Evidence map›Paper›PMID 41241677›Full record

ArticleGeroScience2026

A scalable step count-based predictor of biological age: development and validation of MoveIt! Age in community-dwelling adults and geriatric rehabilitation inpatients.

Jessica K Lu, Weilan Wang, Lihuan Guan, Jeroen van der Velde, Joris Hoeks, Patrick Schrauwen, Gajja S Salomons, Riekelt H Houtkooper, Andrea B Maier, Georges E Janssens

Abstract readValidation Study
In one paragraph

Article in GeroScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Jessica K LuHealthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Weilan WangHealthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Lihuan GuanHealthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Jeroen van der VeldeDepartment of Clinical Epidemiology, Leiden University Medical Centre, Leiden, the Netherlands.
Joris HoeksDepartment of Nutrition and Movement Sciences, NUTRIM Institute of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands.
Patrick SchrauwenDepartment of Clinical Epidemiology, Leiden University Medical Centre, Leiden, the Netherlands.
Gajja S SalomonsLaboratory Genetic Metabolic Diseases, Amsterdam UMC - Location AMC, University of Amsterdam, AMC, F0-132, Meibergdreef 9, Amsterdam, 1105 AZ, the Netherlands.
Riekelt H HoutkooperLaboratory Genetic Metabolic Diseases, Amsterdam UMC - Location AMC, University of Amsterdam, AMC, F0-132, Meibergdreef 9, Amsterdam, 1105 AZ, the Netherlands.
Andrea B MaierHealthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. a.b.maier@vu.nl.ORCID 0000-0001-7206-1724
Georges E JanssensLaboratory Genetic Metabolic Diseases, Amsterdam UMC - Location AMC, University of Amsterdam, AMC, F0-132, Meibergdreef 9, Amsterdam, 1105 AZ, the Netherlands. g.e.janssens@amsterdamumc.nl.

Funding

European Union's Horizon 2020 program 689238European Union's Horizon 2020 Program 675003
6 · The paper itself

Abstract

Measuring biological age typically requires invasive and costly procedures. To address this, the MoveIt! Age Score was developed: a simple, scalable, and interpretable aging clock that predicts biological age using only wearable-derived steps data. MoveIt! Age was trained on steps data from the United States National Health and Nutrition Examination Survey (NHANES), using chronological age, maximum step count, and step count variability to predict PhenoAge, a blood biochemistry biological age score. MoveIt! Age performance was evaluated in two independent cohorts: Mitochondria and Muscle Health in Elderly (MitoHealth; N = 55; healthy young adults or older adults from the Netherlands) and Restoring Health of Acutely Unwell Adults (RESORT; N = 145; geriatric rehabilitation inpatients from Australia). In RESORT, MoveIt! Age was assessed and compared to SenoClock-BloodAge and PhenoAge (hematological aging clocks). Delta age was the predicted biological age minus chronological age. In the NHANES testing dataset, MoveIt! Age demonstrated high predictive accuracy of chronological age (r = 0.97, RMSE = 5.4 years) and was more significantly associated with mortality than PhenoAge. In MitoHealth, delta MoveIt! Age showed differences between young adults and older adults who were normal, healthy, or health-impaired, with MoveIt! Age more significantly associated with muscle NAD

Indexed as

AgingGeriatric AssessmentWalkingAdultAgedAged, 80 and overAustraliaFemaleHumansIndependent LivingMaleMiddle AgedNutrition SurveysYoung AdultAgingBiological ageLongevityPhysical fitnessWearable electronic devices

Identifiers

PMID41241677
PMCPMC12972362

What Socratic holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.