Evidence map›Paper›PMID 23721370›Full record

SynthesisBMC public health2013

The effects of smoke-free legislation on acute myocardial infarction: a systematic review and meta-analysis.

Hualiang Lin, Hongchun Wang, Wei Wu, Lingling Lang, Qinzhou Wang, Linwei Tian

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMC public health, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 4 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

31 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  11. Support for smoke-free public places among adults in four countries in sub-Saharan Africa.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2020
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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

6 authors.

Hualiang LinGuangdong Provincial Institute of Public Health, Guangzhou, China.
Hongchun Wang
Wei Wu
Lingling Lang
Qinzhou Wang
Linwei Tian

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComprehensive smoke-free legislation has been implemented in many countries. The current study quantitatively examined the reduction in risk of acute myocardial infarction (MI) occurrence following the legislations and the relationship with the corresponding smoking prevalence decrease.

methodsPubMed, EMBASE, and Google Scholar databases and bibliographies of relevant studies and reviews were searched for potential original studies published from January 1, 2004, through October 31, 2011. Meta-analysis was performed using a random effect model to estimate the overall effects of the smoking-free legislations. Meta-regression was used to investigate possible causes of heterogeneity in risk estimates.

resultsA total of 18 eligible studies with 44 estimates of effect size were used in this study. Meta-analysis produced a pooled estimate of the relative risk of 0.87 (95% confidence interval (CI): 0.84 to 0.91). There was significant heterogeneity in the risk estimates (overall I² = 96.03%, p<0.001). In meta-regression analysis, studies with greater smoking prevalence decrease produced larger relative risk (adjusted coefficient -0.027, 95% CI: -0.049 to -0.006, p=0.014).

conclusionSmoke-free legislations in public and work places were associated with significant reduction in acute MI risk, which might be partly attributable to reduced smoking prevalence.

Indexed as

Air Pollution, IndoorHumansMyocardial InfarctionRisk FactorsSmoke-Free PolicySmokingTobacco Smoke PollutionTobacco Smoke Pollution

Identifiers

PMID23721370
PMCPMC3671962

What OpenQuestion holds

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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.