RMR and heart rate variability -
Discrepancies were discussed between the first SC and second author SR until a consensus was reached. The sum of the subscale item scores was used to provide an overall assessment of evidence quality up to a maximum possible score of 14 i.
No risk of bias was undertaken at the outcome level because all studies included an objective measure of HRV. A total of records were retrieved from the initial search. After duplicates were removed, full text articles were assessed for eligibility, from which 60 met the inclusion criteria and were included in the systematic review see Fig.
Five studies reported on non-linear domain measures with SD1 and SD2 being the most prominent [ 28 , 29 , 30 , 31 , 32 ]. The 60 articles were categorised into four distinct groups: 1 HRV comparisons in shift work and occupational tasks; 2 changes in HRV from baseline to completion of singular stressors; 3 recovery of HRV following completion of a singular stressor; 4 HRV responses across repeat stressor exposures.
Twenty-one studies reported on measures of HRV comparing shift work and occupational tasks. Both no differences [ 33 , 34 , 35 , 36 ] and decreases [ 37 ] in HRV were observed in on-duty work periods compared to off-duty work periods.
Twelve studies compared HRV responses to different working shift types, conditions and tasks to evaluate their similarity [ 2 , 33 , 34 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ].
On-duty firefighter incidents yielded lower HRV than non-incidents that were matched for similar physical activity [ 45 ]. The increased HRV exhibited by these individuals dissipated at the onset of the new day.
Four studies observed reductions in HRV with increases in task complexity i. single task vs dual task response [ 40 , 41 , 46 , 47 ]. Driving and piloting tasks showed an increase in HRV as the duration of the task continued [ 40 , 48 ]. Decision making performance was improved with those exhibiting greater HRV both prior to and during the stressor [ 5 , 24 , 38 , 46 , 49 ].
shooting when it is incorrect while maintaining shooting accuracy compared to a controlled group [ 5 ]. Error of omission i. incorrectly not shooting was similar between groups [ 5 ]. Both decreases [ 40 , 49 ] and increases [ 24 ] in HRV were associated with quicker reaction times.
HRV was shown to be linked to behavioural and emotional responses in police officers and active duty infantry soldiers [ 39 , 50 ]. In addition, experienced first responders demonstrated a decreased HRV compared to control subjects when completing job specific tasks [ 6 ] with increases in momentary resilience under stress coinciding with reductions in HRV [ 51 ].
Twenty-one studies observed HRV responses from a baseline resting period to a subsequent stress exposure with seventeen studies observing a decrease in HRV see Table 1. From rest to during the stress exposure, time and non-linear domain HRV metrics consistently showed reductions i.
time domain metrics RMSSD, SDNN, PNN50 and non-linear metrics SD1, SD2 [ 5 , 23 , 28 , 29 , 46 , 53 , 54 , 55 , 56 , 58 , 59 , 60 , 61 , 62 , 66 ]. Frequency domain variables showed less consistency with LF, LF n. TP and HF appeared more consistent with both measures showing reductions [ 28 , 53 , 63 , 65 ], or no change [ 52 , 57 , 63 ] from rest to stress.
Of the stressors, both physical and cognitive stressors elicited a reduction in HRV from baseline to during the exposure period [ 53 , 58 , 59 ]. Twenty studies looked at baseline and during stressor HRV compared to immediately post stressor measures see Table 2.
From stress to immediately post stressor, ten of eleven studies observed increases in time domain metrics of HRV [ 23 , 24 , 46 , 52 , 56 , 58 , 59 , 60 , 61 , 65 ].
Only two studies reported frequency domain metrics between stress and immediately post stressor, which did not mimic each other [ 52 , 65 ].
Mixed results were observed in time and frequency domain measures when comparing baseline HRV to immediately post stressor. Stressors of a greater magnitude induced a greater suppression of LF and HF [ 76 ]. Six studies observed changes in HRV post exposure to a single stressor see Table 3.
Frequency domain metrics mirrored time domain metrics for the most part, with the exception of one study [ 72 ]. Dussalt et al. Six studies monitored HRV across repeated stress exposures with five of the studies observing increases in HRV across those exposures see Table 4.
Increases in time domain and non-linear domain metrics coincided with markers of physical adaption [ 79 , 81 ], for example increased predicted VO 2 max [ 32 ], and the completion of military and police training courses [ 31 , 32 , 80 ].
Reductions in SDNN, LF and HF were observed post a six-month peacekeeping mission of Bulgarian soldiers in Kosovo, which were also lower when compared to healthy control subjects [ 82 ]. HF showed consistent increases in both supine and standing conditions with markers of physical adaptation and course completions [ 31 , 32 , 79 ] except in one instance [ 79 ].
appeared more sensitive in the supine position with increases in HF n. The majority of work that has utilised HRV has been in the context of acute single-stressor exposure see Tables 1 , 2 , 3 ; with only six studies measuring HRV in response to repeat stressor exposure see Table 4.
The rate of HRV restoration to baseline levels appears to be dependent on the magnitude of the stressor endured. For singular stressors, individuals of greater HRV repeatedly exhibited better decision-making performance in occupational tasks [ 5 , 24 , 38 , 46 , 49 ]. With only six studies monitoring HRV with repeated stressor exposure, more research is required to determine the chronic effects of stress and allostatic load on health and performance, and the relationships with HRV.
While greater consistency in results was observed for time domain indices of HRV, the greater coefficient of variation of frequency domain metrics and their ratio values [ 83 ] requires greater participant numbers to determine their utility.
It is recommended that future research recruit larger sample sizes appropriate for the metrics being assessed. In the transition from baseline to stress exposure in exercise and cognitive tasks, the expected response is a decrease in HRV as a result of parasympathetic withdrawal and sympathetic activation [ 84 , 85 ].
This matches the uniform reduction in time RMSSD, SDNN and PNN50 and non-linear domain metrics SD1 and SD2 observed in Table 1 , while frequency domain metrics showed mixed results.
The frequency domain findings may be partially due to five of the seven studies that reported no change in frequency domain metrics recruited less than 20 participants.
Of the time domain metrics that recorded no change in HRV, four of five studies also had less than 20 participants indicating that a lack of power may be present in determining frequency domain HRV responses.
Three studies reported conflicting results identifying increases or no changes in RMSSD from rest to stress in soldiers and navy personnel [ 24 , 63 , 64 ].
This response may be explained by the presence of an anticipatory anxiety response, which has been observed elsewhere in tennis [ 86 ], where the cognitive anticipation of the task elicits a physiological stress response prior to commencement of the task, lowering baseline HRV [ 24 , 63 , 64 ].
The reduced HRV at baseline, due to parasympathetic downregulation, was either maintained or elevated once the task commenced and HRV increased in the period after the completion of the task due to the removal of sympathetic stimulation [ 24 , 63 , 64 , 87 ].
The reduced parasympathetic activity at baseline is a prefrontal cortex response to regulate arousal that is followed by an increase sympathetic activity once the physical exertion task commences involving the baroreflex mechanism [ 88 ]. This response may be more relevant and prevalent in military and law enforcement personnel than general population individuals [ 63 ] due to their exposure to potentially fatal scenarios.
This response also demonstrates HRV being sensitive to non-physical stressors. Additionally, in solely cognitive tasks, several studies have observed a decrease in HRV in transition from rest to the cognitive stressor [ 5 , 24 , 40 , 49 , 56 ]. These findings are further supported by studies demonstrating a negative association between HRV and increasing subjective job stress [ 89 , 90 ] highlighting the impact of psychological stress on HRV.
Therefore, individuals implementing HRV as a method for ongoing monitoring of personnel need to be aware of the factors influencing HRV when trying to interpret the data. When transitioning from a stressor to the subsequent recovery period, increases in time domain HRV were observed in the majority of studies see Table 2.
This response is expected and consistent with responses to exercise [ 85 ] and cognitive stress [ 87 ] due to sympathetic withdrawal and parasympathetic reactivation [ 91 ].
In police recruits and military soldiers, increasingly stressful and complex tasks showed a greater reduction in RMSSD and SDNN [ 40 , 41 , 46 ], which is consistent with responses to exercise in athletic populations [ 92 ]. In addition, physical stressors of greater magnitude caused a more delayed restoration of HR and HRV metrics which influences post stressor HRV [ 93 ].
Therefore, consideration of the stressor magnitude and any anticipatory anxiety response occurring at baseline need to be considered when comparing baseline to post stressor measurements of HRV. It is clear that HRV predominantly trends towards greater variability with the cessation of the stressor.
As time domain metrics demonstrated greater consistency over frequency domain metrics in these studies, they would appear a more suitable option as markers of acute stress in the occupational setting currently.
Frequency domain measures have received less exploration within these studies with some utilising low participant numbers which may mask any responses that may be present as they exhibit larger coefficients of variation [ 83 ].
Future research should look to investigate frequency domain variable responses with greater participant numbers in the acute stressor setting. Recordings of HRV after a single stressor exposure ranged from 15 min to 3 days post stressor.
Only two studies observed HRV at the same time intervals post stressor, complicating study comparisons see Table 3. However, it is clear that the removal of the stressful stimuli results in a gradual return of HRV metrics to baseline levels [ 30 , 54 , 62 , 72 , 78 ].
The rate of return of HRV to baseline appears to be dependent on the magnitude of the stressor individuals were exposed to. Typically, frequency ratio values exhibit greater variation the frequency domain variables [ 83 ]. As this study utilised twelve consecutive, five-minute segments to analysis both baseline and during shift HRV, greater variations in LF and HF occurred throughout the 2 h while proportions of sympathetic and parasympathetic activation remained similar [ 52 ].
Therefore, the use of ratio metrics such as LF n. What should be taken from these studies is that HRV appears sensitive to the magnitude of stressors experienced in first responders and tactical operators that can indicate the residual stress on individuals after occupational tasks, and potential readiness for subsequent tasks or shifts.
Of particular interest to tactical operators and first responders is the relationship between HRV and occupational performance. Soldiers and navy personnel with greater HRV, both at rest and under stress, exhibited better performance in decision making and cognitive tasks, for example threat discrimination shooting tasks [ 5 , 24 , 38 , 40 , 49 ].
An essential requirement of these occupations is decision making in highly stressful scenarios. In particular Head et al. identified an increased error of commission in shooting responses i. shooting when it is incorrect of mentally fatigued individuals who exhibited lower HRV; however, no changes were seen in shot accuracy or error of omission, i.
incorrectly not shooting [ 5 ]. This poses as an issue as the mentally fatigued individuals with lower HRV maintained their lethality, as demonstrated by their accuracy, when shooting at incorrect targets.
In sport, scenarios requiring decisions of greater consequence, that are indicative of higher anxiety, have been shown to impair decision making performance [ 94 ] which may be particularly relevant to this target rich shooting task. It may indicate that HRV could be used as a potential identifier of poorer decision-making capacity in this context.
Observations into the performance of different cognitive tasks have identified different HRV responses occur irrespective of physical exertion, highlighting the complex and dynamic interplay of parasympathetic and sympathetic activity that is required [ 88 , 95 ]. In addition, emotional and behavioural responses to situations can alter the level of stress depicted by HRV, highlighting inter-individual differences in stress responses [ 39 , 50 , 67 ].
While HRV may provide great utility in managing first responders and tactical personnel, each of these studies examined decision making or cognitive performance at a single timepoint that may be affected by these inter-individual differences. Future research would benefit from investigating whether within subject changes in HRV could predict changes in these performance outcomes.
Nevertheless, it indicates a relationship between the two variables that may render HRV as a useful monitoring tool for cognitive performance capacity in these occupations if supported by future studies adopting within subject designs.
Of the studies that met the inclusion criteria, fifty-eight of the sixty studies involved tasks that contribute to fatigue as a result from stressors and potentially inadequate recovery. In contrast, two papers reported the opposing response whereby fatigue results from passive driving and piloting tasks that exhibit a lack of stimulation [ 30 , 48 ].
Tasks of long duration may lead to increased parasympathetic activation acting as a calming response as increases in time on task are associated with increased subjective fatigue and HRV [ 96 ]. These effects may be particularly prevalent in nocturnal shift work in which greater HRV was accompanied by increased ratings of sleepiness that could compromise occupation performance [ 22 , 43 ].
While this review is focusing on HRV responses to sympathetic stressors it is important to consider the opposing response in which HRV may provide a useful monitoring tool for passive fatigue that results from certain driving and piloting tasks in these occupations.
Further research should investigate the utility of HRV to mitigate the risk of fatigue related accidents. In summary, using HRV as a measure to monitor acute allostatic load following exposure to a single acute stressor appears suitable with a few key considerations.
It has shown to be sensitive to both physical [ 53 ] and cognitive stressors [ 40 ], and provides an indication of the magnitude of stress exposure or internal stress on an individual.
The rate of recovery of HRV metrics post stimulus appears to provide an indication of the changes in strain over time, which can be useful for monitoring recovery in first responders and tactical personnel.
Currently, it appears that more consistent responses are seen in time RMSSD, SDNN and PNN50 and non-linear domain metrics SD1 and SD2 of HRV compared with frequency domain measures in response to an acute stressor.
However, further investigations into frequency domain measures are warranted as low participant numbers were utilised in papers that observed no changed in these metrics. Furthermore, HF power showed the greatest consistency in HRV changes between baseline and immediately post stressor, which aligned with RMSSD.
From the six studies reporting on HRV responses to repeat stressor exposure there is insufficient data available to determine whether HRV is an appropriate measure of physiological status in first responders and tactical operators.
To date, only one study has assessed daily resting HRV with changes in other markers of stress to give a depiction of what these daily changes mean [ 79 ]. This can make potential explanations difficult and highlights that further research into the suitability of HRV as a repeated resting measure of allostatic load and physiological status is still required if it is to be used as a monitoring tool.
Of the six studies that reported on repeat stress events, four of these studies reported increases in time domain HRV indices RMSSD, SDNN, RRi and PNN50 [ 31 , 32 , 79 , 80 ]. These studies identify HRV increases at the completion of a training period or course [ 31 , 32 , 79 , 80 ] and some are identified with other markers of physical adaption i.
increases in cardiorespiratory fitness and the testosterone to cortisol relationship [ 32 , 79 ]. Increases in HRV have been observed with increases in cardiorespiratory fitness in these populations indicating an adapted state [ 35 , 36 , 67 ].
Increases in HRV observed at the completion of training courses may be due to the reduced allostatic load as a result of the course completion, similar to the responses observed in the acute setting.
In contrast, decreases in HRV were observed in Bulgarian soldiers returning from a six-month peacekeeping mission [ 82 ].
The cause of this response in unknown but may involve some aspects of stress with returning home or potential reductions in cardiorespiratory fitness [ 97 ].
The lack of research repeatedly measuring HRV across these programs leaves these hypotheses to be further tested. Decreases in testosterone are normally associated with increased fatigue and poor recovery which is the opposite of what is expected of increased HRV [ 10 , 33 ].
Looking at a more granular data set investigating soldier HRV responses to exercise and altitude acclimatisation, a reduction and subsequent super compensatory increase in some HRV indices were observed over a three-day period [ 81 ]. Due to a low number of participants and the inter-individual variation in HRV indices, only some variables show significant changes, however similar responses have been observed in sport settings [ 98 ] and with increasing altitude exposure [ 99 ].
These findings suggest that there may be a more complex HRV response following repeat stressor exposures than what is observed in the acute stressor setting, and further research is required to better understand this response.
In summary, the use of HRV to monitor acute stress and recovery responses to tasks of first responders and tactical operators appears sensitive and suitable. Research into the suitability of HRV as a monitoring tool of chronic allostatic load in first responders and emergency service personnel is currently not sufficient for inferences to be made.
Future research should look to repeatedly assess HRV with sufficient power in these environments along with other markers of physical, psychological and cognitive stress to determine whether HRV can be used as a viable marker of allostatic load in these contexts. Understanding how HRV relates to job specific performance in a within subject design is also required.
Current evidence shows that it is important that practitioners looking to use HRV need to be conscious of the manner and context in which it is recorded when interpreting results.
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Do existing measures of Poincare plot geometry reflect nonlinear features of heart rate variability? IEEE Trans Biomed Eng. Roberts SSH, Teo W-P, Warmington SA. Effects of training and competition on the sleep of elite athletes: a systematic review and meta-analysis. As well as significant daily drops in HRV during the week, his overall baseline also reduced without having done any training.
In dealing with this stress we reduce our ability to adapt and recover from training. Nutritionally, one of the most common factors driving chronic inflammation is an imbalance between Omega-3 and Omega-6 fat sources, with the latter being both more common in a pro-inflammatory processed food diet.
The answer could be to increase dietary quantities of Omega-3 fats, preferably from wild fatty fish; farmed fatty fish has very little Omega-3 due to its altered diet.
Trans-fats are also known to be pro-inflammatory and are found in foods such as pastries, doughnuts, margarine, and other snack foods. Foods that reduce inflammation include fruits especially berries and green vegetables, olive oil, ginger, garlic, turmeric, organic meat and fish, and green tea.
Studies have also shown the Mediterranean diet to be associated with higher levels of HRV and overall health. In this article, we reviewed mechanisms and evidence that nutritional practices common amongst age group athletes create a stress load that the body has to bear in addition to training.
This extra load delays recovery and prevents the athlete from training as hard and effectively as they might to gain maximum adaptations and performance. The good news is that all of these factors are relatively easily managed, and that regular HRV monitoring provides an overall health barometer to help identify what is working.
In the final part of this series, we will be looking at how sleep or more commonly, the lack of it contributes to total load in the athlete.
The next article in this five-part series will take a closer look at how sleep contributes to total load. Four hours after active dehydration heart rate variability and resting metabolic rate were re-assessed T2. showed a significant reduction in heart rate variability.
More so, the change in resting metabolic rate was significantly higher in dehydration group compared to rehydration group. Discussion: Hydric homeostasis after exercise affects resting metabolic rate and heart rate variability, highlighting the necessity to control hydration state before resting metabolic rate and heart rate variability assessment.
Introducción: La variabilidad del ritmo cardiaco y la tasa metabólica basal se utilizan en evaluaciones de deportistas.
Variabipity Autonomic nervous Vitamin B and fat metabolism ANS RMR and heart rate variability an heagt role rwte the exchange of metabolic information between organs and regulation on peripheral metabolism with Injury nutrition plan variabipity rhythm in a healthy state. Injury nutrition plan, a vital brain phenomenon, significantly affects both ANS and metabolic function. Objectives: Injury nutrition plan study hdart the relationships among sleep, ANS and metabolic Wound healing diet in type 2 diabetes mellitus T2DMto support the evaluation of ANS function through heart rate variability HRV metrics, and the determination of the correlated underlying autonomic pathways, and help optimize the early prevention, post-diagnosis and management of T2DM and its complications. Materials and methods: A total of 64 volunteered inpatients with T2DM took part in this study. Conclusions: HRV metrics during sleep period play more distinct role than during awake period in investigating ANS dysfunction and metabolism in T2DM patients, and sleep rhythm based HRV analysis should perform better in ANS and metabolic function assessment, especially for glycemic control in non-linear analysis among T2DM patients. Type 2 diabetes mellitus T2DM is a chronic hyperglycemia that causes physiological dysfunction and failure of various organs.
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