Evidence map›Paper›PMID 23237165›Full record

ArticleAmerican journal of public health2013

School and community predictors of smoking: a longitudinal study of Canadian high schools.

Chris Lovato, Allison Watts, K Stephen Brown, Derrick Lee, Catherine Sabiston, Candace Nykiforuk, John Eyles, Steve Manske, H Sharon Campbell, Mary Thompson

Open access · greenAbstract readMulticenter Study
In one paragraph

Article in American journal of public health, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 23% of its field
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

7 citing papers in PubMed, 15 citations in OpenAlex.

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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

10 authors at 1 institution in 1 country.

Chris LovatoSchool of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada. clovato@ubc.ca
Allison Watts
K Stephen Brown
Derrick Lee
Catherine Sabiston
Candace Nykiforuk
John Eyles
Steve Manske
H Sharon Campbell
Mary Thompson
University of Waterloo · CA

Funding

Canadian Institutes of Health Research
6 · The paper itself

Abstract

objectivesWe identified the most effective mix of school-based policies, programs, and regional environments associated with low school smoking rates in a cohort of Canadian high schools over time.

methodsWe collected a comprehensive set of student, school, and community data from a national cohort of 51 high schools in 2004 and 2007. Hierarchical linear modeling was used to predict school and community characteristics associated with school smoking prevalence.

resultsBetween 2004 and 2007, smoking prevalence decreased from 13.3% to 10.7% in cohort schools. Predictors of lower school smoking prevalence included both school characteristics related to prevention programming and community characteristics, including higher cigarette prices, a greater proportion of immigrants, higher education levels, and lower median household income.

conclusionsEffective approaches to reduce adolescent smoking will require interventions that focus on multiple factors. In particular, prevention programming and high pricing for cigarettes sold near schools may contribute to lower school smoking rates, and these factors are amenable to change. A sustained focus on smoking prevention is needed to maintain low levels of adolescent smoking.

Indexed as

AdolescentAdultCanadaCohort StudiesEducational StatusEmigrants and ImmigrantsFemaleHealth PolicyHealth PromotionHumansIncomeLongitudinal StudiesMalePrevalenceResidence CharacteristicsSchools

Identifiers

PMID23237165
PMCPMC3558763
OpenAlexW2121481328

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.