ArticleSensors (Basel, Switzerland)2021
Diurnal Physical Activity Patterns across Ages in a Large UK Based Cohort: The UK Biobank Study.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Not just how much, but how it's done: movement activity bout distributions and everyday cognition in older adults with elevated dementia risk.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2026Article
- Circadian physiology changes with aging: age is just a number, but circadian physiology keeps time.Current opinion in physiology · 2026Article
- Physical activity and DNA methylation-based markers of ageing in 6208 middle-aged and older Australians: cross-sectional and longitudinal analyses.GeroScience · 2025Article
- Age- and sex-related differences in sleep patterns and their relations to self-reported sleep and mood.Sleep advances : a journal of the Sleep Research Society · 2025Article
- "International journal of environmental research and public health · 2023Article
- Can genetics guide exercise prescriptions in osteoarthritis?Frontiers in rehabilitation sciences · 2022Article
- Registration of 24-hour accelerometric rest-activity profiles and its application to human chronotypes.Biological rhythm research · 2022Article
- Clustering Accelerometer Activity Patterns from the UK Biobank Cohort.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The ability of individuals to engage in physical activity is a critical component of overall health and quality of life. However, there is a natural decline in physical activity associated with the aging process. Establishing normative trends of physical activity in aging populations is essential to developing public health guidelines and informing clinical perspectives regarding individuals' levels of physical activity. Beyond overall quantity of physical activity, patterns regarding the timing of activity provide additional insights into latent health status. Wearable accelerometers, paired with statistical methods from functional data analysis, provide the means to estimate diurnal patterns in physical activity. To date, these methods have been only applied to study aging trends in populations based in the United States. Here, we apply curve registration and functional regression to 24 h activity profiles for 88,793 men (N = 39,255) and women (N = 49,538) ages 42-78 from the UK Biobank accelerometer study to understand how physical activity patterns vary across ages and by gender. Our analysis finds that daily patterns in both the volume of physical activity and probability of being active change with age, and that there are marked gender differences in these trends. This work represents the largest-ever population analyzed using tools of this kind, and suggest that aging trends in physical activity are reproducible in different populations across countries.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.