A parsimonious explanation for intersecting perinatal mortality curves: understanding the effects of race and of maternal smoking

对交叉围产期死亡率曲线的简洁解释:理解种族和孕妇吸烟的影响

阅读:1

Abstract

BACKGROUND: Neonatal mortality rates among black infants are lower than neonatal mortality rates among white infants at birth weights <3000 g, whereas white infants have a survival advantage at higher birth weights. This finding is also observed when birth weight-specific neonatal mortality rates are compared between infants of smokers and non-smokers. We provide a parsimonious explanation for this paradoxical phenomenon. METHODS: We used data on births in the United States in 1997 after excluding those with a birth weight <500 g or a gestational age <22 weeks. Birth weight- and gestational age-specific perinatal mortality rates were calculated per convention (using total live births at each birth weight/gestational age as the denominator) and also using the fetuses at risk of death at each gestational age. RESULTS: Perinatal mortality rates (calculated per convention) were lower among blacks than whites at lower birth weights and at preterm gestational ages, while blacks had higher mortality rates at higher birth weights and later gestational ages. With the fetuses-at-risk approach, mortality curves did not intersect; blacks had higher mortality rates at all gestational ages. Increases in birth rates and (especially) growth-restriction rates presaged gestational age-dependent increases in perinatal mortality. Similar findings were obtained in comparisons of smokers versus nonsmokers. CONCLUSIONS: Formulating perinatal risk based on the fetuses-at-risk approach solves the intersecting perinatal mortality curves paradox; blacks have higher perinatal mortality rates than whites and smokers have higher perinatal mortality rates than nonsmokers at all gestational ages and birth weights.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。