Albites-Sanabria, JosePalumbo, PierpaoloBandinelli, StefaniaD'Ascanio, IlariaMellone, SabatoParaschiv-Ionescu, AnisoaraKüderle, ArneCereatti, AndreaDel Din, SilviaKluge, FelixGazit, EranJansen, Carl-PhilippDelgado Ortiz, LauraGarcía Aymerich, JudithRochester, LynnKlenk, JochenFerrucci, LuigiBecker, ClemensChiari, LorenzoPalmerini, Luca2025-09-162025-09-162025Albites-Sanabria J, Palumbo P, Bandinelli S, D'Ascanio I, Mellone S, Paraschiv-Ionescu A, et al. Walking into aging: real-world mobility patterns and digital benchmarks from the InCHIANTI Study. NPJ Aging. 2025 Jul 5;11(1):60. DOI: 10.1038/s41514-025-00245-w2731-6068http://hdl.handle.net/10230/71200Mobility is a cornerstone of health and quality of life, particularly in older adults. Digital mobility outcomes (DMOs) from real-world walking data offer crucial insights into the functional status and early markers of mobility decline. This study provides reference values for walking activity, pace, rhythm, and gait bout-to-bout variability in community-dwelling older adults and evaluates the effects of age, sex, height, and weight on these parameters. Using data from 200 older adults (aged 65-94 years) from the InCHIANTI Study and applying the Mobilise-D computational pipeline, we analyzed real-world walking over a week. Significant differences by sex and age were found, with males showing higher walking activity in younger age groups (65-74 and 75-84 years) but not in the oldest group (85-94 years). Additionally, we observed non-linear trends in mobility metrics with age, indicating an accelerated reduction in mobility at certain age ranges. These findings underscore the importance of monitoring real-world walking data to pinpoint critical periods of mobility decline and guide targeted interventions. This work offers valuable benchmarks for clinical assessments and future research.application/pdfeng© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.info:eu-repo/semantics/articlehttp://dx.doi.org/10.1038/s41514-025-00245-wBiomarkersHealth careMedical researchRisk factorsinfo:eu-repo/semantics/openAccess