Association of annual percentage changes in anthropometric indices with all-cause mortality: a 14-year longitudinal study of older US adults.

Authors

Furong Xu, Jacob E Earp, Kathleen Woolf, Mary L Greaney, Bryan J Blissmer

Published in

Frontiers in public health. Volume 14. Pages 1894939. Epub Jul 30, 2026.

Abstract

Longitudinal anthropometric changes may provide prognostic information beyond single timepoint measurements in older adults. We tested whether the annual percentage change (APC) in five anthropometric metrics (body mass index [BMI], waist circumference [WC], weight-adjusted waist index [WWI], waist-to-height ratio [WHtR], and waist-to-height^0.5 [WHT.5R]) were associated with all-cause mortality in a 14-year U.S. cohort of older adults.
Using data from the National Health and Aging Trends Study (NHATS) 2011-2024 (N = 5,245 after excluding deaths < 2 years), we calculated APC in BMI, WC, WWI, WHtR, WHT.5R using participant specific log-linear models. Survey-weighted Cox proportional hazard models were used to examine APC categories (stable [≤ 2% change] vs. larger gain/loss [> 2% change]) in relation to all-cause mortality, adjusted for baseline age, sex, race, education, annual income, smoking status, homebound status, major chronic disease status, physical frailty, functional status, and cognitive impairment. To ensure the robustness of study findings across all five indices, supplementary restricted cubic spline analyses were performed to validate our primary categorization analysis. Sensitivity analyses included 3- and 5-year lags to minimize reverse causation, explore sex-specific differences, and a two-point APC to confirm findings were not a modeling artifact.
Compared to stable (≤ 2% change) measures, fluctuations in all five anthropometric indices were associated with an elevated mortality risk (pooled HR range: 2.15-9.74; 95% CI boundaries ranged from 1.68 to 17.49; p < 0.001). Restricted cubic splines analyses supported a generally V-shaped association between anthropometric changes and mortality (all p _{non-linearity} < 0.05). Lagged sensitivity analyses produced findings generally consistent with the primary models (all p < 0.05). This elevated risk was observed for both gain and loss categories and were generally consistent across sex-stratified and two-point APC sensitivity analyses.
These findings suggest that stability in anthropometric metrics may reflect a lower-risk physiological profile in older adults. Fluctuations (gain or loss) in the examined anthropometric metrics were associated with higher mortality risk, with generally consistent findings across sensitivity analyses. However, these associations should be interpreted cautiously as anthropometric changes may reflect underlying illness, frailty, or other unmeasured factors.

PMID:
42598090
Bibliographic data and abstract were imported from PubMed on 14 Aug 2026.

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