WHO guidelines on waist circumference and physical activity and their joint association with cancer risk
Bibliographic record
Abstract
OBJECTIVE: Low body fat and high physical activity levels are key lifestyle factors in cancer prevention, but the interplay of abdominal obesity and physical activity on cancer risk remains unknown. We explored individual and joint associations of waist circumference and physical activity with cancer risk. METHODS: Using UK Biobank data (n=315 457), we categorised individuals according to WHO guideline thresholds for waist circumference and self-reported physical activity levels. Multivariable-adjusted Cox regression was used to estimate HRs and 95% CIs of total cancer. The reference group comprised individuals with recommended levels of waist circumference (<88 cm for women and <102 cm for men) and physical activity (>10 metabolic equivalent of task hours/week). Furthermore, we estimated the proportion of cancers attributable to abdominal obesity and insufficient physical activity. RESULTS: During a median follow-up period of 11 years (3 321 486 person-years), 29 710 participants developed any type of cancer. Participants not meeting the WHO guideline on waist circumference had increased cancer risk, even when sufficiently physically active according to the WHO (HR 1.11, 95% CI 1.08 to 1.15). Similarly, individuals not achieving the WHO guideline for physical activity showed an elevated risk, even if they were abdominally lean (HR 1.04, 95% CI 1.01 to 1.07). Not adhering to either guideline yielded the strongest increase in risk (HR 1.15, 95% CI 1.11 to 1.19). We estimated that abdominal obesity coupled with insufficient physical activity could account for 2.0% of UK Biobank cancer cases. CONCLUSION: Adherence to both WHO guidelines for waist circumference and physical activity is essential for cancer prevention; meeting just one of these guidelines is insufficient.
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 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 | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".