获取怀孕和分娩队列的概率样本:问题审查和实际解决方案
Michael R Elliott1,2, Jean M Kerver3, Alexa Drew3
1Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, United States.
American journal of epidemiology
|May 23, 2025
概括
密歇根儿童健康研究档案成功创建了密歇根州1000多个出生代表性样本. 这种创新方法为未来的儿童健康研究提供了一个可行的模型,解决了以前的大规模队列研究的局限性.
科学领域:
- 儿科 儿科 儿科
- 公共卫生 公共卫生
- 流行病学 流行病学
背景情况:
- 建立代表性的出生队伍对于了解儿童健康决定因素至关重要.
- 美国和英国以前的大规模前性出生队列研究面临着重大挑战.
- 需要有效的方法来招募和保留各种出生样本.
研究的目的:
- 开发和实施一项成功的概率抽样策略,用于密歇根州一个庞大,具有代表性的出生队列.
- 评估采样方法的可行性和代表性.
- 为未来关于儿童健康的产前和产后研究提供一个模型.
主要方法:
- 使用密歇根州出生证明数据创建了一个概率与大小成比例的抽样框架.
- 10家医院被随机选择,每家医院招募大约100例怀孕.
- 该样本补充了来自密歇根州弗林特的一家特定医院的分娩,总共有1130例分娩.
主要成果:
- 参与率很高:100%的样本医院和65%的样本诊所.
- 最终的样本与密歇根州整体出生人口在关键出生结果和母亲人口统计学方面非常接近.
- 报告指出,西班牙裔族群的少量代表性不足,吸烟的代表性过高.
结论:
- 这项研究展示了一种成功且具有成本效益的方法,用于生成代表性的出生概率样本.
- 这种方法为开展关于儿童健康的强有力的产前和产后研究提供了可行的途径.
- 密歇根儿童健康研究档案馆的研究为设计未来的大规模出生队列研究提供了宝贵的见解.
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