Direct and indirect costs of smoking in Vietnam
Bibliographic record
Abstract
OBJECTIVE: To estimate the direct and indirect costs of active smoking in Vietnam. METHOD: A prevalence-based disease-specific cost of illness approach was utilised to calculate the costs related to five smoking-related diseases: lung cancer, cancers of the upper aerodigestive tract, chronic obstructive pulmonary disease, ischaemic heart disease and stroke. Data on healthcare came from an original survey, hospital records and official government statistics. Morbidity and mortality due to smoking combined with the average per capita income were used to calculate the indirect costs of smoking by applying the human capital approach. The smoking-attributable fraction was calculated using the adjusted relative risk values from phase II of the American Cancer Society Cancer Prevention Study (CPS-II). Costs were classified as personal, governmental and health insurance costs. RESULTS: The total economic cost of smoking in 2011 was estimated at 24 679.9 billion Vietnamese dong (VND), equivalent to US$1173.2 million or approximately 0.97% of the 2011 gross domestic product. The direct costs of inpatient and outpatient care reached 9896.2 billion VND (US$470.4 million) and 2567.2 billion VND (US$122.0 million), respectively. The government's contribution to these costs was 4534.3 billion VND (US$215.5 million), which was equivalent to 5.76% of its 2011 healthcare budget. The indirect costs (productivity loss) due to morbidity and mortality were 2652.9 billion VND (US$126.1 million) and 9563.5 billion VND (US$454.6 million), respectively. These indirect costs represent about 49.5% of the total costs of smoking. CONCLUSIONS: Tobacco consumption has large negative consequences on the Vietnamese economy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".