Impact of NCD policies on change in blood pressure and cholesterol in the WHO European Region
Bibliographic record
Abstract
Introduction This study aimed to analyse changes in mean systolic blood pressure (SBP) and total cholesterol in relation to non-communicable disease (NCD) policies in the WHO European countries between 2000 and 2014 for men and women. Methods Mean SBP and cholesterol levels for adults aged 25+ years were used from the estimates of Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group. The 2010 WHO Global NCD Country Capacity Survey (CCS) data were used to generate the NCD Policy Score (NCDPS). Absolute change in mean SBP and cholesterol levels between 2000 and 2014 was used to dichotomize countries into low and high performance using changes (2 mmHg in men and 3 mmHg women) as cut-off for SBP and 0.2mmol/L as cut off for change in cholesterol. Mann Whitney-U test was used to compare NCDPS between the groups. Logistic regression was used to analyse the association between NCDPS and change in SBP and cholesterol. R2 values indicated the variability explained in change in SBP and cholesterol by the NCDPS. Results Overall, mean SBP decreased in the WHO European Region, except for increases observed in 9 countries for men and 3 countries for women. Mean NCDPS scores did not differ between men in low and high performance countries (73.3 vs 84.1, p = 0.06). In women, the NCDPS were negatively associated with changes in SBP such that countries with higher NCDPS scores experienced higher SBP decreases (67.9 vs 85.5, p = 0.001). In logistic regression, NCDPS explained 13% and 33% of the variability in mean SBP change in men and women respectively. Mean total cholesterol levels decreased between 2000 and 2014 in all WHO European countries, except for Serbia. Change in cholesterol levels was not significantly associated with NCDPS in univariate or multivariate analyses. Conclusions There is a general decrease in mean SBP and cholesterol levels in WHO European countries between 2000 and 2014. NCD policy score explained more variability in SBP change in women. Key messages: There is a general decrease in mean SBP and cholesterol levels in WHO European countries between 2000 and 2014. A simple NCD control policy score developed from the WHO Global NCD CCS was not associated with the decrease in cholesterol.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".