Trial reportThe international journal of behavioral nutrition and physical activity2024
Using functional principal component analysis (FPCA) to quantify sitting patterns derived from wearable sensors.
Trial report in The international journal of behavioral nutrition and physical activity, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03473145 (Sedentary Behavior Interrupted), which is not on this map. Cited by 4 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.
Sedentary Behavior Interrupted: A Randomized Trial of 3-month Effects on Biomarkers of Healthy Aging and Physical Functioning in the Real World (Project 2)
Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- The Relation of Within-Day Physical Activity Patterns With All-Cause Mortality in Adults With Knee Osteoarthritis: Findings From the Osteoarthritis Initiative.Arthritis care & research · 2026Observational
- Contribution of Longitudinal Mobile Health Measures in the Dynamic Track of Patients With Major Depressive Disorder: Multiple Centers, Prospective Cohort Study Using Functional Data Analysis and Machine Learning.JMIR mHealth and uHealth · 2026Article
- The relation of activity patterns with incident slow gait speed over 4 years in adults with knee osteoarthritis: Data from the Osteoarthritis Initiative.Osteoarthritis and cartilage · 2025Article
- Comparative Analysis of Force-Sensitive Resistors and Triaxial Accelerometers for Sitting Posture Classification.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundSedentary behavior (SB) is a recognized risk factor for many chronic diseases. ActiGraph and activPAL are two commonly used wearable accelerometers in SB research. The former measures body movement and the latter measures body posture. The goal of the current study is to quantify the pattern and variation of movement (by ActiGraph activity counts) during activPAL-identified sitting events, and examine associations between patterns and health-related outcomes, such as systolic and diastolic blood pressure (SBP and DBP).
methodsThe current study included 314 overweight postmenopausal women, who were instructed to wear an activPAL (at thigh) and ActiGraph (at waist) simultaneously for 24 hours a day for a week under free-living conditions. ActiGraph and activPAL data were processed to obtain minute-level time-series outputs. Multilevel functional principal component analysis (MFPCA) was applied to minute-level ActiGraph activity counts within activPAL-identified sitting bouts to investigate variation in movement while sitting across subjects and days. The multilevel approach accounted for the nesting of days within subjects.
resultsAt least 90% of the overall variation of activity counts was explained by two subject-level principal components (PC) and six day-level PCs, hence dramatically reducing the dimensions from the original minute-level scale. The first subject-level PC captured patterns of fluctuation in movement during sitting, whereas the second subject-level PC delineated variation in movement during different lengths of sitting bouts: shorter (< 30 minutes), medium (30 -39 minutes) or longer (> 39 minute). The first subject-level PC scores showed positive association with DBP (standardized
conclusionIn this work we implemented MFPCA to identify variation in movement patterns during sitting bouts, and showed that these patterns were associated with cardiovascular health. Unlike existing methods, MFPCA does not require pre-specified cut-points to define activity intensity, and thus offers a novel powerful statistical tool to elucidate variation in SB patterns and health.
trial registrationClinicalTrials.gov NCT03473145; Registered 22 March 2018; https://clinicaltrials.gov/ct2/show/NCT03473145 ; International Registered Report Identifier (IRRID): DERR1-10.2196/28684.
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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.