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Record W7119440274

Influence of age group and practice maintenance on cognitive, functional and anthropometric parameters of middle-aged and older adults engaged in a multicomponent physical exercise program: a 5-year longitudinal study

2023· dissertation· pt· W7119440274 on OpenAlexaboutno aff
João Gabriel da Silveira Rodrigues

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2023
Typedissertation
Languagept
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsAnthropometryCognitionStroop effectVerbal fluency testEffects of sleep deprivation on cognitive performanceCognitive skillPhysical fitnessPhysical exerciseLongitudinal study
DOInot available

Abstract

fetched live from OpenAlex

Human beings manifest a variety of functional losses, highlighting musculoskeletal, cardiovascular, and nervous systems impairments. Anthropometric and cognitive alterations, muscle strength, and functional capacity reductions also occur throughout aging. Physical exercise is a cornerstone of successful aging, potentially contributing to maintaining cognitive functions, body composition, functionality, and muscle strength. Furthermore, the maintenance of physical exercise practice seems necessary to preserve these promising healthy benefits of exercise in older population. This thesis compared, through two distinct studies, (1) the influence of age group on cognitive, functional, and anthropometric parameters of middle-aged adults and middle-aged and elderly adults participating in a physical activity program, (2) the progression of functional, anthropometric, cognitive and blood pressure variables in middle-aged and elderly adults after five years of follow-up. Methods: Four hundred and seventy-three older adults aged 55 to 84 years (84% women), regular participants in the Programa Envelhecimento Ativo (EEFFTO-UFMG) were enrolled in the first study. Eighty-five older women re-evaluated after five years were enrolled in the second study. The first study was conducted in 2017 and 2018, and the second in 2022 and 2023. Tests were carried out to evaluate cognitive functions (Montreal Cognitive Assessment, verbal fluency test, Digit Span test, Stroop Color, and Word test), functional capacity ("Senior Fitness Test" battery, handgrip strength, 10-meter gait test), anthropometric assessment (body mass, height, circumferences and skinfolds), and blood pressure. All procedures performed were approved by the university's Research Ethics Committee (CAAE: 49313121.0.0000.5149). Results: The older age group showed a reduction in global cognition and specific cognitive domains. In addition, there was also a reduction in muscle strength, muscle power, and functional capacity, a worsening of agility scores, and anthropometric changes (reduction in height, muscle mass, circumferences, and skinfolds). Muscle strength explained only 2.7% of the global cognition of older adults. In the second study, it was observed that maintaining the practice of multicomponent physical exercises for five years caused functional improvements and reduced the risk of cognitive decline compared to the group who abandoned the practice during the period. Conclusion: By several low-cost variables, the study showed that middle-aged and elderly adults of different age groups showed significant cognitive, functional, and anthropometric differences. Furthermore, maintaining the practice of multicomponent physical exercise can reverse at least part of the effects of aging on strength, power, and muscle mass and appears to prevent the risk of cognitive decline after five years.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.057
GPT teacher head0.324
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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