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Record W2025154718 · doi:10.1136/jech-2014-204726.12

OP09 Coronary mortality reductions attributable to primary prevention medications versus dietary changes in Scotland 2000–2010: modelling study using routine linked data

2014· article· en· W2025154718 on OpenAlexaff
Ruth Dundas, JW Hotchkiss, CA Davies, Nathaniel M. Hawkins, PS Jhund, Shaun Scholes, Madhavi Bajekal, Martín O’Flaherty, Julia Critchley, AH Leyland, Simon Capewell

Bibliographic record

VenueOral Presentations · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineBlood pressureDemographyPopulationCoronary heart diseaseInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Background Between 2000 and 2010, coronary heart disease (CHD) mortality rates in Scotland fell by over one third. Important contributions came from reductions in blood pressure and serum cholesterol (primary prevention). However, the relative contributions from preventive medications (anti-hypertensives and statins) in individuals and from population-wide dietary changes remain unclear. We therefore examined the impact of differential effects on health inequalities. Methods We used the previously validated IMPACTsec model to estimate the contributions of population-level risk factor changes and treatment changes to the CHD mortality decline in Scotland between 2000 and 2010 for adults aged over 25. Data were stratified using the Scottish Index of Multiple Deprivation (SIMD), a small area measure of deprivation. Model outputs were quantified as deaths prevented or postponed (DPPs) by each intervention. Sensitivity analyses were conducted using Ersatz-based Monte Carlo simulations. Results Between 2000 and 2010, 5770 fewer CHD deaths than expected occurred in Scotland; an estimated 3570 (62%) were attributable to reductions in blood pressure and serum cholesterol. Declines in blood pressure were responsible for approximately 2285 DPPs (minimum estimate 1630, maximum estimate 2915). The vast majority (2130 DPPs) came from population-wide blood pressure falls, with bigger absolute mortality decreases in the most deprived quintile compared with the least deprived (460 vs. 340 DPPs respectively); relative contributions were similar (37.2% and 37.5%). Anti-hypertension medications resulted in only 155 fewer deaths, with similar DPPs in the most (35) and least (30) deprived quintiles. Reductions in serum cholesterol resulted in 1280 fewer deaths; approximately 515 of these were attributable to population-wide changes in diet with more deaths prevented in the most deprived quintile compared with the least deprived (170 vs. 45 DPPs; relative contribution 13.8% and 4.7%). Conversely, approximately 770 fewer deaths were attributable to statin use, with very similar absolute numbers of deaths prevented in most (140) and least (140) deprived quintiles, but relatively greater contributions in the least deprived (15.4% vs 11.2%). Statin uptake was higher in the most deprived areas (17% vs 13.2%). Conclusion Population-wide falls in blood pressure helped to reduce CHD mortality; however the benefit from hypertension treatment was small. Improved diet and statins for high-risk individuals both made important contributions to the fall in population cholesterol. Population-wide falls in blood pressure and reductions due to medical treatments for hypertension were equitable between socio-economic groups. Higher socio-economic groups appeared to benefit more from statins, probably due to better compliance; this may perpetuate inequalities.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.522

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.389
GPT teacher head0.482
Teacher spread0.094 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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