Association of back pain with all-cause and cause-specific mortality among older men: a cohort study
Bibliographic record
Abstract
OBJECTIVE: We evaluated whether more severe back pain phenotypes-persistent, frequent, or disabling back pain-are associated with higher mortality rate among older men. METHODS: In this secondary analysis of a prospective cohort, the Osteoporotic Fractures in Men (MrOS) study, we evaluated mortality rates by back pain phenotype among 5215 older community-dwelling men (mean age, 73 years, SD = 5.6) from 6 sites in the United States. The primary back pain measure used baseline and Year 5 back pain questionnaire data to characterize participants as having no back pain, nonpersistent back pain, infrequent persistent back pain, or frequent persistent back pain. Secondary measures of back pain from the Year 5 questionnaire included disabling back pain phenotypes. The main outcomes measured were all-cause and cause-specific death. RESULTS: After the Year 5 exam, during up to 18 years of follow-up (mean follow-up = 10.3 years), there were 3513 deaths (1218 cardiovascular, 764 cancer, 1531 other). A higher proportion of men with frequent persistent back pain versus no back pain died (78% versus 69%; sociodemographic-adjusted HR = 1.27, 95% CI = 1.11-1.45). No association was evident after further adjustment for health-related factors, such as self-reported general health and comorbid chronic health conditions (fully adjusted HR = 1.00; 95% CI = 0.86-1.15). Results were similar for cardiovascular deaths and other deaths, but we observed no association of back pain with cancer deaths. Secondary back pain measures, including back-related disability, were associated with increased mortality risk that remained statistically significant in fully adjusted models. CONCLUSION: Although frequent persistent back pain was not independently associated with risk of death in older men, additional secondary disabling back pain phenotypes were independently associated with increased mortality rate. Future investigations should evaluate whether improvements in disabling back pain affect general health and well-being or risk of death.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".