Examining morbidity and mortality trajectory profiles of hypertension, diabetes and dementia across healthcare systems: an analysis of Catalan and German administrative medical data for the years 2010 to 2019.

IF 2.5 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Anna-Victoria Holtz, Jordi Gumà, Iñaki Permanyer, Gabriele Doblhammer
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引用次数: 0

Abstract

Background: Hypertension, diabetes and dementia are prevalent morbidities in ageing populations and share complex relationships as risk factors and comorbidities. Understanding their temporal order is essential to understand health inequalities. Routinely collected medical data offers potential for cross-population comparisons, yet their feasibility for examining morbidity and mortality trajectories across healthcare systems remains underexplored.

Methods: We analyzed administrative medical data from a cohort of more than 1.5 million Catalans and a cohort of 250,000 Germans aged 50 years and above. Data from both cohorts covered the years 2005 to 2019. Efforts were made to harmonize the data from the two healthcare systems. Prevalence was estimated for hypertension, diabetes and dementia. Further analyses focused on individuals born between 1930 and 1954 with at least one of the three morbidities between 2010 and 2019. Morbidity and mortality trajectory profiles were identified using sequence and cluster analysis for large datasets, resulting in 11 distinct profiles per population. Birth cohort and sex-specific profile characteristics were evaluated by multinomial logistic regression.

Results: Age-standardized prevalence of the three morbidities was lower for Catalans (hypertension: 22.4%, CI [22.2-22.5%], diabetes: 8.1% [8.0-8.2%], dementia: 2.9% [2.8-2.9%]) compared to Germans (hypertension: 69.4% [69.0-69.8%]; diabetes: 29.4% [29.2-29.7%], dementia: 8.2% [8.1-8.4%]) at age 55 years and above in 2010. Prevalence differences may largely reflect differences in diagnostic recording and data-generation practices. Among 174,798 Catalans and 121,547 Germans born between 1930 and 1954 with at least one of the three morbidities, Catalans were more likely to be initially free from any of the three morbidities, whereas Germans were more likely to begin with hypertension and experienced a higher proportion of morbidity combinations. Profiles within each population showed differences based on birth cohort and sex.

Conclusions: Profound differences in prevalence as well as in morbidity and mortality trajectories existed between Catalonia and Germany between 2010 and 2019, reflecting more favorable health outcomes in Catalonia. Although administrative medical data yield meaningful insights for each population, comparing results across populations demands careful attention to variations in healthcare systems. To fully realize the potential of a European health data space, efforts are required to further harmonize data.

检查高血压、糖尿病和痴呆在医疗系统中的发病率和死亡率轨迹:对2010年至2019年加泰罗尼亚和德国行政医疗数据的分析。
背景:高血压、糖尿病和痴呆是老龄化人群中的常见疾病,它们作为危险因素和合并症有着复杂的关系。了解它们的时间顺序对于了解卫生不平等至关重要。常规收集的医疗数据为跨人群比较提供了可能,但其在检查医疗保健系统中发病率和死亡率轨迹的可行性仍未得到充分探索。方法:我们分析了来自150多万加泰罗尼亚人和25万50岁及以上的德国人的行政医疗数据。这两个队列的数据涵盖了2005年至2019年。我们努力协调两个医疗保健系统的数据。估计了高血压、糖尿病和痴呆的患病率。进一步的分析集中在1930年至1954年之间出生的人,他们在2010年至2019年期间至少患有三种疾病中的一种。利用大型数据集的序列和聚类分析确定了发病率和死亡率轨迹概况,得出每个人群11个不同的概况。通过多项逻辑回归评估出生队列和性别特征。结果:2010年55岁及以上人群中,加泰罗尼亚人(高血压:22.4%,CI[22.2-22.5%],糖尿病:8.1%[8.0-8.2%],痴呆:2.9%[2.8-2.9%])的年龄标准化患病率低于德国人(高血压:69.4%[69.0-69.8%],糖尿病:29.4%[29.2-29.7%],痴呆:8.2%[8.1-8.4%])。患病率差异可能在很大程度上反映了诊断记录和数据生成实践的差异。在1930年至1954年间出生的174,798名加泰罗尼亚人和121,547名德国人中,至少有三种疾病中的一种,加泰罗尼亚人更有可能最初没有这三种疾病中的任何一种,而德国人更有可能开始患有高血压,并且经历了更高比例的发病率组合。每个人群的概况显示出基于出生队列和性别的差异。结论:2010年至2019年,加泰罗尼亚和德国在患病率、发病率和死亡率轨迹方面存在巨大差异,反映出加泰罗尼亚的健康状况更为有利。虽然行政医疗数据为每个人群提供了有意义的见解,但比较不同人群的结果需要仔细关注医疗保健系统的差异。为了充分发挥欧洲卫生数据空间的潜力,需要努力进一步统一数据。
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来源期刊
Population Health Metrics
Population Health Metrics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
6.50
自引率
0.00%
发文量
21
审稿时长
29 weeks
期刊介绍: Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.
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