Hubungan Asupan Serat, Kolesterol, Natrium dan Olahraga Dengan Kadar Kolesterol dan Hipertensi pada Lansia
Bibliographic record
Abstract
Hypercholesterolemia is an excess of cholesterol in the blood, can be factors for heart disease and stroke. The cause of hypertension is heredity, age, sex, obesity (overeating), lack of exercise, stress, excessive salt intake, another effect: smoking, alcohol consumption, taking drugs. The purpose of this study was to determine the relationship of fiber intake, cholesterol, sodium and exercise with cholesterol and hypertension in the elderly group S. Parman Banjarmasin. Type of research is descriptive analytic research using cross sectional design of the study, which was conducted in a group of elderly Regional Health Center S. Parman Banjarmasin. This research was conducted in January through June 2015 with a sample size of 50 people. The data obtained is the intake of cholesterol, sodium, exercise and cholesterol and hypertension. The statistical test used is Chi Square test (p <0.005). The results of this study are most of the respondents were female (68%), most of the respondents aged less than 60 years (56%), and respondents work mostly does not work / housewife (48%). Most fiber intake respondents are not good (96%), cholesterol intake was mostly good (82%), sodium intake are all good (100%), most of the sports activities of respondents are less good (88%), there was no association between dietary fiber intake and kolestero cholesterol levels and hypertension, there is no relationship between exercise activities cholesterol levels and hypertension Keywords: fiber intake, sodium intake, exercise, cholesterol levels, hypertension
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".