测量流产的红心方法:在七种情况下实施标准化的比较分析方法。

IF 3.2 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Onikepe O Owolabi, Margaret Giorgio, Ellie Leong, Elizabeth Sully
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引用次数: 0

摘要

背景:在限制性背景下获得具有代表性的流产发生率估计是具有挑战性的。虽然在这种情况下,红颜知己方法越来越多地用于收集这些数据,但这种方法通常存在一些偏差。此外,研究人员在如何实施该方法以及评估/调整潜在偏差方面存在显著差异,限制了现有估计的可比性和解释。本研究提出了一种标准化的方法来分析红颜知己方法的数据,从以前发表的研究中得出可比较的流产发生率估计,并推荐了报告偏倚评估的标准,并为未来的红颜知己方法研究提供了调整。方法:我们使用红颜法在Côte科特迪瓦、埃塞俄比亚、加纳、爪哇(印度尼西亚)、尼日利亚、乌干达和拉贾斯坦邦(印度)的应用数据。我们估计了各种情况下知己一年的人工流产发生率,试图以标准化的方式调整选择、报告和传播偏差。结果:在每种情况下,大多数基本的红颜知己方法假设被违反。与其他已发表的方法相比,使用自我报告流产调整传播偏倚始终产生最高的发生率估计值。分析决策和偏倚评估的差异导致我们标准化分析的发生率估计值与最初公布的发生率相差很大。解释:我们建议未来的研究清楚地说明评估了哪些偏倚,是否违反了相关假设,以及如何对违反进行调整。这将提高红颜知己方法估计在国家一级决策中的效用,并作为全球或区域基于模型的堕胎估计的输入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The confidante method to measure abortion: implementing a standardized comparative analysis approach across seven contexts.

The confidante method to measure abortion: implementing a standardized comparative analysis approach across seven contexts.

The confidante method to measure abortion: implementing a standardized comparative analysis approach across seven contexts.

The confidante method to measure abortion: implementing a standardized comparative analysis approach across seven contexts.

Background: Obtaining representative abortion incidence estimates is challenging in restrictive contexts. While the confidante method has been increasingly used to collect this data in such settings, there are several biases commonly associated with this method. Further, there are significant variations in how researchers have implemented the method and assessed/adjusted for potential biases, limiting the comparability and interpretation of existing estimates. This study presents a standardized approach to analyzing confidante method data, generates comparable abortion incidence estimates from previously published studies and recommends standards for reporting bias assessments and adjustments for future confidante method studies.

Methods: We used data from previous applications of the confidante method in Côte d'Ivoire, Ethiopia, Ghana, Java (Indonesia), Nigeria, Uganda, and Rajasthan (India). We estimated one-year induced abortion incidence rates for confidantes in each context, attempting to adjust for selection, reporting and transmission bias in a standardized manner.

Findings: In each setting, majority of the foundational confidante method assumptions were violated. Adjusting for transmission bias using self-reported abortions consistently yielded the highest incidence estimates compared with other published approaches. Differences in analytic decisions and bias assessments resulted in the incidence estimates from our standardized analysis varying widely from originally published rates.

Interpretation: We recommend that future studies clearly state which biases were assessed, if associated assumptions were violated, and how violations were adjusted for. This will improve the utility of confidante method estimates for national-level decision making and as inputs for global or regional model-based estimates of abortion.

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来源期刊
Population Health Metrics
Population Health Metrics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
6.50
自引率
0.00%
发文量
21
审稿时长
29 weeks
期刊介绍: Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.
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