Evidence map›Paper›PMID 11854347›Full record

ArticleJournal of epidemiology and community health2002

Smoking in young adolescents: an approach with multilevel discrete choice models.

J Pinilla, B González, P Barber, Y Santana

Abstract read
In one paragraph

Article in Journal of epidemiology and community health, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. School policies for preventing smoking among young people.The Cochrane database of systematic reviews · 2014
    Pooled it
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  14. Effect of a smoking ban and school-based prevention and control policies on adolescent smoking in Spain: a multilevel analysis.Prevention science : the official journal of the Society for Prevention Research · 2012
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  18. The influence of school smoking policies on student tobacco use.Archives of pediatrics & adolescent medicine · 2007
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  19. Article
  20. Is there a "school effect" on pupil outcomes? A review of multilevel studies.Journal of epidemiology and community health · 2006
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

J PinillaDepartment of Quantitative Methods, University of Las Palmas de Gran Canaria, Canary Islands, Spain.
B González
P Barber
Y Santana

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

objectiveTo understand the context for tobacco smoking in young adolescents, estimating the effects of individual, family, social, and school related factors.

designCross sectional analysis performed by multilevel logistic regression with pupils at the first level and schools at the second level. The data came from a stratified sample of students surveyed on their own, their families' and their friends' smoking habits, their schools, and their awareness of cigarette prices and advertising.

settingThe study was performed in the Island of Gran Canaria, Spain.

participants1877 students from 30 secondary schools in spring of 2000 (model's effective sample sizes 1697 and 1738). MAIN

results14.2% of the young teenagers surveyed use tobacco, almost half of them (6.3% of the total surveyed) on a daily basis. According to the ordered logistic regression model, to have a smoker as the best friend increases significantly the probability of smoking (odds ratio: 6.96, 95% confidence intervals (CI) (4.93 to 9.84), and the same stands for one smoker living at home compared with a smoking free home (odds ratio: 2.03, 95% CI 1.22 to 3.36). Girls smoke more (odds ratio: 1.85, 95% CI 1.33 to 2.59). Experience with alcohol, and lack of interest in studies are also significant factors affecting smoking. Multilevel models of logistic regression showed that factors related to the school affect the smoking behaviour of young teenagers. More specifically, whether a school complies with antismoking rules or not is the main factor to predict smoking prevalence in schools. The remainder of the differences can be attributed to individual and family characteristics, tobacco consumption by parents or other close relatives, and peer group.

conclusionsA great deal of the individual differences in smoking are explained by factors at the school level, therefore the context is very relevant in this case. The most relevant predictors for smoking in young adolescents include some factors related to the schools they attend. One variable stood out in accounting for the school to school differences: how well they enforced the no smoking rule. Therefore we can prevent or delay tobacco smoking in adolescents not only by publicising health risks, but also by better enforcing no smoking rules in schools.

Indexed as

Adolescent BehaviorAdolescentChoice BehaviorCross-Sectional StudiesFamily CharacteristicsFemaleHumansLongitudinal StudiesMalePeer GroupPrevalenceRisk FactorsSmokingSpain

Identifiers

PMID11854347
PMCPMC1732090

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.