Association of Socioeconomic Disparities and Predisposing Factors with Higher Prevalence of Hypertension related Left Ventricular Hypertrophy in Males: a Malaysian Community-Based Study
Bibliographic record
Abstract
ABSTRACT Left Ventricular Hypertrophy (LVH) is a risk for various cardiovascular events among those with hypertension (HT). However the prevalence of hypertension-related LVH (HT LVH+) in communities with lower socioeconomic status (SES) is not adequately reported. This study investigated the prevalence of HT LVH+ among the urban and rural males and the attributing factors. A total of 1,923 males who had echocardiographic examinations done were recruited. Their blood pressure was measured to diagnose those with or without hypertension. Left ventricular mass index was determined. Univariate analysis was performed to identify associated factors predisposing to LVH. A total of 992 males had HT, of which 264 had LVH, and were more prevalent in older age groups and Malays (p<0.001). Individuals from rural areas, with low income and low educational background were associated with higher LVH prevalence (p<0.001). Those with moderate aortic regurgitation was 3.17-fold higher in LVH. Ninety-nine normotensives had LVH, 71.7% came from rural. Total cholesterol and low density lipoprotein cholesterol levels were significantly higher in HT LVH+ from urban than the rural areas (p=0.029 and p=0.002, respectively). A quarter of the HT population in Malaysia develop LVH, majority of them were from rural, indicating that socioeconomic disparities contribute to the higher risk of HT LVH+. The rural populations may have attributed to different risk factors as opposed to those from urban, hence emphasize the need to deliver targeted strategies for prevention and management HT LVH+ by different SES.
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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".