Suppr超能文献

《美国 1986-2019 年按阶级、性别和种族/族裔划分的死亡劳动:死亡率不平等》

Dead Labor: Mortality Inequities by Class, Gender, and Race/Ethnicity in the United States, 1986-2019.

机构信息

Jerzy Eisenberg-Guyot and Megan C. Finsaas are with the Department of Epidemiology and Seth J. Prins is with the Departments of Epidemiology and Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, NY.

出版信息

Am J Public Health. 2023 Jun;113(6):637-646. doi: 10.2105/AJPH.2023.307227. Epub 2023 Mar 16.

Abstract

To estimate social class inequities in US mortality using a relational measure based on power over productive property and workers' labor. We used nationally representative 1986-2018 National Health Interview Survey data with mortality follow-up through December 31, 2019 (n = 911 850). First, using business-ownership, occupational, and employment-status data, we classified respondents as incorporated business owners (IBOs), unincorporated business owners (UBOs), managers, workers, or not in the labor force (NLFs). Next, using inverse-probability-weighted survival curves, we estimated class mortality inequities overall, after subdividing workers by employment status and occupation, and by period, gender, race/ethnicity, and education. UBOs, workers, and NLFs had, respectively, 6.3 (95% confidence interval [CI] = -8.1, -4.6), 6.6 (95% CI = -8.1, -5.0), and 19.4 (95% CI = -21.0, -17.7) per 100 lower 34-year survival rates than IBOs. Mortality risk was especially high for unemployed, blue-collar, and service workers. Inequities increased over time and were greater among male, racially minoritized, and less-educated respondents. We estimated considerable mortality inequities by class, gender, and race/ethnicity. We also estimated that class mortality inequities are increasing, threatening population health. Addressing class inequities likely requires structural, worker-empowering interventions. ( 2023;113(6):637-646. https://doi.org/10.2105/AJPH.2023.307227).

摘要

利用基于对生产性财产和工人劳动的权力的关系衡量标准来估计美国死亡率中的社会阶层不平等。我们使用了具有通过 2019 年 12 月 31 日进行的死亡率随访的全国代表性的 1986-2018 年国家健康访谈调查数据(n=911850)。首先,使用企业所有权、职业和就业状况数据,我们将受访者分为有法人所有权的企业主(IBO)、无法人所有权的企业主(UBO)、经理、工人或未就业(NLF)。接下来,我们使用逆概率加权生存曲线,在按就业状况和职业细分工人后,以及按时期、性别、种族/族裔和教育程度细分工人后,分别估计了总体阶级死亡率的不平等。UBO、工人和 NLF 的 34 年生存率分别低 6.3(95%置信区间[CI]=-8.1,-4.6)、6.6(95% CI=-8.1,-5.0)和 19.4(95% CI=-21.0,-17.7)。失业、蓝领和服务工人的死亡率风险特别高。不平等现象随着时间的推移而增加,在男性、种族少数群体和受教育程度较低的受访者中更为明显。我们估计阶级、性别和种族/族裔之间存在相当大的死亡率不平等。我们还估计,阶级死亡率不平等正在加剧,威胁着人口健康。解决阶级不平等问题可能需要结构性的、增强工人权力的干预措施。(2023;113(6):637-646。https://doi.org/10.2105/AJPH.2023.307227)。

相似文献

本文引用的文献

8
Increasing Disparities in Mortality by Socioeconomic Status.社会经济地位导致死亡率差距不断扩大。
Annu Rev Public Health. 2018 Apr 1;39:237-251. doi: 10.1146/annurev-publhealth-040617-014615.
9
Propensity Score Analysis with Survey Weighted Data.使用调查加权数据的倾向得分分析。
J Causal Inference. 2015 Sep;3(2):237-249. doi: 10.1515/jci-2014-0039. Epub 2015 May 14.
10
The Key Role of Work in Population Health Inequities.工作在人群健康不平等中的关键作用。
Am J Public Health. 2018 Mar;108(3):296-297. doi: 10.2105/AJPH.2017.304288.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验