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Record W2599112793 · doi:10.1093/schbul/sbx022.055

M58. Sedentary Behavior Profiles and Obesity Among People With Schizophrenia

2017· article· en· W2599112793 on OpenAlexaffabout
Markus J. Duncan, Kelly P. Arbour‐Nicitopoulos, Mehala Subramaniapillai, Gary Remington, Guy Faulkner

Bibliographic record

VenueSchizophrenia Bulletin · 2017
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsCentre for Addiction and Mental HealthUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsWaistSedentary behaviorObesityMedicineBody mass indexPhysical activitySedentary lifestylePhysical therapyDemographyGerontologyInternal medicine

Abstract

fetched live from OpenAlex

Background: Sedentary behavior has been identified as a risk factor for cardiovascular disease and mortality independent of physical activity; the purpose of this study was to profile sedentary behavior in a sample of people with schizophrenia and identify relationships between patterns of sedentary behavior and measures of adiposity. Methods: Participant waist circumference (WC) and body mass index (BMI) were measured at intake. Participants subsequently wore accelerometers for 7 days. Valid wear time was considered to be 10 hours or more on at least 4 days. Sedentary behavior was considered any period with less than 100 counts per minute, for at least 1 minute. A profile of sedentary behavior was assessed to identify volume of sedentary time, the daily average duration of sedentary bouts and frequency of varying sedentary bout lengths. Pearson correlations were calculated between sedentary behavior and health variables for the full sample, and stratified by sex. Hierarchical regression models were calculated for WC and BMI, first controlling for age, sex, and chlorapromazine equivalents, followed by moderate to vigorous physical activity (MVPA) and accelerometer wear time, and finally sedentary variables. Results: One hundred thirty participants enrolled in the study, of which 113 completed the study and 101 wore their accelerometers for a sufficient amount of time. Mean (SD) daily sedentary time was 455.8 (125.3) minutes, or 53% of daily accelerometer wear time. Sedentary time was broken up by 79.6 (17.4) breaks in sedentary time. The average bout of sedentary behavior lasted 5.9 (1.7) minutes. Sedentary bouts under 5 minutes were most common across the sample, mean (SD) = 53.57 (15.5) per day, followed by bouts lasting 5 to <10 minutes, 13.49 (4.5) per day. Sedentary bouts longer than an hour occurred, on average, .4 (.4) times per day. WC was significantly related to total sedentary breaks r = .20, P = .04, and average sedentary bout length r =.25, P = .015, however BMI was not. When stratified by sex, WC was only related to the average sedentary bout length in men, r = .40, P = .002, whereas there was no relationship in women. However, in the regression models no sedentary behavior variable was associated with WC or BMI after controlling for other variables such as MVPA. Conclusion: To date, this is the largest reported sample of objectively measured sedentary behavior data among people with schizophrenia we are aware of. This study provides a comprehensive profile of sedentary behavior patterns in this sample. Overall sedentary time in this sample was lower than what has been previously reported by studies using other objective measures. There was little evidence that sedentary behavior was associated with measures of adiposity. Further assessment of sedentary behavior and its relationship with other metabolic and cardiovascular health outcomes is warranted. Funding by a Canadian Institutes of Health Research operating grant.

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)0.000
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.266
Teacher spread0.250 · 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".

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Citations0
Published2017
Admission routes2
Has abstractyes

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