Stressful life events and low back pain in older men: A cross‐sectional and prospective analysis using data from the <scp>MrOS</scp> study
Bibliographic record
Abstract
BACKGROUND: Stressful life events, such as loss of a partner, loss of a pet or financial problems, are more common with increasing age and may impact the experience of pain. The aim of the current study is to determine the cross-sectional and prospective association between stressful life events and low back pain reporting in the Osteoporotic Fracture in Men Study, a cohort of older men aged ≥65 years. METHODS: At a study visit (March 2005-May 2006), 5149 men reported whether they had experienced a stressful life event or low back pain in the prior 12 months. Following that visit, data on low back pain patients were gathered through triannual questionnaires every 4 months for 1 year. Multivariable logistic regression analyses estimated the association of stressful life events with recent past low back pain or future low back pain. RESULTS: N = 2930, (57%) men reported at least one stressful life event. The presence of a stressful life event was associated with greater odds of any low back pain (OR = 1.42 [1.26-1.59]) and activity-limiting low back pain (OR = 1.74 [1.50-2.01]) in the same period and of any low back pain (OR = 1.56 [1.39-1.74]) and frequent low back pain (OR = 1.80 [1.55-2.08]) in the following year. CONCLUSION: In this cohort of men, the presence of stressful life events increased the likelihood of reporting past and future low back pain. SIGNIFICANCE: Stressful life events such as accident or illness to a partner are common in later life and may impact the experience of pain. We present cross-sectional and prospective data highlighting a consistent association between stressful life events and low back pain in older men. Further, there is evidence to suggest that this relationship is upregulated by an individual's living situation. This information may be used to strengthen a biopsychosocial perspective of an individual's pain experience.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".