Evidence map›Paper›PMID 21108783›Full record

ArticleBMC public health2010

Estimation of cancer incidence and mortality attributable to alcohol drinking in China.

Hao Liang, Jianbing Wang, Huijuan Xiao, Ding Wang, Wenqiang Wei, Youlin Qiao, Paolo Boffetta

Abstract read
In one paragraph

Article in BMC public health, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 3 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

31 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  16. Esophageal cancer genetics in South Africa.Clinical and experimental gastroenterology · 2019
    Review
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  19. Article
  20. Cancer incidence and mortality in Gansu province, 2012.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2016
    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

7 authors.

Hao LiangDepartment of Cancer Epidemiology, Cancer Institute, Chinese Academy of Medical Sciences, Beijing, China.
Jianbing Wang
Huijuan Xiao
Ding Wang
Wenqiang Wei
Youlin Qiao
Paolo Boffetta

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCancer constitutes a serious burden of disease worldwide and has become the second leading cause of death in China. Alcohol consumption is causally associated with the increased risk of certain cancers. Due to the current lack of data and the imperative need to guide policymakers on issues of cancer prevention and control, we aim to estimate the role of alcohol on the cancer burden in China in 2005.

methodsWe calculated the proportion of cancers attributable to alcohol use to estimate the burden of alcohol-related cancer. The population attributable fraction was calculated based on the assumption of no alcohol drinking. Data on alcohol drinking prevalence were from two large-scale national surveys of representative samples of the Chinese population. Data on relative risk were obtained from meta-analyses and large-scale studies.

resultsWe found that a total of 78,881 cancer deaths were attributable to alcohol drinking in China in 2005, representing 4.40% of all cancers (6.69% in men, 0.42% in women). The corresponding figure for cancer incidence was 93,596 cases (3.63% of all cancer cases). Liver cancer was the main alcohol-related cancer, contributing more than 60% of alcohol-related cancers.

conclusionsParticular attention needs to be paid to the harm of alcohol as well as its potential benefits when making public health recommendations on alcohol drinking.

Indexed as

AdolescentAgedAlcohol DrinkingChinaFemaleForecastingHumansMaleMeta-Analysis as TopicMiddle AgedNeoplasmsPublic Health

Identifiers

PMID21108783
PMCPMC3009646

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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.