Evidence map›Paper›PMID 34229627›Full record

ArticleBMC public health2021

Factors influencing smoking behaviour of online ride-hailing drivers in China: a cross-sectional analysis.

Xinlin Chen, Xuefei Gu, Tingting Li, Qiaoyan Liu, Lirong Xu, Bo Peng, Nina Wu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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  7. Co-Design of an eHealth Intervention to Reduce Cardiovascular Disease Risk in Male Taxi Drivers: ManGuard.International journal of environmental research and public health · 2022
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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

7 authors.

Xinlin ChenSchool of Public Health, Capital Medical University, No 10 Xitoutiao, Youanmenwai Street, Fengtai District, Beijing, China.
Xuefei GuChina National Health Development Research Center, Beijing, China.
Tingting LiChina National Health Development Research Center, Beijing, China.
Qiaoyan LiuChina Rehabilitation Research Center, Beijing, China.
Lirong XuSchool of Public Health, Capital Medical University, No 10 Xitoutiao, Youanmenwai Street, Fengtai District, Beijing, China.
Bo PengInstitute of Medical Information, China Academy of Chinese Medical Sciences, Beijing, China.
Nina WuSchool of Public Health, Capital Medical University, No 10 Xitoutiao, Youanmenwai Street, Fengtai District, Beijing, China. wunina@ccmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOnline ride-hailing is a fast-developing new travel mode. However, tobacco control policies on its drivers remain underdeveloped. This study aims to reveal the status and determine the influencing factors of ride-hailing drivers' smoking behaviour to provide a basis for the formulation of tobacco control policies.

methodsWe derived our cross-sectional data from an online survey of full-time ride-hailing drivers in China. We used a survey questionnaire to collect variables, including sociodemographic and work-related characteristics, health status, health behaviour, health literacy and smoking status. Finally, we analysed the influencing factors of current smoking by conducting chi-square test and multivariate logistic regression.

resultsA total of 8990 ride-hailing drivers have participated in the survey, in which 5024 were current smokers, accounting to 55.9%. Nearly one-third of smokers smoked in their cars (32.2%). The logistic regression analysis results were as follows: male drivers (OR = 0.519, 95% CI [0.416, 0.647]), central regions (OR = 1.172, 95% CI [1.049, 1.309]) and eastern regions (OR = 1.330, 95% CI [1.194, 1.480]), working at both daytime and night (OR = 1.287, 95% CI [1.164, 1.424]) and non-fixed time (OR = 0.847, 95% CI [0.718, 0.999]), ages of 35-54 years (OR = 0.585, 95% CI [0.408, 0.829]), current drinker (OR = 1.663, 95% CI [1.526, 1.813]), irregular eating habits (OR = 1.370, 95% CI [1.233, 1.523]), the number of days in a week of engaging in at least 10 min of moderate or vigorous exercise ≥3 (OR = 0.752, 95% CI [0.646, 0.875]), taking the initiative to acquire health knowledge occasionally (OR = 0.882, 95% CI [0.783, 0.992]) or frequently (OR = 0.675, 95% CI [0.591, 0.770]) and underweight (OR = 1.249, 95% CI [1.001, 1.559]) and overweight (OR = 0.846, 95% CI [0.775, 0.924]) have association with the prevalence of current smoking amongst online ride-hailing drivers.

conclusionThe smoking rate of ride-hailing drivers was high. Sociodemographic and work-related characteristics and health-related factors affected their smoking behaviour. Psychological and behavioural interventions can promote smoking control management and encourage drivers to quit or limit smoking. Online car-hailing companies can also establish a complaint mechanism combined with personal credit.

Indexed as

AutomobilesSmokingAdultChinaCross-Sectional StudiesHumansMaleMiddle AgedPrevalenceSmokersChinaDriversInfluencing factorsOnline ride-hailingSmoking

Identifiers

PMID34229627
PMCPMC8259384

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.