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European journal of epidemiology · 2026

Cohort profile: Swiss personalized health network cohort consortium.

СтатьяНазвание и аннотация: Перевод в очереди
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Bochud Murielle, Tiali Samuel El Bouzaïdi, Armida Jan, Wissa Rita, Österle Sabine, Blanco Juan Manuel, Ghobril Jean Pierre, Henchoz Yves, Pittet Valérie, Benkert Pascal, Kuhle Jens, Castelao Enrique, Preisig Martin, Chizzolini Carlo, Günthard Huldrych F, Kusejko Katharina, Imboden Medea, Probst-Hensch Nicole, Koller Michael, Marques-Vidal Pedro, Vollenweider Peter, Pruijm Menno, Rauch Andri, Ribi Camillo, Scherer Almut, Tellenbach Christoph, Ponte Belen, Vaucher Julien, Fortier Isabel

Аннотация

Swiss cohort studies provide high-quality longitudinal data, but finding and comparing relevant studies across cohorts has historically been challenging. The Swiss Personalized Health Network Cohort Consortium (SPHN-CC) was established to address these limitations by creating the first coordinated network of Swiss cohort studies within the internationally recognized Maelstrom Research catalogue. Participating cohorts were invited in 2021-2022, including longitudinal and cross-sectional studies with 1010-21,993 participants. Data collected include questionnaires, physical and cognitive assessments, administrative records, and biological samples. Variables were classified into 18 domains and 134 subdomains, and an online metadata catalogue was implemented to document study designs, explore variable content, and assess harmonization potential. The catalogue enables researchers to identify study-specific and harmonized variables for co-analysis. Core variables, such as age, sex/gender, anthropometrics, and medication use, are widely available, while other variables vary across cohorts. Harmonization assessments demonstrate that several key variables can be co-analyzed across multiple studies, supporting collaborative research with over 37,000 participants. A use case illustrates the potential for harmonizing and co-analyzing data across studies. The SPHN-CC strengthens Swiss cohort research by enhancing data discoverability, supporting harmonization, and facilitating cross-cohort and international research, providing a model for more efficient use of high-value longitudinal data.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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