Secondhand Smoking and Obesity Among Nonsmoking Adolescents Aged 12–15 Years From 38 Low- and Middle-Income Countries
Bibliographic record
Abstract
INTRODUCTION: Secondhand smoking (SHS) may be a risk factor for obesity in adolescence, but data on the association between SHS and obesity are scarce, especially from low- and middle-income countries (LMICs). Therefore, the aim of this study was to assess the association between SHS and obesity among adolescents aged 12-15 years from 38 LMICs. METHODS: Cross-sectional data from 38 LMICs that participated in the Global School-based Student Health Survey (GSHS) were analyzed. Body mass index was calculated based on measured weight and height. The 2007 WHO Child Growth reference was used to define obesity. SHS was categorized as no exposure, non-daily exposure (ie, 1-6 days), and daily exposure (ie, 7 days) based on the number of days exposed to secondhand smoke in the past 7 days. Multivariable logistic regression and meta-analyses were conducted to assess the associations. RESULTS: The analyzed sample consisted of 88 209 adolescents aged 12-15 years who never smoked. The overall prevalence of non-daily and daily SHS was 34.2% and 15.7%, respectively. After adjustment for potential confounders, compared with no SHS, there was no significant association between non-daily SHS and obesity (odds ratio [OR] = 0.94; 95% confidence interval [CI] = 0.86-1.02), but adolescents who reported daily SHS were significantly more likely to have obesity (OR = 1.19; 95% CI = 1.06-1.34). CONCLUSIONS: The prevalence of SHS was high among adolescents in LMICs, and daily SHS was associated with a significant increase in odds of obesity. Future studies with longitudinal designs are warranted to assess causality and whether prevention of SHS can reduce the risk of obesity in adolescence. IMPLICATIONS: In the present large multi-country study on adolescents aged 12-15 years from LMICs, nearly half of the students were exposed to non-daily or daily secondhand smoke. Overall, while non-daily SHS was not significantly associated with obesity, adolescents who reported daily SHS had a significant 1.19 (95% CI = 1.06-1.34) times higher odds of obesity than those who reported no exposure to secondhand smoke. To the best of our knowledge, this is the first multi-country study on SHS and obesity from LMICs, and also the largest study on this topic to date.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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".