Associations Between Physical Activity, Metabolic Risk Factors, And Comorbidities In Cancer Survivors
Bibliographic record
Abstract
PURPOSE: Cancer survivors with high metabolic risks or comorbidities have poorer survival. Moreover, physical activity is associated with improved cancer prognosis. We investigated the associations between physical activity, metabolic risk factors, and comorbidities in Korean cancer survivors. METHODS: The Korean National Health and Nutrition Examination Survey data from 2007 to 2013 were analyzed with a total number of 1,225 cancer survivors. Complex sample general linear models and logistic regression analyses were used. Moderate-to-vigorous physical activity (MVPA) was measured by self-administered questionnaire. Metabolic risk factors included waist circumference, blood pressure, triglyceride (TG), high-density lipoprotein-cholesterol, total cholesterol (TC), and fasting glucose. Comorbidities included diabetes, hypertension, stroke, arthritis, osteoporosis, and back pain.. RESULTS: In the sample overall, 38.4% were male, mean age and body mass index (BMI) were 62.3±12.4 years and 23.3±3.2 kg/m2 respectively. Cancer types included stomach (n=276), cervical (n=179), breast (n=176), colorectal (n=145), lung (n=48), liver (n=44), and other cancers (n=402). The average time spent in MVPA was 148.1±355.7 min/wk and 26.1% met ACSM/ACS physical activity guidelines for cancer patients (≥ 150 min of moderate intensity or 75 min of vigorous intensity activity per week). The total amount of MVPA was inversely correlated with TG (p=.008), fasting glucose (p =.003) and insulin level (p =.025) after adjustment for sex, age, and BMI. Those who did not meet ACSM/ACS guidelines showed higher systolic blood pressure (p =.003) and an increased risk of hypertension (odds ratio [OR]=1.52; 95% confidential interval[CI]=1.01 to 2.28) compared to those who met the guidelines. Furthermore, those who participated in strength exercises less than 2 days/wk showed a higher level of fasting glucose (p=.001) and TC (p=.031), and a higher risk of stroke (OR=5.03; 95% CI=1.38 to 18.37), arthritis (OR=1.62; 95% CI=1.05 to 2.51), and back pain (OR=2.30; 95% CI=1.10 to 4.80) compared to those who participated in strength exercises at least 2 days/wk. CONCLUSIONS: MVPA and strength exercise may play important roles in improving metabolic risk factors and preventing potential comorbidities in Korean cancer survivors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".