Summary Consumer “Smartbands” can collect physiological parameters, such as heart rate (HR), continuously across the sleep–wake cycle. Nevertheless, the quality of HR data detected by such devices and their place in the research and clinical field is debatable, as they are rarely rigorously validated. The objective of the present study was to investigate the reliability of pulse photoplethysmographic detection by the Fitbit ChargeHR™ (FBCHR, Fitbit Inc.) in a natural setting of continuous recording across vigilance states. To fulfil this aim, concurrent portable polysomnographic (pPSG) and the Fitbit’s photoplethysmographic data were collected from a group of 25 healthy young adults, for ≥12 hr. The pPSG‐derived HR was automatically computed and visually verified for each 1‐min epoch, while the FBCHR HR measurements were downloaded from the application programming interface provided by the manufacturer. The FBCHR was generally accurate in estimating the HR, with a mean (SD) difference of −0.66 (0.04) beats/min (bpm) versus the pPSG‐derived HR reference, and an overall Pearson’s correlation coefficient (r) of 0.93 (average per participant r = 0.85 ± 0.11), regardless of vigilance state. The correlation coefficients were larger during all sleep phases (rapid eye movement, r = 0.9662; N1, r = 0.9918; N2, r = 0.9793; N3, r = 0.9849) than in wakefulness (r = 0.8432). Moreover, the correlation coefficient was lower for HRs of >100 bpm (r = 0.374) than for HRs of <100 bpm (r = 0.84). Consistently, Bland–Altman analysis supports the overall higher accuracy in the detection of HR during sleep. The relatively high accuracy of FBCHR pulse rate detection during sleep makes this device suitable for sleep‐related research applications in healthy participants, under free‐living conditions.
Background The lockdown measures implemented to face the 2019 Coronavirus Disease (COVID-19) first wave deeply modified the lifestyle of the Italian population. Despite its efficacy in limiting the number of infections, forced home confinement was paralleled by sleep/wake cycle disruptions, psychological distress and maladaptive coping strategies (i.e., unhealthy behaviours, such as tobacco and alcohol consumption). Under these unprecedented stress conditions, we explored a possible association between poor sleep quality and increased likelihood of engaging in an unhealthy lifestyle. Methods A cross-sectional study was conducted by disseminating an online survey via social networks and e-mail. We collected information on demographics, COVID-19-related data, sleep quality, chronotype, circadian misalignment, and lifestyle before and during the lockdown (i.e., consumption of cigarettes, alcoholic beverages, coffee, hypnotics, comfort food and fresh food; practice of physical activity). A global healthiness score was computed to assess participants’ modifications in lifestyle since the beginning of the lockdown. Results 1297 respondents were included in the study: 414 (31.9%) from Northern Italy, 723 (55.8%) from Central Italy, 160 (12.3%) from Southern Italy. The following variables were found to be significant predictors of the adoption of an unhealthy lifestyle since the beginning of the lockdown: poor sleep quality, high BMI and considering the measures adopted by the government to fight the pandemic as excessive. Living in Northern Italy, instead, was associated with healthier habits compared to living in Central Italy. Conclusions Poor sleepers may represent the share of the general population who paid the highest price for social isolation. Further investigations are required to explore the role of sleep quality assessment in the identification of individuals vulnerable to unhealthy behaviours under stressful conditions.
Adolescents’ conflict between circadian rhythm and early school start time is more pronounced in evening chronotypes, who tend to reduce sleep duration during school days compensating during the free days by oversleeping (i.e., social jetlag). Cumulative weekly sleep debt may impair sport performance, which relies on physical and cognitive skills modulated by sleep. We hypothesized that chronotype predicts sport performance, and that it may interact with the day of the week. Moreover, given the role sleep plays in motor memory consolidation, we tested the hypothesis that school attendance, and the related chronic sleep deprivation, might be detrimental for participants in a training phase. Ninety-three adolescent male basketball players performed multiple free throw sessions ( n = 7880) during both the school and holiday periods. Chronotype and its interaction with the day of the week significantly predicted shooting accuracy when attending school, but not on holidays. Evening types’ performance gradually decreased from Monday to Friday. Participants with a more unstable performance (i.e., who did not complete the acquisition of the free throw motor scheme) worsened their accuracy when attending school. Our results suggest that the impact of chronotype and day of the week on sport performance is related to the presence of an externally imposed sleep/wake schedule and is consistent with evening types’ increased likelihood of experiencing social jetlag. Possibly due to early school start time, attending school worsened the performance of participants in a training phase. Further investigations are required to assess whether reducing the mismatch between biological and social clocks might improve sport performance, along with other aspects of adolescents’ life.
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