Socio-economic inequalities in high blood pressure and additional risk factors for cardiovascular disease among older individuals in Colombia: Results from a nationally representative study
Bibliographic record
Abstract
BACKGROUND: Studies in high-income countries have documented a consistent gradient between socio-economic status (SES) and high blood pressure (HBP), a key risk factor for cardiovascular disease (CVD). However, evidence from Latin American countries (LA) remains comparatively scarce and inconclusive. DATA: Data for 3,984 individuals came from a nationally representative survey of individuals aged 60 years or above in Colombia (Encuesta de Salud, Bienestar y Envejecimiento) (SABE) conducted in 2015. SES was measured by educational achievement and household assets. CVD risk factors included objectively measured HBP and body mass index (BMI), as well as behaviors (smoking, alcohol consumption, fruit and vegetables intake, and physical activity). METHODS: Bivariate methods and multivariate regression models were used to assess associations between SES with HBP as well as additional risk factors for CVD. RESULTS: Individuals with lower SES have significantly higher risk of suffering from HBP. Compared to those with no formal education, individuals with secondary or post-secondary education have a 37% lower risk of HBP (odds ratio [OR] = 0.63, P-value<0.001). Being in the highest asset quartile (most affluent) is associated with a 44% lower risk (OR = 56, P-value = 0.001) of HBP compared to those in the lowest asset quartile (most deprived). Individuals with lower SES are more likely to smoke, not engage in regular physical activity and not regularly consume fruits or vegetables. In contrast, individuals with higher SES are more likely to consume alcohol and, those with more assets, more likely to be obese. CONCLUSIONS: Among older Colombians there exists a marked SES gradient in HBP as well as several additional risk factors for CVD. The results highlight the importance of a public health approach towards HBP and additional CVD risk factors that takes into account the specific conditions of older individuals, especially among disadvantaged groups.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".