ArticleNutrients2023
Trajectories of 24-Hour Physical Activity Distribution and Relationship with Dyslipidemia.
Article in Nutrients, 2023. 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.
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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.
- Association Between Free Sugar Intake and Risk of Dyslipidemia in Chinese Adults-Evidence from the Chinese Food Consumption Survey and the China Health and Nutrition Survey.Foods (Basel, Switzerland) · 2026Article
- Accelerometer-measured weekly and diurnal moderate-to-vigorous physical activity patterns and incident osteoporosis.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2026Article
- Impact of physical activity, health literacy and cognitive health on quality of life in dyslipidemia: an observational study.Scientific reports · 2025Observational
- The PLANS model predicts recurrent strokes in patients with minor ischemic strokes.Scientific reports · 2025Article
- Unraveling the link between hypertriglyceridemia, dampness syndrome, and chronic diseases: A comprehensive observational study.Medicine · 2024Observational
- An App-Based Physical Activity Intervention in Community-Dwelling Chinese-, Tagalog-, and Vietnamese-Speaking Americans: Single-Arm Intervention Study.JMIR formative research · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The association between physical activity (PA) and dyslipidemia is well known, but the relationship between a temporal pattern of PA and dyslipidemia remain unknown. Here, we aimed to identify the intensity and temporal patterns of PA clustered by the trajectory model and their relationship with dyslipidemia. The participants were 701 adults (305 males) aged 18−60 years undergoing continuous measurement of PA with Actigraph GT3X+ accelerometers for at least 3 days. A trajectory analysis was applied based on moderate-to-vigorous intensity physical activity (MVPA) accumulated values over every period per day. The association between PA and dyslipidemia was estimated using a logistic regression model. Four distinct PA trajectory groups in the population were identified (continued low, stable and moderate, late increasing, and early increasing). Specifically, the “moderate and stable group” was associated with a decreased rate of high TG (p < 0.05) and the “moderate and stable group” and “late increasing group” were associated with decreased rates of low HDL-C (p < 0.05). In conclusion, there were four activity trajectory groups in this population and the continued low PA trajectory was associated with a high prevalent rate of an abnormal lipid profile, and continued and moderate activity or late afternoon increasing activity might have lower HDL-C distribution.
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Registered trials
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