Association between socioeconomic deprivation and bone health status in the UK biobank cohort participants
Bibliographic record
Abstract
The effect of deprivation on total bone health status has not been well defined. We examined the relationship between socioeconomic deprivation and poor bone health and falls and we found a significant association. The finding could be beneficial for current public health strategies to minimise disparities in bone health. PURPOSE: Socioeconomic deprivation is associated with many illnesses including increased fracture incidence in older people. However, the effect of deprivation on total bone health status has not been well defined. To examine the relationship between socioeconomic deprivation and poor bone health and falls, we conducted a cross-sectional study using baseline measures from the United Kingdom (UK) Biobank cohort comprising 502,682 participants aged 40-69 years at recruitment during 2006-2010. METHOD: We examined four outcomes: 1) low bone mineral density/osteopenia, 2) fall in last year, 3) fracture in the last five years, and 4) fracture from a simple fall in the last five years. To measure socioeconomic deprivation, we used the Townsend index of the participant's residential postcode. RESULTS: At baseline, 29% of participants had low bone density (T-score of heel < -1 standard deviation), 20% reported a fall in the previous year, and 10% reported a fracture in the previous five years. Among participants experiencing a fracture, 60% reported the cause as a simple fall. In the multivariable logistic regression model after controlling for other covariates, the odds of a fall, fracture in the last five years, fractures from simple fall, and osteopenia were respectively 1.46 times (95% confidence interval [CI] 1.42-1.49), 1.26 times (95% CI 1.22-1.30), 1.31 times (95% CI 1.26-1.36) and 1.16 times (95% CI 1.13-1.19) higher for the most deprived compared with the least deprived quantile. CONCLUSION: Socioeconomic deprivation was significantly associated with poor bone health and falls. This research could be beneficial to minimise social disparities in bone health.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".