Changes in parental smoking behavior and children's health status in Chile
Bibliographic record
Abstract
Studies on parental smoking behavior have mostly been conducted for developed countries and show that current parental smoking is negatively associated with children's current health. Using four waves of a Chilean longitudinal survey (Encuesta de Protección Social), we estimate probit and ordinary least squares models relating parents' self-report of their children's current health status to several covariates, including current parental smoking status and change (transitions) in parental smoking status across the waves of the survey. The data were collected in the years 2004, 2006, 2009, and 2015. The working sample includes 25,052 observations. The study revealed that parents' self-report of their children's current health status is strongly associated with current and past parental smoking status. Parents who smoke have an increased 11.17% probability of reporting that their children are in fair, poor, or very poor health status, when compared to non-smoking parents. The effect is stronger if the smoker is the mother, and it is exacerbated if she is less educated or unemployed/inactive. In addition, quitting smoking has a significant positive effect on children's reported health status, which is greater if the mother quits smoking. Cessation among mothers who are unemployed or inactive is also associated with a more positive assessment of their children's health status. The findings suggest that cessation programs may have health benefits not only for smoking parents, but also for their children. Improving coverage or establishing a national cessation program may have important present and future effects on population health and well-being.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".