Evidence map›Paper›PMID 26633704›Full record

ArticlePloS one2015

What Are the Major Determinants in the Success of Smoking Cessation: Results from the Health Examinees Study.

Jae Jeong Yang, Minkyo Song, Hyung-Suk Yoon, Hwi-Won Lee, Yunhee Lee, Sang-Ah Lee, Ji-Yeob Choi, Jong-Koo Lee, Daehee Kang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

43 citing papers in PubMed, 76 citations in OpenAlex.

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  9. The Rise of Gastrointestinal Cancers as a Global Phenomenon: Unhealthy Behavior or Progress?International journal of environmental research and public health · 2023
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  14. Trajectories of motivation and self-efficacy during a smoking quit attempt: An ecological momentary assessment study.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2022
    Article
  15. Observational
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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

9 authors at 3 institutions in 1 country.

Jae Jeong YangDepartment of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
Minkyo SongDepartment of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
Hyung-Suk YoonDepartment of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
Hwi-Won LeeDepartment of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
Yunhee LeeDepartment of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
Sang-Ah LeeDepartment of Preventive Medicine, Kangwon National University, Kangwon-do, Korea.
Ji-Yeob ChoiDepartment of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
Jong-Koo LeeJW Lee Center for Global Medicine, Seoul National University College of Medicine, Seoul, Korea.
Daehee KangDepartment of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
Seoul National University · KRSeoul National University Hospital · KRKangwon National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding mechanisms underlying smoking-related factors should be prioritized in establishing smoking prevention and cessation policy. The aim of this study was to identify factors significantly associated with smoking initiation and/or smoking cessation as well as the most important determinants of successful smoking cessation in a developed non-Western setting. Based on multiple logistic regression models, the odds ratios (ORs) for smoking initiation and cessation were estimated among males (N = 24,490) who had participated in the Health Examinees (HEXA) study. The Cox proportional hazards regression model was used to assess the association between selected predictors of smoking cessation and the likelihood of reaching this goal. Finally, Kaplan-Meier curves were constructed to illustrate the distribution of time from age at smoking initiation to age at smoking cessation. We found that the ORs for successfully quitting smoking increased with age, married status, educational achievement, having a non-manual job, drinking cessation and disease morbidity. Those exposed to secondhand smoking showed less likelihood of quitting smoking. A continual decrease in the ORs for successfully quitting smoking was observed according to increased smoking duration, smoking dose per day and lifetime tobacco exposure (ptrend <0.001). Among the selected predictors, lifetime tobacco exposure, educational attainment, alcohol drinking status and birth cohort were the major determinants in the success of smoking cessation. Our findings suggest that lifetime tobacco exposure, educational attainment, alcohol drinking status and birth cohort can determine success in smoking cessation. Public interventions promoting a smoke-free environment are needed to reinforce discouraging the initiation of, reducing, and quitting cigarette smoking.

Indexed as

AchievementMotivationAdultAgedAlcohol DrinkingEducational StatusFemaleHumansMaleMiddle AgedModels, TheoreticalSmoking CessationTobacco Smoke PollutionTobacco Smoke Pollution

Identifiers

PMID26633704
PMCPMC4669113
OpenAlexW2186060815

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.