Associations Between Obesity, Rural-Urban Continuum Codes, And Physical Activity Program Preferences Among Breast Cancer Survivors
Bibliographic record
Abstract
PURPOSE: Many cancer survivors in rural areas with obesity fail to meet the American College of Sports Medicine physical activity (PA) guidelines. PA promotion programs are needed for these populations. This study examined the associations between obesity, rural-urban continuum (RUCC) codes, and PA program preferences. METHODS: Physically inactive breast cancer survivors (N=222) completed the baseline assessment for a randomized controlled PA trial including surveys to assess PA program preferences (i.e., location, exercise counseling source, exercise counseling delivery, exercise type [walking vs yoga], program type [aerobic vs resistance training], supervised vs unsupervised exercise, individual vs group exercise, flexible vs scheduled, amount willing to pay for exercise program, distance willing to travel, and distance willing to travel if gas costs were covered). Chi-Square analyses using dichotomized variables were conducted. Obesity was defined as body mass index ≥ 30. RUCC codes were classified as metro [RUCC=1 and3] vs non-metro [RUCC=6]. RESULTS: Participants were primarily white (85%), non-Hispanic (98%), and employed (71%) with an average age of 54.4 ± 8.5 years; half (51%) were obese. Most resided in metro areas with <250,000 population (RUCC=3; 73.6%) while the remaining resided in metro areas with >1 million population (RUCC=1; 22%) or nonmetro with 2,500-19,999 population (RUCC=6, 5%). When compared with non-obese, survivors with obesity were more likely to prefer exercise counseling from a personal trainer rather than a cancer exercise specialist, health club exercise specialist, or other cancer survivor (44% of non-obese vs. 57% of obese, p=.03). RUCC was associated with the farthest distance willing to travel (≥16 miles acceptable to 95% of RUCC 1 and 3 vs. 5% of RUCC 6, p<.001) and farthest distance willing to travel if gas costs were covered (≥16 miles acceptable to 42% of RUCC 1 and 3 vs 4% of RUCC 6, p=.027). No other preferences were associated with obesity or RUCC. CONCLUSIONS: Exercise counseling source and distance traveled are preferences associated with obesity or metro vs. nonmetro residency. Future PA programs should consider these factors along with potential reach and access concerns when targeting breast cancer survivors with obesity or living in nonmetro areas.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".