Back pain precedes sleep problems in older men
Bibliographic record
Abstract
Abstract Background and Objectives While cross-sectional associations between any pain and sleep problems have been established, longitudinal studies examining the temporal relationship between back pain and multidimensional sleep health remain limited. We evaluated whether the association between back pain and sleep problems was bidirectional in older men aged 65 years and above. Research Design and Methods Data came from the Osteoporotic Fractures in Men Study with a sample of 1,055 older men who completed 2 clinical sleep visits. A composite sleep problems score was created using self-report and actigraphy data reflecting irregularity, dissatisfaction, lack of daytime alertness, suboptimal timing, inefficiency, and suboptimal duration. Participants were queried by mail about back pain every 4 months, and we calculated the prevalence of any, frequent, severe, and activity-limiting back pain around their 2 sleep visits. Cross-lagged panel models estimated bidirectional associations between sleep problems and subsequent back pain, and vice versa, over 6 years. Results Multivariable-adjusted results showed that having any back pain, frequent back pain, severe back pain, and activity-limiting back pain predicted 12%–25% greater sleep problems 6 years later (Exp(β) = 1.12; 95% confidence interval [CI] = 1.03–1.21 to Exp(β) = 1.25; 95% CI = 1.05–1.48), but sleep problems did not predict subsequent back pain. Discussion and Implications This study highlights the long-term temporal directionality of the association between back pain and sleep problems in older men. Back pain preceded more sleep problems, but an inverse association was not observed. Our findings suggest that interventions targeting back pain may help decrease sleep problems in older men and warrant further investigation into potential mechanisms.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".