Factors Associated with Changes in E-Cigarette Use and Tobacco Smoking by Adolescents and Young People in Nigeria during the COVID-19 Pandemic
Bibliographic record
Abstract
This study aimed to assess the proportion of adolescents and young people (AYP) in Nigeria who changed their frequency of e-cigarette use and tobacco smoking during the COVID-19 pandemic; and factors associated with the increase, decrease or no change in e-cigarette use and tobacco smoking (including night smoking). This study was a cross-sectional study of AYP recruited from all geopolitical zones in the country. Multivariate logistic regression analyses were conducted to determine if respondents’ health HIV and COVID-19 status and anxiety levels were associated with changes in e-cigarette use and tobacco smoking frequency. There were 568 (59.5%) e-cigarette users, of which 188 (33.1%) increased and 70 (12.3%) decreased e-cigarette use and 389 (68.5%) increased night e-cigarette use. There were 787 (82.4%) current tobacco smokers, of which 305 (38.8%) increased and 102 (13.0%) decreased tobacco smoking and 534 (67.9%) increased night tobacco smoking. Having a medical condition was associated with lower odds of increased e-cigarette use (AOR:0.649; p = 0.031). High anxiety (AOR:0.437; p = 0.027) and having a medical condition (AOR:0.554; p = 0.044) were associated with lower odds of decreased e-cigarette use. Having COVID-19 symptoms (AOR:2.108; p < 0.001) and moderate anxiety (AOR:2.138; p = 0.006) were associated with higher odds of increased night e-cigarette use. We found complex relationships between having a medical condition, experiencing anxiety, changes in tobacco smoking and e-cigarette use among AYP in Nigeria during the COVID-19 pandemic that need to be studied further.
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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 | 0.001 |
| 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) | 0.000 | 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".