Evidence map›Paper›PMID 32447314›Full record

ArticleTobacco control2020

Future smoking prevalence by socioeconomic status in England: a computational modelling study.

Fujian Song, Tim Elwell-Sutton, Felix Naughton, Sarah Gentry

Abstract read
In one paragraph

Article in Tobacco control, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

8 citing papers in PubMed.

  1. Trial
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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

4 authors.

Fujian SongNorwich Medical School, University of East Anglia, Norwich, UK fujian.song@uea.ac.uk.ORCID http://orcid.org/0000-0002-4039-1531
Tim Elwell-SuttonNorwich Medical School, University of East Anglia, Norwich, UK.
Felix NaughtonSchool of Health Sciences, University of East Anglia, Norwich, UK.
Sarah GentryNorwich Medical School, University of East Anglia, Norwich, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe difference in smoking across socioeconomic groups is a major cause of health inequality. This study projected future smoking prevalence by socioeconomic status, and revealed what is needed to achieve the tobacco-free ambition (TFA) by 2030 in England.

methodsUsing data from multiple sources, the adult (≥18 years) population in England was separated into subgroups by smoking and highest educational qualification (HEQ). A discrete time state-transition model was used to project future smoking prevalence by HEQ deterministically and stochastically.

resultsIn a status quo scenario, smoking prevalence in England is projected to be 10.8% (95% uncertainty interval: 9.1% to 12.9%) by 2022, 7.8% (5.5% to 11.0%) by 2030 and 6.0% (3.7% to 9.6%) by 2040. The absolute difference in smoking rate between low and high HEQ is reduced from 12.2% in 2016 to 7.9% by 2030, but the relative inequality (low/high HEQ ratio) is increased from 2.48 in 2016 to 3.06 by 2030. When applying 2016 initiation/relapse rates, achievement of the TFA target requires no changes to future cessation rates among adults with high qualifications, but increased rates of 37% and 149%, respectively, in adults with intermediate and low qualifications.

conclusionsIf the current trends continue, smoking prevalence in England is projected to decline in the future, but with substantial differences across socioeconomic groups. Absolute inequalities in smoking are likely to decline and relative inequalities in smoking are likely to increase in future. The achievement of England's TFA will require the reduction of both absolute and relative inequalities in smoking by socioeconomic status.

Indexed as

cessationdisparitiesend gamesocioeconomic status

Identifiers

PMID32447314
PMCPMC8237189

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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.