The effect of physical activity timing on insomnia and sleep quality: a randomized cross-over trial in older adults
Albalak, G.; Noordam, R.; van der Elst, M.; Drop, T.; Caneda Cabrera, E.; Oudendijk, L.; Lammers, G. J.; Gordijn, M.; Kervezee, L.; Exadaktylos, V.; van Bodegom, D.; van Heemst, D.
Show abstract
Background Insomnia symptoms are common in older adults. While observational studies suggest physical activity (PA) timing affects health outcomes, its effect on sleep remains unclear. We compared morning versus evening PA effects on insomnia severity and sleep quality in older adults with insomnia symptoms. Methods Eligible participants were aged 60 to 80 years with (sub)clinical insomnia (Insomnia Severity Index [ISI] score [≥]10). In a randomized cross-over trial, participants engaged in coached PA in the morning (10:00 - 11:00) or evening (19:30 - 20:30) for 14 days each. ISI scores were assessed post-intervention. Objective sleep parameters; duration, latency, efficiency, and timing, were assessed with a Withings Sleep Analyzer under the mattress. Subjective sleep quality was reported daily via smartphone app. Salivary dim light melatonin onset (DLMO) was measured on the final day of each intervention. Results Of 37 participants (mean ISI 14.3 {+/-} 3.3), 27 completed the study (mean age 69.8 {+/-} 5; 63% women). ISI scores improved after both morning ({Delta} - 2.5; 95% CI: - 1.14, - 3.83) and evening ({Delta} - 2.0; 95% CI: - 0.63, - 3.38) activity relative to baseline, but were not different between interventions. Compared to evening activity, sleep midpoint occurred earlier with morning activity (03:40 vs 04:00; {Delta} - 20 min; 95% CI: - 31, - 8). No differences in subjective sleep quality or DLMO were found. Exploratory analyses suggested insomnia scores improved specifically in late chronotypes following morning activity. Conclusions While morning vs. evening PA timing did not impact most sleep quality measures, it influenced sleep timing. Larger studies are needed to define optimal and personalized PA timing for improving sleep.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Changes of evening exposure to electronic devices during the COVID-19 lockdown affect the time course of sleep disturbances 96%
- Light Enhanced Cognitive Behavioral Therapy (CBT + ) for Insomnia and Fatigue During Chemotherapy for Breast Cancer: A Randomized Controlled Trial 95%
- Performance of an Electroencephalography-Measuring Headband or Actigraphy Compared with Polysomnography in Older Adults with Sleep Disturbances 95%
Similar papers in this journal
- Sleep improvement for metabolic health: A feasibility trial of a digital sleep treatment in people with insomnia and non-diabetic hyperglycaemia. 96%
- The effects of daylight saving time clock changes on accelerometer-measured sleep duration in the UK Biobank 95%
- Sleeping under the waves: a longitudinal study across the contagion peaks of COVID-19 pandemic in Italy 95%
Similar papers in this journal
- Home-EEG assessment of possible compensatory mechanisms for sleep disruption in highly irregular shift workers - The ANCHOR study 97%
- A clinical trial to evaluate the dayzz smartphone app on employee sleep, health, and productivity at a large US employer 95%
- Sleep does not influence schema-facilitated motor memory consolidation 94%
Similar papers in this journal
- Methodological approach to sleep state misperception in insomnia disorder: comparison between multiple nights of actigraphy recordings and a single night of polysomnography recording 97%
- Effects of cognitive behavioral therapy for insomnia on subjective and objective measures of sleep and cognition 96%
- Effects of mindfulness meditation and Acceptance and Commitment Therapy in patients with obstructive sleep apnea with residual excessive sleepiness: A randomized controlled pilot study 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.