Cross-sectional Associations of Neighborhood Social and Environmental Contextual Factors with Telomere Length in Male and Female Health Professionals
Bibliographic record
Abstract
BACKGROUND: Telomere length attrition has been proposed as a mediator through which the adverse neighborhood social and environmental context affects cancer risk through stress-related pathways, but associations have been inconsistent. We examined associations between neighborhood social and environmental factors in a population with extensive capture of behavioral factors and comorbidities. METHODS: Data were pooled from nested case-control studies using blood samples collected in two large prospective US-based cohorts of male (n = 3,065) and female (n = 9,993) health professionals. Relative leukocyte telomere length was assayed using qPCR and geospatial measures of socioeconomic status, air pollution, green space, and temperature were linked to participants' address at blood draw. RESULTS: After adjusting for sociodemographic and lifestyle covariates, no statistically significant associations of relative leukocyte telomere length with any of the address-level neighborhood socioeconomic or environmental factors were observed. CONCLUSIONS: In this large nation-wide cross-sectional study of male and female health professionals in the United States, neighborhood social and environmental contextual factors were not associated with telomere length. IMPACT: Further cross-sectional studies of associations between neighborhood social and environmental factors and telomere length are unlikely to improve understanding of this potential mediating mechanism. Studies with repeated measures may be required.
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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 | 0.000 | 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) | 0.001 | 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".