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威斯康星州 1999-2016 年婴儿死亡率差异的连接点趋势分析。

Joinpoint Trend Analysis of Infant Mortality Disparities in Wisconsin, 1999-2016.

机构信息

The authors are with University of Wisconsin Population Health Institute, Madison.

出版信息

Am J Public Health. 2019 May;109(5):714-718. doi: 10.2105/AJPH.2018.304945. Epub 2019 Mar 21.

Abstract

OBJECTIVES

To address shortcomings of previous research exploring trends in racial, educational, and race by educational disparities in infant mortality rates (IMRs) by using nonlinear methods to compare improvement within and between disparity domains.

METHODS

We used joinpoint regression modeling to perform a cross-sectional analysis of IMR trends from linked birth and death certificates in Wisconsin between 1999 and 2016.

RESULTS

In the race and education domains, IMR decreased by 1.9% per year for infants of White mothers and 1.1% per year for infants of less-educated mothers. Further analysis showed these IMR reductions to be among infants of White mothers with more education (-0.6%/year) and Black mothers with less education (-2.0%/year).

CONCLUSIONS

As previously reported, gaps in IMR by race and education in Wisconsin appear to be closing; however, only the change by education is statistically significant. Evidence suggests the racial divide in IMR might soon widen after years of progress in reducing IMR among infants of Black mothers. Public Health Implications. Those advancing strategies to address IMR disparities should pursue data and methods that provide the most accurate and refined information about the challenges that persist and progress that has been realized.

摘要

目的

利用非线性方法比较差异领域内和之间的改善情况,解决先前研究中探索婴儿死亡率(IMR)种族、教育和种族差异趋势的不足。

方法

我们使用联合点回归模型对 1999 年至 2016 年威斯康星州链接出生和死亡证明中 IMR 趋势进行了横断面分析。

结果

在种族和教育领域,白人母亲所生孩子的 IMR 每年下降 1.9%,受教育程度较低的母亲所生孩子的 IMR 每年下降 1.1%。进一步的分析表明,这些 IMR 降低是在受过更多教育的白人母亲(每年下降 0.6%)和受教育程度较低的黑人母亲(每年下降 2.0%)的婴儿中。

结论

正如先前报道的那样,威斯康星州 IMR 种族和教育方面的差距似乎正在缩小;然而,只有教育方面的变化具有统计学意义。有证据表明,在多年来降低黑人母亲所生孩子的 IMR 之后,IMR 的种族差距可能很快会扩大。公共卫生意义。那些推进解决 IMR 差异策略的人应该寻求提供关于持续存在的挑战和已实现进展的最准确和精细信息的数据和方法。

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