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Record W7162022250 · doi:10.82308/21777

Assessing physical activity and sedentary behaviour long-term post Roux-en-Y gastric bypass surgery

2017· dissertation· en· W7162022250 on OpenAlexaboutno aff
Ryan Reid

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsObesityPhysical activitySedentary lifestyleWeight lossPopulationGastric bypass surgeryGastric bypassSTRIDEOverweight

Abstract

fetched live from OpenAlex

Over the past 30 years, the prevalence of obesity (BMI ≥ 30kg/m2) in Canada has increased 400 %. Even more concerning, the prevalence of Class III (BMI ≥ 40kg/m2) obesity has increased over 1000 % during the same period. Obesity is associated with type-2-diabetes, cardiovascular disease, depression, and musculoskeletal pain. These co-morbidities collectively cost the Canadian economy $ 4.3 billion per year in healthcare costs and lost productivity at work. Moreover, obesity results in mobility impairments including reduced stride length and slower walking cadence. For individuals living with extreme obesity and a related co-morbidity, bariatric surgery is the preferred treatment option. Bariatric surgery yields dramatic weight loss, resolution of most co-morbidities, reductions in pain, and improvements in physical functioning. Although these alterations are thought to yield more physical activity, to date, no changes in steps per day or sedentary time have been objectively measured from pre- to one-year post-surgery. After surgery, patients fail to meet established physical activity guidelines and begin to show small amounts of weight regain as early as two-years post-surgery.The first two manuscripts presented in this dissertation focused on evaluating the free-living movement patterns of individuals' long-term post-bariatric surgery (steps, sedentary time, and cadence), and determining if these patterns affect weight regain. It was found that patients do not step enough (6375 ± 2690 steps/day), are excessively sedentary (9.7 ± 2.3 hrs/day), and walk at significantly slower speeds on weekends compared to weekdays. As the built environment plays a role in physical activity and sedentary time on a population scale, it became important to assess if these constructs had the same effect on the bariatric population. Therefore, the third and fourth investigations evaluated the effect of neighbourhood walkability and employment status on physical activity, sedentary time, and weight regain respectively. These investigations proved that the built environment does not affect activity habits or obesity severity in the bariatric population. As substantial weight loss from surgery and aspects of the built environment have failed to promote physical activity and limit sedentary time, it is apparent that self-monitoring in this population is important. Therefore, the final investigation of this dissertation examined the validity of inexpensive, commercially available physical activity monitors against a research-grade accelerometer. This study showed that FitbitTM activity monitors are effective measurement tools for monitoring daily steps and time spent in light intensity activities. This confirmation allows bariatric surgeons to prescribe these activity monitors with confidence and can help patients self-monitor, meet established physical activity guidelines, and avoid weight regain post-surgery.This thesis was the first to objectively monitor physical activity and sedentary time long-term post-bariatric surgery. These studies filled important gaps in the literature related to the effects of the built and occupational environments on physical activity, sedentary habits, and weight regain post-surgery. Future studies should evaluate the effectiveness of interventions pre- and post-surgery designed to reduce and break up extended periods of sedentary time, while simultaneously promoting walking through light intensity activities. Interventions should employ the use of inexpensive commercially available activity monitors to improve self-monitoring, which can help individuals to meet established national activity guidelines.

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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.031
GPT teacher head0.349
Teacher spread0.318 · 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
Published2017
Admission routes1
Has abstractyes

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