4.7 Article

Energy Metabolism and the Burden of Multimorbidity in Older Adults: Results From the Baltimore Longitudinal Study of Aging

出版社

OXFORD UNIV PRESS INC
DOI: 10.1093/gerona/glu209

关键词

Multimorbidity; Resting metabolic rate; Aging; Health status; Metabolism

资金

  1. Intramural Research Program of National Institutes of Health, National Institute on Aging [03-AG-0325]
  2. Paul Beeson Career Development Award Program [NIA K23 AG032910]
  3. Paul Beeson Career Development Award Program (AFAR)
  4. Paul Beeson Career Development Award Program (John A. Hartford Foundation)
  5. Paul Beeson Career Development Award Program (Atlantic Philanthropies)
  6. Paul Beeson Career Development Award Program (Starr Foundation)

向作者/读者索取更多资源

Excessively elevated resting metabolic rate ( RMR) for persons of a certain age, sex, and body composition is a mortality risk factor. Whether elevated RMR constitutes an early marker of health deterioration in older adult has not been fully investigated. Using data from the Baltimore Longitudinal Study of Aging, we hypothesized that higher RMR ( i) was cross-sectionally associated with higher multimorbidity and ( ii) predicted higher multimorbidity in subsequent follow-ups. The analysis included 695 Baltimore Longitudinal Study of Aging participants, aged 60 or older at baseline, of whom 248 had follow-up data available 2 years later and 109 four years later. Multimorbidity was assessed as number of chronic diseases. RMR was measured by indirect calorimetry and was tested in regression analyses adjusted for covariates age, sex, and dual-energy x-ray absorptiometrymeasured total body fat mass and lean mass. Baseline RMR and multimorbidity were positively associated, independent of covariates ( p =.002). Moreover, in a three-wave bivariate autoregressive cross-lagged model adjusted for covariates, higher prior RMR predicted greater future multimorbidity above and beyond the cross-sectional and autoregressive associations ( p = .034). RMR higher than expected, given age, sex, and body composition, predicts future higher multimorbidity in older adults and may be used as early biomarker of impending health deterioration. Replication and the development of normative data are required for clinical translation.

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