Sleep quality and duration are associated with performance in maximal incremental test

Antunes, Bárbara de Moura Mello; Campos, Eduardo Zapaterra; Parmezzani, S. S.; Santos, Ronaldo Vagner Thomatieli dos; Franchini, Émerson; Lira, Fábio Santos

doi:10.1016/j.physbeh.2017.05.014

Cited by 31 publications

(19 citation statements)

References 25 publications

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“…A decrease in maximal oxygen uptake measured in an incremental maximal exercise test due to a shorter duration of sleep as well as lower quality of sleep was previously reported. 44 The researchers reported oxygen uptakes of 44-59mL•Kg -1 •min -1 , which are comparable with the results of this study. 44 The result of this study show that for the most part, subjects were able to achieve slightly higher HRmax values, which could be explained by the fact that they were somewhat younger in age.…”

Section: Discussionsupporting

confidence: 90%

“…44 The researchers reported oxygen uptakes of 44-59mL•Kg -1 •min -1 , which are comparable with the results of this study. 44 The result of this study show that for the most part, subjects were able to achieve slightly higher HRmax values, which could be explained by the fact that they were somewhat younger in age. 44 In a study from 2017, recovery was influenced for the worse by one night of partial sleep deprivation.…”

Section: Discussionsupporting

confidence: 90%

“…44 The result of this study show that for the most part, subjects were able to achieve slightly higher HRmax values, which could be explained by the fact that they were somewhat younger in age. 44 In a study from 2017, recovery was influenced for the worse by one night of partial sleep deprivation. Although subjects were cyclists and older in age, as well as the exercise test being a HIIT session, recovery was impaired twenty-four hour post (Appendix A).…”

Section: Discussionmentioning

confidence: 64%

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The effects of partial sleep deprivation and the maximal ndks exercise testing protocol on s-klotho, maximal oxygen uptake, and hemodynamic responses in young men

Sciamama-Saghiv¹,

Welch²,

Goldhammer³

et al. 2019

SMDIJ

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Purpose: The purpose of the study was to examine the influences of partial sleep deprivation on young healthy trained men's responses to the maximal NDKS exercise testing protocol. Methods: 33 males 21.2±2.31 years of age, volunteered to participate in this study. Subjects underwent two maximal NDKS exercise tests, once after 7-8hours of sleep, and once after staying awake for 20hours. S-Klotho, blood pressure, and heart rate were obtained at baseline, immediate-post, and post a dynamic recovery of 15minutes. Oxygen uptake was measured throughout exercise. Results: Significant differences were found between S-Klotho values at baseline and immediate-post of PSD and NPSD (463.31±64.18vs 651.17±70.81 pg•mL-¹, F(1,65) = 33.45, p = 0.01 and 463.31±64.18vs 727.14±81.3 pg•mL-¹, F(1,65) = 38.06, p = 0.01 respectively). Significant differences were found between conditions regarding PSD immediate-post S-Klotho concentration and that of NPSD (651.17±70.81 vs 727.14±80.3 pg•mL-¹, respectively, F(1,65) = 14.648, p = 0.02). Significant differences were found between conditions regarding baselinepost-recovery S-Klotho concentration and PSD(463.31±64.18 vs 522.68±51.98 pg•mL-¹, respectively, F(1,65) = 12.96, p-0.03). Significant differences were found between immediate-post S-Klotho values and postrecovery (PSD: 651.17±70.81 vs 522.68±51.98 pg•mL-¹, F(1,65) = 31.2, p = 0.03) and (NPSD: 727.14±80.3 vs 513.41±55.24 pg•mL-¹, F(1,65) = 34.2, p = 0.02). Conclusion: Partial sleep deprivation induced multiple negative significant differences in S-Klotho concentrations and in some cases, hemodynamic responses as well. Oxygen uptake was significantly lower while partially sleep deprived.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 64%

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The effects of partial sleep deprivation and the maximal ndks exercise testing protocol on s-klotho, maximal oxygen uptake, and hemodynamic responses in young men

Sciamama-Saghiv¹,

Welch²,

Goldhammer³

et al. 2019

SMDIJ

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“…In our study, users were considered to have normal sleep values if their weekly sleep average was less than 0•5 SD below their overall sleep average, as nights of short sleep duration have been shown to result in elevated heart rate the following day. 19,20 We found that our correlations improved slightly when we classified people as displaying normal values when they had low sleep. In the future, improved measurements of stress by wearable devices, either by detection of voice changes or galvanic skin response, could further improve our ability to identify other non-infectious causes of elevated RHR.…”

Section: Discussionmentioning

confidence: 79%

Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study

Radin

Wineinger

Topol

et al. 2020

The Lancet Digital Health

270

211

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Background Acute infections can cause an individual to have an elevated resting heart rate (RHR) and change their routine daily activities due to the physiological response to the inflammatory insult. Consequently, we aimed to evaluate if population trends of seasonal respiratory infections, such as influenza, could be identified through wearable sensors that collect RHR and sleep data. Methods We obtained de-identified sensor data from 200 000 individuals who used a Fitbit wearable device from March 1, 2016, to March 1, 2018, in the USA. We included users who wore a Fitbit for at least 60 days and used the same wearable throughout the entire period, and focused on the top five states with the most Fitbit users in the dataset: California, Texas, New York, Illinois, and Pennsylvania. Inclusion criteria included having a self-reported birth year between 1930 and 2004, height greater than 1 m, and weight greater than 20 kg. We excluded daily measurements with missing RHR, missing wear time, and wear time less than 1000 min per day. We compared sensor data with weekly estimates of influenza-like illness (ILI) rates at the state level, as reported by the US Centers for Disease Control and Prevention (CDC), by identifying weeks in which Fitbit users displayed elevated RHRs and increased sleep levels. For each state, we modelled ILI case counts with a negative binomial model that included 3-week lagged CDC ILI rate data (null model) and the proportion of weekly Fitbit users with elevated RHR and increased sleep duration above a specified threshold (full model). We also evaluated weekly change in ILI rate by linear regression using change in proportion of elevated Fitbit data. Pearson correlation was used to compare predicted versus CDC reported ILI rates. Findings We identified 47 249 users in the top five states who wore a Fitbit consistently during the study period, including more than 13•3 million total RHR and sleep measures. We found the Fitbit data significantly improved ILI predictions in all five states, with an average increase in Pearson correlation of 0•12 (SD 0•07) over baseline models, corresponding to an improvement of 6•3-32•9%. Correlations of the final models with the CDC ILI rates ranged from 0•84 to 0•97. Week-to-week changes in the proportion of Fitbit users with abnormal data were associated with week-to-week changes in ILI rates in most cases. Interpretation Activity and physiological trackers are increasingly used in the USA and globally to monitor individual health. By accessing these data, it could be possible to improve real-time and geographically refined influenza surveillance. This information could be vital to enact timely outbreak response measures to prevent further transmission of influenza cases during outbreaks.

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“…However, these sports and exercise related adverse effects do not result from the sports itself, but from the difficulties in biological clock adjustment due to the aforementioned economic pressure in such branches of sports 21 . It was demonstrated that sleep helped gaining full power after an intensive training session, which was also coined as "You can gain the full power of the sleep-sweat" 22 . Since research on sleep-exercise relationship is generally applied on small populations, power of current evidence with respect to the positive effect of exercise on sleep is being discussed and speculated on a certain extent.…”

Section: Sedentary N=30mentioning

confidence: 99%

Untitled

2019

IJAEP

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There suggested to be a reciprocal relationship between sleep and exercise capacity, as physical activity is considered to be beneficial for improved sleep quality especially in those with sleep problems while adequate sleep increases exercise capacity and reduces risk of exercise-induced injuries. But the exact mechanism of this relationship and whether being engaged with every kind of sport branch is beneficial to sleep quality is not clear yet. Yet, the demands and expectations from modern people including elite athletes have placed increasing demands by cutting back on sleep despite scientific research is revealing that sufficient sleep is critical for safety, performance and productivity and the cost of insufficient sleep is well beyond than most people recognize. The aim of this study was to investigate profiles of sleep quality in rowing athletes. For this purpose, profiles of sleep quality, both objectively and subjectively assessed in 30 elite male rowing athletes (mean age 19.36±4.1 years) and age (22.20±2.5 years) and gender-matched non-athlete sedentary control individuals. Subjective sleep quality was evaluated using the the Pittsburgh Sleep Quality Index (PSQI); while a metabolic holter (SenseWear armband) was used for obtaining objective sleep quality related parameters. Independent ttest was used for comparing sleep quality between the group means. Statistical significance was set at p<0.05. In elite rower athletes, the means of sleep duration (according to metabolic holter: 442±56 min; according to PSQI: 449±37, p>0.05) and sleep efficiency [(in athletes 85.5±5.0%; in sedentary group 75.9±8.5 % (n=30)] (P<0.05) was better than sedantery individuals. The findings of the present study indicate that both objective and subjective sleep quality of elite rowers was significantly better than non-athlete sedentary controls.

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Sleep quality and duration are associated with performance in maximal incremental test

Cited by 31 publications

References 25 publications

The effects of partial sleep deprivation and the maximal ndks exercise testing protocol on s-klotho, maximal oxygen uptake, and hemodynamic responses in young men

The effects of partial sleep deprivation and the maximal ndks exercise testing protocol on s-klotho, maximal oxygen uptake, and hemodynamic responses in young men

Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study

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