Some of the NY had brief acquaintance with some practices, while none of the MS group had prior experience with yoga and were given time to practice and get acquainted with the interventions till they performed them accurately.

As Hindi was the native language of most participants, the consent forms and demographic forms were all translated into Hindi language by professional translators. Reliability and validity of the translation was checked via a different group of professional translators providing back translation to English.

After providing written consent, participants were asked to empty their bladder and switch off their mobile phones. They then had their height, body weight, waist circumference, seated BP and radial artery pulse measured before commencing the experimental session.

All measurements were performed by the same experimenter with participants in a recumbent position. The laboratory was maintained at a comfortable temperature of 23 degrees Celsius with subdued lighting.

Before gas exchange recording commenced, subjects were asked to relax and adjust to the environment of the canopy for 10 minutes. The experimental session lasted around 60 minutes and involved multiple phases of equal duration with intervention phases interspersed with the neutral condition of eyes open rest.

The experimental sequence involved nine separate 5 minute phases, each preceded by a one minute pause Pause during which BP was measured and they were instructed on the next phase Figure 1. The yogic practices were all based on traditional yoga texts with some slight variation to account for the recumbent position and the requirements of the measuring equipment.

During the neutral condition participants were instructed to breathe spontaneously, avoid movement, yawning or mental agitation and have a relaxed quiet mind. The Mental Arithmetic Stress Test MAST involved participants having their eyes closed and being instructed in a crisp tone of voice to read a 4 digit number written on a piece of cardboard and to then count backwards by 3 s as quickly and accurately as possible until asked to stop.

The ANB phase involved subjects gently occluding alternate nostrils with their fingers as described by Niranjanananda[ 60 ] and continue this cycle rhythmically, soundlessly and effortlessly for 5 minutes until instructed to stop.

The experienced yoga practitioners were informed not to perform retention during breathing cycles. Participants were instructed to breathe through their nostrils at around 48 BPM 0.

As this type of yogic breathing can be stressful and result in dizziness or discomfort for some people, the non-yoga and MS group were suggested to continue a cycle of spontaneous breathing in the event of any discomfort.

The meditation phase involved subjects lying with their body relaxed and still and eyes gently closed. Body weight and height were measured using an electronic platform scale Gold Tec GTEP K , and stadiometer Seca Waist circumference was measured with subjects standing with arms at their side, feet close together and weight evenly distributed.

Measures were taken at the midpoint between the lower margin of the last palpate rib and the top of the iliac crest at the end of expiration to ensure a relaxed abdominal wall as per WHO guidelines[ 61 ]. Blood pressure was measured before and after every experimental condition using an automatic digital blood pressure monitor Welch Allyn, Redding Medical, USA with the cuff positioned on the left arm at the level of the right atrium.

The BP monitor was calibrated and checked using a mercury sphygmomanometer and stethoscope as described by the British Hypertension Society[ 62 ].

This study focused on weight-adjusted OC relative OC which is more reliable when comparing people with different body weight[ 63 ].

This calorimeter uses a canopy hood and dilution technique that allows measurements to be made with subjects breathing spontaneously or as instructed according to the study protocol without the encumbrance of a face mask, mouth piece or nose clips Quark CPET, Italy.

Before each experimental session the calorimeter was calibrated using a reference gas mixture. Measurement of O2 consumption and CO2 production was performed at 5 second intervals. Calibration of flow was performed using a certified 3 L calibrated syringe and calibration of the O2 and CO2 gas analysers was performed prior to each experimental session using a certified calibration gas.

Before each experimental session a 5 minute steady state was achieved as per previous studies[ 64 ]. The calorimeter provided both absolute and relative per kg of body weight values. Demographic details of the Participants Table 1. Data were analysed using SPSS The single between-subjects factor was group Yoga Practitioner, Non-yoga Practitioners and Metabolic Syndrome ; the single within-subjects factor was made up of the nine levels of Phase NC1, MAST, NC2, ANB, NC3, KB, NC4, MED, NC5.

Any significant group by phase interactions were followed by a full analysis of simple main effects. The descriptive values of metabolic variable across nine phases in three groups are shown in Table 2. The pairwise comparison of the estimated marginal means for the main effect for group revealed a significant difference in relative OC between the YP group and both MS and NY groups, and has been illustrated in Table 3.

Table 4 illustrates, p values for pairwise mean comparisons based on the analysis of estimated marginal means with Bonferroni-adjusted α values revealed significant differences between the YP and MS groups in phases NC1, NC2, ANB, NC3, NC4, Med and NC5.

Significant differences were also found between the YP and NY groups in phases NC1, MA, NC2, NC3, NC4 and Med. The NY group was significantly different from the MS group at NC2, ANB and NC4. At the level of pairwise comparison for simple main effect of groups within phases, several significant differences were evident in the three groups in different phases Table 5 describes: p values of comparison of each intervention with pre and post phase.

There is also some evidence indicating that YP group exhibited a higher level of recovery that the other two groups. This observational study found that regular yoga practitioners had significantly less OC and greater variability in their OC across all phases compared to non-yoga practitioners or metabolic syndrome patients.

While the YP group had lower baseline OC, their OC increased substantially in response to the active interventions and fully recovered back to baseline levels during resting periods. These findings related to metabolic activity are consistent with previous studies that have found regular yoga practitioners have a lower basal metabolic rate compared to non-yoga practitioners[ 51 , 52 ] with greater recovery from stress[ 65 , 66 ].

This is the first study to report OC in yoga practitioners during and after mental arithmetic stress and the first to measure metabolic reactivity and recovery both within and between different participant populations involving metabolic syndrome patients.

Our study is also the first to examine OC in yoga practitioners using indirect calorimetry with a ventilatory hood. While other studies have examined yoga using similar indirect calorimetry methods[ 67 ], the use of a ventilatory hood is reported to less stressful than calorimetry that uses a mouth piece or mask[ 68 , 69 ] and hence is likely to have facilitated greater relaxation amongst our participants and therefore more accurate results.

While our study used a rigorous experimental method, it is an observational study rather than a randomised clinical trial and the differential effects between groups may have been due to factors other than their history of yoga practice. The selection of our study population and protocol may have also introduced some bias.

For example there were numerous differences between the groups with the MS group being on average 10 years older than the other groups and the baseline OC being lowest in the YP and highest in the MS groups. Furthermore, there were some smokers in the MS group and none in the YP group and the YP group were all well versed with the yoga practices and were also involved in routine ashram life, which included activities such as meditation, yoga philosophy discussions, meetings with spiritual leaders and teachers, Ayurvedic diet and structured daily routines.

Some of the YP group were also familiar with the laboratory testing, whereas the NY and MS groups were not well versed with the yoga techniques or the laboratory and were only temporary ashram residents or resided outside the ashram where they were subjected to the stresses of everyday life.

This may have led to the NY and MS groups being less relaxed than the YP group and less able to perform the active practices correctly.

Some aspect of the yoga interventions also lacked uniformity, for example there was a difference in the breath rate between groups during Kapabhati breathing, due to the advanced nature of these practices, which are difficult to learn and perform by novices. Comparing these practices in novice and advanced practitioners may therefore produce unreliable results unless the practices are specifically paced to achieve uniform breath rates across groups.

The timing and sequencing of the different experimental phases may have also influenced the results, as they were of relatively small duration with only brief rest periods that may not have allowed full recovery between the phases.

Due to these limitations we have limited our discussion to the analysis of the mental arithmetic stress test, which occurred first in the experimental sequence, and have not discussed the responses to the ANB, KB or meditation practices. It is evident that mental arithmetic induced a metabolic burden on our participants, with all groups having significantly raised OC during the mental arithmetic phase.

Mental arithmetic stress is widely used to elicit β-adrenergic sympatho-adrenal responses in laboratory conditions[ 12 , 70 ] and cardiovascular reactivity to mental arithmetic-induced stress is reported to be unrelated to personality type[ 71 ], yet more pronounced in subjects with high BP[ 72 ].

Cardiovascular reactivity to mental stress is also reported to be an independent risk factor for features of metabolic syndrome including hypertension and insulin resistance[ 70 , 73 , 74 ] as well as for atherosclerosis[ 75 ] and future cardiovascular risk[ 76 ]. However, cardiovascular reactivity is not always associated with negative health outcomes and may be adaptive and reflect behavioural flexibility, energy mobilisation and effective coping rather than pathology[ 75 ] as indicated by reports of a negative association between cardiovascular reactivity and obesity, depression and self-reported health[ 77 ].

We found that while mental stress placed a metabolic burden on all groups, the MS group had a significantly blunted post-stress recovery. This supports previous suggestions that recovery responses may be a better predictor of subsequent cardiovascular risk than stress-induced reactivity[ 78 — 81 ].

Our finding that the YP group had a greater post-stress recovery in oxygen consumption than either the NY or MS group are consistent with reports of greater recovery in heart rate in meditators compared to non-meditators after watching a stressful film[ 65 ] and greater recovery in self-reported measures after watching negative emotion-evoking slides[ 66 ].

Our results further support suggestions that individuals who are able to rapidly return their cardiovascular activity to baseline following a stressful event are more likely to have better cardiovascular health[ 75 ]. While the biological mechanism linking stress responses and cardiovascular diseases and mortality is poorly understood, there is evidence to suggest that cardiovascular responses to psychological stress are associated with increased allostatic load[ 82 ] and thus poor cardiovascular health[ 4 ].

This may be indicated by changes in the autonomic nervous system, hypothalamic-pituitary-adrenal axis and metabolic, immune, cellular and physiological and psychological changes that include endothelial dysfunction, shortened telomere length and less focused thought processes[ 6 , 83 — 85 ].

Slower recovery from psychological stress may also reflect a greater allostatic load and reduced sympatho-adrenal flexibility[ 82 ], while yoga and meditation appears to enhance adaptability and post-stress recovery[ 44 ].

It has been further suggested that the relaxation response may be associated with improved mitochondrial energy production and utilisation that promotes mitochondrial resilience through upregulation of ATPase and insulin function[ 86 ]. In our study the YP group had a greater metabolic response to mental arithmetic stress than the other groups as well as having a more rapid recovery.

This is consistent with previous studies that suggest that yoga practices enhance autonomic regulatory reflex mechanisms associated with stress[ 87 ] and improve autonomic function, pulmonary function and metabolic function[ 88 — 90 ].

Single yoga sessions have also been shown to reduce HR and BP in sedentary individuals[ 91 ], healthy non-yoga practitioners[ 35 ], as well as in patients with hypertension[ 92 — 94 ] and congestive heart failure[ 95 ].

Regular yoga practice has been further shown to down regulate the HPA axis and sympatho-adrenal pathways with reduction in catecholamine and cortisol levels[ 29 , 41 ], and improve immune response[ 38 , 87 ], vascular function[ 96 ] and melatonin secretion[ 97 , 98 ].

Regular yoga practice has also been shown to contribute to cognitive improvement[ 29 ] physical relaxation[ 99 ] and reductions in emotional distress[ ] and anxiety[ ].

The results of this study suggest that regular yoga practitioners have enhanced metabolic resilience with reduced basal metabolic demands and enhanced recovery after stress while metabolic syndrome patients have higher basal metabolic demands and blunted post-stress recovery. These results are consistent with other studies that report that regular yoga practice enhances metabolic function and improves obesity[ ], dyslipidemia[ ], hyperglycaemia[ ] hypertension[ , ] and metabolic syndrome[ — ].

Yoga practitioners have reduced oxygen requirements during resting conditions and greater metabolic flexibility compared to non-yoga practitioners and metabolic syndrome patients. Yoga practitioners are also better able to respond to and recover from the increased metabolic burden due to mental arithmetic stress, while metabolic syndrome patients have significantly blunted post-stress recovery.

Further, long term studies are needed in order to establish, if regular yoga practices have an influential role in reducing resting metabolic demand. In future, studies should incorporate longer intervention phases to investigate the metabolic reactivity and recovery to stress and to determine if yoga practices are able to enhance metabolic resilience in metabolic syndrome patients.

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Abstract The effect of psychological stress on resting metabolic rate RMR and diet-induced thermogenesis DIT was assessed in 12 healthy young non-obese men of body weight A complete guide to B vitamins, types, sources, and more. Some research has suggested that eating spices such as chili, which contains capsaicin, can increase metabolic rate, including the rate at which the body burns fat and uses energy.

A study from China found that people who ate spicy food every day were more likely to have a high body mass index BMI than those who did not. The researchers noted that more investigations are needed to find out why this happens. The Academy of Nutrition and Dietetics says that while eating hot chilies might boost metabolic rate temporarily, it is unlikely to have a significant impact.

What are some healthy herbs and spices? Thyroid hormone stimulates the production of substances that increase oxygen consumption, respiration rate, and body temperature. This involves a higher rate of energy consumption.

Conversely, the body of a person with hypothyroidism is likely to burn energy at lower rate. Their metabolic rate may be slower, and they may have a higher risk of weight gain and obesity.

For those with hypothyroidism, taking medications that increase the levels of thyroid hormone can increase their resting metabolic rate. Seeking help for hypothyroidism can help speed up metabolic rate and reduce the risk of complications linked to this condition.

What is hypothyroidism and how can you recognize it? Metabolic rate refers to the rate at which the body uses energy and burns calories. The body uses most of its energy this way. Metabolic rates vary widely between individuals, so it is not possible to specify a standard or high metabolic rate. However, the higher the rate, the quicker a person will use the energy they take in from food, which may reduce the chance of weight gain.

It is not always possible for a person to change their metabolic rate, but exercise and dietary measures may help. A good metabolic rate may help with weight management. But for those seeking to lose weight, it is better to focus on eating a varied diet with plenty of whole foods and being physically active.

While some foods, such as spices, may help boost rates temporarily, they are not a long term solution. It is always best to speak with a doctor before adjusting the diet or making changes to an exercise routine. Metabolism is the process the body uses to break down food and nutrients for energy, as well as to support different body functions.

What people eat…. Metabolism involves biochemical reactions in the body and is central to maintaining life. What are the myths and facts of metabolism? Can you speed…. The Everlywell Metabolism Test measures the levels of cortisol, thyroid stimulating hormone, and free testosterone in the body.

Learn what the results…. Recent evidence suggests that a plant-based diet can aid weight loss by improving metabolism and reducing the amount of fat that accumulates around…. Researchers say bariatric surgery can help with weight loss, but it can also help improve cognitive functions including memory.

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Medical News Today. Health Conditions Health Products Discover Tools Connect. How to increase your metabolism. Medically reviewed by Adam Bernstein, MD, ScD — By Rachel Nall, MSN, CRNA — Updated on December 9, Eat at regular times.

Eat enough calories. Eat more protein. Drink green tea. Do resistance training. Drink enough water.

Unfortunately, though, many people have noticed that the stress of daily life makes weight loss even more difficult.

Why is this the case? When we want to lose weight, we essentially need to ensure that we are in a negative energy balance. That means that we are expending more energy than we consume — continue this pattern for a few days and you should lose a pound.

Simple, right? Unfortunately, there are myriad factors that play into energy balance. how many calories did you eat, how many calories did you burn during your workout s , and how many calories do you burn just staying alive? However, when it comes to RMR resting metabolic rate there are a few variables that can change what we typically assume to be a constant.

Your RMR is essentially your resting metabolism — in a basic sense, this number reflects how many calories you burn simply to stay alive. We included only experimentally-induced increases of energy expenditure to avoid potential masking effects of anticipatory responses or delayed effects of GCs.

Because metabolic rate and GCs can fluctuate rapidly, we targeted metabolic rate and GC measurements taken simultaneously or when animals could be assumed to be in the same physiological state e. within the same day and experimental treatment. We further investigated ii whether the magnitude of the experimentally induced changes in metabolic rate and GCs were correlated quantitative approach through meta-regression.

Our predictions are that i increases in metabolic rates are associated with increases in plasma GC concentrations, ii that changes in GCs are proportional to induced changes in metabolic rate, and iii that the association between increases in metabolic rate and GCs is independent of the treatment used to increase the metabolic rate.

We here consider GC regulation from the perspective of their role in fuelling metabolic rate. When metabolic rate is low, for example during periods of inactivity, circulating GCs are maintained at low levels and glucose release from fuel stores is released in the blood stream at a low rate matching the modest metabolic needs.

permissive actions; Sapolsky et al. An increase in metabolic rate can be anticipated or unanticipated GCs will exert preparative or stimulating actions, respectively; Sapolsky et al.

Unanticipated but gradual increases in metabolic rate will occur for example when thermoregulatory costs unexpectedly increase. Schematic representation of the association between metabolic rate and plasma levels of glucocorticoids and glucose. Green arrows represent increasing effects whereas red arrows represent reducing effects.

In both gradual and acute increases in metabolic rate, a main role of GCs is to increase circulating glucose at a rate matching the metabolic requirements through diverse mechanisms.

Decreasing plasma glucose levels trigger a series of hormonal changes that promote a switch in energy usage. Blood glucose level then increases, both by mobilization from existing stores, and by inhibition of further storage. GCs also inhibit glucose uptake and glycogen synthesis in the liver, redirecting resources to gluconeogenesis and glycogenolysis, along with glucagon and catecholamines as part of the most immediate acute response.

Catecholamines act quickly and increase within seconds to induce the release of energy needed to fuel the response Herman et al.

The GC response lags in time -as GCs are produced de novo at the adrenal and take minutes to be secreted— and lasts substantially longer, depending on active feedback signalling and passive GC degradation processes Herman et al.

In addition, inhibition of peripheral glucose transport and utilization in response to GCs increases the availability for other tissues, such as the brain reviewed in Sapolsky et al.

GCs also act in other substrates, further increasing lipolysis by inducing hormone-sensitive lipase Slavin et al. In various muscle types, GCs suppress protein synthesis while promoting protein degradation and amino acid export. When the energetic and substrate requirements of the organism are further increased e.

This prediction of a strong association between GCs and metabolic rate, however, is not well researched, and does not necessarily imply that one trait necessarily affects the other per se, as their interplay is likely to be shaped by the environmental or physiological context.

Additionally, although we consider GCs to be regulated to meet energetic demands, we are aware GCs have many complex downstream effects at both baseline and stress-induced levels, besides energy-mobilization Fig.

We reviewed the literature to identify empirical studies reporting measurements of both metabolic rate and plasma GCs. We compiled studies that met all following criteria: 1 Including an experimental manipulation of any kind leading to increases in metabolic rate which was quantified i.

both significant and non-significant increases. Among these, we also included those studies reporting heart rate as a metabolic measure, as heart rate and metabolic rate are strongly correlated Bevan et al. not exogenous or chemically induced —e. with ACTH or CRH. The latter condition excludes, for example, studies with daily energy expenditure measurements combined with GCs measured at one time-point.

Finally, we only included studies on endotherms birds and mammals , because metabolic regulation differs strongly between endotherms and ectotherms. After the search, we consecutively selected articles after a abstract review, b full text review and c data availability for effect size calculations.

Using this approach, we identified a total of 14 studies that met all our criteria see Table S1 for additional information on the number of studies obtained on each of the search steps.

We also systematically checked the reference list of these 14 papers, which yielded an additional 7 papers. Thus, we included a total of 21 papers in our analyses, of which 12 were on birds, and 9 on mammals.

Nine of the 22 papers included more than one experimental treatment, yielding a total of 35 effect sizes. For each of these studies, we extracted information on study species or metabolic and GC variables reported, among others Table S2.

all individuals went through all experimental treatments ; c Whether metabolic rate or heart rate was the metabolic variable; and d The type of treatment that induced an increase in metabolic rate see below Table S2.

To estimate effect sizes of metabolism and GCs, we used the web-based effect size calculator Practical Meta-Analysis Effect Size Calculator www. See Table S3 for details on data extraction and effect size calculations.

For each study, we compared the mean metabolic rate and level of plasma GCs of individuals in the treatment group s to that of individuals in the control group. For studies in which treatment was confounded with time, because pre-treatment measurements were used as control and compared with measurements during treatment, the pre-treatment measure was used as control when calculating effect sizes in studies where there was a single treatment.

When studies with a before-after design included more than one experimental treatment, the treatment yielding the lowest metabolism was taken as control for the effect size calculations. Thus, confounding time with treatment was avoided whenever possible.

We conducte d all meta-analyses using the rma. mv function from the metafor package Viechtbauer , implemented in R version 4. Standard errors were used for the weigh factor. All models contained a random intercept for study identity to account for inclusion of multiple experimental treatments or groups from the same study.

Most species were used in a single study, and we therefore did not include species as a random effect in addition to study identity. The number of species was however insufficient to reliably estimate phylogenetic effects, we therefore limited the analysis in this respect with a comparison between birds and mammals see below.

The dependent variable was either the metabolic rate or the GC effect size. One model was fitted with the metabolic rate effect size as a dependent variable, to estimate the average effect on metabolic rate across all studies in the analyses. All other models had the GC effect size as dependent variable, and metabolic rate effect size as a moderator.

Distribution of metabolic rate effect sizes was skewed which was resolved by ln-transformation, which yielded a better fit when compared to a model using the linear term evaluated using AIC, see results for details.

Our first GC model contained only the metabolic rate effect size as a fixed independent variable. This model provides a qualitative test of whether GC levels increase when metabolic rate is increased and tests prediction i by providing an estimate of the intercept, which represents the average GC effect size because we mean centered the ln-transformed metabolic rate effect size Schielzeth The same model tests prediction ii whether the GC effect increases with an increasing metabolic rate effect size, which will be expressed in a significant regression coefficient of the metabolic rate effect size.

In: International Journal of Sports Science and Coaching. In: International Journal of Sports Science and Coaching , TY - JOUR T1 - Wearable technology metrics are associated with energy deficiency and psychological stress in elite swimmers AU - Lundstrom, Emily A.

AU - De Souza, Mary Jane AU - Koltun, Kristen J. AU - Strock, Nicole C. AU - Canil, Hannah N. AU - Williams, Nancy I. N1 - Publisher Copyright: © The Author s PY - Y1 - N2 - Energy deficiency ED and psychological stress affect athlete health. Lundstrom EA , De Souza MJ , Koltun KJ, Strock NCA, Canil HN , Williams NI.

doi: