Suppr超能文献

基于大规模人群的出生队列研究能就发育、学习和行为障碍儿童的过去、现在和未来提出哪些问题?

What can large population-based birth cohort study ask about past, present and future of children with disorders of development, learning and behaviour?

作者信息

Katusic Slavica K, Colligan Robert C, Myers Scott M, Voigt Robert G, Yoshimasu Kouichi, Stoeckel Ruth E, Weaver Amy L

机构信息

Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.

Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA.

出版信息

J Epidemiol Community Health. 2017 Apr;71(4):410-416. doi: 10.1136/jech-2016-208482. Epub 2017 Feb 6.

Abstract

A large cohort consisting of all children born to mothers from community provides 'natural' selection into different exposures and is a powerful resource for epidemiological research. A large population-based birth cohort with detailed systematic information already recorded, as part of longitudinal medical care, historical and current school data, detailed birth certificate data and all three resources available for every member of the birth cohort, are extremely rare. Our population-based birth cohort consists of all children born between 1976 and 2000 to mothers residing in Olmsted County, Minnesota, at the time of child's birth (N=39 890). In this paper, we provide a comprehensive report of the method describing the identification, the characteristics and longitudinal follow-up of each child (and family members) from the birth cohort, wealth of complementary resources of data and study measures and designs (retrospective, combined retrospective/prospective). In the last decade or so, we obtained scientific and clinically needed answers for incidence rates, potential risk/protective factors, treatment, comorbidities, outcomes, cost/usage and potential biases (that are always assessed and clinically interpreted) of many developmental learning and behavioural disorders (DLBDs) including learning and attention-deficit/hyperactivity disorders, intellectual disability, speech-language impairment and autism spectrum disorder. Many current and future questions related to DLBDs are remaining to be answered. The Olmsted County Birth Cohort (OCBC) is an example of a comprehensive, contemporary epidemiological research model for the development of similar research infrastructures, and its current and future results are important for replication and comparison with other population-based retrospective and prospective birth cohort studies.

摘要

一个由社区母亲所生的所有儿童组成的大型队列提供了对不同暴露因素的“自然”选择,是流行病学研究的强大资源。一个基于大量人群的出生队列,其中已经记录了详细的系统信息,作为纵向医疗护理、历史和当前学校数据、详细出生证明数据的一部分,并且出生队列的每个成员都可获得所有这三种资源,这种情况极为罕见。我们基于人群的出生队列包括1976年至2000年间在明尼苏达州奥尔姆斯特德县居住的母亲所生的所有儿童(N = 39890)。在本文中,我们提供了一份关于该方法的全面报告,描述了出生队列中每个儿童(及其家庭成员)的识别、特征和纵向随访情况、丰富的数据补充资源以及研究措施和设计(回顾性、回顾性/前瞻性结合)。在过去十年左右的时间里,我们针对许多发育性学习和行为障碍(DLBDs),包括学习和注意力缺陷/多动障碍、智力残疾、语言障碍和自闭症谱系障碍的发病率、潜在风险/保护因素、治疗、合并症、结局、成本/使用情况以及潜在偏差(始终进行评估并进行临床解读),获得了科学和临床所需的答案。与DLBDs相关的许多当前和未来问题仍有待解答。奥尔姆斯特德县出生队列(OCBC)是一个全面的当代流行病学研究模型的范例,可用于发展类似的研究基础设施,其当前和未来的研究结果对于与其他基于人群的回顾性和前瞻性出生队列研究进行复制和比较非常重要。

相似文献

引用本文的文献

本文引用的文献

7
Restoring science to the National Children's Study.让科学回归国家儿童研究。
JAMA. 2013 May 1;309(17):1775-6. doi: 10.1001/jama.2013.3870.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验