Evidence map›Paper›PMID 26420222›Full record

ArticleBMC public health2015

Smoking behaviors before and after implementation of a smoke-free legislation in Guangzhou, China.

Xiaohua Ye, Sidong Chen, Zhenjiang Yao, Yanhui Gao, Ya Xu, Shudong Zhou, Zhengwei Zhu, Liang Wang, Yi Yang

Abstract readComparative Study
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 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  15. Observational
  16. Subnational smoke-free laws in China.Tobacco induced diseases · 2019
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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.

Xiaohua YeDepartment of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China. smalltomato@163.com.
Sidong ChenDepartment of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China. sdchen2@126.com.
Zhenjiang YaoDepartment of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China. zhjyao2001@yahoo.com.
Yanhui GaoDepartment of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China. gao_yanhui@163.com.
Ya XuDepartment of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China. yaoxuya@163.com.
Shudong ZhouDepartment of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China. 13802733994@139.com.
Zhengwei ZhuGuangzhou Association on Tobacco Control, Guangzhou, China. zhu.zhengwei@163.com.
Liang WangCollege of Public Health, East Tennessee State University, Johnson, USA. WANGL2@etsu.edu.
Yi YangDepartment of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China. yangyigz@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccording to the partial smoke-free legislation implemented on 1 September 2010 in Guangzhou, China, smoke-free did not cover all indoor areas. Some places have a full smoking ban (100 % smoke-free), other places have a partial smoking ban, and homes have no ban. This study aimed to compare the smoking behaviors before and after implementation of a smoke-free legislation.

methodA repeated cross-sectional survey was conducted on smoking-related behaviors with a total of 4,900 respondents before, and 5,135 respondents after the legislation was instituted. For each wave of the survey, a three-stage stratified sampling process was used to obtain a representative sample. Pearson's Chi-square test was used to determine differences of smoking prevalence and quit ratio between the two samples. Logistic regression models were used to examine the associations of a smoke-free legislation with smoking behaviors.

resultsThe overall daily smoking rate declined significantly from 20.8 % to 18.2 % (p < 0.05), especially among those aged 15-24 years. The quit ratios increased significantly (from 14.5 % to 17.9 %), but remained low among 15-44 year olds. The overall self-reported smoking behaviors in locations with a full smoking ban decreased significantly from 36.4 % to 24.3 % with the greater drops occurring in cultural venues, public transport vehicles, and government offices. Smoking in places with partial smoking bans remained high (89.6 % vs. 90.4 %), although a slight decrease was observed in some of these areas. The implementation of a smoke-free legislation did not lead to more smoking in homes (91.0 % vs 89.4 %), but smoking in homes remained high.

conclusionsThese findings highlight the urgent need for a comprehensive smoke-free legislation covering all public places in Guangzhou, simultaneously educational interventions and campaigns promoting voluntary changes in home smoking need to occur.

Indexed as

Government RegulationHealth BehaviorSmoking PreventionAdolescentAdultAgedChinaCross-Sectional StudiesFemaleHumansLogistic ModelsMaleMiddle AgedPrevalenceSelf ReportSmokeSmokeTobacco Smoke Pollution

Identifiers

PMID26420222
PMCPMC4588461

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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.