Anticholinergic medication exposure predicts poor physical capability: Findings from a large prospective cohort study in England
Bibliographic record
Abstract
OBJECTIVES: To examine whether anticholinergic medication exposure in middle and late life is associated with physical capability. STUDY DESIGN: We used data from 8477 men and women who had enrolled in the European Prospective Investigation of Cancer-Norfolk study at baseline (1HC; 1993-1997) and who had attended its third health examination (3HC; 2004-2010). Medication history at the 1HC and 3HC was used to score participants according to the Anticholinergic Cognitive Burden (ACB) Scale at baseline and 3HC; participants were categorised as ACB = 0, ACB = 1, ACB>2. MAIN OUTCOME MEASURE: At 3HC, physical capability was objectively measured by: usual walking speed, maximum grip strength, timed chair stands speed (TCSS) and standing balance. Linear and logistic regression models examined prospective and cross-sectional associations between ACB and physical capability, controlling for co-morbidity, sociodemographic and lifestyle factors. RESULTS: The analyses included 3386 men and 4110 women who were 56.4 (SD 7.9) and 55.0 (7.7) years old respectively at baseline and 69.4 (8.1) and 67.9 (8.0) years old at follow-up. Significant cross-sectional and prospective relationships were observed for all physical capability measures in women, except grip strength. For example, women with ACB ≥ 2 compared with ACB = 0 at baseline had 0.07 m/s (95 % CI -0.11, -0.03) slower usual walking speed, 2.61 stands/min (-4.17, -1.05) slower TCSS and higher odds of being unable to complete a tandem stand (odds ratio 2.40, 95 % CI 1.53, 3.76). These trends were observed in men but were less consistent in prospective analyses. CONCLUSION: Exposure to anticholinergic medication predicts poor physical capability and is a potentially reversible risk factor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".