Evidence map›Paper›PMID 30111202›Full record

ArticleThe Journal of international medical research2018

Effect of characteristics and life in cities in China on residents' smoking behaviour.

Yang Chen, Hongsheng Chen, Zhigang Li

Abstract read
In one paragraph

Article in The Journal of international medical research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Cigarette smoking and lung function decline beyond quitting.Annals of translational medicine · 2020
    Article
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

3 authors.

Yang Chen1 School of Architecture, Southeast University, Xuanwu District, Nanjing, China.
Hongsheng Chen1 School of Architecture, Southeast University, Xuanwu District, Nanjing, China.ORCID https://orcid.org/0000-0003-3917-4764
Zhigang Li2 School of Urban Design, Wuhan University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective This study aimed to identify the relationship between city-level economic development and smoking behaviour. Methods Using multilevel mixed-effects logistic methods, we examined the relationship between smoking/passive smoking and respondents' lifestyles in the city. Results We found that respondents living in cities with higher per capita gross domestic product (GDP) were less likely to smoke than those living in cities with lower per capita GDP (odds ratio [OR] = 0.977, 95% confidence interval [CI]: 0.958-0.997). Further, respondents with higher levels of life satisfaction and subjective social status were less likely to smoke than those with lower levels of these variables (OR = 0.942, 95% CI: 0.893-0.994; OR = 0.955, 95% CI: 0.928-0.983, respectively). In terms of passive smoking, respondents with higher levels of subjective social status in their cities were less likely to smoke than those with lower levels (OR = 0.972, 95% CI: 0.948-0.996). Smoking and exposure to second-hand smoke were more common among those with lower socioeconomic status. Conclusions Smoking is one of the most serious public health hazards in China. People's smoking behaviour is significantly related to characteristics of their cities and their socioeconomic status. Improved smoking-prevention measures are urgently required in China.

Indexed as

AdultChinaCitiesCross-Sectional StudiesFemaleHumansLife StyleMaleMiddle AgedPersonal SatisfactionSmokingSocial ClassSocioeconomic FactorsTobacco Smoke PollutionUrban PopulationTobacco Smoke PollutionChinaCity lifehealth hazardpassive smokingsmoking behavioursocioeconomic status

Identifiers

PMID30111202
PMCPMC6166327

What OpenQuestion holds

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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.