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基于树的自然流产两阶段风险因素分析。

Tree-based, two-stage risk factor analysis for spontaneous abortion.

作者信息

Zhang H, Bracken M B

机构信息

Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT 06520-8034, USA.

出版信息

Am J Epidemiol. 1996 Nov 15;144(10):989-96. doi: 10.1093/oxfordjournals.aje.a008869.

Abstract

The authors utilize an analytic strategy that combines tree-based analyses with the method of Mantel-Haenszel to evaluate the association of 11 putative risk factors to spontaneous abortion by controlling for 19 potential confounders. Logistic regression is also used for comparison. The data for this study were collected in southern Connecticut, during 1988-1991. The putative risk factors are employment; standing, walking, or sitting more than 2 hours at work; exposure to vibration at work; commuting to work; reaching over the shoulders at work; carrying loads over 9 kg on the job; drinking alcohol or coffee in the first month of pregnancy; and gynecologic problems before pregnancy. The potential confounding factors are maternal age, marriage status, race, years of education mother's height, use of birth control, number of pregnancies, smoking before pregnancy, years of smoking, whether the mother stopped smoking, smoking marijuana, passive exposure to marijuana, chronic problems, infertility cocaine use and history of negative pregnancy outcomes. This analysis indicates that carrying loads over 9 kg on the job at least once a day increases the risk of spontaneous abortion by 70% (relative risk (RR) = 1.71, 95% CI 1.25-2.32). Drinking three or more cups of coffee daily in the first month of pregnancy also elevates the risk of spontaneous abortion (RR = 2.34, 95% CI 1.45-3.77). Reaching over the shoulders at least once daily has a marginally significant impact on spontaneous abortion (RR = 1.35, 95% CI 1.02-1.78). The authors conclude that this analytic strategy offers an efficient approach to the exploration of new risk factors for a disease where many potential confounders already exist.

摘要

作者采用了一种分析策略,将基于树的分析方法与Mantel-Haenszel方法相结合,通过控制19个潜在混杂因素来评估11个假定风险因素与自然流产之间的关联。同时也使用逻辑回归进行比较。本研究的数据于1988年至1991年在康涅狄格州南部收集。假定风险因素包括就业;工作时站立、行走或坐着超过2小时;工作时接触振动;通勤上班;工作时过肩伸展;工作中搬运超过9公斤的重物;怀孕第一个月饮酒或喝咖啡;以及怀孕前的妇科问题。潜在混杂因素有母亲年龄、婚姻状况、种族、受教育年限、母亲身高、避孕措施使用情况、怀孕次数、怀孕前吸烟、吸烟年限、母亲是否戒烟、吸食大麻、被动接触大麻、慢性疾病、不孕、使用可卡因以及不良妊娠结局史。该分析表明,每天至少有一次在工作中搬运超过9公斤的重物会使自然流产风险增加70%(相对风险(RR)=1.71,95%置信区间1.25 - 2.32)。怀孕第一个月每天饮用三杯或更多杯咖啡也会增加自然流产风险(RR = 2.34,95%置信区间1.45 - 3.77)。每天至少有一次过肩伸展对自然流产有边缘显著影响(RR = 1.35,95%置信区间1.02 - 1.78)。作者得出结论,这种分析策略为探索存在许多潜在混杂因素的疾病的新风险因素提供了一种有效的方法。

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