Suppr超能文献

拉丁裔人口算术分数上教育程度的收益递减:来自美国社区调查(UAS)数据的见解

Diminished Returns of Educational Attainment on Numeracy Score of Latino Populations: Insights from UAS Data.

作者信息

Assari Shervin, Zare Hossein, Akhlaghipour Golnoush, Mendez Mario F

机构信息

Marginalized-Related Diminished Returns (MDRs) Research Center, Los Angeles, CA, USA.

Department of Family Medicine, Charles R Drew University of Medicine and Science, Los Angeles, CA, USA.

出版信息

Open J Neurosci. 2024;2(1):14-24. doi: 10.31586/ojn.2024.1098. Epub 2024 Nov 5.

Abstract

BACKGROUND

Educational attainment is a well-established social determinant of various domains of cognitive function across the lifespan. However, the theory of Minorities' Diminished Returns (MDRs) suggests that the health benefits of educational attainment tend to be weaker for ethnic minorities compared to non-Latino Whites. This phenomenon may reflect the impact of structural inequalities, social stratification, and historical disadvantage.

OBJECTIVE

This study examines whether the association between educational attainment and numeracy score, one domain of cognitive function, is weaker in Latino individuals compared to non-Latino individuals, as predicted by the MDRs framework.

METHODS

Data were drawn from the 2014 wave of the Understanding America Study (UAS), a national internet-based panel. Numeracy score, a domain of the cognitive function was measured using an 8-item measure. Linear regression models were used to analyze the association between educational attainment and numeracy score, with an interaction term for ethnicity × educational attainment to explore differences between Latino and non-Latino participants. Models were adjusted for age, gender, marital status, immigration, and employment, and results were presented as beta coefficients, p-values, and 95% confidence intervals (CIs).

RESULTS

Overall, 5,659 participants entered our analysis. Higher educational attainment was positively associated with higher numeracy score for both Latino and non-Latino participants (p < 0.001). However, the interaction between education and ethnicity was significant (p < 0.05), indicating that Latino individuals experienced smaller numeracy benefits from education compared to non-Latino individuals. These results support the MDRs framework, suggesting that structural barriers may reduce the numeracy returns of education for Latino individuals.

CONCLUSION

This study provides evidence of diminished returns of educational attainment in terms of numeracy scores among Latino individuals. While education is a key determinant of cognitive abilities such as numeracy, its benefits are not equitably distributed across ethnic groups. Structural inequalities particularly in educational opportunities likely contribute to this disparity. Addressing these underlying factors through targeted policy interventions is necessary to promote cognitive equity for Latino populations.

摘要

背景

教育程度是贯穿一生的认知功能各个领域中既定的社会决定因素。然而,少数族裔回报递减理论(MDRs)表明,与非拉丁裔白人相比,教育程度对少数族裔的健康益处往往较弱。这种现象可能反映了结构性不平等、社会分层和历史劣势的影响。

目的

本研究旨在检验,正如少数族裔回报递减理论框架所预测的那样,与非拉丁裔个体相比,拉丁裔个体的教育程度与认知功能的一个领域——算术分数之间的关联是否较弱。

方法

数据来自2014年的美国理解研究(UAS),这是一个基于互联网的全国性样本。算术分数作为认知功能的一个领域,使用一个8项量表进行测量。线性回归模型用于分析教育程度与算术分数之间的关联,并使用种族×教育程度的交互项来探索拉丁裔和非拉丁裔参与者之间的差异。模型对年龄、性别、婚姻状况、移民和就业进行了调整,结果以β系数、p值和95%置信区间(CIs)呈现。

结果

总体而言,5659名参与者进入了我们的分析。对于拉丁裔和非拉丁裔参与者来说,更高的教育程度都与更高的算术分数呈正相关(p < 0.001)。然而,教育与种族之间的交互作用显著(p < 0.05),这表明与非拉丁裔个体相比,拉丁裔个体从教育中获得的算术益处较小。这些结果支持了少数族裔回报递减理论框架,表明结构性障碍可能会降低拉丁裔个体教育的算术回报。

结论

本研究提供了证据,证明拉丁裔个体在算术分数方面教育回报递减。虽然教育是算术等认知能力的关键决定因素,但其益处并未在不同种族群体中公平分配。特别是教育机会方面的结构性不平等可能导致了这种差异。通过有针对性的政策干预来解决这些潜在因素,对于促进拉丁裔人群的认知公平是必要的。

相似文献

5
Educated but Unhealthy? Examining Minorities' Diminished Returns.受过教育却不健康?审视少数族裔的收益递减问题。
Glob J Epidemol Infect Dis. 2024;4(1):82-91. doi: 10.31586/gjeid.2024.1105. Epub 2024 Nov 9.
6
Trauma Erodes Financial Returns of Educational Attainment.创伤侵蚀了教育成就带来的经济回报。
Open J Educ Res. 2025;5(1):40-53. doi: 10.31586/ojer.2025.1199. Epub 2025 Feb 14.

本文引用的文献

1
The Understanding America Study (UAS).《理解美国研究》(UAS)。
BMJ Open. 2024 Oct 23;14(10):e088183. doi: 10.1136/bmjopen-2024-088183.

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