Predictors of declining levels of physical activity among adult survivors of childhood cancer.
Bibliographic record
Abstract
10062 Background: Childhood cancer survivors are at increased risk of developing obesity-related diseases, yet many survivors do not meet established guidelines for physical activity. We aimed to identify demographic and health-related predictors of declining physical activity among participants in the Childhood Cancer Survivor Study (CCSS). Methods: Analyses included 6617 >5 year childhood cancer survivors diagnosed between 1970-86 who completed the CCSS 2003 and 2007 follow-up questionnaires, and1992 siblings. Participants were classified as active if they reported engaging in any physical activity other than their regular job duties in the prior month. Generalized linear models using a log-link and Poisson distribution were used to compare participants whose physical activity levels fell from active to inactive over the study interval to those who remained active or whose activity levels improved. In addition to analyses comparing survivors to siblings, selected demographic factors and chronic conditions (CTCAE v4.0 Grade 3 and 4) were evaluated as risk factors in an analysis among survivors alone. Risk ratios (RR) with 95% confidence intervals (CI) are reported. Results: The median age at last follow-up among survivors and siblings was 36 (range: 21-58) and 38 (range: 21-62) years, respectively. Approximately 14% of survivors and 9% of siblings reported declines in physical activity across the study interval (p<0.01). Factors that predicted declining levels of physical activity included BMI≥30kg/m2 (RR=1.4, 95% CI=1.3-1.7, p<0.01), BMI<18.5kg/m2 (RR=1.4, 95% CI=1.0-1.8, p=0.03), not completing high school (RR=1.7, 95% CI=1.2-2.2, p<0.01), and black race (RR=1.6, 95% CI=1.2-2.1, p<0.01). In a model limited to survivors, declining levels of physical activity were more likely among survivors who reported the presence of Grade 3 or 4 neurological (RR=1.5, 95% CI=1.2-1.8, p<0.01) or cardiac conditions (RR=1.5, 95% CI=1.3-1.9, p<0.01). Conclusions: Childhood cancer survivors are at increased risk of becoming inactive over time compared to siblings. Interventions targeting survivors at highest risk of decline are required to reduce the risk of chronic diseases associated with an inactive lifestyle.
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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 | 0.003 |
| 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 | 0.001 |
| 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".