The Association of Objectively Measured Physical Activity and Sedentary Behavior with (Instrumental) Activities of Daily Living in Community-Dwelling Older Adults: A Systematic Review
Bibliographic record
Abstract
Elvira S Amaral Gomes,1 Keenan A Ramsey,1 Anna GM Rojer,1 Esmee M Reijnierse,2 Andrea B Maier1– 3 1Department of Human Movement Sciences, @AgeAmsterdam, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands; 2Department of Medicine and Aged Care, @AgeMelbourne, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, 3050, Australia; 3Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Centre for Healthy Longevity, @AgeSingapore, National University Health System, SingaporeCorrespondence: Andrea B MaierDepartment of Human Movement Sciences, @AgeAmsterdam, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Van der Boechorststraat 7, Amsterdam, 1081 BT, the NetherlandsTel +31 20 5982000Email a.b.maier@vu.nlAbstract: Up to 60% of older adults have a lifestyle characterized by low physical activity (PA) and high sedentary behavior (SB). This can amplify age-related declines in physical and cognitive functions and may therefore affect the ability to complete basic and instrumental activities of daily living (ADL and IADL, respectively), which are essential for independence. This systematic review aims to describe the association of objectively measured PA and SB with ADL and IADL in community-dwelling older adults. Six databases (PubMed, Embase, the Cochrane library, CINAHL, PsychINFO, SPORTDiscuss) were searched from inception to 21/06/2020 for articles meeting our eligibility criteria: 1) observational or experimental study, 2) participants’ mean/median age ≥ 60 years, 3) community-dwelling older adults, 4) PA and SB were measured with a(n) accelerometer/pedometer, 5) PA and SB were studied in relation to ADL and/or IADL. Risk of bias was assessed in duplicate using modified versions of the Newcastle–Ottawa scale. Effect direction heat maps provided an overview of associations and standardized regression coefficients (βs) were depicted in albatross plots. Thirty articles (6 longitudinal; 24 cross-sectional) were included representing 24,959 (range: 23 to 2749) community-dwelling older adults with mean/median age ranging from 60.0 to 92.3 years (54.6% female). Higher PA and lower SB were associated with better ability to complete ADL and IADL in all longitudinal studies and overall results of cross-sectional studies supported these associations, which underscores the importance of an active lifestyle. The median [interquartile range] of βs for associations of PA/SB with ADL and IADL were, respectively, 0.145 [0.072, 0.280] and 0.135 [0.093, 0.211]. Our strategy to address confounding may have suppressed the true relationship of PA and SB with ADL or IADL because of over-adjustment in some included studies. Future research should aim for standardization in PA and SB assessment to unravel dose–response relationships and inform guidelines.Keywords: accelerometry, independent living, aged
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".