Changes in ideal cardiovascular health among Malawian adults from 2009 to 2017
Bibliographic record
Abstract
Abstract Ideal Cardiovascular Health (CVH) is a concept defined by the American Heart Association (AHA) as part of its 2020 Impact Goals. Until now, changes in ideal CVH have been poorly evaluated in Sub-Saharan African populations. We aimed to investigate changes in the prevalence of ideal CVH and its components in a population of Malawian adults. Secondary analysis was done on cross-sectional data from 2009 to 2017, obtained from the Malawi STEPS surveys which included 5730 participants aged 25–64 years. CVH metrics categorized into “ideal (6–7 ideal metrics)”, “intermediate (3–5 ideal metrics)” and “poor (0–2 ideal metrics)” were computed using blood pressure, body mass index (BMI), fasting glycaemia, fruit and vegetable intake, physical activity, smoking, and total cholesterol. Sampling weights were used to account for the sampling design, and all estimates were standardised by age and sex using the direct method. The mean participant age across both periods was 40.1 ± 12.4 years. The prevalence of meeting ≥ 6 ideal CVH metrics increased substantially from 9.4% in 2009 to 33.3% in 2017, whereas having ≤ 2 ideal CVH metrics decreased from 7.6% to 0.5% over this time. For the individual metrics, desirable levels of smoking, fruit and vegetable intake, physical activity, blood pressure (BP), total cholesterol and fasting glucose all increased during the study period whilst achievable levels of BMI (< 25 kg/m2) declined. From 2009 to 2017, the mean number of ideal CVH metrics was higher in women compared to men (from 2.1% to 5.1% vs 2.0% to 5.0%). However, poor levels of smoking and fruit and vegetable intake were higher in men compared to women (from 27.9% to 23.6% vs. 7.4%% to 1.9% , and from 33.7% to 42.9% vs 30.8% to 34.6%, respectively). Also, whilst achievable levels of BMI rose in men (from 84.4% to 86.2%) the proportion reduced in women (from 72.1% to 67.5% ). Overall, CVH improved in Malawian adults from 2009 to 2017 and was highest in women. However, the prevalence of poor fruit and vegetable intake, and poor smoking remained high in men whilst optimal levels of BMI was declined in women. To improve this situation, individual and population-based strategies that address body mass, smoking and fruit and vegetable intake are warranted for maximal health gains in stemming the development of cardiovascular events.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".