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Record W2002188026 · doi:10.1093/ntr/ntq117

Tobacco smoking in urban neighborhoods: Exploring social capital as a protective factor in Santiago, Chile

2010· article· en· W2002188026 on OpenAlexaff
Jaime Sapag, Fernando Poblete, Christiane Eicher, Marcela Aracena, Constanza Caneo, G. Vera, R. Hoyos, L Villarroel, E. Bradford

Bibliographic record

VenueNicotine & Tobacco Research · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsPromotion (chess)MedicineLibrary scienceHumanitiesPolitical scienceArtLaw

Abstract

fetched live from OpenAlex

INTRODUCTION: Research examining the relationship between social capital and health in Latin America has been limited. The aim of this study is to evaluate the association between social capital and tobacco use in four low-income neighborhoods in Santiago, Chile. METHODS: A multistage probability sample was used to select households in 4 of the 10 poorest neighborhoods in the district of Puente Alto, in Santiago, Chile. A cross-sectional survey of 781 participants (81.2% response rate for households) included sociodemographic variables, questions pertaining to neighborhood social capital, and questions pertaining to tobacco. Main analyses were carried out at the individual level by performing a multiple logistic regression of individual tobacco use on individual perceptions of community social capital. RESULTS: The prevalence of smoking was 43.9% of the surveyed population. A five-factor structure for social capital was identified, including "perceived trust in neighbors," "perceived trust in organizations," "reciprocity within the neighborhood," "neighborhood integration," and "social participation." An inverse relationship between trust in neighbors and tobacco smoking was statistically significantly with an adjusted odds ratio of 0.95 (95% CI: 0.91-0.99). Trust in neighbors was also significantly inversely associated with the number of cigarettes smoked. DISCUSSION: Tobacco control remains a significant challenge in global health, requiring innovative strategies that address changing social contexts as well as the changing epidemiological profile of developing regions.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.133
GPT teacher head0.426
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2010
Admission routes1
Has abstractyes

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