ArticleSensors (Basel, Switzerland)2020
Activity Energy Expenditure Predicts Clinical Average Levels of Physical Activity in Older Population: Results from Salus in Apulia Study.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Can real-world measures of activity, sleep, and cardiorespiratory function stratify Sjogren's disease participants with persistent fatigue? Insights from the BRC tools study.EULAR rheumatology open · 2025Article
- Ultra-processed food consumption and nutritional frailty in older age.GeroScience · 2023Article
- Dietary profiling of physical frailty in older age phenotypes using a machine learning approach: the Salus in Apulia Study.European journal of nutrition · 2023Article
- Editorial: The role of nutrition in healthy aging.Frontiers in medicine · 2023Article
- Motoric Cognitive Risk Syndrome, Subtypes and 8-Year All-Cause Mortality in Aging Phenotypes: The Salus in Apulia Study.Brain sciences · 2022Article
- Wearable Motion Sensors in Older Adults: On the Cutting Edge of Health and Mobility Research.Sensors (Basel, Switzerland) · 2022Article
- Visualization-Driven Time-Series Extraction from Wearable Systems Can Facilitate Differentiation of Passive ADL Characteristics among Stroke and Healthy Older Adults.Sensors (Basel, Switzerland) · 2022Article
- Role of biomechanical assessment in rotator cuff tear repair: ArthroscopicWorld journal of orthopedics · 2021Article
- Traditional Old Dietary Pattern of Castellana Grotte (Apulia) Is Associated with Healthy Outcomes.Nutrients · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Self-report questionnaires are a valuable method of physical activity measurement in public health research; however, accuracy is often lacking. Resolving the differences between self-reported and objectively measured physical activity is an important surveillance challenge currently facing population health experts. The present work aims at providing the relationship between activity energy expenditure estimated from wrist-worn accelerometers and intensity of self-reported physical activity (InCHIANTI structured interview questionnaire) in a sub-cohort of a population-based study on aging in Southern Italy. Linear regression was used to test the association between measured and reported physical activity. We found that activity energy expenditure predicted clinical average levels of PA assessed through InCHIANTI classification.
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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.