Neighbourhood deprivation and smoking and quit behaviour among smokers in Mexico: findings from the ITC Mexico Survey
Bibliographic record
Abstract
BACKGROUND: In high-income countries (HICs), higher neighbourhood socioeconomic deprivation is associated with higher levels of smoking. Few studies in low-income and middle-income countries (LMICs) have investigated the role of the neighbourhood environment on smoking behaviour. OBJECTIVE: To determine whether neighbourhood socioeconomic deprivation is related to smoking intensity, quit attempts, quit success and smoking relapse among a cohort of smokers in Mexico from 2010 to 2012. METHODS: Data were analysed from adult smokers and recent ex-smokers who participated in waves 4-6 of the International Tobacco Control (ITC) Mexico Survey. Data were linked to the Mexican government's composite index of neighbourhood socioeconomic deprivation, which is based on 2010 Mexican Census data. We used generalised estimating equations to determine associations between neighbourhood deprivation and individual smoking behaviours. FINDINGS: Contrary to past findings in HICs, higher neighbourhood socioeconomic deprivation was associated with lower smoking intensity. Quit attempts showed a U-shaped pattern whereby smokers living in high/very high deprivation neighbourhoods and smokers living in very low deprivation neighbourhoods were more likely to make a quit attempt than smokers living in other neighbourhoods. We did not find significant differences in neighbourhood deprivation on relapse or successful quitting, with the possible exception of people living in medium-deprivation neighbourhoods having a higher likelihood of successful quitting than people living in very low deprivation neighbourhoods (p=0.06). CONCLUSIONS: Neighbourhood socioeconomic environments in Mexico appear to operate in an opposing manner to those in HICs. Further research should investigate whether rapid implementation of strong tobacco control policies in LMICs, as occurred in Mexico during the follow-up period, avoids the concentration of tobacco-related disparities among socioeconomically disadvantaged groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".