Authors
Qu Tian, Suha Shin, Amber B Courtier, Kong Y Chen, Luigi Ferrucci
Published in
The journals of gerontology. Series A, Biological sciences and medical sciences. Sep 01, 2026. Epub Sep 01, 2026.
Abstract
Aging changes whole-body anthropometry. Accelerated anthropometric aging can be operationalized as the age gap between the anthropometric-predicted age and the chronological age (AAG). What disease conditions affect AAG and subsequent functional deficits remains unclear.
In 302 Baltimore Longitudinal Study of Aging participants (mean age=71.7 years, 58% women, 30% Black), we examined the associations between AAG and disease conditions using multivariable linear regression, adjusted for age, sex, and race, and further tested whether AAG would mediate the association between diseases and functional outcomes.
Across disease conditions examined, AAG was specifically associated with osteoporosis, connective tissue disease, and neurodegenerative disease (including mild cognitive impairment, dementia, and Parkinson's disease) (p = 0.006, 0.047, and 0.034, respectively) and showed a trend to spinal stenosis (p = 0.098). AAG was not associated with pulmonary and vascular conditions, diabetes, hyperlipidemia, liver and kidney diseases, eye diseases, or cancer. AAG significantly mediated the associations between osteoporosis, connective tissue disease, and neurodegenerative disease and a range of cognitive and physical function measures (mediation effects all p < 0.05). Notably, AAG mediated the associations between neurodegenerative disease and measures important for motor planning and control, such as visuospatial ability, gesture imitation, and rapid gait speed. AAG also mediated the associations of osteoporosis and spinal stenosis with muscle strength.
Anthropometric aging is specifically associated with neuromusculoskeletal diseases and may partly account for the associations between certain disease conditions and subsequent functional deficits. Future studies involving blood biomarkers are warranted to uncover the biological processes of anthropometric aging.
PMID:
42678368
Bibliographic data and abstract were imported from PubMed on 01 Sep 2026.
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