Housing Characteristics and Hospital Admissions due to Falls on Stairs: A National Birth Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To assess associations between housing characteristics and risk of hospital admissions related to falls on/from stairs in children, to help inform prevention measures. STUDY DESIGN: An existing dataset of birth records linked to hospital admissions up to age 5 for a cohort of 3 925 737 children born in England between 2008 and 2014, was linked to postcode-level housing data from Energy Performance Certificates. Association between housing construction age, tenure (eg, owner occupied), and built form and risk of stair fall-related hospital admissions was estimated using Poisson regression. We stratified by age (<1 and 1-4 years), and adjusted for geographic region, Index of Multiple Deprivation, and maternal age. RESULTS: The incidence was higher in both age strata for children in neighborhoods with homes built before 1900 compared with homes built in 2003 or later (incidence rate ratio [IRR], 1.40; 95% CI, 1.10-1.77 [age <1 year], 1.20; 95% CI, 1.05-1.36 [age 1-4 years]). For those aged 1-4 years, the incidence was higher for those in neighborhoods with housing built between 1900 and 1929, compared with 2003 or later (IRR, 1.26; 95% CI, 1.13-1.41), or with predominantly social-rented homes compared with owner occupied (IRR, 1.21; 95% CI, 1.13-1.29). Neighborhoods with predominantly houses compared with flats had higher incidence (IRR, 1.24; 95% CI, 1.08-1.42 [<1 year] and IRR 1.16; 95% CI, 1.08-1.25 [1-4 years]). CONCLUSIONS: Changes in building regulations may explain the lower fall incidence in newer homes compared with older homes. Fall prevention campaigns should consider targeting neighborhoods with older or social-rented housing. Future analyses would benefit from data linkage to individual homes, as opposed to local area level.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 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".