Evidence map›Paper›PMID 37985789›Full record

ArticleScientific reports2023

Update from a cohort study for birth defects in Hunan Province, China, 2010-2020.

Xu Zhou, Shenglan Cai, Hua Wang, Junqun Fang, Jie Gao, Haiyan Kuang, Donghua Xie, Jian He, Aihua Wang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

6 citing papers in PubMed, 9 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 1 institution in 1 country.

Xu ZhouHunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, China. chzhouxu@163.com.
Shenglan CaiHunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, China.
Hua WangThe Hunan Children's Hospital, Changsha, Hunan, China. wanghua213@aliyun.com.
Junqun FangHunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, China. 40112079@qq.com.
Jie GaoHunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, China. gaojie712@126.com.
Haiyan KuangHunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, China.
Donghua XieHunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, China.
Jian HeHunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, China.
Aihua WangHunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, China.
Hunan Provincial Maternal and Child Health Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To define the relationship between sex, residence, maternal age, and a broad range of birth defects by conducting a comprehensive cross-analysis based on up-to-date data. Data were obtained from the Birth Defects Surveillance System in Hunan Province, China, 2010-2020. Prevalences of birth defects (number of cases per 10,000 fetuses (births and deaths at 28 weeks of gestation and beyond)) with 95% confidence intervals (CI) were calculated by sex, residence, maternal age, year, and 23 specific defects. Cross-analysis of sex, residence, and maternal age was conducted, and crude odds ratios (ORs) were calculated to examine the association of each maternal characteristic with birth defects. A total of 1,619,376 fetuses and 30,596 birth defects were identified. The prevalence of birth defects was 188.94/10,000 (95% CI 186.82-191.05). Birth defects were more frequent in males than females (210.46 vs. 163.03/10,000, OR = 1.30, 95% CI 1.27-1.33), in urban areas than in rural areas (223.61 vs. 162.90/10,000, OR = 1.38, 95% CI 1.35-1.41), and in mothers ≥ 35 than mothers 25-29 (206.35 vs. 187.79/10,000, OR = 1.10, 95% CI 1.06-1.14). Cross-analysis showed that the prevalence of birth defects was higher in urban females than in rural males (194.53 vs. 182.25/10,000), the difference in prevalence between males and females was more significant for maternal age < 20 compared to other age groups (OR = 1.64, 95% CI 1.37-1.95), and the prevalence difference between urban and rural areas is more significant for maternal age 25-34 compared to other age groups (OR = 1.49, 95% CI 1.43-1.57). Cleft palates were more frequent in males, and nine specific defects were more frequent in females. Five specific defects were more frequent in rural areas, and eight were more frequent in urban areas. Compared to mothers 25-29, five specific defects were more frequent in mothers < 20, seven specific defects were more frequent in mothers 20-24, two specific defects were more frequent in mothers 30-34, and ten specific defects were more frequent in mothers ≥ 35. Our data indicate that sex, residence, and maternal age differences in the prevalences of birth defects and most specific defects are common. We have found some new epidemiological characteristics of birth defects using cross-analysis, such as residence is the determining factor for the prevalence of birth defects, the difference in prevalence between males and females was more significant for maternal age < 20 compared to other age groups, the prevalence difference between urban and rural areas is more significant for maternal age 25-34 compared to other age groups. And differences in the epidemiological characteristics of some specific defects from previous studies. Future studies should examine mechanisms. Our findings contributed to clinical counseling and advancing research on the risk factors for birth defects.

Indexed as

MothersAdultChinaCohort StudiesFemaleHumansMaleMaternal AgePrevalenceRisk Factors

Identifiers

PMID37985789
PMCPMC10662386
OpenAlexW4388833596

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.