also identified a strong connection between participants’ intentional (that is, paced) breathing and activation in the insula. The insula regulates the autonomic nervous system and is linked to body awareness. Prior studies have linked intentional breathing to posterior insular activation, suggesting that paying particular attention to the breath may increase awareness of one’s bodily states—a key skill learned in practices like yoga and meditation.

Finally, researchers noted that when participants accurately tracked their breath, both the insula and the anterior cingulate cortex, a region of the brain involved in moment-to-moment awareness, were active.

All told, the results of this study support a link between types of breathing (rapid, intentional, and attentional) and activation in brain structures involved in thinking, feeling, and behavior. This raises the possibility that particular breathing strategies may be used as a tool to help people to manage their thoughts, moods, and experiences.

This article was originally published on Mindful.org, a nonprofit dedicated to inspiring, guiding, and connecting anyone who wants to explore mindfulness. View the original article .

About the Author

B Grace Bullock

B Grace Bullock, Ph.D. , is a psychologist, organizational consultant, research scientist, educator, author, and motivational speaker. She has spent the past two decades teaching and studying physiological and psychological interventions that foster resilience and support healthy relationships and systems, and is the author of the acclaimed book, Mindful Relationships: Seven Skills for Success—Integrating the Science of Mind, Body and Brain .

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Effect of breathwork on stress and mental health: A meta-analysis of randomised-controlled trials

Guy william fincham.

1 Department of Psychology, University of Sussex, Brighton, UK

Clara Strauss

2 Research and Development Department, Sussex Partnership NHS Foundation Trust, Brighton, UK

Jesus Montero-Marin

3 Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK

4 Teaching, Research and Innovation Unit, Parc Sanitari Sant Joan de Déu, Barcelona, Spain

5 Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiology and Public Health—CIBERESP), Madrid, Spain

Kate Cavanagh

Associated data.

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Deliberate control of the breath (breathwork) has recently received an unprecedented surge in public interest and breathing techniques have therapeutic potential to improve mental health. Our meta-analysis primarily aimed to evaluate the efficacy of breathwork through examining whether, and to what extent, breathwork interventions were associated with lower levels of self-reported/subjective stress compared to non-breathwork controls. We searched PsycInfo, PubMed, ProQuest, Scopus, Web of Science, ClinicalTrials.gov and ISRCTN up to February 2022, initially identifying 1325 results. The primary outcome self-reported/subjective stress included 12 randomised-controlled trials ( k  = 12) with a total of 785 adult participants. Most studies were deemed as being at moderate risk of bias. The random-effects analysis yielded a significant small-to-medium mean effect size, g  = − 0.35 [95% CI − 0.55, − 0.14], z  = 3.32, p  = 0.0009, showing breathwork was associated with lower levels of stress than control conditions. Heterogeneity was intermediate and approaching significance, χ 2 11  = 19, p  = 0.06, I 2  = 42%. Meta-analyses for secondary outcomes of self-reported/subjective anxiety ( k  = 20) and depressive symptoms ( k  = 18) showed similar significant effect sizes: g  = − 0.32, p  < 0.0001, and g  = − 0.40, p  < 0.0001, respectively. Heterogeneity was moderate and significant for both. Overall, results showed that breathwork may be effective for improving stress and mental health. However, we urge caution and advocate for nuanced research approaches with low risk-of-bias study designs to avoid a miscalibration between hype and evidence.

Introduction

Breathwork comprises various practices which encompass regulating the way that one breathes, particularly in order to promote mental, emotional and physical health (Oxford English Dictionary) 1 . These techniques have emerged worldwide with complex historical roots from various traditions such as yoga (i.e., alternate nostril breathing) and Tibetan Buddhism (i.e., vase breathing) along with psychedelic communities (i.e., conscious connected breathing) and scientific/medical researchers and practitioners (i.e., coherent/resonant frequency breathing). Recently, breathwork has been garnering public attention and popularity in the West due to supposed beneficial effects on health and well-being 2 in addition to the breathing-related pathology of covid-19, however it has only been partly investigated by clinical research and psychiatric medical communities.

Slow-paced breathing practices have gained most research attention thus far. Several psychophysiological mechanisms of action are proposed to underpin such techniques: from polyvagal theory and interoception literature 3 along with enteroception, central nervous system effects, and increasing heart-rate variability (HRV) via modulation of the autonomic nervous system (ANS) and increased parasympathetic activity 4 . ANS activity can be measured using HRV, the oscillations in heart rate connected to breathing (i.e., the fluctuation in the interval between successive heart beats) 5 . Fundamentally, as one inhales and exhales, heart rate increases and decreases, respectively. Higher HRV, arising from respiratory sinus arrhythmia 6 , is typically beneficial as it translates into robust responses to changes in breathing and thus a more resilient stress-response system 7 .

Stress-response dysfunction, associated with impaired ANS activity, and low HRV are common in stress, anxiety, and depression 8 – 12 . This may explain why techniques like HRV biofeedback can be helpful 13 , however, it is possible that simply pacing respiration slowly at approximately 5–6 breaths/minute, requiring no monitoring equipment, can elicit similar effects 14 . Polyvagal Theory 3 , for instance, posits that vagal nerves are major channels for bidirectional communication between body and brain. Bodily feedback has profound effects on mental states as 80% of vagus nerve fibres transmit messages from body to brain 15 . Further, the neurovisceral integration model states that high vagal tone is associated with improved health along with emotional and cognitive functioning 16 , 17 . Vagal nerves form the main pathway of the parasympathetic nervous system, and high HRV indicates greater parasympathetic activity 7 .

Modifying breathing alters communication sent from the respiratory system, rapidly influencing brain regions regulating behaviour, thought and emotion 18 . Likewise, respiration may entrain brain electrical activity 19 , with slow breathing resulting in synchrony of brain waves 20 , thereby enabling diverse brain regions to communicate more effectively 21 . It has been observed that adept long-term Buddhist meditation practitioners can achieve states where brain waves are synchronised continuously 22 .

Breathwork and stress

Stress, anxiety and depression have markedly exceeded pre-covid-19 pandemic population norms 23 . Thus, research is needed to address how this can be mitigated 24 . A recent survey based on more than 150,000 interviews in over 100 countries suggested that 40% of adults had experienced stress the day preceding the survey (Gallup, US) 25 . Prior to the pandemic, mental health difficulties were already a significant issue. For instance, stress has been identified by the World Health Organisation as contributing to several non-communicable diseases 26 and a 2014 survey, led in collaboration with Harvard, of over 115 million adults showed that 72% and 60% frequently experienced financial and occupational stress, respectively (Robert Wood Johnson Foundation, US) 27 .

Chronic stress is associated with, and can significantly contribute to, many physical and mental health conditions, from hypertension and cardiovascular disease to anxiety and depression 28 . For common mental health problems such as anxiety and depression, cognitive behavioural therapy (CBT) is widely recommended in treatment guidelines worldwide 29 , 30 , yet many do not recover and waiting times can be long 31 , 32 , in addition to extensive professional training and ongoing supervision being required for therapists. Moreover, such treatment is typically individualised and offered on a one-to-one basis making it resource intensive. The present state of global mental health coupled with the access barriers to psychological therapies requires interventions that are easily accessible and scalable 7 , and manualised practices such as breathwork may meet this remit.

Breathing exercises can be easily taught to both trainers and practitioners, and learned in group settings, increasingly via synchronous and asynchronous methods remotely/online. Therefore, given the need for effective treatments that can be offered at scale with limited resources, interventions focusing on deliberately changing breathing might have significant potential. Indeed, some government public health platforms already recommend deep breathing for stress, anxiety and panic symptoms (NHS and IAPT, UK) 33 , 34 . However, the evidence underlying this recommendation has not been scrutinised in a comprehensive systematic review and meta-analysis and this is the aim of the current study.

Moreover, it is not only slow-paced breathing which may help reduce stress. Fast-paced breathwork may also offer therapeutic benefit as temporary voluntarily induced stress is also known to be beneficial for health and stress resilience. For example, regular physical exercise can improve stress, anxiety and depression levels 35 , along with HRV 36 . Similarly, fast-paced breathing techniques can induce short-term stress that may improve mental health 37 , and have also been shown to volitionally influence the ANS, promoting sympathetic activity 38 . There are countless breathwork techniques—and such variation in their potential modalities and underlying principles warrants exploration.

Review aims

It is important that hype around breathwork is grounded in evidence for efficacy—and effects are not overstated to the public. Whilst some previous reviews of breathwork have been published, it is not possible to conclude the effectiveness of breathwork for stress (nor mental health in general) based on previous meta-analyses, since they have been restricted by certain factors. These include focusing on populations with impaired breathing (i.e., chronic obstructive pulmonary disease—COPD, and Asthma) 39 , 40 , insufficient focus on the breathwork intervention itself (i.e., including interventions where breathwork is combined with several other intervention components) 41 making it hard to elicit separate effects, along with spanning more literature on self-reported/subjective anxiety and depression compared to stress 14 . On the other hand, systematic reviews with narrative syntheses of quantitative data may have overlooked key studies because of too much focus on a specific technique (i.e., slow breathing or diaphragmatic breathing) 4 , 42 , an absence of randomised-controlled trials (RCTs), scanter literature on self-reported/subjective stress compared to self-reported/subjective symptoms of anxiety and depression, along with limited databases 4 , or exclusion of unpublished studies and grey literature (i.e., theses/dissertations) 43 .

Furthermore, in keeping with the participant, intervention, control, outcome and study design (PICOS) framework 44 , there is an absence of examining dose–response correlates with effects and subgroup analyses evaluating differential effects of different breathwork interventions and how they were delivered, what controls were used, effects on populations with differing health statuses and, finally, the psychological outcome measures used. All of these are crucial for an adequate ethical, precautional and practical implementation of breathwork interventions. Accordingly, subgroup analyses were explored to account for these, for the primary outcome of stress. It could be relevant to investigate potential sources of heterogeneity in terms of effects on stress, and this might be related to how some subgroups (such as mental/physical health populations, along with nonclinical/general populations) receive the intervention. Moreover, other subgroups such as the type of breathwork intervention (i.e., slow/fast) and how it is delivered (i.e., online/in-person or individual/group-based), along with the type of comparator (active/inactive control) and outcome measure (questionnaire) used to self-report on stress, may be sources of heterogeneity and thus warrant investigation.

So far, there is no existing meta-analysis of RCTs on the effect of breathwork on psychological stress. Thus, to fill this research gap, the aim of our meta-analysis was to estimate the effect of breathwork in targeting stress. Because prolonged stress can significantly contribute to anxiety and depressive symptoms and there is considerable overlap between them 45 , 46 , we included these two common mental health issues as secondary outcomes, to provide a bigger picture and greater context around the findings on stress. The primary outcome was pre-registered as stress since it is a transdiagnostic variable, relevant in a variety of disorders, and also in people without a diagnosis but suffering from high levels of psychological distress 47 . This makes stress a very interesting target for breathwork-based interventions.

In brief, our research question was the following: do breathwork interventions lead to lower self-reported/subjective stress (primary outcome), anxiety, and depression (secondary outcomes) in comparison to non-breathwork control conditions? We propose this work as a first comprehensive systematic review and meta-analysis exploring the effects of breathwork on stress and mental health, to help lay a solid foundation for the field to grow and evolve in an evidence-based manner.

We focused solely on RCTs reporting psychological measures, to gauge any potential efficacy or effectiveness of breathwork. We also explored sub-analyses for stress outcomes depending on the health status of the study population, technique, and delivery of breathwork, along with types of control groups and stress outcome measures used. Finally, we examined dose–response effects of breathwork on stress.

Pre-registration and search strategy

Our meta-analysis was pre-registered on the international prospective register of systematic reviews PROSPERO (2022 CRD42022296709). Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards were applied throughout. We searched published, unpublished, and grey literature in the following five databases: PsycInfo, PubMed, ProQuest, Scopus, and Web of Science, along with two clinical trial registers: ClinicalTrials.gov and ISRCTN. The search was run up to February 2022 for all seven electronic repositories, with no date restrictions, in line with the search criteria pre-registered on Prospero, including keywords such as: breath*, respir*, random*, RCT, and stress (see Online Appendix A for the detailed search). For purposes of feasibility in conducting the search, we maintained our focus on the pre-registered primary outcome, following Cochrane Collaboration guidelines to meet the highest criteria for self-reported/subjective stress outcomes by searching trial registers for unpublished studies. There is limited search functionality on trial registers and time involved in contacting researchers for trial data. Moreover, as mentioned above, some previous reviews have not searched unpublished, grey literature before and there are less data available on breathwork and self-reported/subjective stress, in comparison to self-reported/subjective anxiety and depression. In brief, given our focus on stress (paired with time and resource constraints), we conducted the most robust search possible for the primary outcome whilst secondary outcomes only included published data—and we were explicit about this from pre-registration onwards.

Inclusion and exclusion criteria

Inclusion criteria were that studies: (1) were published in the English language, (2) included a breathwork intervention where breathwork formed 50% or more of the intervention (and home practice/self-practice, if any), (3) were RCTs, (4) included an outcome measure of self-reported/subjective stress, anxiety, or depression, (5) included an adult participant sample 18 + years of age. For the five databases, studies with abstracts that did not include either the primary outcome keyword (stress), or a secondary outcome keyword (anxiety or depression), were excluded. For the two registers, if it was clear from the summary information that trials did not comprise the primary outcome of stress, they were excluded. As mentioned above, stress is a transdiagnostic health variable, relevant across various (clinical and nonclinical) populations and conditions, hence it was our primary interest. Additional rationale included the fact that there is far more limited research literature available on self-reported/subjective stress and breathwork (as opposed to anxiety and depression) and, since this was the primary outcome, because fewer (published) data were available, and to make the secondary search (which was only used in the present study to contextualise findings) more feasible, we used the referred search strategy, as this allowed us to find more information on stress from unpublished sources.

For all electronic repositories, studies with control conditions that comprised components of breathwork were excluded, except for studies which had time-points wherein data were collected before controls participated in breathwork (i.e., crossover RCTs). Only non-breathwork controls were used as post-intervention comparisons. Studies with interventions that comprised of equipment (oronasal or otherwise) which physically altered and/or assisted breathing activity were excluded. Breathwork was operationalised as techniques which involved conscious and volitional control or manipulation of one's breath (depth, pattern, speed or otherwise) through deliberate breathing practices. Interventions that affected breathing as a by-product, e.g., mindfulness, singing, and aerobic exercise, were excluded.

Review strategy and study selection

The first author conducted the search and initial screening against eligibility criteria along with full-text screening. Records were then screened, excluding reports based on review of titles and keywords in abstracts or summary information (for trials), or if the inclusion criteria were not met. Remaining reports were sought for retrieval and the full-text reports assessed for eligibility, before final eligibility decisions were made. Further identification of studies comprised forward and backward citation searching via Google Scholar and reference lists, respectively, of the final reports included from the database/registry search. For inter-rater consistency purposes, one of the authors (JMM) checked a random sample (10% of reports) after duplicates had been removed. Furthermore, where GWF was unsure after full-text screening, they consulted authors KC and CS to come to a collective decision on eligibility. Any discrepancies between authors were resolved by discussion and reaching consensus.

Data extraction

Our primary outcome was self-reported/subjective stress. Secondary outcomes were self-reported/subjective anxiety, depression, and global mental health (where two or more of stress, anxiety and depression were combined into a total measure without providing subscale data). We extracted the following data across the studies’ conditions: sample sizes, means, and standard deviations of outcome scores post-intervention (timepoint 1—T1, where T0 is pre-intervention/baseline) along with at latest follow-up where possible (a true follow-up was classed as when participants no longer received any instruction for the breathwork intervention). Where studies involved crossover designs, the midpoints were categorised as post-intervention (before the control group started the breathwork given initially to the intervention group). For studies which required multiple groups’ mean and standard deviation (M ± SD) scores to be combined, or for just SDs to be calculated, these were calculated in accordance with the Cochrane Collaboration handbook 48 . For example, calculating SDs from Ms and 95% confidence intervals (CIs) or combining multiple groups’ M ± SD scores if two or more groups completed an intervention that involved breathwork (but the study still comprised a non-breathwork control).

Risk of bias and quality assessment

The most recent, revised Cochrane Collaboration’s tool for assessing risk of bias in randomised trials (RoB 2) 49 was used for analysing studies on the primary outcome measure of self-reported/subjective stress. The studies were analysed across the following five domains for the stress outcomes: randomisation process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result. Each domain produced an algorithmic judgement of “low risk of bias”, “some concerns”, or “high risk of bias”, resulting in an overall risk of bias judgement. For further inter-rater consistency purposes, both JMM and GWF completed bias scoring using RoB 2 on all included studies for stress, with any discrepancies resolved via discussion.

Data synthesis and analysis

To evaluate whether breathwork can effectively lower stress compared to non-breathwork controls and to quantify the estimation we ran a quantitative synthesis meta-analysis using standardised mean differences and a random-effects model. This used aggregate participant data of M ± SD scores on stress outcome measures for intervention and control conditions of each study at post-intervention (T1), along with the groups’ sample sizes. We also conducted a sensitivity analysis by removing one study at a time, to evaluate the robustness of effects. Separate random-effects meta-analyses were run for the secondary outcomes. The software Review Manager (RevMan) version 5.4 50 was used. For the between-group effect sizes (ESs) we computed Hedges’ g , based on the standardised between-group difference at post-intervention considering sampling variance among groups; an ES of 0.2 is classed as small, 0.5 medium and 0.8 large 51 . For each separate outcome, the ESs were calculated via comparison of post-breathwork intervention scores between the conditions. Intention-to-treat data were chosen over per-protocol data where available, since the former provides a more conservative estimate of between-group differences.

Heterogeneity of ESs variance was assessed using Cochran’s Q 52 based on a chi-square distribution ( χ 2 ) and Higgins’ I 2 53 . If χ 2 is significant and an I 2 index value is around 50%, this implies variance may be explained by variables other than breathwork and such statistical heterogeneity is moderate, respectively. A funnel plot was produced to examine publication bias for the primary outcome, and the software R (version 4) 54 was used to explore asymmetry of the funnel plot via the Egger’s test 55 (i.e., correlations between standard error and ESs). Moreover, Rosenthal’s fail-safe N was calculated (to estimate how many further studies yielding zero effect would be required to make the overall ES non-significant for stress) 56 . Kendall's tau-b (τ B ) correlations were used to detect any potential relationships between ESs of breathwork on stress and: estimated total duration of intervention/home practice, total number of intervention/home practice sessions, and intervention/home practice session frequency. If intervention time was not provided by a study (where participants only had home practice), we used the minimum estimated home practice duration (recommended in the study) to gauge the approximate time taken for participants to ‘learn’ the breathwork technique. Minimum recommended duration was used for most conservative estimates, helping account for common attrition found across behavioural studies.

Lastly, subgroup analyses were run for stress, again using a random-effects model. These subsets included: health status of population (physical, nonclinical, or mental health), technique type (fast or slow-paced breathing) and delivery method of the breathwork intervention (individual, group, or a combination of both, and remote (self-help), in-person, or combination) along with the type of control group (active or inactive; in line with Cochrane Collaboration guidelines 48 ), and outcome measure used (scale).

Search results

As shown in Fig.  1 , the search produced 1325 results: 1175 and 150 records from databases and registers, respectively. After duplicates were removed, the titles and abstracts (or summary information for registers) of 679 records were screened. During screening, the eligibility of 11% of reports were decided collectively among GWF, KC, and CS. All studies included by GWF were checked by KC and CS to ensure none were incorrectly included. One particular study 57 that comprised a global mental health measure only had to be excluded as there were insufficient studies to reliably interpret results ( n  < 5) 58 —the only other available was Goldstein et al. 59 (which also included a measure of self-reported/subjective stress). Accordingly, the global mental health secondary outcome was dropped from the analysis.

PRISMA flow diagram showing the identification of eligible studies via databases, registers, and citation searching. Self-reported/subjective stress was the primary outcome for the quantitative synthesis random-effects meta-analysis. Total number of included studies was 26. Trial registries searched primary outcome only.

Further data were required for eight reports; corresponding authors were contacted, and data from four studies were retrieved, but not the remaining half 60 – 63 subsequently excluded from the analysis. Thus, a total of 104 reports were screened and 81 were excluded, leaving 23. As a result of citation searching, a further three studies were included. Of the 26 total reports included in the quantitative synthesis meta-analyses, stress comprised 12 studies 59 , 64 – 74 . Secondary outcomes of self-reported/subjective anxiety and depression comprised of 20 studies 64 – 70 , 72 – 84 and 18 studies 64 – 67 , 69 – 72 , 74 , 78 – 82 , 85 – 88 , respectively. Please see Online Appendix B for more information on the secondary outcomes.

Summary of findings for stress

In terms of data extraction, all studies provided raw M ± SD scores apart from two 55 , 56 where estimated marginal M ± SDs were given (raw data was requested from corresponding authors but could not be obtained). One study 65 required SDs from Ms and 95% confidence intervals (CIs) provided, both of which were calculated in accordance with Cochrane Collaboration guidelines 48 . Furthermore, another study 70 required two groups’ M ± SD scores (there was one control group and two intervention groups) to be combined and two further studies 64 , 71 involved crossover designs (hence data were extracted at the midpoints of each study before controls started the breathwork intervention). Analyses of follow-up scores were not possible for self-reported/subjective stress as there were insufficient studies for results to be reliably interpreted 58 .

The 12 studies included in the meta-analysis for the primary outcome of stress were completed from 2012 to 2021 (seven, or 60%, were conducted from 2020 onwards). Half of these studies were conducted in the US 59 , 64 – 66 , 68 , 74 , two in India 71 , 72 , one globally 73 , and one each in: Israel 70 , Turkey 67 , and Canada 69 . The average age was 41.7 (± 8.47) and 75% identified as female, since the largest study 68 was for women only. Attrition rates (after the breathwork intervention began) ranged from 3 to 40%. Participant sample sizes ranged from 10 to 150, with the total number of participants analysed being 785. The number of participants randomised to a breathwork intervention or control condition was 417 and 368, respectively. The minimum total estimated durations of an intervention/home practice ranged from 80 to 5625 min.

Half of the studies comprised physical health, five nonclinical, and one mental health samples. Ten and two studies comprised interventions with a primary focus on slow-paced breathing and fast-paced breathing, respectively. Seven were individual-based interventions, four taught to groups, and one a combination of both modes. Half were remote/self-help interventions, five in-person, and one combination. Seven and five studies had inactive and active control groups, respectively. Eight studies used the perceived stress scale (PSS) 89 , three used the stress subscale from the depression anxiety stress scale (DASS) 90 , and one used the perceived stress questionnaire (PSQ) 91 .

Risk of bias for stress

Risk of bias scoring for the 12 studies on the primary outcome is reported using RoB 2 in Fig.  2 . Three studies’ overall assessment were algorithmically scored as being at high risk of bias, with domain two (deviations from the intended interventions) contributing to most bias. The remaining nine studies’ overall risk of bias were algorithmically scored as having some concerns. Only one study did not disclose how randomisation was conducted. Most of the domains, from randomisation to selection of the reported result, were scored as having some concerns or low risk of bias. We did not find reported adverse events or lasting bad effects directly attributed to breathwork interventions; four studies (six in total including secondary outcome studies) actively reported on this. Nonetheless, regarding safety and tolerability, a small subgroup of participants in Ravindran et al.’s study 71 focusing on fast-paced breathwork in unipolar and bipolar depression reported side effects such as hot flushes, shortness of breath and/or sweating. However, these participants opted to continue the intervention and no participants dropped out of the breathwork group due to adverse effects.

Risk of bias scoring using Cochrane Collaboration’s RoB 2 tool. Green and red colours correspond to low and high risk of bias, respectively. Yellow represents some concerns. D1 Randomisation process, D2 Deviations from the intended interventions, D3 Missing outcome data, D4 Measurement of the outcome, D5 Selection of the reported result.

As shown in Fig.  3 , the random-effects meta-analysis (k  = 12) displayed a small-medium but significant post-intervention between-group ES, g  = − 0.35 [95% CI − 0.55, − 0.14], z  = 3.32, p  = 0.0009, denoting breathwork was associated with lower levels of self-reported/subjective stress at post-intervention than controls. There were insufficient studies including follow-up measures for a meta-analysis. Heterogeneity was moderate but non-significant, χ 2 11  = 19, p  = 0.06, I 2  = 42%. Via removing one individual study at a time, the ES of breathwork on stress ranged from − 0.27 to − 0.39 and remained significant in all cases. Initial visual inspection of the funnel plot in Online Appendix  C suggested some skew due to studies with small samples; however, the Egger’s test was non-significant, z  = 0.03, p  = 0.947, indicating a low chance of publication bias. Fail-safe N  analysis denoted that a further 69 studies yielding zero effect would need to be added to make the overall ES non-significant for stress. On removal of the one potential outlier 67 the ES remained significant but became smaller: − 0.27. On removal of the two studies using estimated marginal M ± SDs, the ES remained significant and became larger: − 0.40.

Forest plot comparing breathwork interventions to non-breathwork control groups on primary outcome of self-reported/subjective stress at post-intervention. Squares and their size represent individual studies and their weight, respectively. Lines through squares are 95% CIs and diamond is the overall effect size with 95% CIs. More negative values denote larger effect of breathwork on self-reported/subjective stress in comparison to control condition. Effect sizes calculated using Hedges’ g . Figure produced using RevMan v5.4.

Subgroup analyses for stress

As displayed by Table ​ Table1, 1 , we conducted five sub-analyses for the primary outcome self-reported/subjective stress. There were no significant differential effects between subgroups.

Subgroup analyses on effect of breathwork on self-reported/subjective stress at post-intervention. *p  < 0.05, **p  < 0.01 . Heterogeneity not applicable where one study ( n  = 1) analysed. There were no significant differences between subgroups.

There was a significant effect of breathwork on stress in nonclinical samples, but not in mental (only one study) or physical health populations. Moreover, significant effects were yielded when breathwork was primarily focused on slow-paced breathing (but not for fast-paced breathing), taught to individuals alone, and when taught to groups (but not in combination, which comprised only one study). There were also significant effects of breathwork on stress when the intervention was taught remotely, in-person, and using a combination of these two delivery methods. Significant effects existed for both active and inactive control groups. There were significant effects for studies which used PSS and DASS measures (but not the PSQ, used by only one study).

Heterogeneity was high for studies with physical health samples, slow-paced breathwork, when breathwork was taught to groups and in-person, plus those studies with inactive controls, and when stress was measured by using the DASS, suggesting potential moderating factors that were not accounted for by the subgroup analyses. There was no significant correlation between estimated total duration of breathwork intervention/home practice and ES ( n  = 12) τ B  = − 0.05, p  = 0.418, number of intervention/home practice sessions and ES for stress ( n  = 12) τ B  = − 0.28, p  = 0.107, nor for intervention/home practice session frequency and ES ( n  = 12) τ B  = − 0.17, p  = 0.224.

Breathwork and secondary outcomes

In terms of data extraction, one study 79 had a measure with positively scored anxiety and depression subscales; accordingly, we subtracted the subscale score from the maximum score to reverse the polarity of the measure without changing the magnitude of difference. Another study 88 required two groups’ M ± SD scores to be combined. Analysis of follow-up scores were not possible for secondary outcomes as there were insufficient studies 58 ( n  < 5). Forest plots for the secondary outcomes are reported in Online Appendix  D . Random-effects analysis for anxiety ( k  = 20) showed a significant small-medium between-group ES in favour of breathwork, g  = − 0.32 [95% CI − 0.48, − 0.16], z  = 3.90, p  < 0.0001, with moderate and significant heterogeneity, χ 2 19  = 38.62, p  = 0.005, I 2  = 51%. Sensitivity analysis showed ESs ranging from − 0.29 to − 0.34, significant in all cases. No individual study was responsible for the significant heterogeneity. Random-effects analysis for depression ( k  = 18) displayed a significant small-medium ES in favour of breathwork, g  = − 0.40 [95% CI − 0.58, − 0.22], z  = 4.27, p  < 0.0001, and heterogeneity was moderate and significant, χ 2 17  = 40.5, p  = 0.001, I 2  = 58%. Sensitivity analysis showed ESs ranging from − 0.35 to − 0.44, significant in all cases. On removal of two potential outliers 85 , 88 , the ES remained the same. No single study was responsible for the significant heterogeneity.

We conducted the first comprehensive systematic review and meta-analysis of RCTs on the effect of breathwork on self-reported/subjective stress, analysing 12 studies which comprised a total of 785 participants. Breathwork yielded a significant post-intervention between-group effect of breathwork on stress compared to non-breathwork controls, denoting breathwork was associated with lower levels of stress than controls.

Statistical heterogeneity was moderate but not significant, meaning variance in ESs was likely explained by breathwork rather than other variables, although this non-significance could also be a consequence of the low number of studies included. This small-medium ES should be interpreted in the light of moderate risk of bias overall for the 12 studies. More than half of the studies included in our meta-analysis for stress were completed from 2020 onwards, suggesting a recent emergence of research into breathwork, which may have been accelerated by the covid-19 pandemic. Research on breathwork could be likened to that of meditation, which received an unprecedented surge in scientific exploration two decades ago 92 . We may be at a similar cusp with breathwork and anticipate considerable growth in the field. Given the close ties of breathwork to psychedelic research 93 , which is growing rapidly, this could accelerate growth further.

Regarding subgroup analyses for self-reported/subjective stress, heterogeneity was significant for studies with physical health samples, slow-paced breathwork interventions, inactive control groups, along with studies when breathwork was group-based and in-person. At present, there are too few studies within the sub-analyses to address this issue of statistical heterogeneity. Overall, point estimates were similar and sample sizes were small, hence where results were non-significant, it is unclear whether there was genuinely no effect, or lack of statistical power. Furthermore, no significant differential effects across subgroups were observed, but this could also be the result of the scarce number of studies.

While nonclinical samples showed a significant effect on self-reported/subjective stress outcomes and physical and mental health samples did not, between-subgroup differences were non-significant and the point estimates for these subgroups were similar (ranging from ES = 0.26–0.38). These findings could mean that breathwork is not effective for physical/mental health populations, however, it is also possible that this analysis was underpowered to detect effects given the relatively small number of studies contributing to the subgroups, as we have already mentioned. There were only two studies primarily focused on fast-paced breathwork and stress, insufficient to make a meaningful comparison with the ten studies primarily focused on slow-paced breathwork. Interestingly, delivery modes and styles did not seem to influence the results, which may suggest breathwork can be learned through several different formats. Half of the studies’ interventions were delivered remotely without instructors (self-help), hence breathwork could potentially be widely disseminated and thus accessible and probably scalable. The results were significant for both active and inactive controls, although it would be expected that breathwork would have less effect compared to active controls. This could be due to poor quality of the active controls. Lastly, results were significant for two of three stress outcome measures, most likely due to them being psychometrically well-validated—only one study used the third measure (PSQ).

Concerning dose–response, although associations were in the expected direction, there were no significant correlations between the minimum estimated durations of breathwork intervention/home practice and ES, for all outcomes. This apparent absence of dose–response effects was surprising as increased practice time might be expected to be associated with greater benefit, however compliance to intervention home practice was not reported for many studies and so true dose–response analysis was not possible. Moreover, intention-to-treat analysis data were used for the most conservative estimates of effect. Dhruva et al.’s study 64 included in our meta-analysis specifically investigated dose–response effects, finding a positive relationship between total amount of breathwork intervention/home practice and improvement in quality of life and chemotherapy-associated symptomology—there was a significant decrease in anxiety for each hour increase in breathwork. Alternatively, this could be indicative of breathwork being possibly able to help quickly, as suggested in very recent literature whereby just one session of slow, deep breathing had beneficial effects on anxiety and vagal tone in adults 94 , with vagal tone being measured, albeit indirectly, through HRV 6 . This may be likened to ‘micro dosing’ breathwork, similar to single session mindfulness meditation practices 95 .

The meta-analysis results are largely consistent with and extend upon previous work. For instance, our findings are somewhat in line with Malviya et al.’s recent review which provides some support for breathwork’s effectiveness in alleviating stress 43 . However, this review only included two studies for stress, one of which comprised of both groups incorporating breathing practices (and was thus excluded from our meta-analysis). Hopper et al.’s systematic review on diaphragmatic breathing found just one RCT for stress, however this used physiological measures 42 . Nonetheless, this study showed that the stress hormone cortisol was lower in people undergoing slow-paced breathwork compared to controls 96 . In a different study 38 , participants administered with bacterial endotoxin ( E. coli ) who performed fast-paced breathwork had higher spikes of cortisol compared to non-breathwork controls, during the intervention, but a quicker recovery and stabilisation of cortisol levels after cessation of breathwork. This could be another mechanism of action warranting further investigation.

Breathwork, anxiety and depression

Furthermore, meta-analyses comprising 20 and18 studies run for secondary outcome measures of self-reported/subjective anxiety and depressive symptoms, showed that breathwork interventions also yielded significant small-medium ESs in comparison to controls, favouring breathwork (see Online Appendix  D for results). However, heterogeneity was significant for both outcomes, meaning the variance in ESs may be due to other variables apart from breathwork. Thus, these ESs should be interpreted with caution and need further research. As per Malviya et al.’s review 43 , greater support was offered for breathwork in alleviating anxiety and depressive symptoms (eight studies for both outcomes). The review deemed findings pertaining to the efficacy of breathwork in decreasing anxiety and depression as promising. This was also consistent with Zaccaro et al.’s review findings on slow breathing (15 studies—no RCTs), that had lower self-reported anxiety and depression, possibly linked to increased HRV measured during interventions 4 . Ubolnuar et al.’s review of breathing exercises for COPD found no significant effect on anxiety and depression from a subgroup meta-analysis of two RCTs, however the interventions used for both were singing classes 39 . Nonetheless, a recent meta-analysis by Leyro et al. of 40 RCTs on interventions for anxiety, which comprised a respiratory component (ranging from diaphragmatic breathing to capnometry assisted respiratory training), showed such treatments were associated with significantly lower symptoms of anxiety compared to control groups 41 . Though non-respiratory controls were used, respiratory components did not have to form a significant part of the intervention, thus it is less possible to tease out the effects of such techniques. While some interventions used physically altering equipment such as training of musculature involved in respiration, this might provide further potential for breathwork-related work in clinical conditions.

Comparison to stress-reduction interventions

Through estimating statistically significant differences and 95% CIs among studies 97 , in comparison to interventions for stress, our findings suggest that breathwork might be associated with similar—and non-significantly different—effects. For instance, Heber et al.’s meta-analysis on computer- and online-based stress interventions, including CBT and third-wave CBT (e.g., inclusion of meditation, mindfulness, or acceptance of emotions) compared to controls in adults, found moderate effects on stress, d  = 0.43 [95% CI 0.31, 0.54], anxiety, d  = 0.32 [95% CI 0.17, 0.47], and depression, d  = 0.34 [95% CI 0.21, 0.48] 98 . Each of these effects overlap more than 25% with the width of either interval in our results for breathwork, denoting no indication of a clinically relevant difference between the interventions. Similar meta-analytic findings concerning effects on stress, anxiety and depression have been found for related and more analogous techniques such as mindfulness-based cognitive therapy and stress reduction (MBCT/MBSR) 99 along with self-help (MBSH) 100 . While Pizzoli et al.’s recent post-intervention HRVB meta-analysis (14 published RCTs) 13 found a significant effect on depression, another meta-analysis did not find a significant effect on stress, with the smallest ES being yielded for self-reported stress out of myriad outcomes 14 . Lastly, a meta-analysis of eight meta-analytic outcomes of RCTs on physical activity 99 showed similar significant effects on depression and anxiety. While we are not proposing breathwork as a substitute for other treatments, it could complement other therapeutic interventions, potentially leading to additive effects of such health behaviours.

People with stress and anxiety disorders tend to chronically breathe faster and more erratically, yet with increased meditation practice, respiration rate can become gradually slower, potentially translating into better health and mood, along with less autonomic activity 92 . Positive impacts on HRV may partially explain some of the mechanisms behind mindfulness meditation 101 , 102 . However, the above approaches like MBCT/MBSR and HRVB may be less accessible. MBCT/MBSR teacher training takes at least one year while HRVB is routinely taught by a qualified healthcare professional; this is usually a prerequisite and most certified biofeedback therapists are habitually licensed medical providers, including general practitioners, psychiatrists, dentists, nurses, and psychologists 103 . MBCT/MBSR and HRVB therapist training includes theoretical/practical curricula, while breathwork teacher training can be more quickly and easily taught (i.e., over days and weeks) online and remotely to both healthcare professionals and the general population, thus potentially proving cost-effective.

Two of our studies used the only Food and Drug Administration-approved portable electronic biofeedback device, which encourages deep, slow breathing 103 . However, HRV can be improved in the same way (tenfold) by simply breathing at a rate around 5–6 breaths/min 104 and some Zen Buddhist monks have been found to naturally respire around this rate during deep meditation 105 . It may be possible that breathing rate forms a key component of meditation’s known positive effects. Indeed, it has been shown that HRV can be modulated during the practice of meditation 106 . However, a recent meta-analysis on this exact matter found insufficient evidence suggesting mindfulness/meditation led to improvements in vagally mediated HRV, and more well-designed RCTs without high risk of bias are needed to clarify any such contemplative practices’ impact on this physiological metric 107 , along with potential mechanisms related to cortisol.

Traditional mindfulness-based programmes frequently involve meditation requiring observation of the breath, using it as an object of awareness, not voluntary regulation of respiration like in breathwork. Such breath-focus may be a key active ingredient and potential mechanism of action of the former contemplative practices, since highly experienced meditators have been found to breathe at over 1.5 times slower than nonmeditators, during meditation and at rest 108 . This translates into approximately 2000 less daily breaths for the former group of adept meditation practitioners (i.e., around 700,000 less breaths in a year), placing less demand on the ANS 92 . Meditation could also be complementary; voluntary upregulation of HRV through biofeedback may be improved by mental contemplative training 109 . While there is a possibility that it could simply be the cognitive-attentional components of both meditation and breathing practices that explain their effects, observation of the breath (i.e., most practices within mindfulness curricula) versus control of the breath (i.e., breathwork) warrants nuanced investigation.

Strengths, limitations and future directions

Our systematic review searched published, unpublished and grey literature across numerous electronic databases and the meta-analysis comprised several very recent RCTs with well-validated measures of self-reported/subjective stress. However, like most systematic reviews in this field, given the small sample size (likely due to the recent phenomena of breathwork in the West) and moderate risk of bias across the studies included in our meta-analysis, our results should be interpreted cautiously. Future studies exploring breathwork’s effectiveness should aim for research designs with low risk of bias. While this review attempted to bridge the gap and unify both old and new research, future low risk-of-bias studies are now needed in order to draw definitive conclusions of breathwork’s impact on mental health. There were also not enough studies for valuable subgroup comparisons, and therefore we did not identify any potential sources of heterogeneity. Furthermore, secondary outcomes were not scrutinised with the same level of detail as the primary outcome, as they were only used to provide complementary context and a bigger picture around stress and mental health in general.

Our meta-analysis is the first review of breathwork’s impact on self-reported/subjective stress and its therapeutic potential, and combining this quantitative synthesis of psychological effects of breathwork with other syntheses, i.e., of physiological effects 4 , could help build a stronger psychophysiological model of breathwork’s efficacy along with more robust mechanisms of action. Studies could use stress subscales in DASS as standard in addition to the anxiety/depression scales, as this could be important for nonclinical and subclinical populations experiencing stress and allow for direct comparison of effects across clinical/nonclinical populations. Additionally, psychophysiological RCTs combining both subjective and objective measures in line with proposed mechanisms of action (i.e., self-reported stress and ECG HRV/respiration rate measurements) should be conducted, along with further imaging (MRI, EEG, NIRS, etc.) studies on various breathwork techniques (only one fMRI study was available in Zaccaro et al.’s review 4 ). This could help better determine modalities and underlying principles of different breathwork techniques. Though validated scales were used for stress in the meta-analysis, our review lacks objective outcomes, which increases risk of bias further.

Comparison groups promoting observation versus control of the breath could yield interesting findings when exploring any differences between the effects of meditation and breathwork. However, robust scientific methods that align well with current methodological demands on meditation and contemplative psychological science 110 should be implemented. There was also limited scope to report on follow-up effects, hence more studies could include true follow-up timepoints and longitudinal designs, now more common in meditation and contemplative science research. On top of this, there could be cross-cultural differences in response to breathwork (i.e., between Eastern and Western modalities) which could be explored by future research, along with searching non-English language literature. There could also be differences between age categories (including children); this meta-analysis focused solely on adults across a broad age-range. Lastly, more studies should report on adverse events and lasting bad effects, with further research needed to gauge the safety profile of fast-paced breathwork in particular, so it not administered blindly to potentially vulnerable populations.

Clinical implications

For stress, though not many studies monitored home practice/self-practice, engagement with interventions appeared good, none reporting adverse effects directly attributed to breathwork. This suggests breathwork has a high safety profile and slow-paced breathing techniques can be recommended to subclinical populations or those experiencing high stress. However, regarding clinical populations, the findings from our meta-analysis show non-significant effects for mental and physical health populations, hence it could be premature to recommend breathwork in these contexts. If breathwork can indeed provide therapeutic benefit to specific populations, conducting research with strong, low risk-of-bias design is essential to understanding if breathwork is genuinely effective or not. Ethicality should always take centre stage, with first doing no harm being the priority. Nonetheless, in nonclinical settings (excluding those predisposed to mental and physical health conditions), the low cost and risk profiles make breathwork (primarily focused on slow-paced breathing), scalable, with evidence from this meta-analysis that some techniques can potentially be self-learned, not requiring an instructor in real-time. Providing future robust research shows positive effects of breathwork, only then can an evidence-based canon be borne out of breathwork, using standardised and manualised materials for both training and practicing various secular, accessible techniques. However, there is a possibility rigorous research demonstrates that breathwork is not effective. Moreover, precaution must be exercised at all times; clinicians should consider for the individual whether breathwork may exacerbate the symptoms of certain mental and/or physical health conditions (cf. Muskin et al. 111 ).

Conclusions

More accessible therapeutic approaches are needed to reduce, or build resilience to, stress worldwide. While breathwork has become increasingly popular owing to its possible therapeutic potential, there also remains potential for a miscalibration, or mismatch, between hype and evidence. This meta-analysis found significant small-medium effects of breathwork on self-reported/subjective stress, anxiety and depression compared to non-breathwork control conditions. Breathwork could be part of the solution to meeting the need for more accessible approaches, but more research studies with low risk-of-bias designs are now needed to ensure such recommendations are grounded in research evidence. Robust research will enable a better understanding of breathwork’s therapeutic potential, if any. The scientific research community can build on the preliminary evidence provided here and thus, potentially pave the way for effective integration of breathwork into public health.

Supplementary Information

Acknowledgements.

G.W.F. has a doctoral scholarship from—and is a Fellow of—The Ryoichi Sasakawa Young Leaders Fellowship Fund, Sylff Association, Tokyo. J.M.M. has a “Miguel Servet” research contract from the ISCIII (CP21/00080). J.M.M. is grateful to the CIBER of Epidemiology and Public Health (CIBERESP CB22/02/00052; ISCIII) for its support. Authors thank Dr. Patricia L. Gerbarg, M.D., and Dr. Frances Meeten for reading the manuscript and providing feedback prior to submission for publication. Thank you Dr. Daron A. Fincham for proofreading a final copy of the manuscript.

Author contributions

G.W.F. was responsible for securing funding for the programme of work to which this contributes, conceived the initial idea, and was responsible for leading the meta-analysis. G.W.F. and J.M.M. conducted the literature search. C.S. and K.C. supervised the entire process. G.W.F. conducted the analysis with support from C.S., K.C., and J.M.M. All authors discussed the data and clinical implications of the study. G.W.F. and J.M.M. conducted the risk-of-bias evaluations. G.W.F. drafted the manuscript, with input from C.S., K.C., and J.M.M. All authors read and revised drafts and approved the final manuscript. Each section of the manuscript was discussed among all authors.

Data availability

Competing interests.

G.W.F. has trained as a Breath Teacher with The Breath-Body-Mind Foundation, New York. Remaining authors J.M.M., C.S., and K.C. declare no conflicts of interest.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Guy William Fincham, Email: [email protected] .

Jesus Montero-Marin, Email: [email protected] .

The online version contains supplementary material available at 10.1038/s41598-022-27247-y.

Breath Research Updates, Techniques, and How-To’s

Effectiveness of Exhaled Breath Condensate Collection Using RTube® and Cooling Sleeve Chilled in Household Freezer

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Journal Article Summary – Measuring RNA in Breath Condensate

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The RTube has successfully been used to isolate RNA, microRNA and DNA from Exhaled Breath Condensate (EBC). While the collection process of EBC is similar for each of the target isolates, the processes for isolation vary. This Journal Article Summary provides an example of nucleic acid isolation from EBC collected with the RTube based on a study conducted by Dr. Guillermo Barreto of the European Molecular Biology Organization (EMBO Medicine).

To Filter or Not To Filter

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An Evolving Standard for Exhaled Biomarkers in Lung Disease Meets Old-Fashioned Consistency

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FDA Commentary on Biomarker Qualification

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The Drug-Device Breath Test

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Tips and Methods: Collect EBC and Sample VOC’s Simultaneously

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Acid Breath Test May Help Identify Reopening of Collapsed Alveoli in ARDS

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Gut-Brain Axis

Breathtaking news for depression and schizophrenia, a simple breath test can distinguish depression and schizophrenia..

Posted April 23, 2024 | Reviewed by Michelle Quirk

• Breath tests can evaluate chemicals produced by gut microbes.
• These microbial chemicals indicate the relative health of the gut microbiome.
• An unbalanced, unhealthy gut contains signatures of specific mental issues.

“As long as there's breath in our lungs our story is still being written.” –Bart Millard

Two chemicals from breath samples, butyrate and trimethylamine, are sufficient to distinguish depression and schizophrenia with 80 percent accuracy. These chemicals are both produced by gut microbes. This implies that the correlation between gut microbes and these two mental conditions is surprisingly robust. If, in a room full of people with multiple mental issues, you can distinguish them by their microbes, then perhaps we should be paying more attention to these microbes.

For about two decades now, we have understood that there is an intimate connection between gut microbes and mental health. But many professionals in the psychiatric field have been reticent to incorporate this knowledge into their practice. They know they have some patients with gut issues, but they also have many who seem to be free of them.

However, the gut issue is often hidden and, thus, unlikely to be encountered in normal therapy . Some psychiatrists point out that drugs already help many of their patients. Why mess with something that’s working? If only a fraction of psych patients have obvious gut issues, is it really worth pursuing?

Reasons to look again

There are several problems with this attitude. One is that drugs don’t work for many, and we don’t know why. To complicate the issue, drugs interact with gut microbes. Drugs can kill some microbes and nourish others, which is rarely considered by doctors or the Food and Drug Administration. Microbes can also affect drugs by degrading them or converting them to other chemicals. Could these interactions with gut microbes explain the uneven effects of psychoactive drugs?

For many psychiatrists, this research seems fringe, but studies are finding that the gut-brain axis exerts more influence on mental health than previously appreciated. And, since psychiatric disorders are among the leading causes of disability in the world, the truth here is consequential.

This is not the first study to find such an important association between gut issues and depression. I’ve written about other studies here . A Chinese study found that 70 percent of patients with depression had gastrointestinal (GI) symptoms. The worse the depression, the worse the GI problems. Coming from the other direction, about 80 percent of patients with irritable bowel syndrome (IBS) or inflammatory bowel disease (IBD) also suffer from depression. These numbers imply that the gut-brain connection is much more important than we thought. Far from fringe, it may be a factor in the majority of psychiatric cases.

Correlation is not causation

Correlations are great, but they don’t show whether gut issues cause mental problems or the other way around. However, in this case, it may be enough to simply note the association. The gut-brain axis is really a cycle: We know that the brain can alter gut microbes and vice versa. It almost doesn’t matter which was the primary cause, because once the vicious cycle is set in motion, it can propagate on its own, a perpetual motion machine cranking out malaise.

This sounds pretty gloomy, but it actually offers hope. It means there are two levers to pull: Either change the brain or change the gut.

Twin interventions

On the brain side, intervention works surprisingly well. Intriguingly, cognitive behavioral therapy can improve our gut microbes even as it improves our mood. That unexpected outcome suggests that traditional psychiatry may have been working in concert with gut health all along.

On the gut side, intervention also bears fruit. Improving your gut microbiome to enhance brain function is the ultimate goal of the gut-brain connection. It aims to boost the populations of psychobiotics—microbes that can improve our mood. Our psychobiotic gut microbes love fiber, but, sadly, modern food manufacturers assiduously remove fiber in a quest to make ultra-palatable fast food. Replenishing fiber via veggies and berries can nourish the psychobiotic microbes in our gut, improving cognition , mood, and memory . Prebiotic and probiotic supplements may also help.

Psychobiotic microbes also relish fermented foods, like yogurt, kimchee, kefir, sauerkraut, and pickles. Ferments contain both beneficial microbes and the fiber they love in one package. This is part of the Mediterranean diet , which has been shown to improve overall health and mood.

This research is literally breathtaking. Adding a simple, noninvasive test like this to a psych workup would not be inappropriate. The results could help to guide future therapy.

There will be trauma in our lives, and therapy can help us deal with it. But fixing our gut can also help by making us more resilient to those stressors. Knowing that your gut is involved could even lead to smaller doses of psychoactive drugs, once the toxins in the gut have been addressed.

It seems crazy that microbes could affect our mood, cognition, and even our personality , but recent studies are building a strong case. As Hippocrates noted some 2,500 years ago, all illness starts in the gut. And the state of our gut is up to us.

Henning, Daniush, Marian Lüno, Carina Jiang, Gabriela Meyer-Lotz, Christoph Hoeschen, and Thomas Frodl. “Gut–Brain Axis Volatile Organic Compounds Derived from Breath Distinguish between Schizophrenia and Major Depressive Disorder.” Journal of Psychiatry & Neuroscience  : JPN 48, no. 2 (April 12, 2023): E117–25.

Jia, Huang, Cai Yiwen, Su Yousong, Zhang Ming, Shi Yifang, Zhu Na, Jin Feng, Peng Daihui, and Fang Yiru. “Gastrointestinal Symptoms During Depressive Episodes in 3256 Patients with Major Depressive Disorders: Findings from the NSSD.” Journal of Affective Disorders, February 17, 2021.

Scott C. Anderson is a science journalist and coauthor with John Cryan and Ted Dinan of "The Psychobiotic Revolution" from National Geographic.

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Noted and Quoted, April 2024

Franklin faculty expertise and research findings – from a new COVID test to the rise of hybrid species and the dangers of bounce houses – appeared in a variety of media around the world during April. A sample of the breath of subject matter and the reach of public scholarship, plus coverage of a theatre alumnus:

Black-owned autonomous grocer goes where other stores aren’t – Jerry Shannon , associate professor of geography, quoted by Bloomberg “Ma Nature” expected to nurture warm spring in Savannah – Marshall Shepherd , Georgia Athletic Association Distinguished Professor of Geography and Atmospheric Sciences, quoted by Savannah Morning News Study underlines role of past injustices in medical mistrust – research led by Adam Chen , associate professor in the College of Public Health and the Center for Asian Studies, reported by UGA Today In Steve Yockey’s ‘Mercury,’ revenge is sweet when it goes down with laughs – AJC features producer/playwright Steve Yockey (A.B. Theatre, 2001) Researchers unveil faster, more accurate COVID testing technique – research led by Yiping Zhao , Distinguished Research Professor of Physics, reported by UGA Today , WGAU , Futurity , From pizzly bears to strange fish, here’s why hybrid animal sightings are on the rise – Michael Arnold , Distinguished Research Professor in the department of genetics, quoted on MSN More than meets the eye: Georgia Museum of Natural History seeks to expand public presence – multiple faculty members quoted in feature by the R&B The rise of hybrid species in a warming world – Michael Arnold quoted by One Green Planet Solar eclipses are more common than you think – Marshall Shepherd writing at Forbes Racism may increase Alzheimer's risk – Ronald Simons , Regents' Professor of Sociology, quoted in Newsweek Workaholism: What it is and preventing it in your life and workplace – Q & A with Malissa Clark , associate professor of psychology, in Forbes Earth Day is not about the planet — it’s about us – Marshall Shepherd writing at Forbes John Burke , Distinguished Research Professor and head of the Department of Plant Biology in UGA’s Franklin College of Arts and Sciences, is uncovering the secrets of sunflowers Woman speaks out after dust devil lifts inflatable jumper 100 feet – John Knox, professor of geography, interviewed on ABC News Public forum asks crucial questions regarding the future growth of Micron – Andrew Herod , professor of geography, quoted on chip maker in rural New York by WSYR  

Image: Screenshot of geography professor John Knox interviewed on Good Morning America, April 23, 2024

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The U.S. is cracking down on PFAS — but not in fertilizer

This story was originally published by Grist and appears here as part of the Climate Desk collaboration.

Earlier this month, the Environmental Protection Agency designated two types of “forever chemicals” as hazardous substances under the federal Superfund law . The move will make it easier for the government to force the manufacturers of these chemicals, called per- and polyfluoroalkyl substances or PFAS, to shoulder the costs of cleaning them out of the environment.

The EPA “will focus enforcement on parties who significantly contributed to the release of PFAS chemicals into the environment, including parties that have manufactured PFAS or used PFAS in the manufacturing process, federal facilities, and other industrial parties,” the agency explained in a press release . The designation comes on the heels of an EPA rule limiting the acceptable amount of the two main types of PFAS found in the United States, PFOS and PFOA, to just four parts per trillion .

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Although the EPA’s new restrictions are groundbreaking, they only apply to a portion of the nation’s extensive PFAS contamination problem. That’s because drinking water isn’t the only way Americans are exposed to PFAS, and not all companies spreading PFAS into the environment deliberately added the chemicals to the products. In Texas, a group of farmers whose properties were contaminated with PFAS from fertilizer are claiming the manufacturer should have done more to warn buyers about the dangers of its products. The first-of-its-kind lawsuit illustrates how much more regulation will be needed to rid the environment — and Americans’ bodies — of forever chemicals.

PFAS have been around since the middle of the 20th century when chemical giants DuPont and 3M started putting them in products such as nonstick cookware, firefighting foam, and tape. The chemicals, ultra-effective at repelling water, quickly became ubiquitous in products used by Americans every day: pizza boxes, takeout containers, popcorn bags, waterproof mascara, rain jackets.

But the stable molecular bonds that make the chemicals so effective in these applications also make them dangerous and long-lasting. The chemicals bind to blood and tissue, where they can build up over time and contribute to a range of health issues. The chemicals have been linked to testicular, kidney, and thyroid cancers ; cardiovascular disease ; and immune deficiencies . Over decades, as chemical companies led by 3M obscured the dangers of PFAS from federal regulators and the public, the chemicals leached into the environment and migrated into soil and drinking water supplies. They seeped into us, too; 97 per cent of Americans have PFAS in their blood .

PFAS are also in our excrement — which is a problem because of where that waste ends up. Biosolids, the concentrated byproducts of waste treatment plants, are commonly spread on farms as a fertilizer. The products are incredibly cheap — a selling point for farmers who are often working with razor-thin profit margins. Some 19 billion pounds of wastewater sludge was spread on farmland in 41 states between 2016 and 2022. The EPA estimates that 60 per cent of biosolids in the U.S. are applied to agricultural lands .

There’s growing evidence that biosolids are rife with forever chemicals that have travelled through people’s bodies. The EPA’s new PFAS rules don’t apply to biosolids , which means this contamination is largely still flying under the radar. The EPA said it aims to conduct a first-ever assessment of PFAS in biosolids later this year , which may result in new restrictions. Preliminary research has shown that the PFAS in waste sludge is absorbed by crops and, in turn, consumed by livestock ; it’s even been found in chicken eggs . Some farmers aren’t waiting for the federal government to take action.

The #EPA is cracking down on #PFAS — but not in fertilizer. #ForeverChemicals #PFAS #PFOS #PFOA

In February, five farmers in Johnson County, Texas, sued Synagro, a biosolids management company based in Maryland, and its subsidiary in Texas. Synagro has contracts with more than 1,000 municipal wastewater plants in North America and handles millions of tons of waste every year . The company separates liquids and solids and then treats the solids to remove some toxins and pathogens. But PFAS, thanks to their strong molecular bonds, can withstand conventional wastewater treatment. Synagro repurposes 80 per cent of the waste it treats, some of which is marketed as Synagro Granulite Fertilizer.

The lawsuit claims Synagro “falsely markets” its fertilizers as “safe and organic.” The plaintiffs accuse the company of selling fertilizer with high levels of PFAS and failing to warn farmers about the dangers of PFAS exposure. They say an individual on a neighbouring property used Synagro Granulite, and the product then made its way onto their farms.

Dana Ames, Johnson County’s environmental crimes investigator, opened an investigation after the plaintiffs made a complaint to the Texas Commission on Environmental Quality and the Johnson County constable’s office. Ames tested soil, surface water, and well water samples from the affected farms for PFAS. She found contamination ranging from 91 to 6,290 parts per trillion in soil and water samples from the plaintiffs’ properties. The county also tested tissue from two fish and two calves on those farms. The fish tested as high as 75,000 parts per trillion. The liver of one of the calves came back with an astounding 610,000 parts per trillion of PFOS — about 152,000 times higher than the EPA’s new PFAS drinking water limits.

The plaintiffs voluntarily stopped selling meat, fish, and other agricultural products after discovering the contamination. They’re suing Synagro to recoup their losses and more damages they say are sure to come. Synagro, the complaint reads, failed to conduct adequate environmental studies and the company “knew, or reasonably should have known, of the foreseeable risks and defects of its biosolids fertilizer.”

A spokesperson for Synagro told Grist the company denies the “unproven and novel” allegations. “EPA continues to support land application of biosolids as a valuable practice that recycles nutrients to farmland and has not suggested that any changes in biosolids management is required,” the spokesperson said, highlighting the lack of federal regulations.

Ames, the investigator, said that federal and state inaction is the real root of the problem. “EPA has failed the American people and our regulatory agency here in the state of Texas has failed Texans by knowingly allowing this to continue and knowingly allowing farms to be contaminated and people, too,” Ames told Grist .

In response to Grist ’s request for comment, the EPA confirmed that recent federal PFAS restrictions do not affect the application of biosolids on farmland. The Texas Commission on Environmental Quality declined to comment on the ongoing litigation in Texas.

Public Employees for Environmental Responsibility, an environmental non-profit that helped organize the PFAS testing on the plaintiffs’ properties in Texas, is considering filing its own lawsuit against the EPA for not implementing restrictions on PFAS in biosolids. “They have a mandatory duty to look at what pollutants are in these biosolids and set standards for them,” said the group’s science policy director, Kyla Bennett, who is a former EPA employee. “They have not followed through.”

The Texas plaintiffs aren’t the only farmers struggling with a PFAS contamination problem due to the use of biosolids. Maine already banned the use of biosolids as fertilizer in 2022 after dozens of farms tested positive for forever chemicals . A farmer in Michigan who used biosolids fertilizer was forced to shut down his 300-acre farm after state officials found PFAS on his property. It’s likely that any farmland in the U.S. that has seen the use of biosolids products has a PFAS problem.

“No one is immune to this,” Bennett said. “If people don’t know that their farms are contaminated, it’s because they haven’t looked.”

• Zoya Teirstein

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« ...Maine has banned the use

« ...Maine has banned the use of ...» That issued flowed over into south-eastern Québec. «Enquête» an investigative program by Radio-Canada looked into this story. see https://ici.radio-canada.ca/recit-numerique/4950/boue-fumier-humain-main...

Since those contaminated biosolids could not be used in the USA, they were exported across the border into neighbouring Québec. This caused an uproar and many farmers became shy about using that king of fertilizer.