Evidence map›Paper›PMID 25886500›Full record

ArticleBMC public health2015

Determinants of tobacco smoking among rural-to-urban migrant workers: a cross-sectional survey in Shanghai.

Yao Liu, Huijiang Song, Tianying Wang, Tianhao Wang, Hua Yang, Jian Gong, Yao Shen, Wei Dai, Jing Zhou, Shanzhu Zhu and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.0field-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

25 citing papers in PubMed, 54 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

11 authors at 4 institutions in 1 country.

Yao LiuDepartment of General Practice, Zhongshan Hospital Fudan University, 180 Fenglin Road, Shanghai, 20032, China. yao_liuliu@163.com.
Huijiang SongDepartment of General Practice, Sanlin Community Health Service Center, 375 Sanlin Road, Shanghai, 200124, China. songhj008@126.com.
Tianying WangDepartment of General Practice, Sanlin Community Health Service Center, 375 Sanlin Road, Shanghai, 200124, China. yktjw2008@163.com.
Tianhao WangDepartment of General Practice, Zhongshan Hospital Fudan University, 180 Fenglin Road, Shanghai, 20032, China. tianhao74@hotmail.com.
Hua YangDepartment of General Practice, Zhongshan Hospital Fudan University, 180 Fenglin Road, Shanghai, 20032, China. yokieyoung@hotmail.com.
Jian GongDepartment of General Practice, Zhongshan Hospital Fudan University, 180 Fenglin Road, Shanghai, 20032, China. gongjian0518@126.com.
Yao ShenDepartment of General Practice, Zhongshan Hospital Fudan University, 180 Fenglin Road, Shanghai, 20032, China. 13611692261@163.com.
Wei DaiDepartment of General Practice, Zhongshan Hospital Fudan University, 180 Fenglin Road, Shanghai, 20032, China. Vavien77@sina.com.
Jing ZhouDepartment of General Practice, Zhongshan Hospital Fudan University, 180 Fenglin Road, Shanghai, 20032, China. dreamingkoala@126.com.
Shanzhu ZhuDepartment of General Practice, Zhongshan Hospital Fudan University, 180 Fenglin Road, Shanghai, 20032, China. zhu_shanzhu@126.com.
Zhigang PanDepartment of General Practice, Zhongshan Hospital Fudan University, 180 Fenglin Road, Shanghai, 20032, China. zhigang_pan@163.com.
Sun Yat-sen University · CNFudan University · CNThe First Affiliated Hospital, Sun Yat-sen University · CNZhongshan Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough there are several studies to investigate the smoking behaviors among rural-to-urban Chinese migrants, no study has focused individually on this population in Shanghai. This study was performed to estimate the prevalence and identify the determinants of tobacco smoking among rural-to-urban migrants in Shanghai.

methodsIn this cross-sectional study, multi-stage quota sampling was used to select 5,856 rural-to-urban migrants aged 18 years or older from seven districts in Shanghai between July and October 2012. A structured questionnaire was administered to assess smoking knowledge, attitude, behavior and demographic characteristics. Mental health was assessed by the self-reported SCL-90. Multiple logistic regression analysis was used to determine the risk factors of smoking behavior.

resultsA total of 5,380 of the 5,856 migrants enrolled completed the questionnaire, among whom 45.0% of male and 2.0% of female participants reported current smoking. Multivariate analysis revealed current smoking in female migrants to be significantly associated with working at construction (OR, 8.08; 95% CI, 1.80-36.28), hotels/restaurants (OR, 5.06; 95% CI, 1.68-15.27), entertainment sector (OR, 6.79; 95% CI, 2.51-18.42), with monthly income > 3500 yuan (OR, 2.69; 95% CI, 1.21-5.98), number of migratory cities of 2 (OR, 2.39; 95% CI, 1.23-4.65), and SCL-90 total score > 160 (OR, 2.03; 95% CI, 1.03-3.98), while the male migrants working at construction (OR, 1.30; 95% CI, 1.04-1.62), entertainment sector (OR, 1.86; 95% CI, 1.36-2.56), being divorced/widowed (OR, 2.20; 95% CI, 1.02-4.74), with duration of migration of 4 or more than 4 years (OR, 1.42; 95% CI, 1.06-1.91), number of migratory cities of 3 or more than 3 (OR, 1.42; 95% CI, 1.13-1.80), and SCL-90 total score > 160 (OR,1.39; 95% CI, 1.07-1.79) showed an excess smoking prevalence.

conclusionMigration lifestyle and mental status were associated with current smoking behaviors. The identifications of risk factors for current smoking may help to target health promotion interventions.

Indexed as

Mental HealthAgedAsian PeopleChinaCross-Sectional StudiesFemaleHealth Knowledge, Attitudes, PracticeHumansMaleMiddle AgedMultivariate AnalysisOccupationsPrevalenceResidence CharacteristicsRisk FactorsSmoking

Identifiers

PMID25886500
PMCPMC4334770
OpenAlexW2047226794

What OpenQuestion holds

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LicenceCC BY
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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.