Device-measured movement behaviours and cancer incidence in a population sample of UK adults: Dual 24-hour analyses of postural and intensity compositions
Bibliographic record
Abstract
BACKGROUND: Insufficient physical activity (PA) and excessive sedentary behaviour is associated with several cancers. Personalised approaches to increasing healthy movement behaviours over unhealthy behaviours may be more effective than a one-size-fits-all approach. Exploring both postures, and intensities across the 24-hour day may reveal actionable behavioural alternatives from current guidance. METHODS: Using a novel dual-compositional approach, we assessed how differences in participant's composition of 24-hour daily movement (postures and intensities) and sleep are differentially associated with PA-related cancer incidence (a composite of 13 sites linked with physical inactivity). This prospective analysis involved adults drawn from the UK Biobank accelerometry subsample each followed-up by health linkage. Participant's daily movement was classified into two 24-hour compositions. Composition 1 (posture-focused): sleep duration, sedentary behaviour (SB), standing, moving at any intensity. Composition 2 (intensity-focused): sleep duration, sedentary time (ST), light PA (LPA), moderate PA (MPA), and vigorous PA (VPA). Secondary analysis combined VPA and MPA as moderate-to-vigorous PA (MVPA). PA-related cancer diagnoses were captured from health registry data for up to 9.5 years (y). Cox-proportional hazards models were adjusted for age, sex, education, smoking, alcohol, diet, parental cancer history, cardiovascular disease and medication use. RESULTS: Analyses included 59,218 (55% female) participants (mean [SD] age: 61.7 [7.8]y), with a median follow-up of 8.0y [IQR: 7.4-8.5y; 464,640 person years] with 2,385 (4%) incident cancer events. Among the average, active participant, greater moving in place of other behaviours was associated with lower cancer risk, e.g. theoretically replacing 15 min of sleep or SB with 15 min of moving was associated with hazard ratios (HR) of 0.98 (95% Confidence Interval (95%CI): 0.97-0.99) and 0.98 (95%CI: 0.97-0.99), respectively. Similar risk reduction was observed with 30 min additional standing in place of sleep or SB. Regarding intensity, greater MVPA, in place of any behaviour proved most robustly associated with lower risk, although notably, the VPA component within MVPA proved the critical intensity. CONCLUSIONS: Beyond MVPA, moving at any intensity, in place of other postures, was associated with reduced risk of cancer. However, greater standing may also provide a plausible behavioural adjunct or alternative, warranting further investigation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".