Associations of weather and air pollution with objective physical activity and sedentary time before and after bariatric surgery: a secondary analysis of a prospective cohort study
Bibliographic record
Abstract
Purpose: Identifying factors that influence moderate-to-vigorous intensity physical activity (MVPA) and sedentary time in metabolic and bariatric surgery (MBS) patients is necessary to inform the development of interventions. Weather/environmental factors may be especially important considering rapid climate change and the vulnerability of people with obesity to heat and pollution. Our study aimed to examine the associations of weather (maximal, average and Wet Bulb Globe Temperatures), and air pollution indices (air quality index [AQI]) with daily physical activity (PA) of both light (LPA) and MVPA and sedentary time before and after MBS. Materials and methods: Participants (n = 77) wore an accelerometer at pre- and 3, 6, and 12-months post-MBS to assess LPA/MVPA/ sedentary time (min/d). These data were combined with participants' local (Boston, MA or Providence, RI, USA) daily weather and AQI data (extracted from federal weather and environmental websites). Results: Multilevel generalized additive models showed inverted U-shaped associations between weather indices and MVPA, with a marked reduction in MVPA for daily maximal temperatures ≽20 °C. Sensitivity analysis showed a less marked decrease of MVPA (min/d) during higher temperatures after versus before MBS. Both MVPA before and after MBS and sedentary time before MBS were negatively impacted by higher AQI levels. Conclusion: This study is the first to show that weather and air pollution indices, even in locations with good AQI and moderate temperatures, are related to variability in activity behaviors, particularly MVPA, during pre- and post-MBS. Weather/environmental conditions should be considered in MVPA prescription/strategies for adults who have undergone MBS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".