Evidence map›Paper›PMID 34590067›Full record

ArticleThe Lancet regional health. Western Pacific2021

Hepatitis B virus infection among 90 million pregnant women in 2853 Chinese counties, 2015-2020: a national observational study.

Jue Liu, Xiaoyan Wang, Qian Wang, Yaping Qiao, Xi Jin, Zhixin Li, Min Du, Wenxin Yan, Wenzhan Jing, Min Liu and 1 more

Abstract read
In one paragraph

Article in The Lancet regional health. Western Pacific, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

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

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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

11 authors.

Jue LiuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38, Xueyuan Road, Haidian District, Beijing, 100191, China.
Xiaoyan WangNational Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing, No. 12, Dahuishi Road, Haidian District, Beijing, 100081, China.
Qian WangNational Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing, No. 12, Dahuishi Road, Haidian District, Beijing, 100081, China.
Yaping QiaoNational Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing, No. 12, Dahuishi Road, Haidian District, Beijing, 100081, China.
Xi JinNational Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing, No. 12, Dahuishi Road, Haidian District, Beijing, 100081, China.
Zhixin LiNational Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing, No. 12, Dahuishi Road, Haidian District, Beijing, 100081, China.
Min DuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38, Xueyuan Road, Haidian District, Beijing, 100191, China.
Wenxin YanDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38, Xueyuan Road, Haidian District, Beijing, 100191, China.
Wenzhan JingDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38, Xueyuan Road, Haidian District, Beijing, 100191, China.
Min LiuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38, Xueyuan Road, Haidian District, Beijing, 100191, China.
Ailing WangNational Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing, No. 12, Dahuishi Road, Haidian District, Beijing, 100081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChina has the largest disease burden of hepatitis B virus (HBV) infection and is considered as a major contributor to the global elimination of hepatitis B by 2030. However, the national prevalence of HBV infection among Chinese pregnant women was not reported yet. We evaluated the national and regional prevalence of HBV infection among pregnant women in China between 2015-2020, aiming to provide the latest baseline data.

methodsWe assessed the prevalence of HBV infection from data gathered through a nationwide cross-sectional study of Chinese pregnant women. Data were obtained from the National Integrated Prevention of Mother-to-Child Transmission of HIV, Syphilis and Hepatitis B Programme (iPMTCT Programme) in China, which covered all the 2856 counties from 31 provinces from 2015 to 2020. HBV infection was defined as being tested seropositive for hepatitis B surface antigen (HBsAg).

findingsA total of 90.87 million pregnant women in mainland China were testing for HBV between 2015 and 2020, with 5.60 million (6.17%, 95%CI: 6.16-6.18%) tested positive for HBsAg. From 2015 to 2020, the prevalence of HBV infection among pregnant women declined by 25.44%, from 7.30% in 2015 to 5.44% in 2020 (p for trend < 0.001), with an estimated annual percentage change (EAPC) of -5.27% (95% CI: -3.19% to -7.32%). Compared with the prevalence in 2015, reginal disparities in eastern, central, and western China were narrowed. Declines were also observed at provincial level and county level. HBV prevalence declined in most provinces (90.3%, 28/31) and counties (76.96%, 2198/2856) from 2015 to 2020. However, disparities still exist.

interpretationHBV prevalence in pregnant women in China was intermediate endemic and declined continuously from 2015 to 2020. The decline has been widespread across regions, but disparities remain. Regions with relatively higher disease burden on HBV infection should receive most attention in achieving the 2030 elimination goals.

fundingNational Natural Science Foundation of China.

Identifiers

PMID34590067
PMCPMC8429967

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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.