A multimodal analysis of physical activity, sleep, and work shift in nurses with wearable sensor data.
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ABSTRACT:
SUBMITTER: Feng T
PROVIDER: S-EPMC8062546 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In the present study, we sought to determine the degree of circadian misalignments of hormonal and transcriptional rhythms with the timing of sleep-wake behavior on days off in day-shift and night-shift hospital nurses. We conducted a genome-wide microarray analysis on RNA isolated from PBMCs to examine individual variability of transcriptional rhythms.
2019-01-01 | GSE122541 | GEO
Project description:PurposeThis study sought to assess the performance of the Fitbit Charge HR, a consumer-level multi-sensor activity tracker, to measure physical activity and sleep in children.Methods59 healthy boys and girls aged 9-11 years old wore a Fitbit Charge HR, and accuracy of physical activity measures were evaluated relative to research-grade measures taken during a combination of 14 standardized laboratory- and field-based assessments of sitting, stationary cycling, treadmill walking or jogging, stair walking, outdoor walking, and agility drills. Accuracy of sleep measures were evaluated relative to polysomnography (PSG) in 26 boys and girls during an at-home unattended PSG overnight recording. The primary analyses included assessment of the agreement (biases) between measures using the Bland-Altman method, and epoch-by-epoch (EBE) analyses on a minute-by-minute basis.ResultsFitbit Charge HR underestimated steps (~11.8 steps per minute), heart rate (~3.58 bpm), and metabolic equivalents (~0.55 METs per minute) and overestimated energy expenditure (~0.34 kcal per minute) relative to research-grade measures (p< 0.05). The device showed an overall accuracy of 84.8% for classifying moderate and vigorous physical activity (MVPA) and sedentary and light physical activity (SLPA) (sensitivity MVPA: 85.4%; specificity SLPA: 83.1%). Mean estimates of bias for measuring total sleep time, wake after sleep onset, and heart rate during sleep were 14 min, 9 min, and 1.06 bpm, respectively, with 95.8% sensitivity in classifying sleep and 56.3% specificity in classifying wake epochs.ConclusionsFitbit Charge HR had adequate sensitivity in classifying moderate and vigorous intensity physical activity and sleep, but had limitations in detecting wake, and was more accurate in detecting heart rate during sleep than during exercise, in healthy children. Further research is needed to understand potential challenges and limitations of these consumer devices.
| S-EPMC7473549 | biostudies-literature
Project description:BackgroundShift work has been hypothesized as a risk factor for obesity. In this study, we investigated the association between current shift work and body mass index (BMI) among female nurses in Korea. The relationship between duration of shift work and BMI of the participants was also evaluated.MethodsThis cross-sectional survey evaluated participants in the Korean Nurses' Survey, conducted from October to December 2011, using web-based self-administered questionnaires. A total of 9,989 nurses were included among 10,000 who registered on the survey web site (5,287 shift workers and 4,702 non-shift workers). Current shift workers were divided into tertiles of shift work duration (0.08-3.00 years, n = 1,732; 3.08-6.75 years, n = 1,731; and 6.83-38.00 years, n = 1,686). The BMI thresholds of overweight and obesity were ?23 kg/m² and ?25 kg/m², respectively. Data were analyzed using SPSS software.ResultsMean participant age was 33.2 ± 8.6 years and the mean BMI was 20.9 ± 2.5 kg/m². There were statistically significant differences in current smoking status, regular drinking habit, dietary habits, regular exercise, sleep problems and self-perceived health status according to duration of shift work. The overall prevalence of overweight/obesity (18.6%) and obesity (7.4%) increased significantly as shift work duration increased from the lowest to highest tertile (P for trend <0.001). Multivariate logistic regression analysis revealed no association between current shift work and BMI. However, after adjusting for potential confounders, the participants with the longest duration of shift work were 1.63 (95% CI, 1.22-2.17) times more likely to be overweight or obese than those with the shortest duration. There was a significant positive association between obesity and shift work duration in the unadjusted analysis; however, it was attenuated and no longer significant in the multivariate model.ConclusionsThe duration of shift work was positively associated with prevalence of overweight/obesity in nurses in Korea. Although these findings need to be confirmed in prospective studies, they suggest that special attention should be paid to female nurses with a long duration of shift work.
| S-EPMC3878177 | biostudies-literature
Project description:This study aimed to evaluate the effectiveness of supervised exercise among nurses conducting shift work for health promotion.A total of 30 healthy female nurses conducting shift work participated in this study and they were randomly assigned to one of the following 2 groups: The supervised exercise group (SG; participants exercised under the supervision of a physical therapist (PT)) and the voluntary exercise group (VG; participants exercised without supervision). The study participants were asked to exercise twice/week for 12 weeks for 24 sessions. The primary outcome was aerobic fitness, and the secondary outcomes were muscle strength, anthropometric data, biochemical parameters, and mental health. We compared all the outcomes before and after the intervention within each group and between both groups at follow-up.Aerobic fitness increased in the SG whereas it decreased in the VG, but these changes were not statistically significant (p=0.053 and 0.073, respectively). However, the between-group difference was significant in the intervention effect (p=0.010). Muscle strength, high-density lipoprotein cholesterol and metabolic profile (high-molecular weight adiponectin), and depressive symptom significantly improved in the SG over time, even though the SG exercised less as compared with the VG. Moreover, significant differences in muscle strength, and low-density lipoprotein cholesterol and reactive oxygen metabolite levels were observed between both groups, and these parameters were better in the SG than in the VG.Our data-suggest the effectiveness of exercise supervised by a PT at the workplace of nurses conducting shift work for health promotion.
| S-EPMC5557819 | biostudies-other
Project description:BackgroundSleepiness associated with night shift working (NSW) is known to adversely affect workers' health and well-being. It has been associated with adverse safety outcomes and is a recognized workplace hazard among healthcare workers.AimsThis study was aimed to assess the prevalence of self-reported sleepiness in NSW nurses and midwives. This study also explored the consequences of sleepiness on safety at work and driving.MethodsA cross-sectional study of NSW nurses and midwives was conducted at an National Health Service (NHS) hospital trust from 16 March 2020 to 1 June 2020. Data were collected by online questionnaire and included information on demographics, shift work and safety aspects. Sleepiness was assessed with the Epworth Sleepiness Scale (ESS).ResultsData collection coincided with the first coronavirus pandemic peak in England. Out of 1985 eligible NSW nurses and midwives, 229 participated in the study, with a response rate of 12%. The prevalence of sleepiness was 28%. Following a night shift, 49% of nurses reported nodding off at the wheel and 44% reported a near-miss car accident in past 12 months. An abnormal ESS score was significantly associated with near-miss car accidents (odds ratio [OR] 2.75, 95% confidence interval [CI] 1.31-5.77) and with low confidence in undertaking complex tasks at night (OR 2.64, 95% CI 1.20-5.84).ConclusionsMore than a quarter of NSW nurses and midwives reported excessive daytime sleepiness although, due to the low response rate, this may not be representative. Adverse driving events were common. Elevated ESS scores correlated well with safety issues relating to work and driving.
| S-EPMC8574312 | biostudies-literature
Project description:BackgroundNight shift work is associated with cardiovascular disease, but its associations with cardiovascular disease biomarkers are unclear. We investigated these associations in a study of female nurses.MethodsWe used data from the Nurses' Health Study II for total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, C-reactive protein (CRP), and fibrinogen. The sample sizes for our analysis ranged from 458 (fibrinogen) to 3574 (total cholesterol). From questionnaires, we determined the number of night shifts worked in the 2 weeks before blood collection and total years of rotating night shift work. We used quantile regression to estimate differences in biomarker levels by shift work history, adjusting for potential confounders.ResultsNurses working 1 to 4 recent night shifts had median HDL cholesterol levels 4.4 mg/dL (95% confidence interval [CI]: 0.3, 7.5) lower than nurses without recent night shifts. However, working ≥5 recent night shifts and years of rotating night shift work were not associated with HDL cholesterol. There was no association between recent night shifts and CRP, but median CRP levels were 0.1 (95% CI: 0.0, 0.2), 0.2 (95% CI: 0.1, 0.4), and 0.2 (95% CI: 0.0, 0.4) mg/L higher among nurses working rotating night shifts for 1 to 5, 6 to 9, and ≥10 years compared with nurses never working rotating night shifts. These associations were attenuated when excluding postmenopausal women and women taking statins. We observed no associations between night shift work and other biomarkers.ConclusionsWe found suggestive evidence of adverse short-term and long-term effects of night shift work on select cardiovascular disease biomarkers.
| S-EPMC8572536 | biostudies-literature
Project description:Objectives: Shift work is associated with several negative health effects. The underlying pathophysiological mechanisms are unclear, but low-grade inflammation has been suggested to play a role. This project aimed to determine whether levels of immunological biomarkers differ depending on work schedule, self-reported sleep duration, self-reported sleep quality, and presence of shift work disorder (study 1). Furthermore, we aimed to determine whether these biomarkers differ after a night of sleep vs. at the end of a night or a day shift (study 2). Methods: In study 1, 390 nurses provided blood samples after a night of sleep with the dried blood spot method. In study 2, a subset of 55 nurses also provided blood samples after a day shift and after a night shift. The following biomarkers were measured: interleukin-1alpha, interleukin-1beta, interleukin-4, interleukin-6, interleukin-8, interleukin-10, interleukin-13, monocyte chemoattractant protein-1, interferon-gamma, and tumor necrosis factor-alpha. Multiple linear regressions with adjustment for age, sex and body mass index (study 1) and ANOVAs with repeated measures (study 2) were conducted. Results: In study 1, neither work schedule, number of night shifts, number of quick returns (<11 h between consecutive shifts), sleep duration, poor sleep quality, nor shift work disorder were systematically associated with most of these biomarkers. Compared with day only work, day-evening work was associated with higher levels of IL-1alpha and IL-13, quick returns were associated with higher levels of IL-1beta and MCP-1, short sleep duration (<6 h) was associated with lower levels of IL-1beta and higher levels of TNF-alpha, and long sleep duration (8+ h) was associated with higher levels of IL-13. In study 2, IL-1beta levels were higher (large effect size) both after a day shift (14% increase) and a night shift (75% increase) compared with levels after a night of sleep. Similarly, TNF-alpha levels were higher (moderate-large effect size) after a day shift (50% increase) compared to after a night of sleep. In contrast, MCP-1 levels were lower (large effect size) both after a day shift (22% decrease) and a night shift (12% decrease) compared with after a night of sleep. Conclusions: We found some indications that shift work influenced immunological biomarkers. The results should be interpreted with caution due to limitations, e.g., related to the sampling procedure and to low levels of biomarkers in the blood samples.
| S-EPMC7521138 | biostudies-literature
Project description:Shift work can lead to circadian desynchronization due to temporary misalignment between working hours and physiological and behavioral functioning, resulting in compromised health, insomnia, worsening of sleep quality, reduced ability to work during waking hours, and increased cardiovascular risk. We evaluated the effects of shift work on the rest-activity circadian rhythm (RAR) and health status of Italian orthopaedic nurses. The study population was 59 nurses: 44 worked the night shift and 15 worked the day shift. All carried out continuous 5-day actigraphic monitoring to assess RAR, including both the working and the rest period. The rhythmometric analysis showed that, during the working period, the night shift nurses had a significantly lower amplitude than the day shift nurses (p < 0.001), and the acrophase was significantly different between the two groups (p < 0.01). When we stratified the two groups by median body mass index (<25 kg/m2 normal weight and ≥25 kg/m2 overweight), during the working period, we noted a significantly lower amplitude for both the normal weight and the overweight nurses who worked the night shift (p < 0.01 and p < 0.001, normal weight and overweight respectively). The current findings suggest the need for further study of the relationship between activity levels and shift work.
| S-EPMC8391482 | biostudies-literature
Project description:ObjectiveThe current study was conducted to assess the prevalence and associated factors of shift work sleep disorder among nurses working at Ethiopian federal government hospitals in Addis Ababa.MethodsAn institutional-based, cross-sectional study was conducted from April to June 2018 using self-administered structured questionnaires. Computer-generated simple random sampling technique was used to select a total of 422 nurses as study participants. The International Classification of Sleep Disorders - Third Edition, Bargen Insomnia Scale and/or Epworth Sleepiness Scale were used to measure the outcome shift work sleep disorder. Descriptive statistics and bivariate and multivariate binary logistic regression were used. OR with 95%?CI was used to measure the strength of association, and a p value <0.05 was considered statistically significant in multivariate analysis.ResultsAbout a quarter (25.6%) of the study participants have shift work sleep disorder. The average number of nights per month for the last 1?year (adjusted OR=6.3, 95%?CI 3.513 to 12.35) and working in three-shift rotation (adjusted OR=3.1, 95%?CI 1.68 to 5.83) were significantly associated with shift work sleep disorder.ConclusionA quarter of shift worker nurses are suffering from shift work sleep disorder. The number of nights on average per month for the last 1?year and working in three-shift rotation were significantly associated with shift work sleep disorder. Shift working conditions should be improved to provide less stressful conditions for nurses, ensuring at the same time an appropriate quality of care over a 24-hour period. More studies are necessary to better highlight the burden of shift work on the health and well-being of both nurses and patients.
| S-EPMC6720246 | biostudies-literature
Project description:Current public health guidelines on physical activity and sleep duration are limited by a reliance on subjective self-reported evidence. Using data from simple wrist-worn activity monitors, we developed a tailored machine learning model, using balanced random forests with Hidden Markov Models, to reliably detect a number of activity modes. We show that physical activity and sleep behaviours can be classified with 87% accuracy in 159,504?minutes of recorded free-living behaviours from 132 adults. These trained models can be used to infer fine resolution activity patterns at the population scale in 96,220 participants. For example, we find that men spend more time in both low- and high- intensity behaviours, while women spend more time in mixed behaviours. Walking time is highest in spring and sleep time lowest during the summer. This work opens the possibility of future public health guidelines informed by the health consequences associated with specific, objectively measured, physical activity and sleep behaviours.
| S-EPMC5962537 | biostudies-literature