Alcohol consumption in Mozambique: Results from a national survey including primary and surrogate respondents
Bibliographic record
Abstract
BACKGROUND: Data on the correspondence between information on alcohol consumption obtained from household members directly interviewed and those evaluated through surrogate respondents are scarce in developing countries. AIM: To estimate alcohol consumption in Mozambique and to compare the information self-reported by subjects directly interviewed with data provided by surrogate respondents referring to household members that were absent during interview. SUBJECTS AND METHODS: A representative sample of 20 033 Mozambicans aged 25-64 years was evaluated in 2003 as part of a national household survey. Face-to-face interviews were conducted using a structured questionnaire assessing socio-demographic and behavioural factors (12 902 participants were directly interviewed and for 7238 data were provided by surrogate respondents). RESULTS: Nearly a quarter of women and half the men were current drinkers, of which about 60% drank 1-2 days/week and more than 75% reported traditional beverages as the most frequently consumed. No meaningful differences were observed between the estimates obtained using only data reported directly by the participants and when surrogate reports were also considered. CONCLUSION: Alcohol consumption was frequent in Mozambique, especially consumption of traditional beverages. Proxy respondents provided valid information on alcohol intake, which may be used to improve the efficiency of household surveys in this setting.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".