Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China.
School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.
J Med Internet Res. 2022 Feb 25;24(2):e27146. doi: 10.2196/27146.
Multimorbidity represents a global health challenge, which requires a more global understanding of multimorbidity patterns and trends. However, the majority of studies completed to date have often relied on self-reported conditions, and a simultaneous assessment of the entire spectrum of chronic disease co-occurrence, especially in developing regions, has not yet been performed.
We attempted to provide a multidimensional approach to understand the full spectrum of chronic disease co-occurrence among general inpatients in southwest China, in order to investigate multimorbidity patterns and temporal trends, and assess their age and sex differences.
We conducted a retrospective cohort analysis based on 8.8 million hospital discharge records of about 5.0 million individuals of all ages from 2015 to 2019 in a megacity in southwest China. We examined all chronic diagnoses using the ICD-10 (International Classification of Diseases, 10th revision) codes at 3 digits and focused on chronic diseases with ≥1% prevalence for each of the age and sex strata, which resulted in a total of 149 and 145 chronic diseases in males and females, respectively. We constructed multimorbidity networks in the general population based on sex and age, and used the cosine index to measure the co-occurrence of chronic diseases. Then, we divided the networks into communities and assessed their temporal trends.
The results showed complex interactions among chronic diseases, with more intensive connections among males and inpatients ≥40 years old. A total of 9 chronic diseases were simultaneously classified as central diseases, hubs, and bursts in the multimorbidity networks. Among them, 5 diseases were common to both males and females, including hypertension, chronic ischemic heart disease, cerebral infarction, other cerebrovascular diseases, and atherosclerosis. The earliest leaps (degree leaps ≥6) appeared at a disorder of glycoprotein metabolism that happened at 25-29 years in males, about 15 years earlier than in females. The number of chronic diseases in the community increased over time, but the new entrants did not replace the root of the community.
Our multimorbidity network analysis identified specific differences in the co-occurrence of chronic diagnoses by sex and age, which could help in the design of clinical interventions for inpatient multimorbidity.
多种疾病共存代表了一个全球性的健康挑战,这需要我们从更宏观的角度来理解多种疾病共存的模式和趋势。然而,迄今为止完成的大多数研究往往依赖于自我报告的疾病,而且尚未对整个慢性疾病共存的全貌进行同步评估,尤其是在发展中地区。
我们试图提供一种多维方法来了解中国西南部普通住院患者的慢性疾病共存全貌,以调查多种疾病共存的模式和时间趋势,并评估其在年龄和性别上的差异。
我们基于中国西南部一个特大城市 2015 年至 2019 年期间约 500 万人的 880 万份住院记录进行了回顾性队列分析。我们使用 ICD-10(国际疾病分类,第 10 版)3 位码对所有慢性疾病进行了诊断,并重点关注了每个年龄和性别分层中患病率≥1%的慢性疾病,这总共导致了男性和女性分别有 149 种和 145 种慢性疾病。我们根据性别和年龄构建了普通人群中的多种疾病共存网络,并使用余弦指数来衡量慢性疾病的共现情况。然后,我们将网络划分为社区,并评估了它们的时间趋势。
结果表明,慢性疾病之间存在复杂的相互作用,男性和≥40 岁的住院患者之间的联系更加紧密。在多种疾病共存网络中,共有 9 种慢性疾病同时被归类为中心疾病、枢纽疾病和突发疾病。其中,有 5 种疾病在男性和女性中均为常见疾病,包括高血压、慢性缺血性心脏病、脑梗死、其他脑血管疾病和动脉粥样硬化。最早的跃升(度跃升≥6)出现在男性 25-29 岁时的糖蛋白代谢紊乱,比女性早约 15 年。随着时间的推移,社区中的慢性疾病数量有所增加,但新进入者并没有取代社区的根源。
我们的多种疾病共存网络分析确定了性别和年龄对慢性诊断共现的具体差异,这有助于为住院患者多种疾病的临床干预提供设计依据。