Health Outcomes and Policy Program, University of Tennessee Health Science Center, Memphis, TN, USA.
Health Informatics and Information Management Program, University of Tennessee Health Science Center, 66 North Pauline St. rm 221, Memphis, TN, 38163, USA.
Sci Rep. 2022 Jun 11;12(1):9716. doi: 10.1038/s41598-022-13733-w.
The objective of our study is to assess differences in prevalence of multimorbidity by race/ethnicity. We applied the FP-growth algorithm on middle-aged and elderly cohorts stratified by race/ethnicity, age, and obesity level. We used 2016-2017 data from the Cerner HealthFacts electronic health record data warehouse. We identified disease combinations that are shared by all races/ethnicities, those shared by some, and those that are unique to one group for each age/obesity level. Our findings demonstrate that even after stratifying by age and obesity, there are differences in multimorbidity prevalence across races/ethnicities. There are multimorbidity combinations distinct to some racial groups-many of which are understudied. Some multimorbidities are shared by some but not all races/ethnicities. African Americans presented with the most distinct multimorbidities at an earlier age. The identification of prevalent multimorbidity combinations amongst subpopulations provides information specific to their unique clinical needs.
我们的研究目的是评估不同种族/民族的多种疾病患病率差异。我们应用 FP 增长算法对按种族/民族、年龄和肥胖水平分层的中年和老年队列进行分析。我们使用了来自 Cerner HealthFacts 电子健康记录数据仓库的 2016-2017 年数据。我们确定了在每个年龄/肥胖水平下所有种族/民族都共有的疾病组合、某些种族/民族共有的疾病组合以及仅属于一个组别的疾病组合。我们的研究结果表明，即使按年龄和肥胖程度分层，不同种族/民族之间的多种疾病患病率仍存在差异。有些种族群体特有的多种疾病组合——其中许多尚未得到充分研究。有些多种疾病组合在某些种族/民族中共有，但并非所有种族/民族都有。非裔美国人在更早的年龄出现了最独特的多种疾病。确定亚人群中的常见多种疾病组合可以提供针对其独特临床需求的信息。
