ArticlePreventive medicine reports2020
Associations of physical activity and sleep with cardiometabolic risk in older women.
Article in Preventive medicine reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 10 citations in OpenAlex.
- Accelerometer-measured sedentary time accumulation patterns and cardiometabolic risk severity in community-dwelling older adults: A cross-sectional study.BMC geriatrics · 2025Article
- Methodological Choices on 24-h Movement Behavior Assessment by Accelerometry: A Scoping Review.Sports medicine - open · 2025Review
- Reallocating just 10 min to moderate-to-vigorous physical activity from other components of 24-hour movement behaviors improves cardiovascular health in adults.BMC public health · 2024Article
- A systematic review of research reporting practices in observational studies examining associations between 24-h movement behaviors and indicators of health using compositional data analysis.Journal of activity, sedentary and sleep behaviors · 2024Review
- The association between reallocations of time and health using compositional data analysis: a systematic scoping review with an interactive data exploration interface.The international journal of behavioral nutrition and physical activity · 2023Article
- A compositional analysis of time spent in sleep, sedentary behaviour and physical activity with all-cause mortality risk.The international journal of behavioral nutrition and physical activity · 2021Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
In this study, we investigate the associations of objectively measured waking (sedentary, light physical activity [LPA] and moderate-to-vigorous physical activity [MVPA]) and sleep duration and quality characteristics with cardiometabolic risk among older women. Participants from the Healthy Women Study 2010-11 follow-up visit (n = 136, age = 73 ± 2 years, white = 91.9%) concurrently wore an ActiGraph GT1M accelerometer and Actiwatch-2 for seven days. A composite cardiometabolic risk score was calculated by transforming metabolic syndrome (MetS) components and summing z-scores. Multivariable regression models were fitted to relate waking and sleep estimates with the MetS z-score after adjustment for covariates. Compositional data analysis was used to predict the MetS z-score when fixed durations of time were reallocated from one characteristic to another. MVPA (per 10 min/day increase; β = -7.80, P < 0.01), LPA (per 30 min/day increase; β = -0.29, P = 0.04), and sleep efficiency (β = -0.10, P = 0.04) were inversely associated with MetS z-score, while sedentary time (per 30 min/day increase; β = 0.34, P = 0.01) was positively associated with MetS z-score. Reallocation of 5 min from MVPA to sleep, sedentary, or LPA resulted in the greatest predicted change in MetS z-score. On average, the reallocation of 5 min from MVPA to other characteristics predicted an 11% increase in triglycerides, 6% decrease in HDL-C, and 5% increase in waist circumference. Lastly, reallocating 30 min of sedentary time to LPA was associated with a modestly lower predicted MetS z-score. This study suggests that MVPA is the most important contributor of MetS and that maintaining MVPA and increasing LPA may be beneficial for reducing cardiometabolic risk among older women.
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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.