Jose Albites-Sanabria, Pierpaolo Palumbo, Stefania Bandinelli, Ilaria D'Ascanio, Sabato Mellone, Anisoara Paraschiv-Ionescu, Arne Küderle, Andrea Cereatti, Silvia Del Din, Felix Kluge, Eran Gazit, Carl-Philipp Jansen, Laura Delgado-Ortiz, Judith Garcia-Aymerich, Lynn Rochester, Jochen Klenk, Luigi Ferrucci, Clemens Becker, Lorenzo Chiari, Luca Palmerini
{"title":"步入老龄化:来自InCHIANTI研究的现实世界的移动模式和数字基准。","authors":"Jose Albites-Sanabria, Pierpaolo Palumbo, Stefania Bandinelli, Ilaria D'Ascanio, Sabato Mellone, Anisoara Paraschiv-Ionescu, Arne Küderle, Andrea Cereatti, Silvia Del Din, Felix Kluge, Eran Gazit, Carl-Philipp Jansen, Laura Delgado-Ortiz, Judith Garcia-Aymerich, Lynn Rochester, Jochen Klenk, Luigi Ferrucci, Clemens Becker, Lorenzo Chiari, Luca Palmerini","doi":"10.1038/s41514-025-00245-w","DOIUrl":null,"url":null,"abstract":"<p><p>Mobility 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.</p>","PeriodicalId":94160,"journal":{"name":"npj aging","volume":"11 1","pages":"60"},"PeriodicalIF":4.1000,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12227531/pdf/","citationCount":"0","resultStr":"{\"title\":\"Walking into aging: real-world mobility patterns and digital benchmarks from the InCHIANTI Study.\",\"authors\":\"Jose Albites-Sanabria, Pierpaolo Palumbo, Stefania Bandinelli, Ilaria D'Ascanio, Sabato Mellone, Anisoara Paraschiv-Ionescu, Arne Küderle, Andrea Cereatti, Silvia Del Din, Felix Kluge, Eran Gazit, Carl-Philipp Jansen, Laura Delgado-Ortiz, Judith Garcia-Aymerich, Lynn Rochester, Jochen Klenk, Luigi Ferrucci, Clemens Becker, Lorenzo Chiari, Luca Palmerini\",\"doi\":\"10.1038/s41514-025-00245-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Mobility 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.</p>\",\"PeriodicalId\":94160,\"journal\":{\"name\":\"npj aging\",\"volume\":\"11 1\",\"pages\":\"60\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2025-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12227531/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"npj aging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1038/s41514-025-00245-w\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj aging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/s41514-025-00245-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
Walking into aging: real-world mobility patterns and digital benchmarks from the InCHIANTI Study.
Mobility 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.