Evidence map›Paper›PMID 29165167›Full record

ArticleEnvironmental health and preventive medicine2017

The relation between cigarette taxes and older adult smoking in Zhejiang and Gansu: what happened following the 2009 Chinese Tax adjustments?

Qing Wang

Abstract read
In one paragraph

Article in Environmental health and preventive medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

  1. Pooled it
  2. 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

1 author.

Qing WangSchool of business, Dalian University of Technology, Panjin, 124221, Liaoning, China. qingwang@dlut.edu.cn.

Funding

Liaoning Finance Fund 16C011the Fundamental Research Funds for the Central Universities DUT15RC (3) 061the National Natural Science Foundation of China 71503059the Social Science Foundation of Dalian 2016dlskyb005
6 · The paper itself

Abstract

backgroundIn May 2009, the Chinese government raised cigarette excise tax rates and adjusted standards for Grade A cigarettes and Grade B cigarettes. The present study aimed to examine the effects of the tax adjustments in 2009 on smoking behaviors and health outcomes among smokers aged above 45.

methodsData from the 2008 and 2012 China Health and Retirement Longitudinal Study of Zhejiang and Gansu provinces were used to estimate the influence of tax increase on the number of cigarettes smoked daily and health capital. The sample included 706 smokers who were 45 years old and older at the time of data collection in 2008. The sample group was surveyed again in 2012. The final sample size was 1366. Logit model was applied.

resultsCigarette tax adjustment in 2009 resulted in the decrease in the likelihood of smoking 0-10 cigarettes per day by 1.06%; the increase in the likelihood of those smoking 11-20 cigarettes per day by 0.44%; and, those smoking 20 cigarettes or more by 0.63%; the decrease in the likelihood of good health by 0.47%; the increase in the prevalence of chronic disease by 1.34%.

conclusionsThe smoke tax adjustment in 2009 worsened individual unhealthy smoking behaviors and health outcomes. The proposed cigarette tax levied at the retail level can reduce the State Tobacco Monopoly Administration's control overall and each price and increase the influence of the market on cigarette consumption in China.

Indexed as

AgedAged, 80 and overChinaFemaleHumansLongitudinal StudiesMaleMiddle AgedPrevalenceSmokingTaxesTobacco IndustryTobacco ProductsTobacco SmokingChinaChronic diseaseCigarette excise tax ratesDaily consumed cigarettes numberSelf-reported healthSmoking

Identifiers

PMID29165167
PMCPMC5664447

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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.