Improving Quality of Mortality Estimates Among Non-Hispanic American Indian and Alaska Native People, 2020.

IF 5 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Melissa A Jim, Elizabeth Arias, Donald S Haverkamp, Roberta Paisano, Andria Apostolou, Stephanie C Melkonian
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引用次数: 0

Abstract

Racial misclassification on death certificates leads to inaccurate mortality data for American Indian and Alaska Native (AI/AN) populations. We describe methods for correcting for racial misclassification among non-Hispanic AI/AN (NH-AI/AN) populations using data from the year 2020. We linked National Death Index (NDI) records with the Indian Health Service (IHS) patient registration database to identify AI/AN decedents. Matches were then linked to the National Vital Statistics System (NVSS) mortality data to identify AI/AN individuals that had been misclassified as another race on their death certificates. Analyses were limited to NH-AI/AN and purchased/referred care delivery areas (PRCDA) or urban areas. We compared death rates and counts pre- and post- linkage and calculated sensitivity and classification ratios by region, sex, age, cause of death (COD) and urban area. Racial misclassification on death certificates among NH-AI/AN varied by geographic region. Some of the highest racial misclassification occurred in the Southern Plains and Pacific Coast. Death rates for NH-AI/AN people and differences between NH-AI/AN and Non-Hispanic White (NHW) people were larger using the linked data. Improving AI/AN mortality data using linkages between vital statistics data and IHS strengthens data quality and can help address health disparities through public health planning efforts.

提高非西班牙裔美国印第安人和阿拉斯加原住民死亡率估计的质量,2020年。
死亡证明上的种族错误分类导致美洲印第安人和阿拉斯加原住民(AI/AN)人口的死亡率数据不准确。我们描述了使用2020年的数据纠正非西班牙裔AI/AN (NH-AI/AN)人群中种族错误分类的方法。我们将国家死亡指数(NDI)记录与印度卫生服务(IHS)患者登记数据库联系起来,以确定AI/AN死者。然后将匹配与国家生命统计系统(NVSS)死亡率数据联系起来,以识别在死亡证明上被错误分类为另一个种族的AI/AN个人。分析仅限于NH-AI/AN和购买/转诊护理提供区(PRCDA)或城市地区。我们比较了关联前后的死亡率和计数,并按地区、性别、年龄、死因(COD)和城市地区计算了敏感性和分类比率。NH-AI/AN在死亡证明上的种族错误分类因地理区域而异。一些最严重的种族错误分类发生在南部平原和太平洋沿岸。使用关联数据,NH-AI/AN人群的死亡率以及NH-AI/AN与非西班牙裔白人(NHW)人群之间的差异更大。利用生命统计数据与IHS之间的联系改进人工智能/AN死亡率数据,可提高数据质量,并有助于通过公共卫生规划工作解决健康差距问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
American journal of epidemiology
American journal of epidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
7.40
自引率
4.00%
发文量
221
审稿时长
3-6 weeks
期刊介绍: The American Journal of Epidemiology is the oldest and one of the premier epidemiologic journals devoted to the publication of empirical research findings, opinion pieces, and methodological developments in the field of epidemiologic research. It is a peer-reviewed journal aimed at both fellow epidemiologists and those who use epidemiologic data, including public health workers and clinicians.
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