{"title":"Sources of bias in studies reporting birth prevalence of congenital anomalies: a scoping review and reporting checklist.","authors":"Sumedha Dharmarajan, Prajkta Bhide, Anita Kar","doi":"10.1093/pubmed/fdae299","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Data on the birth prevalence of congenital anomalies in low- and middle-income countries report wide variations in prevalence estimates. We conducted a scoping review to identify the sources of bias in studies reporting birth prevalence of congenital anomalies in World Health Organization South-East Asia region (SEAR) countries.</p><p><strong>Methods: </strong>PubMed and Google Scholar databases were screened for relevant literature. Data on study characteristics and sources of bias was extracted. A narrative synthesis of the data is reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. A checklist for reporting studies on birth prevalence of congenital anomalies (CD-Checklist) was developed.</p><p><strong>Results: </strong>The literature search retrieved 47 articles. Birth prevalence varied from 0.21% to 9.68%. Sampling bias was evident as studies were single hospital studies, lacked relevant description of sample, did not justify sample size or describe the process of sampling. Information bias was identified as studies did not mention classification system used, and failed to clearly distinguish between number of malformations and babies with malformations. Observer and reporting bias were noted.</p><p><strong>Conclusions: </strong>Several sources of bias introduce variations in birth prevalence reports of congenital anomalies in SEAR countries. A checklist (CD-Checklist) has been suggested which can guide investigators to minimize the risk of bias in studies.</p>","PeriodicalId":94107,"journal":{"name":"Journal of public health (Oxford, England)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of public health (Oxford, England)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/pubmed/fdae299","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
背景:有关中低收入国家先天性畸形出生率的数据显示,其流行率估计值存在很大差异。我们对世界卫生组织东南亚地区(SEAR)国家先天性畸形出生率的研究报告进行了范围界定,以确定偏倚的来源:方法:筛选 PubMed 和 Google Scholar 数据库中的相关文献。方法:筛选 PubM 和 Google 学术数据库中的相关文献,提取有关研究特点和偏倚来源的数据。采用 "系统综述和元分析首选报告项目"(Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews)核对表对数据进行叙述性综合报告。此外,还制定了先天性畸形出生率研究报告核对表(CD-Checklist):文献检索共检索到 47 篇文章。出生率从 0.21% 到 9.68% 不等。抽样偏差很明显,因为这些研究都是单家医院的研究,缺乏对样本的相关描述,没有说明样本大小或抽样过程。由于研究未提及所使用的分类系统,也未明确区分畸形数量和畸形婴儿数量,因此存在信息偏倚。研究还发现了观察偏差和报告偏差:结论:在东南亚国家联盟(SEAR)国家中,先天性畸形的出生率报告存在多种偏差来源。建议制定一份核对表(CD-核对表),以指导调查人员最大限度地降低研究中的偏倚风险。
Sources of bias in studies reporting birth prevalence of congenital anomalies: a scoping review and reporting checklist.
Background: Data on the birth prevalence of congenital anomalies in low- and middle-income countries report wide variations in prevalence estimates. We conducted a scoping review to identify the sources of bias in studies reporting birth prevalence of congenital anomalies in World Health Organization South-East Asia region (SEAR) countries.
Methods: PubMed and Google Scholar databases were screened for relevant literature. Data on study characteristics and sources of bias was extracted. A narrative synthesis of the data is reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. A checklist for reporting studies on birth prevalence of congenital anomalies (CD-Checklist) was developed.
Results: The literature search retrieved 47 articles. Birth prevalence varied from 0.21% to 9.68%. Sampling bias was evident as studies were single hospital studies, lacked relevant description of sample, did not justify sample size or describe the process of sampling. Information bias was identified as studies did not mention classification system used, and failed to clearly distinguish between number of malformations and babies with malformations. Observer and reporting bias were noted.
Conclusions: Several sources of bias introduce variations in birth prevalence reports of congenital anomalies in SEAR countries. A checklist (CD-Checklist) has been suggested which can guide investigators to minimize the risk of bias in studies.