比较两个大型数据存储库,以了解人口统计、健康史和行为属性的差异。

IF 3 Q1 DENTISTRY, ORAL SURGERY & MEDICINE
Frontiers in oral health Pub Date : 2024-12-04 eCollection Date: 2024-01-01 DOI:10.3389/froh.2024.1427109
Nihmath Nasiha Maliq, Toan Ong, Zachary Giano, William Rivera, Tamanna Tiwari
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引用次数: 0

摘要

本研究对两个大型数据存储库进行了比较分析,即All of Us (AoU)医疗数据和BigMouth牙科数据存储库。方法:比较分析包括与行为和系统健康、健康素养以及跨种族、民族和性别的整体健康状况相关的变量。分析方法采用描述性统计、卡方、优势比和95%置信区间;用Cohen's D效应量来衡量显著性比较。结果:在AoU数据集中,80.6%的西班牙裔或拉丁裔参与者报告饮酒,而BigMouth数据存储库中的这一比例为16.8%。在AoU的女性队列中,有87.9%的人饮酒,而BigMouth的比例为26.0%。此外,AoU地区女性糖尿病患病率为8.8%,而BigMouth地区为21.6%。观察到健康素养的差异,在AoU的西班牙裔或拉丁裔参与者中有49.2%,而BigMouth的这一比例为3.2%。尽管如此,在AoU的西班牙裔或拉丁裔受访者中,70.1%的人表示健康状况令人满意,而BigMouth的数字要高得多,为98.3%。讨论:这些差异突出了解决种族/民族和性别影响的有针对性的卫生干预措施的重要性。差异可能来自招聘方法、参与者人口统计和医疗保健获取。需要通过协作、标准化数据收集和包容性招聘来弥补这些差异。进一步的研究是必要的,以了解潜在的原因,促进解决差距的干预措施,并倡导一个更具包容性的医疗保健系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparing two large data repositories to understand the differences in demographics, health history, and behavioral attributes in populations.

Introduction: This study conducted a comparative analysis between two large data repositories, the All of Us (AoU) medical data and BigMouth dental data repositories.

Methods: The comparison analysis includes variables related to behavioral and systemic health, health literacy, and overall health status across race, ethnicity, and gender. The analytic approach used descriptive statistics, Chi-square, odds ratio, and 95% confidence intervals; significant comparisons were measured with Cohen's D effect sizes.

Results: In the AoU dataset, 80.6% of Hispanic or Latino participants reported alcohol use compared to 16.8% in the BigMouth data repository. The female cohort in AoU showed 87.9% alcohol use, a contrast to BigMouth's 26.0%. Additionally, the diabetes prevalence among females was 8.8% in AoU vs. 21.6% in BigMouth. Differences in health literacy were observed, with 49.2% among Hispanic or Latino participants in AoU, in contrast to BigMouth's 3.2%. Despite this, 70.1% of Hispanic or Latino respondents in AoU reported satisfactory health status, while BigMouth indicated a much higher figure at 98.3%.

Discussion: These variations highlight the importance of targeted health interventions addressing racial/ethnic and gender influences. Differences may arise from recruitment approaches, participant demographics, and healthcare access. There is a need for collaboration, standardized data collection, and inclusive recruitment to remedy these discrepancies. Further research is imperative to understand the underlying causes, facilitate interventions that address the disparities, and advocate for a more inclusive healthcare system.

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来源期刊
CiteScore
3.30
自引率
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