Evidence map›Paper›PMID 38340146›Full record

SynthesisWorld journal of pediatrics : WJP2024

Perinatal prevalence of birth defects in the Mainland of China, 2000-2021: a systematic review and meta-analysis.

Liang-Yu Kang, Zi-Rui Guo, Wei-Jing Shang, Gui-Ying Cao, Yi-Ping Zhang, Qiao-Mei Wang, Hai-Ping Shen, Wan-Nian Liang, Min Liu

Abstract readSystematic ReviewMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in World journal of pediatrics : WJP, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
6.1field-weighted citation impact, top 4% of its field
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

9 citing papers in PubMed, 11 citations in OpenAlex.

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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

9 authors at 3 institutions in 2 countries.

Liang-Yu KangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38, Xueyuan Road, Haidian District, Beijing, 100191, China.
Zi-Rui GuoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38, Xueyuan Road, Haidian District, Beijing, 100191, China.
Wei-Jing ShangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38, Xueyuan Road, Haidian District, Beijing, 100191, China.
Gui-Ying CaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38, Xueyuan Road, Haidian District, Beijing, 100191, China.
Yi-Ping ZhangDepartment of Maternal and Child Health, National Health Commission of the People's Republic of China, No. 1, Xizhimenwai South Road, Xicheng District, Beijing, China.
Qiao-Mei WangDepartment of Maternal and Child Health, National Health Commission of the People's Republic of China, No. 1, Xizhimenwai South Road, Xicheng District, Beijing, China.
Hai-Ping ShenDepartment of Maternal and Child Health, National Health Commission of the People's Republic of China, No. 1, Xizhimenwai South Road, Xicheng District, Beijing, China.
Wan-Nian LiangVanke School of Public Health, Tsinghua University, No. 1, Tsinghua Garden, Haidian District, Beijing, 100084, China. liangwn@tsinghua.edu.cn.ORCID 0000-0001-7116-0878
Min LiuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38, Xueyuan Road, Haidian District, Beijing, 100191, China. liumin@bjmu.edu.cn.ORCID 0000-0002-5059-3743
Peking University · CNNational Health and Family Planning Commission · CNTsinghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough birth defects are of great concern globally, the latest national prevalence has not yet been quantified in China. We conducted a systematic review and meta-analysis to estimate the perinatal prevalence of birth defects in the Mainland of China between 2000 and 2021.

methodsWe performed a systematic literature search of six databases for relevant articles published between January 1, 2000, and March 1, 2023. We included published studies that reported data on the perinatal prevalence of birth defects in the Mainland of China. The DerSimonian and Laird random-effects models were used to estimate the pooled prevalence and its 95% confidence interval (CI). We also conducted subgroup analyses and univariable meta-regressions to explore differences in prevalence by time period, geographic region, and other characteristics.

resultsWe included 254 studies reporting the perinatal prevalence of birth defects and 86 studies reporting only the prevalence of specific types of birth defects. Based on 254 studies covering 74,307,037 perinatal births and 985,115 cases with birth defects, the pooled perinatal prevalence of birth defects was 122.54 (95% CI 116.20-128.89) per 10,000 perinatal births in the Mainland of China during 2000-2021. Overall, the perinatal prevalence of birth defects increased from 95.60 (86.51-104.69) per 10,000 in 2000-2004 to 208.94 (175.67-242.22) per 10,000 in 2020-2021. There were also significant disparities among different geographical regions. Congenital heart defects (33.35 per 10,000), clefts of the lip and/or palate (13.52 per 10,000), polydactyly (12.82 per 10,000), neural tube defects (12.82 per 10,000), and inborn errors of metabolism (11.41 per 10,000) were the five most common types of birth defects. The perinatal prevalence among males was significantly higher than that among females (β = 2.44 × 10

conclusionComprehensive and sustained efforts are needed to strengthen surveillance and detection of birth defects, improve prenatal and postnatal healthcare, and promote rehabilitation, especially in underdeveloped areas.

Indexed as

Congenital AbnormalitiesChinaFemaleHumansInfant, NewbornPregnancyPrevalenceBirth defectsChinaPerinatalPrevalence

Identifiers

PMID38340146
OpenAlexW4391715997

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.