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L6 Environmental Correlates of Physical Activity and Sedentary Behaviour in Chronic Obstructive Pulmonary Disease

2021· article· en· W3124894822 on OpenAlexaff
Daniel Stevens, Pantelis Andreou, Daniel Rainham

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineCOPDSittingEnvironmental healthBayesian multivariate linear regressionPopulationLogistic regressionPhysical therapyLinear regressionInternal medicinePathologyStatistics

Abstract

fetched live from OpenAlex

Introduction and Objectives Physical activity predicts important health outcomes in chronic obstructive pulmonary disease (COPD), and is recognised as a therapeutic treatment that is recommended in current disease management guidelines. Environmental factors have the potential to influence physical activity, however, there are limited data in this clinical population. Therefore, the objective of the present study is to investigate both atmospheric and physical environmental correlates of physical activity and sedentary behaviour in individuals with COPD. Methods Socio-demographic and behavioural data were collected from a prospective cohort of 418 individuals with COPD (65% female; 58 ± 8 years). Physical activity behaviour was captured using the International Physical Activity Questionnaire, while sitting time was used as a measure of sedentary behaviour. Environmental data was drawn from a national environmental data repository and individually matched to each participant’s postal code. Environmental variables included social and material deprivation, urban form index, surrounding greenness, and air quality (concentrations of air pollution for fine particles; nitrogen dioxide; ozone; and sulphur dioxide). Logistic and multivariate linear regression models were used to investigate the strongest environmental predictors of physical activity and sedentary behaviour, respectively. Results In the models, a statistically significant correlation was shown between physical activity level and ozone pollution (p = 0.023; Adjusted OR = 0.85; 95%CI = 0.74–0.98). Indicating, that a higher level of physical activity was associated with a lower level of ozone pollution in the environment. Urban form index was significantly associated with sitting time per day (beta = 0.113; t-value = 1.71; p = 0.011). Suggesting, that those living in less urban environments spend less time sedentary. ‘Self-rated health’ of the participants was positively correlated with physical activity level (p = 0.006; Adjusted OR = 2.22; 95%CI = 1.25–3.94), and inversely correlated with sitting time per day (beta = -0.159; t-value = -2.42; p = 0.016). Conclusions Physical activity is a complex behaviour influenced by a combination of individual, sociocultural, and environmental factors. Clinicians may wish to consider the individual’s environment in the discussion and prescription of physical activity/exercise; particularly when hospital based, face-to-face, pulmonary rehabilitation is not possible.

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)0.003
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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.274
Teacher spread0.258 · 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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Citations1
Published2021
Admission routes1
Has abstractyes

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