Latent Trajectories and Profiles of Commercial Cigarette Smoking Frequency From Adolescence to Young Adulthood Among North American Indigenous People
Bibliographic record
Abstract
INTRODUCTION: North American Indigenous people (ie, American Indian/Alaska Native and Canadian First Nations) have the highest rates of commercial cigarette smoking, yet little is known about long-term trajectories of use among this population. The purpose of this study is to examine heterogeneous trajectories and profiles of Indigenous cigarette use frequency from early adolescence (mean age: 11.1 years) to young adulthood (mean age: 26.3 years). AIMS AND METHODS: Data come from a nine-wave prospective longitudinal study spanning early adolescence through young adulthood among Indigenous people in the Upper Midwest of the United States and Canada (N = 706). Smoking frequency was examined at each wave, and latent class growth analysis was used to examine heterogeneous patterns. Early adolescent and young adult demographics and smoking-related characteristics were examined across these latent trajectory groups. RESULTS: In young adulthood, 52% of participants smoked daily/near-daily, and an additional 10% smoked weekly or monthly. Four latent trajectory groups emerged: low/non-smokers (35.2%) who had low probabilities of smoking across the study; occasional smokers (17.2%) who had moderate probabilities of smoking throughout adolescence and declining probabilities of smoking into young adulthood; mid-adolescent onset smokers (21.6%) who showed patterns of smoking onset around mid-adolescence and escalated to daily use in young adulthood; and early-adolescent onset smokers (25.9%) who showed patterns of onset in early adolescence and escalated to stable daily use by late adolescence. CONCLUSIONS: The findings suggest multiple critical periods of smoking risk, as well as a general profile of diverse smoking frequency patterns, which can inform targeted intervention and treatment programming. IMPLICATIONS: Nearly two-thirds (62%) of this sample of Indigenous people were current smokers by early adulthood (mean age = 26.3 years), which is substantially higher than national rates in the United States and Canada. Moreover, in all but one trajectory group, smoking prevalence consistently increased over time, suggesting these rates may continue to rise into adulthood. The longitudinal mixture modeling approach used in this study shows that smoking patterns are heterogeneous, and implications for public health policy likely vary across these diverse patterns characterized by timing of onset of use, escalation in frequency of use, and stability/change over time.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".