The goldilocks days represent optimal time-use to prevent obesity, low physical performance, risk and fear of falling in older adults
Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu časopisecké články
Grantová podpora
22-02392S
Grantová Agentura České Republiky
PubMed
40634482
PubMed Central
PMC12241422
DOI
10.1038/s41598-025-09645-0
PII: 10.1038/s41598-025-09645-0
Knihovny.cz E-zdroje
- Klíčová slova
- Accelerometry, Compositional data analysis, Physical behavior, Posture-specific behavior,
- MeSH
- akcelerometrie MeSH
- cvičení fyziologie MeSH
- index tělesné hmotnosti MeSH
- lidé MeSH
- obezita * prevence a kontrola MeSH
- postura těla MeSH
- sedavý životní styl MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- strach * psychologie MeSH
- tělesná a funkční výkonnost * MeSH
- úrazy pádem * prevence a kontrola MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Česká republika MeSH
This study introduces the concept of the "Goldilocks Day" - the optimal 24-hour time-use of intensity- or posture-specific composition specifically tailored for young-old (65-70 years) and old-old (> 70 years) adults. We aimed (1) to describe optimal 24-hour time-use of compositions for each health outcome, and (2) identify the 'Goldilock Day' for all outcomes together. This approach, involving backwards pivot coordinates (bpcs), we provide a clearer interpretation of physical behavior data, offering practical insights for healthy aging. Data were collected from 309 older adults (65 + years) in Czechia, using accelerometers worn on the non-dominant wrist to assess intensity-specific behaviors (sedentary behavior - SB, light physical activity - LPA, moderate-to-vigorous physical activity - MVPA, and sleep) and on the right thigh and waist to assess posture-specific behaviors (lying, sitting, standing, moving, and walking). Health outcomes included body mass index (BMI), fall risk, fear of falling, and overall physical performance as assessed by the Short Physical Performance Battery. Compositional regression models, based on the bpcs, were used to assess the relationships between time-use and these outcomes. In young-old adults, the time-use composition for optimal BMI included 7.5 h of sleep, 12.0 h of SB, 3.2 h of LPA, and 1.4 h of MVPA. Old-old adults displayed slightly lower MVPA (1.0 h) and increased SB (12.8 h). Generally, higher MVPA and lower SB were associated with better physical performance and reduced fear of falling. The optimal "Goldilocks Day" for both age groups highlighted the benefits of higher physical activity and reduced sedentary time, with significant implications for personalized health recommendations and improved health outcomes in Czech older adults.
Faculty of Physical Culture Palacký University Olomouc Olomouc Czech Republic
Faculty of Science Palacký University Olomouc Olomouc Czech Republic
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American Heart Association. American Heart Association Recommendations for Physical Activity in Adults and Kids. https://www.heart.org/en/healthy-living/fitness/fitness-basics/aha-recs-for-physical-activity-in-adults (2024).
Holtermann, A. et al. 24-hour physical behavior balance for better health for all: the sweet-spot hypothesis. PubMed PMC
World Health Organization. Ageing and health. https://www.who.int/news-room/fact-sheets/detail/ageing-and-health (2022).
Český statistický úřad.
Langhammer, B., Bergland, A. & Rydwik, E. The Importance of Physical Activity Exercise among Older People. PubMed PMC
Gibson-Moore, H. U. K. Chief medical officers’ physical activity guidelines 2019: what’s new and how can we get people more active?
Bull, F. C. et al. World health organization 2020 guidelines on physical activity and sedentary behaviour. PubMed PMC
Ross, R. et al. Canadian 24-hour movement guidelines for adults aged 18–64 years and adults aged 65 years or older: an integration of physical activity, sedentary behaviour, and sleep. PubMed
Dumuid, D. et al. Compositional data analysis in time-use epidemiology: what, why, how. PubMed PMC
Grgic, J. et al. Health outcomes associated with reallocations of time between sleep, sedentary behaviour, and physical activity: A systematic scoping review of isotemporal substitution studies. PubMed PMC
Pedišić, Ž. Measurement issues and poor adjustments for physical activity and sleep undermine sedentary behaviour research—The focus should shift to the balance between sleep, sedentary behaviour, standing and activity.
Hron, K. et al. Analysing pairwise logratios revisited.
Sherrington, C. et al. Exercise for preventing falls in older people living in the community: an abridged Cochrane systematic review. PubMed
Dzierzewski, J. M., Dautovich, N. & Ravyts, S. Sleep and cognition in older adults. PubMed PMC
Hanson, B. L. & Ruthig, J. C. The unique role of sleep quality in older adults’ psychological Well-Being.
Migueles, J. H. et al. Accelerometer data collection and processing criteria to assess physical activity and other outcomes: A systematic review and practical considerations. PubMed PMC
Cohen, J. A power primer. PubMed
Migueles, J. H. et al. A research community–driven open source R package for generating physical activity and sleep outcomes from multi-day Raw accelerometer data.
Fraysse, F. et al. Physical activity intensity cut-points for wrist-worn geneactiv in older adults. PubMed PMC
Rowlands, A. V. et al. Accelerometer-assessed physical activity in epidemiology. PubMed
van Hees, V. T. et al. Estimating sleep parameters using an accelerometer without sleep diary. PubMed PMC
van Hees, V. T. et al. A novel, open access method to assess sleep duration using a wrist-worn accelerometer. PubMed PMC
Stemland, I. et al. Validity of the Acti4 method for detection of physical activity types in free-living settings: comparison with video analysis. PubMed
Skotte, J., Korshøj, M., Kristiansen, J., Hanisch, C. & Holtermann, A. Detection of physical activity types using triaxial accelerometers. PubMed
Winter, J. E., MacInnis, R. J., Wattanapenpaiboon, N. & Nowson, C. A. BMI and all-cause mortality in older adults: a meta-analysis. PubMed
Flegal, K. M., Kit, B. K. & Graubard, B. I. Overweight, obesity, and all-cause mortality—reply. PubMed
Delbaere, K. et al. A multifactorial approach to Understanding fall risk in older people. PubMed
Bischoff, H. A. et al. Identifying a cut-off point for normal mobility: A comparison of the timed ‘up and go’ test in community-dwelling and institutionalised elderly women. PubMed
Topinková, E., Berková, M., Mádlová, P. & Běláček, J. Krátká Baterie pro testování Fyzické Zdatnosti seniorů’ a Její Využití pro diagnózu geriatrické Křehkosti v klinické praxi.
Cesari, M. et al. Prognostic value of usual gait speed in Well-Functioning older People—Results from the health, aging and body composition study. PubMed
Bohannon, R. W. Reference values for the Five-Repetition Sit-to-Stand test: A descriptive Meta-Analysis of data from elders. PubMed
van den Boogaart, K. G., Tolosana, R., Bren, M. & van den Boogaart, M. K. G. Package ‘compositions’.
Templ, M., Hron, K., Filzmoser, P. & robCompositions An R-package for robust statistical analysis of compositional data. In
Aitchison, J. The statistical analysis of compositional data.
Pelclová, J. et al. Are longitudinal reallocations of time between movement behaviours associated with adiposity among elderly women? A compositional isotemporal substitution analysis. PubMed PMC
Milanovic, Z. et al. Age-related decrease in physical activity and functional fitness among elderly men and women. PubMed PMC
Cabanas-Sánchez, V., Higueras-Fresnillo, S., De La Cámara, M. Á. & Esteban-Cornejo, I. Martínez-Gómez, D. 24-h movement and nonmovement behaviors in older adults. The IMPACT65 + study. PubMed
Nesrstová, V. et al. Simple enough, but not simpler: reconsidering additive logratio coordinates in compositional analysis.
Cabanas-Sánchez, V. et al. Twenty four-hour activity cycle in older adults using wrist‐worn accelerometers: the seniors‐ENRICA‐2 study. PubMed
Rosenberg, D. et al. Device-assessed physical activity and sedentary behavior in a community-based cohort of older adults. PubMed PMC
Palmberg, L. et al. The associations of activity fragmentation with physical and mental fatigability among Community-Dwelling 75-, 80-, and 85-Year-Old people. PubMed
Yerramalla, M. S. et al. Association of daily composition of physical activity and sedentary behaviour with incidence of cardiovascular disease in older adults. PubMed PMC
Veen, J. et al. Adherence to the physical activity guideline beyond the recommended minimum weekly amount: impacts on indicators of physical function in older adults. PubMed PMC
Cabanas-Sánchez, V. et al. Twenty four-hour activity cycle in older adults using wrist-worn accelerometers: the seniors-ENRICA-2 study. PubMed
González-Calvo, G., García-Monge, A., Ramalho, A., Hamdi, F. & Duarte-Mendes, P. Older men in motion: bodies, masculinities, and redefinition of identity. PubMed PMC
Wu, S., Wu, W., Xia, X. & Zhou, J. Characteristics of Physical Activities and Environmental Factor Preferences of Older Adults in Rural Resettlement Community in Ningbo, China. PubMed PMC
European Observatory on Health Systems and Policies.