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Record W4415506011 · doi:10.1123/japa.2024-0364

Age- and Sex-Based Differences in Gait Pattern Characteristics Among Adults Over 50: A Cross-Sectional Study

2025· article· en· W4415506011 on OpenAlexaff
Mariève Houle, Gabriel Moisan, Andrée-Anne Marchand, Martin Descarreaux

Bibliographic record

VenueJournal of Aging and Physical Activity · 2025
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsSTRIDEAffect (linguistics)GaitPreferred walking speedActivities of daily livingHeel

Abstract

fetched live from OpenAlex

BACKGROUND/OBJECTIVE: Walking is essential for maintaining functional independence, and understanding gait changes due to aging is crucial, as chronic conditions often overlap with normal aging. The objective of this study was to describe gait characteristics in adults aged 50 and over and to identify differences between age groups and between sexes. METHODS: The study included 34 adults aged 50-59, 38 adults aged 60-69, and 28 adults aged 70+ years. Participant characteristics (age, sex, height, weight, and comorbidities) were collected. Participants walked a 30-m round trip at a self-selected pace. Gait was measured using inertial measurement units. RESULTS: Results showed that stride length, stride velocity, push-off ratio, and minimal toe clearance decreased with age (p < .03) and flat-foot ratio increased with age (p < .01), while cadence, walking phases (stance, swing, double support, and loading ratio), and maximal heel clearance were similar across age groups (p > .05). Males had a lower cadence, a longer stride, and a higher maximal heel clearance than females (p < .04). Stride velocity and minimal toe clearance were similar between sexes (p > .05). CONCLUSIONS: This study found that stride length and velocity decrease with age, and notable sex differences exist in stride length and maximal heel clearance. These findings underscore the importance of considering both age and sex when assessing walking and functional capacity in older adults. Significance/Implications: Aging impacts gait, and inertial measurement units offer a valuable tool to examine how age and sex affect walking. This is an initial step toward a deeper understanding of gait characteristics in older adults.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.366
Teacher spread0.340 · 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 teacher head, 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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

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