Utilização de medicamentos pela população quilombola: inquérito no Sudoeste da Bahia
Bibliographic record
Abstract
OBJECTIVE: To characterize the medication use by the quilombola population. METHODS: A population-based cross-sectional study was conducted with 797 adult quilombola in Vitória da Conquista, BA, Northeastern Brazil, in 2011. Analysis of variance was used to compare means of drugs by subject, according to demographic, socioeconomic and health-related behavior variables. Prevalence, prevalence ratios and their 95% confidence intervals were estimated. Multivariate analysis was carried out using Poisson regression with robust variance. RESULTS: The most widely consumed drugs by the population were those for the cardiovascular and nervous systems. Prevalence of medication use was 41.9%, significantly higher among women (50.3%) than men (31.9%). After adjusted analysis, medication use was associated with being female gender, being aged 60 or older, higher economic level, worse self-rated health, greater number of self-reported diseases and number of medical appointments. CONCLUSIONS: Strategies to improve rational drug use should preferentially focus on women and older adults. Thus, special attention should be given to promote rational prescription in everyday health services.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".